Relative Strength Screener [TradingFinder] RS Rotation Matrix🔵 Introduction
There are times when several markets or symbols move higher at the same time, but that does not mean they are showing the same level of strength. An asset may rise and appear strong at first glance, while its benchmark has performed even better over the same period. In that situation, simply knowing which symbol is moving higher is not enough. The more important question is which asset is actually outperforming the market and which one is beginning to lose relative strength.
This is where Relative Strength analysis becomes useful. Instead of evaluating each symbol independently, a group of assets can be compared against the same benchmark to identify where relative strength is concentrated. This approach can be applied to stocks, indices, funds, currencies, commodities, cryptocurrencies, or any other comparable group of symbols.
Alongside Relative Strength, Relative Momentum adds another important layer because a current leader may still look strong while its relative momentum is starting to weaken, while a weaker symbol may already be entering an improving phase.
The Relative Strength Screener is designed to make these changes easier to identify. It compares multiple symbols against a common benchmark, ranks them using Relative Strength and Relative Momentum, and organizes the results inside a Ranking Dashboard. At the same time, the Rotation Matrix classifies each symbol as Leading, Improving, Weakening, or Lagging, making it easier to distinguish current leaders, emerging strength, weakening leadership, and persistent relative weakness.
This structure helps traders understand where relative strength is currently concentrated and where that strength may be moving next without manually reviewing a large number of charts. The purpose of the screener is not to generate direct Buy or Sell signals. Its main role is to support asset selection, Market Leadership analysis, Market Rotation analysis, and the creation of a more focused watchlist for further technical analysis.
🔵 How to Use
After adding the Relative Strength Screener to the chart, the first step is to define the group of assets that will be compared with one another. This group, or universe, should ideally contain instruments that make sense to evaluate within the same context. For example, users can compare stocks from the same industry, different market indices, funds, commodities, currencies, cryptocurrencies, or any other group of related assets. The indicator supports between 2 and 10 active symbols, and all Relative Strength and Relative Momentum calculations are based on this selected universe.
By default, the screener includes 10 sector funds from the US stock market and uses AMEX:SPY as the Benchmark. This setup provides a practical example of Sector Rotation analysis. AMEX:XLK represents Technology, AMEX:XLF represents Financials, AMEX:XLE represents Energy, AMEX:XLV represents Health Care, and AMEX:XLY represents Consumer Discretionary. The remaining symbols are AMEX:XLP for Consumer Staples, AMEX:XLI for Industrials, AMEX:XLB for Materials, AMEX:XLU for Utilities, and AMEX:XLRE for Real Estate.
These default symbols are only an example universe. The Relative Strength Screener is not limited to sector funds or the US market. Users can replace every symbol and the Benchmark to build a universe that matches their own analysis.
For example, several stocks from the same industry can be compared against a sector index, global equity indices can be compared against a broader market benchmark, or a group of cryptocurrencies can be evaluated relative to a selected crypto market reference. The important point is that all selected instruments should belong to a meaningful comparison framework.
🟣 Benchmark and Scan Timeframe
The Benchmark is the reference point for all Relative Strength calculations. With the default settings, SPY serves as this reference. This means the screener does not simply measure whether a symbol has risen or fallen. Instead, it evaluates how that symbol performed relative to SPY.
For example, an asset may gain 3 percent during the selected period and appear strong when viewed independently. However, if the Benchmark gains 5 percent over the same period, the asset has still underperformed the broader market. This distinction separates Absolute Performance from Relative Performance and helps identify assets that are truly gaining leadership rather than simply moving in the same direction as the market.
The Scan Timeframe determines the timeframe used by the ranking engine. If the Scan Timeframe is set to Daily, for example, the Performance Length and Momentum Length are calculated using daily scan bars. When the Scan Timeframe is equal to or higher than the chart timeframe, the screener uses confirmed scan data. When the Scan Timeframe is lower than the chart timeframe, the indicator uses the latest available intrabar information to create the current snapshot.
The current data mode is displayed directly in the Ranking Dashboard. If lower timeframe data is unavailable or incomplete, the screener displays a visible NO DATA or LIMITED DATA message rather than presenting a potentially misleading ranking.
🟣 Relative Strength and Relative Momentum
The core model of the screener is built around two measurements : Relative Strength and Relative Momentum.
Relative Strength measures how each symbol has performed compared with the Benchmark over the selected Performance Length. A positive Relative Return means the symbol has outperformed the Benchmark, while a negative value means the symbol has underperformed it. This information is displayed directly in the vs Benchmark column.
For example, if the dashboard shows 0.80% ahead, the symbol has delivered approximately 0.80 percent more relative performance than the Benchmark over the selected period. If the table shows 0.45% behind, the symbol has underperformed the Benchmark by approximately 0.45 percent on a relative basis.
Relative Strength describes the current position of an asset, but that alone does not show whether the situation is improving or deteriorating. This is why the indicator also calculates Relative Momentum. Relative Momentum measures how Relative Return has changed compared with its value a specified number of scan bars earlier.
A symbol can therefore remain ahead of the Benchmark while its Relative Momentum becomes negative. In this case, the asset is still an outperformer, but its previous advantage is beginning to fade. In the opposite situation, a symbol may still be behind the Benchmark while Relative Momentum becomes positive. This can be an early sign that its previous weakness is starting to reverse.
🟣 Ranking Dashboard
The Ranking Dashboard is the main analytical component of the Relative Strength Screener. It ranks the selected symbols using a combination of Relative Strength and Relative Momentum, while also showing the evidence behind each position.
The purpose of the table is not simply to tell the user which symbol ranks first or last. It is designed to answer several more useful questions. Which assets deserve further attention? Which leaders are maintaining their strength? Which symbols are improving? Which leaders are beginning to fade? And how persistent has the current relative strength been?
🟣 Rank
The Rank column shows the current position of each valid symbol within the selected universe.
If a symbol displays 1 of 10, it currently has the highest Composite Score among the 10 valid symbols. A reading of 6 of 10 means that five other assets currently have a higher score.
Rank is useful for quickly identifying the strongest members of the universe, but it should not be interpreted in isolation. Ranking is relative to the selected symbols. A symbol can rank first and still be underperforming the Benchmark if the entire universe is weak.
For this reason, Rank should normally be analyzed together with the vs Benchmark column.
🟣 Takeaway and Evidence
The Takeaway / Evidence column converts several underlying calculations into a more readable conclusion. Instead of requiring the user to interpret Relative Return, Momentum, Rank, Rank Change, and Persistence separately, the screener combines these conditions into descriptive states.
Sustained Leadership indicates that the symbol is ahead of the Benchmark, its Relative Momentum is not negative, it is ranked inside the top group, and it has maintained that position for the required Leadership Confirmation period. This condition represents established relative leadership and can identify assets that deserve further technical analysis.
Outperforming, Fading appears when the symbol is still ahead of the Benchmark but its Relative Momentum has turned negative. The asset remains relatively strong, but its advantage is shrinking. This can provide an early warning that an existing market leader is losing strength.
Climbing the Ranks indicates positive Relative Momentum together with an improvement in Rank. A symbol that moves from Rank 8 to Rank 6 and then to Rank 4 is progressively strengthening compared with the other members of the universe.
Recovering, Still Behind describes a symbol that continues to underperform the Benchmark but is showing positive Relative Momentum and improving Rank. This is not confirmed leadership. Instead, it represents an early recovery phase that may justify placing the asset on a watchlist.
Behind, No Recovery indicates that the symbol is behind the Benchmark and is not showing meaningful improvement in either Momentum or Rank. In a Relative Strength based selection process, these assets would normally receive lower priority.
Mixed Evidence is displayed when the available signals do not point in the same direction. Momentum may be improving while Rank remains weak, or other confirmation conditions may not yet be satisfied. The indicator intentionally keeps the conclusion neutral in these situations rather than forcing a stronger interpretation.
If one or more symbols in the universe lack valid data, the dashboard can display Incomplete Comparison. If the individual symbol itself does not have enough valid history, the result becomes Insufficient Data. Since Percentile and Rank calculations depend on cross sectional comparison, the indicator avoids producing strong conclusions when the available universe is incomplete.
🟣 vs Benchmark
The vs Benchmark column shows the actual relative performance of each symbol against the selected Benchmark.
An ahead value means the asset has outperformed the Benchmark over the configured Performance Length. A behind value means it has underperformed.
This column is especially important because it prevents a high Rank from being mistaken for genuine market outperformance. A symbol may rank first among the selected assets while still showing 0.20% behind. In that case, it is the strongest member of the selected universe, but it has not yet outperformed the Benchmark itself.
🟣 Score
The Score column combines Strength Percentile and Momentum Percentile into a single comparison score.
With the default settings, 65 percent of the score is assigned to Strength and 35 percent is assigned to Momentum. A higher score means the symbol has a stronger combination of Relative Strength and Relative Momentum compared with the other members of the universe.
The score is not a probability measurement. A value of 90 does not mean there is a 90 percent probability of a profitable trade, a 90 percent win rate, or a 90 percent probability that the asset will rise. It is simply a relative comparison metric used to rank the selected symbols.
🟣 Top Group Streak
The Top Group Streak shows how long a symbol has remained inside the strongest portion of the selected universe.
The top group is defined using the top quartile. In a universe of 10 symbols, this generally corresponds to the top three ranked assets.
If a symbol displays 8 scans, it means that the asset has remained in the top group for eight consecutive ranking checks. This helps distinguish a temporary jump in Rank from more persistent market leadership.
Top Group Streak does not count how many consecutive times a symbol has outperformed the Benchmark. It only measures persistence inside the top ranking group.
🟣 Rank Change
The Rank Change column shows how the position of a symbol has changed since the previous completed ranking check.
A value such as ↑ 2 places means the symbol improved by two ranking positions. A value of ↓ 2 places means it dropped by two positions. Unchanged means the ranking remained the same.
Current Rank shows where the asset is now, while Rank Change helps show the direction in which it is moving.
For example, a symbol currently ranked fifth may have improved from Rank 9 over the previous scans. This can indicate strengthening relative performance. Another symbol may still hold Rank 3 but may have fallen from Rank 1, suggesting that its leadership is beginning to deteriorate.
🟣 Rotation Matrix
The Rotation Matrix provides a faster and more visual summary of the entire universe. While the Ranking Dashboard shows detailed numerical evidence for every symbol, the Rotation Matrix focuses on the relationship between Strength and Momentum.
The matrix compares Strength Percentile and Momentum Percentile using the 50th percentile as the default boundary. Every valid symbol is then classified as Leading, Improving, Weakening, or Lagging.
A symbol in the Leading state has both Strength and Momentum in the stronger half of the universe. These assets represent the current relative leaders. If a symbol remains in Leading for several scans and the Ranking Dashboard also confirms Benchmark outperformance and a strong Top Group Streak, the evidence for persistent leadership becomes stronger.
An Improving symbol still has Strength in the weaker half of the universe, but its Momentum has moved into the stronger half. This state is particularly useful for identifying Emerging Leadership. The asset is not yet a confirmed leader, but its Relative Performance has started to improve.
One of the most important positive rotation sequences is : Lagging → Improving → Leading
This progression shows an asset moving from relative weakness into improving momentum and eventually into relative leadership.
A Weakening symbol still has above median Strength but below median Momentum. The asset remains relatively strong, but the quality of that strength is deteriorating.
A Leader moving into Weakening may be showing the first signs of losing its previous advantage.
If the deterioration continues, the sequence may become : Leading → Weakening → Lagging
However, a Weakening symbol can also return to Leading if Momentum recovers. For this reason, Weakening should be treated as a change in relative conditions rather than an automatic Sell signal.
A Lagging symbol has both Strength and Momentum in the weaker half of the universe. These assets usually receive lower priority in a Relative Strength selection process. However, movement out of Lagging can be important. A transition from Lagging to Improving can be the first indication that the relative trend is beginning to change.
🟣 Combining the Ranking Dashboard and Rotation Matrix
The most useful way to analyze the indicator is to read the Rotation Matrix and Ranking Dashboard together.
The Rotation Matrix provides the first overview. It shows where Relative Strength is concentrated and which assets are currently Leading, Improving, Weakening, or Lagging. The Ranking Dashboard then provides the numerical evidence needed to understand the quality of each state.
For example, if a symbol appears in Leading, the trader can check the Dashboard to determine whether it is actually ahead of the Benchmark, how high it ranks, how strong its Score is, how long it has remained in the top group, and whether its Rank is improving or deteriorating.
Two symbols can both appear in Leading while having very different profiles. One may be ahead of the Benchmark, ranked first, and have a long Top Group Streak. Another may have only recently entered the stronger half of the universe and have little persistence. The Rotation Matrix places both in the same broad state, while the Ranking Dashboard explains the difference between them.
The same principle applies to Improving. A symbol may be improving while still remaining behind the Benchmark. Another may already have crossed into relative outperformance. Rank Change can then show whether the improvement in Momentum is also beginning to affect its broader ranking.
For Weakening assets, the combination of negative Relative Momentum, declining Rank, and lower persistence can provide stronger evidence that leadership is deteriorating. If Rank remains stable and Momentum weakness is temporary, the condition may simply represent a short pause in relative strength.
It is important to understand that the Dashboard conclusions and Rotation Matrix do not use identical logic. The Rotation Matrix is based only on Strength Percentile and Momentum Percentile. The Dashboard also considers Relative Return, Relative Momentum, Rank Change, and Persistence.
For this reason, a symbol can appear as Improving in the Rotation Matrix while its Dashboard conclusion still shows Mixed Evidence. These outputs are not contradictory. They describe different dimensions of the same relative strength analysis.
🟣 Practical Workflow
A practical workflow begins by selecting a meaningful universe and an appropriate Benchmark. The Scan Timeframe, Performance Length, and Momentum Length can then be adjusted according to the intended analysis horizon.
The Rotation Matrix can first be used to identify current leaders, emerging strength, weakening leadership, and persistent laggards. The Ranking Dashboard can then be used to verify Benchmark Relative Performance, Rank, Score, Rank Change, and leadership persistence.
Symbols in Leading can be examined for current market leadership. Improving assets can be monitored for emerging Relative Strength. Weakening can help identify existing leaders that are beginning to lose Momentum, while Lagging identifies the weaker part of the selected universe.
The strongest or most interesting candidates can then be moved into a focused watchlist for further analysis of Price Structure, Trend, Liquidity, Entry Conditions, and Risk Management.
🔵 Settings
Number of Symbols : Determines how many symbols are included in the Relative Strength Screener. Users can select between 2 and 10 symbols. Only the first selected number of symbol inputs will be included in the Ranking Dashboard and Rotation Matrix.
Symbol 1 to Symbol 10 : Defines the assets used in the Relative Strength comparison. Each symbol can be replaced with any preferred stock, index, fund, currency, commodity, cryptocurrency, or other supported TradingView symbol. For more meaningful results, the selected symbols should belong to a logically comparable market universe.
Benchmark : Defines the reference asset used for all Relative Strength calculations. Each selected symbol is compared with this Benchmark to determine whether it is outperforming or underperforming the reference market. The default Benchmark is SPY.
Scan Timeframe : Determines the timeframe used by the Relative Strength ranking engine. The Scan Timeframe can be higher than, equal to, or lower than the chart timeframe. Higher and equal timeframe calculations use confirmed data, while lower timeframe settings use the latest available intrabar data.
Performance Length : Defines the number of Scan Timeframe bars used to calculate Benchmark Relative Performance. Higher values measure Relative Strength over a longer period, while lower values make the calculation more responsive to recent performance changes.
Momentum Length : Determines the period used to measure changes in Relative Performance. It compares the current Relative Return with its previous value to identify whether Relative Strength is improving or deteriorating.
Momentum Weight % : Defines how much influence Relative Momentum has on the final Score. The remaining percentage is automatically assigned to Relative Strength. For example, the default value of 35 percent creates a Score based on 35 percent Momentum and 65 percent Strength.
Leadership Confirmation : Defines how many consecutive Top Group checks are required before a symbol can be classified as having Sustained Leadership. Higher values require longer persistence before leadership is confirmed.
Symbol : Selects the asset displayed in the Relative Performance Oscillator. The selected symbol should be one of the active screener symbols. If another symbol is selected, Symbol 1 is used automatically.
Performance Length : Determines the lookback period used to calculate the selected symbol's performance relative to the Benchmark in the oscillator. Unlike the Ranking Dashboard, this setting is calculated using chart timeframe bars.
Smoothing : Defines the smoothing period applied to the Relative Performance line. Higher values create a smoother oscillator with less short term fluctuation, while lower values make the line more responsive.
Signal Length : Determines the EMA period used for the oscillator Signal Line. The relationship between the Relative Performance line and its Signal Line can be used to evaluate short term acceleration or deceleration in relative performance.
Show Signal : Enables or disables the oscillator Signal Line and the Relative Acceleration ribbon.
Show Last Value : Enables or disables the label showing the selected Symbol and Benchmark pair together with the latest Relative Performance value.
Send Alerts : Enables or disables the Relative Strength event engine. When enabled, alerts can be generated for Leader Group entries, Rotation State changes, Leadership Loss, and Leadership Confirmation events.
Leader Rank : Defines the Top N ranking group used for Leader Entry and Leadership Loss alerts. For example, when this value is set to 3, a symbol entering the Top 3 can trigger a Leader Entry event, while leaving the Top 3 can trigger a Leadership Loss event.
Show Ranking Table : Shows or hides the Relative Strength Ranking Dashboard on the chart.
Ranking Table Size : Adjusts the visual size of the Ranking Dashboard. Available options include Tiny, Small, Normal, and Large.
Ranking Table Position : Determines where the Ranking Dashboard appears on the chart. Users can select from nine positions using Top, Middle, or Bottom combined with Left, Center, or Right.
Show Rotation Matrix : Shows or hides the Rotation Matrix on the chart.
Matrix Table Size: Adjusts the visual size of the Rotation Matrix. Available options include Tiny, Small, Normal, and Large.
Matrix Table Position : Determines where the Rotation Matrix appears on the chart. Users can select from nine available positions. A different position from the Ranking Dashboard should be selected when both tables are enabled to prevent overlap.
🔵 Conclusion
Markets rarely move in a perfectly uniform way. While one group of assets is gaining leadership, another may be losing momentum, and somewhere else a previously weak symbol may already be starting to recover. Looking at price alone can make these shifts difficult to recognize, especially when several assets are moving in the same direction at the same time.
The Relative Strength Screener is built to make that rotation easier to see. By comparing a selected group of symbols against a common Benchmark, the indicator helps reveal which assets are truly outperforming, which ones are improving, and which current leaders are beginning to fade. The Ranking Dashboard adds the numerical evidence behind that comparison, while the Rotation Matrix turns the same market into a clearer picture of Leading, Improving, Weakening, and Lagging assets.
The goal is not to replace chart analysis or generate an automatic Buy or Sell signal. The value of the screener comes earlier in the decision process, when the trader is still asking which symbols deserve attention in the first place. Once the stronger, improving, or weakening assets have been identified, the next step is to return to the chart and evaluate Price Structure, Trend, Liquidity, Entry Conditions, and Risk Management.
インジケーター
AI K-Means Clustering [TradingFinder] Machine Learning Zones🔵 Introduction
K-Means clustering is an unsupervised machine learning algorithm that groups similar data points around repeatedly updated cluster centers. Each observation is assigned to its nearest center, the centers are recalculated, and the process continues until the clusters converge. In financial market analysis, this structure can separate recurring patterns in price movement, trend direction, volume pressure, and volatility without depending entirely on fixed thresholds. As a result, the same candle may be interpreted differently in a quiet market, a directional trend, or a volatility shock, because its meaning is evaluated in relation to the surrounding market data.
This TradingView indicator applies K-Means machine learning through several connected analysis modules. The Market State engine studies trend bias, price slope, and relative volume pressure to classify the current market regime as an active bullish trend, active bearish trend, soft bullish trend, soft bearish trend, neutral range, or low-volume range. It also compares the current cluster with the dominant cluster across recent candles, helping the trend classification remain more stable when a single large candle, temporary spike, or short-lived price reversal appears.
The Price Zones engine clusters pivot points, historical highs, and historical lows to create dynamic K-Means support and resistance zones. Traders can display all price cluster centers, the nearest K-Means zone, or separate support and resistance lines. Raw, Smooth, and Locked Steps modes control how quickly the zones respond to new price data, while the nearest line changes color according to the detected bullish, bearish, or ranging market state. A Stochastic moving average heatmap is also plotted between the outer zones, adding a visual layer for momentum, overbought and oversold conditions, trend strength, and changing market pressure.
The indicator also combines volatility analysis, price action recognition, cluster quality scoring, and alert conditions. The volatility engine uses normalized ATR, candle range, and return volatility to identify low-volatility compression, normal volatility, high volatility, and volatility shock. The Price Action module evaluates the latest closed candle for bullish and bearish zone breakouts, rejection patterns, momentum candles, and indecision near a clustered price level. A dedicated Quality and Reliability section then measures zone strength, cluster fit, zone width, price distance, and RMSE, helping traders understand whether the current machine learning calculations are strong enough for practical analysis or should be treated only as additional market context.
🔵 How to Use
The easiest way to read this indicator is not to search for one isolated green or red message. Its main value comes from combining several layers of market information: K-Means market state classification, adaptive price zones, price action, volatility conditions, and calculation quality. Each module answers a different question, and the strongest setups usually appear when several modules point in the same direction.
Start with the Market State row in the analysis table. This module applies multidimensional K-Means clustering to trend bias, trend slope, and relative volume pressure. The current cluster shows where the latest market data has been assigned, while the dominant cluster represents the most frequent cluster across the selected state window. The Strength value shows how dominant that cluster is within the recent sample.
The Market State analysis can return the following conditions :
Active Bullish Trend : Positive trend structure supported by stronger relative volume.
Soft Bullish Trend : Positive directional structure, but with weaker participation or less convincing momentum.
Active Bearish Trend : Negative trend structure supported by stronger relative volume.
Soft Bearish Trend : Bearish directional structure that still requires confirmation.
Neutral Range : Trend bias and slope are not strong enough to define a clear direction.
Low-Volume Range : Sideways structure accompanied by relatively weak volume participation.
The distinction between the current and dominant cluster is important. A single large candle can move the current data point into another cluster, but the dominant state may remain unchanged if the broader recent structure still belongs to the previous market regime. This can help prevent every temporary spike, pullback, or abnormal candle from being interpreted as a complete trend reversal.
The next section is Price Zones. Here, K-Means clustering is applied to historical pivot levels, sampled highs, and sampled lows. Instead of drawing a level from only one swing point, the algorithm groups similar historical prices and calculates a center for each price cluster. These cluster centers become adaptive K-Means price zones that may act as support, resistance, breakout references, or reaction areas.
The table displays :
Near : The cluster currently closest to price.
Strength : The percentage of sampled price levels assigned to the nearest cluster.
Nearest : The closest stabilized K-Means zone.
Support : The nearest valid cluster center below the market.
Resistance : The nearest valid cluster center above the market.
A higher Zone Strength means a larger share of the sampled levels belongs to that cluster. However, this should not be interpreted as a guaranteed support or resistance level. It simply shows that more historical observations were grouped around the same price area.
On the chart, users can choose between three visual approaches. Show All K-Means Zone Centers plots the complete set of clustered price levels. Show Nearest Zone displays only the closest stabilized level, while Show K-Means Support/Resistance plots the nearest support and resistance separately.
The nearest line changes color with the detected market state :
Green indicates a bullish market state.
Red indicates a bearish market state.
Blue indicates a neutral or ranging market state.
The zone lines can also be displayed in Raw, Smooth, or Locked Steps mode. Raw mode follows newly calculated cluster centers directly. Smooth mode gradually moves the plotted level toward the new center, creating a more stable visual structure. Locked Steps mode keeps the previous level in place until the new cluster center has moved by a meaningful ATR-based distance.
Between the outer K-Means zones, the indicator draws a Stochastic Moving Average Heatmap. This heatmap is based on a 100-period Stochastic value smoothed with a 50-period exponential moving average. Lower smoothed Stochastic values appear toward the blue and purple side of the color range, middle values move through cyan and green, and higher values progress toward yellow, orange, and red. The heatmap should be read as a visual momentum layer rather than as a standalone buy or sell signal.
The Price Action row studies candle structure in relation to the nearest K-Means zone and recent price behavior. It uses the candle body, upper wick, lower wick, previous high, previous low, and the location of the nearest zone to identify several possible conditions:
Bullish or bearish zone breakout.
Bullish or bearish rejection from a zone.
Bullish or bearish momentum candle.
Indecision at a K-Means zone.
General indecision.
No clear price action.
The Body, Upper Wick Ratio, and Lower Wick Ratio values represent the relative size of the candle body, upper wick, and lower wick compared with the candle’s total range. These values help explain why the indicator classified a candle as momentum, rejection, or indecision. Price Action should always be read together with Market State and Volatility. For example, a bullish momentum candle inside a bearish market state does not automatically create a bullish setup.
The Volatility module runs a separate K-Means model using normalized ATR, candle range percentage, and return volatility. The clustered volatility data is then used to identify four practical market conditions:
Low Volatility Compression : Market movement has contracted and a future expansion may develop;
Normal Volatility : Current movement is close to its recent reference level;
High Volatility : Price movement is elevated and may require smaller position size or wider risk parameters;
Volatility Shock : Abnormal expansion is present, making immediate entries more sensitive to slippage, unstable movement, and rapid reversals.
Volatility acts as a risk filter for the rest of the analysis. Even when Market State and Price Action point in the same direction, a High Volatility or Volatility Shock reading should reduce the confidence placed on an immediate entry.
Finally, review the Quality row. This section provides an internal assessment of how compact, representative, and consistent the current K-Means calculations are. It does not measure future profitability or win rate. Instead, it evaluates the statistical structure of the active price clusters.
The main values include :
Price Q : A combined score based on zone strength, width, fit, and price distance;
Trust : A weighted score combining price-zone quality, market-state dominance, and volatility-cluster dominance;
Fit RMSE : The normalized root mean squared error of the price clusters;
Width : The average dispersion of the nearest cluster around its center;
Reliability : A descriptive grade derived from the internal Trust score.
A narrow cluster with reasonable strength and lower fitting error will usually receive a better score than a wide, weak, or poorly fitted cluster. Use this section to decide how much weight should be given to the current analysis. A weak Quality score does not make the chart unusable, but it suggests that the levels and classifications should be treated as secondary context.
🟣 Bullish Market Reading
A bullish setup becomes more meaningful when the market state, K-Means zones, candle behavior, volatility, and quality readings support the same interpretation.
Check the Market State first : An Active Bullish Trend indicates stronger bullish structure and relative participation. A Soft Bullish Trend still favors the upside, but entries should normally wait for additional confirmation.
Locate price relative to the nearest zone : When price is above the nearest K-Means zone, that level may become an adaptive support reference. A pullback toward the green nearest-zone line can be watched for continuation or rejection behavior.
Look for bullish price action : A Bullish Rejection From Zone suggests that price tested a clustered level and closed with a stronger lower-wick reaction. A Bullish Zone Breakout shows that the candle crossed above the zone with a sufficiently large body. A Bullish Momentum Candle confirms upward pressure, but it is more useful when the Market State is already bullish.
Use the support line as a reference, not an automatic entry : The K-Means support level can help define the area where bullish structure remains valid. A decisive move below it may weaken the long scenario, especially if the Market State also changes.
Confirm volatility conditions : Normal Volatility is generally easier to manage than High Volatility or Volatility Shock. During compression, traders may wait for a confirmed breakout rather than entering before expansion begins.
Review Quality and Reliability : Stronger Quality, Trust, and Zone Strength readings increase the internal consistency of the analysis. Weak scores suggest that the zone may be broad, poorly fitted, or based on a less concentrated cluster.
A practical bullish sequence may therefore look like this: the table shows a Soft or Active Bullish Trend, price remains above or retests a green K-Means zone, a bullish rejection or breakout appears, volatility is not classified as a shock, and Quality remains acceptable. None of these elements guarantees continuation, but their alignment creates a clearer bullish context than any single reading alone.
🟣 Bearish Market Reading
Bearish analysis follows the same process in reverse. The objective is to identify whether downward market structure, clustered resistance, candle behavior, and volatility are supporting the same scenario.
Begin with the Market State : An Active Bearish Trend represents stronger negative bias, slope, and relative volume pressure. A Soft Bearish Trend favors short-side analysis but still requires confirmation before treating the move as established.
Observe price relative to the nearest zone : When price is below the nearest K-Means zone, that level may act as an adaptive resistance reference. A return toward the red nearest-zone line can be monitored for rejection or continuation.
Wait for bearish price action : A Bearish Rejection From Zone appears when price tests a clustered area and forms a stronger upper-wick reaction. A Bearish Zone Breakout indicates that price has crossed below the zone with a sufficiently large bearish body. A Bearish Momentum Candle carries more weight when the broader Market State is already bearish.
Use the resistance line to define context : The K-Means resistance level can help identify where bearish continuation remains structurally reasonable. A sustained break above it may weaken the short scenario, particularly if Market State also shifts toward bullish or neutral conditions.
Do not ignore volatility warnings : A bearish candle during Volatility Shock may be followed by a sharp continuation, but it can also produce rapid retracement and unstable execution. In this condition, the indicator explicitly favors additional confirmation or reduced risk.
Check cluster quality before relying on the level : A weak or wide price cluster may produce a less precise resistance reference. Higher Quality and Reliability readings indicate a more compact and internally consistent zone, not a guaranteed bearish outcome.
A clearer bearish sequence may include a Soft or Active Bearish Trend, price trading below or retesting a red K-Means zone, bearish rejection or breakout behavior, manageable volatility, and an acceptable Quality score. When these components disagree, for example, a bullish momentum candle inside a bearish trend, the table should be read as a warning that momentum alone is not enough to confirm a reversal.
The built-in alert conditions can be used to monitor bullish and bearish K-Means zone breakouts and rejections. Alerts are most useful as notifications that a specific price-action condition has appeared; the final interpretation should still include Market State, Volatility, zone position, and Quality before any trading decision is made.
🔵 Settings
🟣 K-Means Engine Settings
Market State Lookback : Number of recent bars used to cluster trend bias, slope, and relative volume for market-state classification.
Price Zone Lookback : Number of recent bars used to build K-Means price zones from pivots, highs, and lows.
Volatility Lookback : Number of recent bars used to cluster ATR percentage, candle range, and return volatility.
Market State Clusters : Number of clusters used by the Market State model.
Price Zone Clusters : Number of price clusters used to calculate adaptive zone centers.
Volatility Clusters : Number of clusters used by the Volatility model.
Max K-Means Iterations : Maximum number of center-update cycles allowed during each clustering calculation.
Dominant State Window : Number of recent cluster assignments used to determine the dominant market state.
Fast Volatility State Window : Number of recent volatility assignments used to determine the dominant short-term volatility cluster.
Convergence Tolerance : Minimum center movement required to continue the K-Means iteration; lower values increase precision but may require more processing.
🟣 Price Zone Settings
Pivot Length : Number of bars used on each side of a candle to confirm pivot highs and pivot lows.
High/Low Sampling Step : Controls how frequently historical highs and lows are added to the price-zone dataset; lower values use more samples.
Minimum Near-Zone Distance (%) : Minimum percentage distance used to classify price as testing a K-Means zone.
🟣 Execution Control Settings
Historical Calculation Bars : Number of recent historical bars on which calculations and visual outputs are processed.
Refresh Every N Bars : Runs the main K-Means modules once every selected number of bars and always updates them on the latest bar.
🟣 Zone Stabilizer Settings
Zone Plot Mode : Selects how zone lines are displayed: Raw follows new centers directly, Smooth moves gradually, and Locked Steps updates only after a meaningful price shift.
Zone Smooth Length : Controls the smoothing speed in Smooth mode; higher values produce slower and more stable zone movement.
Zone Lock ATR Multiplier : Defines the minimum ATR-based movement required before a zone updates in Locked Steps mode.
Nearest Zone Switch Margin ATR : Prevents frequent switching between nearby zones by requiring the new zone to be closer by an ATR-based margin.
🟣 Display Settings
Show Analysis Table : Shows or hides the market analysis table.
Table Text Size : Sets the size used inside the table.
Table Position : Selects the table location on the chart.
Show All K-Means Zone Centers : Displays all calculated K-Means price-zone centers.
Show Nearest Zone : Displays the stabilized zone closest to the current price, colored by the detected market state.
Show K-Means Support/Resistance : Displays the nearest clustered support below price and resistance above price.
🔵 Conclusion
This indicator brings K-Means clustering, market state analysis, adaptive price zones, volatility classification, and price action context into one structured workflow. Instead of reducing the chart to a single signal, it separates the market into several readable layers: directional behavior, clustered support and resistance areas, candle reactions, volatility conditions, and the internal quality of the current calculations. This makes it easier to understand whether price is trending, ranging, testing a K-Means zone, reacting to a clustered level, or moving through an unstable volatility phase.
Its strongest use comes from confirmation rather than prediction. A bullish or bearish reading becomes more meaningful when the Market State, nearest K-Means zone, Price Action module, Volatility analysis, and Quality score support the same scenario. When these components disagree, the table highlights that uncertainty instead of hiding it. Used this way, the tool works as a machine learning market analysis framework that helps organize recent price data, compare changing market regimes, and identify areas where further confirmation is still required. インジケーター
VWAP Choppy Market Detector [TradingFinder] Trend Range🔵 Introduction
Markets are not always clean. Sometimes price moves with a clear bullish or bearish direction, sometimes it stays inside a range, and sometimes it keeps shifting back and forth with no reliable structure. This indicator uses VWAP-based bands to make these market conditions easier to read directly on the chart, showing trend, range, and choppy price action through simple visual zones.
In trending markets, the bands remain more stable and highlight the dominant side of the market. Green zones show bullish pressure, while red zones show bearish pressure. When price moves sideways, the indicator marks the range area with purple zones and shows the Range High and Range Low, making the upper and lower limits of the consolidation easier to follow.
The choppy market signal comes from the behavior of the colors themselves. When the chart keeps changing between bullish, bearish, and range states, it reflects unstable price action, frequent market behavior shifts, and chaotic volatility. This makes the indicator useful for reading when the market has a clean direction, when it is trapped inside a range, and when price movement becomes too noisy or uncertain.
🔵 How to Use
Start by looking at the overall color behavior on the chart. The main purpose of this indicator is to show the current market environment through VWAP-based bands, so the first step is not to look for a single signal, but to understand the condition of the market. When the colors stay stable for a longer period, the market is usually showing a clearer structure. When the colors change repeatedly, the market is shifting between different states and price action is becoming less stable.
Green areas show bullish trend conditions. In this state, price is trading with stronger upward pressure and the market is moving with a clearer bullish bias. Traders can use this condition as a trend filter, a continuation filter, or a confirmation tool before looking for long setups with their own strategy. A stable green zone usually means the market is cleaner for bullish trend-following ideas compared to a market where the color keeps changing.
Red areas show bearish trend conditions. In this state, price is trading with stronger downward pressure and the market is moving with a clearer bearish bias. Traders can use this condition to filter short setups, confirm bearish continuation, or avoid taking long trades against the dominant market behavior. When the red zone remains stable, it shows that the bearish side of the market is more consistent.
Purple areas show range market conditions. In this state, price is moving inside a more limited structure instead of trending strongly in one direction. The upper and lower range boundaries can be used to understand where the market is consolidating. The upper boundary works as the Range High, while the lower boundary works as the Range Low. These levels help traders see the current sideways structure more clearly and follow how price reacts inside the range.
In a range market, traders can use the Range High and Range Low as visual reference levels. Price near the upper boundary may show that the market is testing the top of the range, while price near the lower boundary may show that the market is testing the bottom of the range. This can be useful for range analysis, mean-reversion setups, support and resistance reading, and identifying where price is likely to react inside a consolidation area.
Choppy market behavior is read through frequent color changes. When the chart keeps switching between green, red, and purple, it shows that the market does not have a clean direction. This kind of behavior usually means price is unstable, market bias is changing quickly, and volatility is becoming chaotic. Instead of treating these color changes as random noise, they should be read as the main warning sign of a choppy market.
One of the most useful applications of this indicator is avoiding poor trading conditions. Many strategies perform well in clean trends but struggle when the market becomes choppy. If the colors change too often and price fails to hold a stable condition, traders can use that information to reduce exposure, wait for a clearer structure, avoid overtrading, or be more selective with entries.
The indicator can also be used as a trend-following filter. When the market remains green, traders can focus more on bullish setups. When the market remains red, traders can focus more on bearish setups. This does not mean every green area is a buy signal or every red area is a sell signal. It means the market condition is more aligned with that side, and traders can combine it with their own entry model, price action setup, support and resistance level, or risk management plan.
Another use case is range detection. When the indicator marks a purple range, traders can quickly see that price is no longer moving with strong directional pressure. This helps separate trending conditions from sideways conditions. Range detection can be useful for traders who use consolidation breakouts, range trading, mean reversion, liquidity sweeps, or support and resistance reactions.
The indicator can also help with breakout context. Before a breakout, price often spends time inside a range. By watching the Range High and Range Low, traders can better understand where the range is forming and where a breakout attempt is happening. If price leaves the purple range and the market shifts into a stable green or red condition, traders can use that as extra context that the market behavior has changed from consolidation to directional movement.
For choppy market analysis, the most important thing is the speed and frequency of the color changes. A few normal changes can happen during transitions, but repeated switching shows that the market is unstable. This can help traders recognize fake breakouts, messy pullbacks, weak trend conditions, and periods where price does not respect a clean structure.
The timeframe setting controls the VWAP anchor period. Daily mode is more suitable for short-term and intraday analysis. Weekly mode gives a broader view of the current week’s VWAP structure. Monthly mode provides a higher-timeframe view and can be useful for swing trading or larger market context. Traders can choose the anchor timeframe based on the way they trade and the amount of market structure they want to see.
The Band Multiplier controls the width of the main VWAP bands. A wider band gives a broader market structure, while a smaller band keeps the bands closer to price. This setting affects how the trend and volatility structure is displayed on the chart. Traders can use it to match the indicator with different symbols, sessions, and volatility conditions.
The Range Multiplier controls the sensitivity of the range detector. A lower value makes the range detection more sensitive, so range areas may appear more actively. A higher value makes the range detection more conservative, so the indicator becomes more selective when marking range conditions. This setting is useful because different markets do not move the same way; some symbols are naturally smoother, while others are more volatile and noisy.
The VWAP line can be shown or hidden depending on the trader’s preference. When enabled, it gives a direct view of the VWAP reference line inside the band structure. Some traders may use it as a central fair-value reference, while others may prefer to keep the chart cleaner and focus only on the colored bands and market regime zones.
This indicator can be used by scalpers, intraday traders, swing traders, and market structure traders. Scalpers may use it to avoid fast choppy conditions and focus on cleaner short-term movement. Intraday traders can use it to read the daily or weekly VWAP structure. Swing traders can use weekly or monthly mode to understand broader market behavior. Price action traders can use it as a visual filter for trend, range, and unstable market conditions.
The best way to use the indicator is as a market condition tool, not as a standalone entry system. Its main value is helping traders understand when the market is trending, when it is ranging, and when price action is too choppy to read clearly. Once the market condition is clear, traders can apply their own strategy with better context.
🔵 Settings
TimeFrame : This setting defines the VWAP anchor period used by the indicator. Traders can choose between Daily, Weekly, and Monthly modes. Daily mode follows the current day’s VWAP structure, Weekly mode uses the current week’s VWAP structure, and Monthly mode shows a broader VWAP structure based on the current month.
Band Multiplier : The Band Multiplier controls the width of the main VWAP bands. A higher value makes the bands wider and gives more space around price, while a lower value keeps the bands closer to price. This setting affects how the indicator displays the main trend and volatility structure.
Range Multiplier : The Range Multiplier controls the sensitivity of the range detector. Lower values create High Range Sensitivity, so the indicator detects range conditions more actively. Higher values create Low Range Sensitivity, making range detection more selective and conservative.
Show VWAP Line : This option shows or hides the VWAP line on the chart. When enabled, the VWAP line can be used as the central reference inside the band structure. When disabled, the chart stays cleaner and the focus remains on the colored market condition zones.
🔵 Conclusion
Market conditions can change quickly, and not every move has the same quality. A clean trend, a structured range, and a choppy market need to be read differently. This indicator helps make that difference more visible by using VWAP-based bands and color behavior to show when price is moving with direction, when it is consolidating, and when the market is becoming unstable.
The main strength of the tool is its visual reading of market behavior. Stable green or red zones make trending conditions easier to follow, while purple zones highlight range structures with clear upper and lower boundaries. When the colors start changing frequently, that shift itself becomes an important warning that price action is noisy, unstable, and moving without a clean direction.
Overall, the indicator gives traders a clearer way to read trend, range, and choppy market conditions before making trading decisions. It is best used as a market environment filter, helping traders understand the current price behavior and decide whether the market is clean enough for their strategy or too chaotic to trade confidently.
インジケーター
RSI Multi Levels kiawosch [TradingFinder] 7-14-42 Consolidation🔵 Introduction
The Relative Strength Index or RSI is a tool used to measure the speed and intensity of price movement, oscillating between zero and one hundred. It is commonly applied to identify strength or weakness in market momentum across different time intervals. Despite its simple formula and wide usage, the behavior of RSI within specific ranges often provides more precise information than traditional overbought and oversold levels.
The Multi RSI layout displays three RSI values with periods 7, 14 and 42. The seven period RSI plays the primary role in short term analysis. When this value enters predefined ranges, it shows highly consistent and interpretable behavior that can signal trend continuation, corrections or the start of a range structure. The other two values, RSI 14 and RSI 42, help reveal higher timeframe momentum and provide context for the depth and quality of price movement.
Three potential zones are defined, each representing a behavioral range. The position zones forms the basis for signal interpretation :
High Potential : 78 to 85 & 22 to 15
Mid Potential : 70 to 78 & 30 to 22
Low Potential : 58 to 62 & 42 to 38
These zones highlight areas where RSI reacts in specific ways to price movement. Entering the High Potential range usually aligns with new highs or lows in price and often precedes continuation after a correction. In contrast, reactions inside the Mid Potential range frequently appear during clean ranges or channel structures. This approach focuses on momentum quality and structural behavior rather than classic overbought and oversold thresholds.
In summary, the logic behind the signals follows three principles :
Trend continuation, When RSI 7 enters the High Potential zone and price prints a new high or low, continuation after a correction becomes the most likely outcome.
Reversal or slowdown, When RSI exits the High Potential zone while price is reaching a previous high or low, the probability of a short term reversal increases.
Range behavior, In clean ranges or channel structures, RSI 7 typically reacts inside the Mid Potential zone and produces consistent swing responses.
🔵 How to Use
This method is based on observing the repeating behavior of RSI within momentum zones and identifying moments when price continues after a shallow correction or, conversely, when signs of slowing and reversal appear. RSI 7 plays the main role since it gives the most sensitive response to short term price changes. Its entry into or exit from a potential zone, combined with the position of price relative to recent highs and lows, forms the core of the signal logic. RSI 14 and RSI 42 provide higher timeframe confirmation and help evaluate the broader strength or weakness behind each movement.
🟣 Trend continuation after entering the High Potential zone
When RSI 7 reaches the High Potential zone while price forms a new high or low, the probability of continuation becomes very high. The typical sequence includes a short correction in price and a retreat of RSI toward the Mid Potential zone. As long as price structure remains intact and RSI turns upward again, continuation becomes the most likely scenario. As shown in the charts, price often expands strongly after this type of correction and breaks the previous high.
🟣 Reversal or slowdown after exiting the High Potential zone
If RSI 7 enters the High Potential zone but then exits while price is interacting with a previous high or low, conditions for a short term reversal appear. This behavior is clear in the charts, where price hits a supply or demand area and RSI can no longer return to the upper zone. The drop in RSI reflects weakening momentum and, when accompanied by a confirming candle, increases the chance of a reversal or at least a temporary pause.
🟣 Strong reversal after hitting the Mid Potential zone during deeper corrections
Sometimes price enters a deeper corrective phase and RSI 7 moves into or through the Mid Potential zone. When this occurs near a previous low, it can mark the start of a significant reversal. The charts show this pattern clearly, where RSI turns upward while price reacts to support. If the other RSI values show relative alignment, the probability of a strong rebound increases. This signal is often seen after fast declines and can mark the beginning of a recovery wave.
🟣 Range structure and repetitive reactions inside the Mid Potential zone
When price enters a clean range or channel, the behavior of RSI 7 changes completely. In such conditions, RSI repeatedly reacts inside the Mid Potential zone. Each time price touches the upper or lower boundary of the range, RSI approaches the upper or lower part of this zone as well. The result is a sequence of predictable swing reactions, perfectly suitable for mean reversion strategies. Breakouts in these environments also tend to show higher failure rates.
🟣 Sharp reactions and fast reversals at extreme levels (RSI near 90 or below 10)
Although this approach is not based on classic overbought and oversold logic, extremely high or low RSI readings such as ninety often produce strong immediate reactions in price. These conditions usually occur after sudden spikes or emotional breakouts. As visible in the charts, RSI collapses quickly after reaching such extremes and price often reverses sharply. While not a core signal, these moments add meaningful context to momentum interpretation.
🔵 Settings
RSI Setting : This section allows enabling or disabling the three RSI values, adjusting their calculation length and customizing their colors. It is designed to help separate short, medium and longer term momentum visually on the chart.
Zones Setting : This section controls the display of momentum zones and the color applied to each area. Adjusting these colors or toggling them on and off helps the trader visually track the intensity and structure of momentum.
Levels Setting : This section allows editing the numeric boundaries of the levels or showing and hiding each one individually. These levels form the visual framework for interpreting RSI behavior within the defined momentum zones.
🔵 Conclusion
Examining RSI behavior across different momentum zones shows that entering these ranges creates relatively consistent patterns in price movement. Reaching the High Potential zone often corresponds to later stages of a trend, where price has the strength to continue after a brief correction and structure remains intact. In contrast, reactions within the Mid Potential zone occur more frequently when the market transitions into a range or a limited movement phase, where repetitive oscillations dominate.
Overall, observing RSI inside these zones helps distinguish between trending movement, corrective phases and range conditions with greater clarity. Entry or exit from each zone provides insight into the underlying strength or weakness of momentum and reveals where the market is positioned within its movement cycle. This perspective, based on momentum regions rather than traditional values alone, offers a more refined understanding of price behavior and highlights the likely direction of the next move.
インジケーター
Smart Money Setup 08 [TradingFinder] Binary Options Gold Scalper🔵 Introduction
In the Smart Money methodology, the market is understood as a structure driven by liquidity flow. This structure forms through the movement of large orders, the accumulation of liquidity, and the reactions that occur around key price zones. The logic of Smart Money is based on the idea that price movement is not random and usually evolves with the intention of collecting liquidity and creating price inefficiencies known as imbalances.
Within this framework, several important stages including the liquidity sweep, the formation of a point of interest, the appearance of an imbalance and the transition of market structure play major roles and collectively define the broader direction of price.
In many bullish scenarios, the market begins by sweeping sell side liquidity and targeting important lows in order to collect the liquidity resting below them. This liquidity collection often becomes the starting point for creating a point of interest which usually marks the area where Smart Money begins to enter the market.
After price moves away from this point, it breaks a structural high and forms a change of character. This shift marks a transition in the balance of power between buyers and sellers and is considered the first clear signal that the market structure is changing.
After the change of character, new institutional order flow often creates a strong and rapid movement that leaves behind an imbalance. This imbalance is one of the most important elements in Smart Money analysis because price tends to return to this area in order to complete structure and restore balance.
The return into the imbalance becomes meaningful when it occurs together with the liquidity sweep, the presence of a validated point of interest and a confirmed structural transition. These conditions frequently mark the beginning of powerful movements within the Smart Money cycle.
Understanding the sequence of liquidity, point of interest, imbalance, change of character and market structure builds the foundation of Smart Money analysis and provides a clear view of the true direction of institutional strength.
Bullish Setup :
Bearish Setup :
🔵 How to Use
To use this framework effectively, the trader must analyze the market through the principles of Smart Money and observe how liquidity drives price. A trade becomes valid only when several essential components appear together in a clear and consistent order.
These components include the liquidity sweep, the formation of a point of interest, the confirmation of a change of character, the transition of market structure and the return of price into an imbalance. The method is built on the understanding that the market first collects liquidity, then shifts order flow and finally provides an entry opportunity inside an inefficient area or inside a point of interest.
For this reason, the trader must follow the path of liquidity from the moment the sweep occurs, through the point of interest and the change of character and finally into the return of price toward the imbalance. When applied correctly, this approach creates entries that are more precise, more structural and more aligned with the real behavior of the market rather than with superficial signals.
🟣 Long Position
A bullish setup in Smart Money structure begins with a liquidity sweep on the sell side. The market first targets the areas where sell side liquidity is located and collects the stops and resting liquidity under previous lows. This collection is the condition that Smart Money requires to begin creating a new order flow. After this liquidity has been taken, a point of interest forms which is usually the last bearish candle or the effective demand zone that initiated the upward movement.
Price then moves away from the point of interest and breaks a structural high which creates a change of character. This event confirms that the market structure has moved from a bearish state to a bullish one and that buying pressure has taken control of the order flow. Following this shift, a strong upward movement often occurs and creates an imbalance between candles. This imbalance reflects the entrance of strong Smart Money orders and is seen as an important confirmation of bullish strength.
When price returns to this imbalance after the displacement, the market enters a phase where Smart Money aims to complete the corrective movement and continue the upward direction. The reaction inside the imbalance when combined with the liquidity sweep, the confirmed point of interest and the change of character completes the bullish setup and forms a structure that often leads to a continuation of the bullish trend.
🟣 Short Position
A bearish setup follows the same Smart Money logic but in the opposite direction. The market begins by collecting buy side liquidity and targets the highs where buy side liquidity and resting stops are located. This liquidity sweep on the buy side becomes the starting phase for Smart Money to initiate a downward order flow. After the liquidity is collected, a bearish point of interest forms which is usually the last bullish candle or the supply zone that created the initial drop.
Price then moves away from this point and breaks the first structural low. This creates a change of character to the downside which confirms that the market structure has transitioned from bullish to bearish and that selling pressure has gained control. After this shift, a strong downward displacement appears and leaves behind a bearish imbalance that clearly shows the dominance of sellers.
As price returns to this imbalance and corrects the inefficient movement, the bearish setup becomes complete as long as the market structure remains bearish. The combination of the buy side liquidity sweep, the bearish point of interest, the change of character, the imbalance and the corrective return creates the ideal structure that Smart Money uses to continue the downward movement and develop a reliable selling opportunity.
🔵 Settings
🟣 Logic Settings
Pivot Period : Defines how many bars are analyzed to identify swing highs and lows. Higher values detect larger, slower structures, while lower values respond to faster patterns. The default value of 5 offers a balanced sensitivity.
🟣 Alert Settings
Alert : Enables alerts for SMS08.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Smart Money approach demonstrates that price movement is not random or based on surface level patterns. Instead, it develops through a clear cycle of liquidity collection, structural transition and corrective movement toward key price zones. By recognizing events such as the liquidity sweep, the formation of the point of interest, the change of character and the return into the imbalance, the trader gains the ability to understand order flow more accurately and identify the true direction of market structure.
Both bullish and bearish setups show that the alignment of these elements creates a transparent view of institutional behavior and reveals the source of strong movements in the market. When the trader correctly identifies this sequence, entry points become more reliable and more aligned with liquidity flow. The combination of liquidity, structure and imbalance provides a consistent framework that removes guesswork and guides decisions through the real logic of the market. インジケーター
Market Structure ICT Screener [TradingFinder] BoS ChoCh🔵 Introduction
Market Structure is the foundation of every Smart Money and ICT based trading model. It describes how price moves through a sequence of highs and lows, forming clear phases of expansion, retracement and reversal. Understanding this structure allows traders to read institutional order flow and align their positions with the true direction of liquidity.
Two of the most critical components in Market Structure are the Break of Structure (BOS) and Change of Character (CHOCH). A BOS represents trend continuation, confirming strength within the current direction. In contrast, CHOCH also known as a Market Structure Shift (MSS) signals the first sign of a trend reversal or liquidity shift where order flow begins to change from bullish to bearish or vice versa.
Because the market is fractal, structure can exist at multiple levels known as Major (External) and Minor (Internal). Major structure defines the overall trend on higher timeframes while minor or internal structure reveals short term swings and early reversals within that larger move.
🔵 How to Use
Understanding Market Structure starts with identifying how price interacts with previous swing highs and swing lows. Every trend in the market, whether bullish or bearish, is built from a sequence of impulsive and corrective moves. Impulsive legs show strong displacement in the direction of liquidity flow, while corrective legs represent temporary pullbacks as the market rebalances before the next expansion. Recognizing these sequences is essential for reading the story of price and anticipating what may happen next.
A Break of Structure (BOS) occurs when price decisively moves beyond a previous structural point by breaking above the last high in an uptrend or falling below the last low in a downtrend. This event confirms that the current trend remains intact and that liquidity has been successfully taken from one side of the market. A BOS acts as confirmation of continuation and reflects strength within the existing directional bias.
A Change of Character (CHOCH) appears when price violates structure in the opposite direction of the prevailing trend. This is the first signal that market sentiment and order flow may be shifting. For example, during a downtrend if price breaks above a previous high, it indicates that sellers are losing control and a potential bullish reversal may be developing. In an uptrend, when price drops below a recent low, it suggests a possible bearish transition.
Because the market is fractal, structure exists across multiple layers. Major structure reflects the dominant movement visible on higher timeframes and defines the broader directional bias. Minor or internal structure represents smaller swings within that move and helps identify early transitions before they appear on the higher timeframe. When internal and external structures align, they offer a high probability signal for trend continuation or reversal.
By observing BOS and CHOCH across both internal and external structures, traders can clearly visualize when the market is expanding, contracting or preparing to shift direction. This structured understanding of price movement forms the foundation for precise trend analysis and high quality decision making in any Smart Money or ICT based trading approach.
🔵 Settings
🟣 Display Settings
Table on Chart : Allows users to choose the position of the signal dashboard either directly on the chart or below it, depending on their layout preference.
Number of Symbols : Enables users to control how many symbols are displayed in the screener table, from 10 to 20, adjustable in increments of 2 symbols for flexible screening depth.
Table Mode : This setting offers two layout styles for the signal table :
Basic : Mode displays symbols in a single column, using more vertical space.
Extended : Mode arranges symbols in pairs side-by-side, optimizing screen space with a more compact view.
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 20 symbol slots comes with a full set of customizable parameters :
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
Pivot Period : Set the length used to detect swing highs and lows. Shorter values increase sensitivity, longer ones focus on major structures.
🔵 Conclusion
Mastering Market Structure and understanding the relationship between BOS and CHOCH allows traders to see the market with greater clarity and confidence. These two elements reveal how liquidity moves through different phases of expansion and retracement and how institutional order flow shifts between accumulation and distribution.
By analyzing both internal and external structures, traders can align short term and long term perspectives and anticipate where price is most likely to react. The ability to read these structural shifts helps identify continuation points, reversals and areas where liquidity is engineered or collected.
Incorporating Market Structure into a consistent trading process transforms the way a trader views the chart. Instead of reacting to random movements, each swing, break and shift becomes part of a logical framework that reflects the true behavior of the market. Understanding BOS and CHOCH is not just a concept but a complete language of price that guides every professional decision in Smart Money and ICT based trading.
インジケーター
Ichimoku PourSamadi Signal [TradingFinder] KijunSen Magic Number🔵 Introduction
The Ichimoku Kinko Hyo system is one of the most comprehensive market analysis tools ever created. Developed by Goichi Hosoda, a Japanese journalist in the 1930s, its purpose was to allow traders to recognize the balance between price, time, and momentum at a single glance. (In Japanese, Ichimoku literally means “one look.”)
At the core of the system lie five key components: Tenkan-sen (Conversion Line), Kijun-sen (Baseline), Chikou Span (Lagging Line), and the two leading spans, Senkou Span A and Senkou Span B, which together form the well-known Kumo or cloud representing both temporal structure and equilibrium zones in the market.
Although Ichimoku is commonly used to identify trends and support/resistance levels, a deeper layer of time philosophy exists within it. Ichimoku was not designed solely for price analysis but equally for time analysis.
In the classical model, the numerical cycles 9, 26, 52 reflect the natural rhythm of the market originally based on the Tokyo Stock Exchange’s trading schedule in the 1930s.
These values repeat across the system’s calculations, forming the foundation of Ichimoku’s time symmetry where price and time ultimately seek equilibrium.
In recent years, modern analysts have explored new approaches to extract time-based turning points from Ichimoku’s structure. One such approach is the analysis of flat segments on the Kijun-sen and Senkou B lines.
Whenever one of these lines remains flat for a period, it signals temporary balance between buyers and sellers; when the flat breaks, the market exits equilibrium and a new cycle begins.
This indicator is built precisely upon that philosophy. Following the timing methodology introduced by M.A. Poursamadi, the focus shifts away from price signals and line crossovers toward identifying flat periods on Kijun-sen (period 52) as time anchors.
From the first candle that changes the line’s slope, the tool begins a temporal count using a fixed sequence of key numbers: 5, 9, 13, 17, 26, 35, 43, 52, 63, 72, 81, 90.
Derived from both classical Ichimoku cycles and empirical testing, these numbers mark potential timing nodes where a market wave may end, a correction may begin, or a new leg may form.
Thus, this method serves not merely as another Ichimoku tool but as a temporal metronome for market structure a way to visualize moments when the market is ready to change rhythm, often before candles reveal it.
🔵 How to Use
The Kijun Timing BoX is built entirely on Ichimoku’s concept of time analysis.
Its core idea is that within every flat segment of the Kijun-sen, the market enters a temporary balance between opposing forces.
When that flat breaks, a new time cycle begins. From that first breakout candle, the indicator starts counting forward through the predefined time sequence(5, 9, 13, 17, 26, 35, 43, 52, 63, 72, 81, 90).
This counting framework creates a temporal map of market behavior, where each number represents an area where meaningful price fluctuations often occur.
A “meaningful fluctuation” does not necessarily imply reversal or continuation; rather, it marks a moment when the market’s internal energy balance shifts, typically visible as noticeable reactions on lower timeframes.
🟣 Identifying the Anchor Point
The first step is recognizing a valid flat zone on the Kijun-sen.
When this line remains flat for several candles and then changes slope, the indicator marks that bar as the Anchor, initiating the time count.
From that point onward, vertical gray lines appear at each interval in the key-number sequence, visualizing the time nodes ahead.
🟣 Reading the Timing Lines
Each numbered line represents a timing node a temporal point where a change in price rhythm is statistically more likely to occur.
At these nodes, the market may :
Enter a consolidation or minor correction phase.
Develop range-bound movement.
Or simply alter the speed and intensity of its move.
These behaviors do not imply a specific direction; they only highlight zones where time-based activity tends to cluster, giving traders a clearer view of cyclical rhythm.
🟣 Applying Time Analysis
The indicator’s primary use is to observe temporal order, not to predict price direction.
By tracking the distance between Anchors and the reactions that appear near major timing lines, traders can empirically identify each market’s characteristic rhythm—its own time DNA.
For example, one asset may consistently show significant fluctuations around the 13- and 26-bar marks,while another might react closer to 9 or 52. Recognizing such patterns helps traders understand how long typical cycles last before new phases of volatility emerge.
🟣 Combining with Other Tools
The indicator does not generate buy/sell signals on its own.
Its best use is in combination with price- or structure-based methods, to see whether meaningful price reactions occur around the same timing nodes.
In practice, it helps distinguish structured time-based fluctuations from random, noise-driven moves an insight often overlooked in conventional market analysis.
🔵 Settings
🟣 Logical Settings
KijunSen Period : Defines the baseline period used for timing analysis. Default = 52. It is the main line for detecting flats and generating time anchors.
Flat Event Filter : Controls how flat segments are validated before triggering a new timing event.
All : Every flat triggers a new Timing Box.
Automatic : Only flats longer than the historical average are used (recommended).
Custom : User manually defines the minimum flat length via Custom Count.
Update Timing Analysis BoX Per Event : If enabled, a new Timing Box is drawn each time a new flat event occurs. If disabled, the box completes its 90-bar window before refreshing.
🟣 Ichimoku Settings
TenkanSen Period : Defines the period for the Conversion Line (Tenkan-sen). Default = 9.
KijunSen Period : Sets the standard Ichimoku baseline (not the timing line). Default = 26.
Span B Period : Defines the period for Senkou Span B, the slower cloud boundary. Default = 52.
Shift Lines : Offsets cloud projection into the future. Default = 26.
🟣 Display Settings
Users can show or hide all Ichimoku lines Tenkan-sen, Kijun-sen, Chikou Span, Span A, and Span B as well as the Ichimoku Cloud.
They can also customize the color of each element to match personal chart preferences and improve visibility.
🔵 Conclusion
This analytical approach transforms Ichimoku’s time philosophy into a visual and measurable framework. A flat Kijun-sen represents a moment of market equilibrium; when its slope shifts, a new temporal cycle begins.
The purpose is not to forecast price direction but to highlight periods when meaningful fluctuations are more likely to develop.
Through this perspective, traders can observe the hidden rhythm of market time and expand their analysis beyond price into a broader time-cycle dimension.
Ultimately, the method revives Ichimoku’s original principle: the market can only be truly understood through the simultaneous harmony of price, time, and balance. インジケーター
Ichimoku Cloud Indicator [TradingFinder] Kinko Hyo Cross Alerts🔵 Introduction
The Ichimoku Cloud (Ichimoku Kinko Hyo) is one of the most powerful and complete trading indicators in technical analysis. Originally developed by Japanese journalist Goichi Hosoda, the Ichimoku system combines multiple tools in one indicator, providing traders with instant insights into trend direction, support and resistance levels, and momentum. Unlike simple moving averages (SMA – Simple Moving Average), the Ichimoku Cloud (Kumo – Cloud) integrates dynamic elements that help traders forecast potential price action with greater clarity.
The Ichimoku Indicator (Ichimoku Signal System) is widely used across global markets, from Forex trading (FX – Foreign Exchange) to stocks, indices, and even cryptocurrencies. Its popularity comes from its ability to generate clear buy signals and sell signals based on the interaction of its components: Tenkan Sen (Conversion Line), Kijun Sen (Base Line), Senkou Span A, Senkou Span B, and Chikou Span (Lagging Line). When combined, these lines create the Ichimoku Cloud, which visually represents the balance between price action and market structure.
Ichimoku Cloud Lines Formulas :
Conversion Line (Tenkan Sen / Conversion Line) : Average of the highest high and lowest low over the past 9 periods => (9-PH + 9-PL) ÷ 2
Base Line (Kijun Sen / Base Line) : Average of the highest high and lowest low over the past 26 periods => (26-PH + 26-PL) ÷ 2
Leading Span A (Senkou Span A / Leading Span A) : Average of the Conversion Line and Base Line, plotted 26 periods ahead => (Tenkan Sen + Kijun Sen) ÷ 2
Leading Span B (Senkou Span B / Leading Span B) : Average of the highest high and lowest low over the past 52 periods, plotted 26 periods ahead => (52-PH + 52-PL) ÷ 2
Lagging Span (Chikou Span / Lagging Span) : Current closing price, plotted 26 periods behind.
One of the biggest advantages of the Ichimoku Trading Strategy (Ichimoku Cloud Trading System) is that it allows traders to identify the market condition at a glance. When the price is above the Kumo (Cloud), it indicates a bullish trend (uptrend). When the price is below the Kumo, the market is in a bearish trend (downtrend). And when the price is inside the cloud, the market is ranging (sideways trend). This simplicity and visual clarity make Ichimoku an essential indicator for both beginner traders and professional analysts.
The Ichimoku Cloud Indicator (Ichimoku Technical Analysis Tool) continues to be one of the most reliable charting methods. Traders often consider it superior to basic moving averages (MA – Moving Average) or exponential moving averages (EMA – Exponential Moving Average), because it not only shows trend direction but also highlights potential future support and resistance levels. With its unique combination of trend analysis, price forecasting, and trading signals, Ichimoku remains a core strategy in modern trading systems.
🔵 How to Use
The Ichimoku Cloud is more than just a set of lines; it’s a complete trading system that helps traders identify trends, momentum, and key support and resistance levels. By combining its five lines Conversion Line, Base Line, Leading Span A, Leading Span B, and Lagging Span traders can develop clear buy and sell strategies.
🟣 Identifying Trend Direction
Bullish Trend (Uptrend) : Price is above the cloud (Kumo), and the cloud is green. Leading Span A is above Leading Span B, signaling strong upward momentum.
Bearish Trend (Downtrend) : Price is below the cloud, and the cloud is red. Leading Span A is below Leading Span B, confirming a downward momentum.
Ranging / Sideways Market : Price is inside the cloud, indicating indecision and consolidation. Traders often avoid opening strong positions during these periods.
🟣 Buy Strategies
Conversion/Base Line Crossover : A buy signal occurs when the Conversion Line (Tenkan Sen) crosses above the Base Line (Kijun Sen). The signal is strongest when this crossover happens above the cloud.
Price Above Base Line : If the price moves above the Base Line while in an uptrend, it confirms bullish momentum and provides a favorable entry point.
Cloud Support Pullback : During a pullback in an uptrend, the price may touch or slightly enter the cloud. Traders can use the cloud as a dynamic support zone for buying opportunities.
Lagging Span Confirmation : Ensure the Lagging Span (Chikou Span) is above the price of 26 periods ago to confirm the strength of the bullish trend.
🟣 Sell Strategies
Conversion/Base Line Crossover : A sell signal is generated when the Conversion Line (Tenkan Sen) crosses below the Base Line (Kijun Sen). This signal is strongest when it occurs below the cloud.
Price Below Base Line : If the price falls below the Base Line in a downtrend, it confirms bearish momentum and strengthens the sell setup.
Cloud Resistance Pullback : During a bounce in a downtrend, the cloud acts as a resistance zone. Traders can enter sell positions when price approaches or touches the cloud from below.
Lagging Span Confirmation : The Lagging Span should be below the price of 26 periods ago, confirming downward momentum.
🟣 Cloud Breakout Signals
A strong buy occurs when the price breaks above the cloud from below, signaling a potential trend reversal.
A strong sell occurs when the price breaks below the cloud from above, indicating a shift toward a bearish trend.
🟣 Combining Signals for Stronger Entries
For higher probability trades, combine multiple signals : trend direction (cloud color and position), crossovers (Tenkan/Kijun), and Lagging Span position.
Avoid trading against the overall trend. For example, avoid buying when price is below a red cloud or selling when price is above a green cloud.
🔵 Setting
Tenkan Sen Period : Lookback period for Conversion Line (default: 9).
Kijun Sen Period : Lookback period for Base Line (default: 26).
Span B Period : Lookback period for Leading Span B, forms one Cloud boundary (default: 52).
Shift Lines : Periods forward for Cloud / backward for Lagging Span (default: 26).
Cross Tenkan/Kijun Alert : Alert on Conversion/Base Line crossover.
Cross Price/Tenkan Alert : Alert when price crosses Tenkan Sen.
Cross Price/Kijun Alert : Alert when price crosses Kijun Sen
🔵 Conclusion
The Ichimoku Cloud (Ichimoku Kinko Hyo) is much more than a simple indicator it is a complete trading system that combines trend detection, momentum analysis, and support/resistance identification in one view. By interpreting the position of price relative to the cloud, the interaction between Tenkan Sen (Conversion Line) and Kijun Sen (Base Line), the leading spans (Senkou Span A and B), and the Chikou Span (Lagging Line), traders can identify potential buy and sell opportunities with higher confidence.
The main advantage of the Ichimoku Cloud is its ability to provide a “one-look equilibrium” snapshot of the market. It highlights bullish trends when the price is above the cloud, bearish conditions when the price is below it, and indecision or transition when the price is inside the cloud. Crossovers, cloud breakouts, and confirmations by the Chikou Span strengthen the trading signals.
However, traders should keep in mind the limitations of the Ichimoku system. It is based on historical data and should not be used in isolation. Combining it with other tools such as RSI, volume analysis, or candlestick patterns can significantly improve accuracy and reduce false signals.
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ICT Venom Trading Model [TradingFinder] SMC NY Session 2025SetupIntroduction
The ICT Venom Model is one of the most advanced strategies in the ICT framework, designed for intraday trading on major US indices such as US100, US30, and US500. This model is rooted in liquidity theory, time and price dynamics, and institutional order flow.
The Venom Model focuses on detecting Liquidity Sweeps, identifying Fair Value Gaps (FVG), and analyzing Market Structure Shifts (MSS). By combining these ICT core concepts, traders can filter false breakouts, capture sharp reversals, and align their entries with the real institutional liquidity flow during the New York Session.
Key Highlights of ICT Venom Model :
Intraday focus : Optimized for US indices (US100, US30, US500).
Time element : Critical window is 08:00–09:30 AM (Venom Box).
Liquidity sweep logic : Price grabs liquidity at 09:30 AM open.
Confirmation tools : MSS, CISD, FVG, and Order Blocks.
Dual setups : Works in both Bullish Venom and Bearish Venom conditions.
At its core, the ICT Venom Strategy is a framework that explains how institutional players manipulate liquidity pools by engineering false breakouts around the initial range of the market. Between 08:00 and 09:30 AM New York time, a range called the “Venom Box” is formed.
This range acts as a trap for retail traders, and once the 09:30 AM market open occurs, price usually sweeps either the high or the low of this box to collect stop-loss liquidity. After this liquidity grab, the market often reverses sharply, giving birth to a classic Bullish Venom Setup or Bearish Venom Setup
The Venom Model (ICT Venom Trading Strategy) is not just a pattern recognition tool but a precise institutional trading model based on time, liquidity, and market structure. By understanding the Initial Balance Range, watching for Liquidity Sweeps, and entering trades from FVG zones or Order Blocks, traders can anticipate market reversals with high accuracy. This strategy is widely respected among ICT followers because it offers both risk management discipline and clear entry/exit conditions. In short, the Venom Model transforms liquidity manipulation into actionable trading opportunities.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The ICT Venom Model is applied by observing price behavior during the early hours of the New York session. The first step is to define the Initial Range, also called the Venom Box, which is formed between 08:00 and 09:30 AM EST. This range marks the high and low points where institutional traders often create traps for retail participants. Once the official market opens at 09:30 AM, price usually sweeps either the top or bottom of this box to collect liquidity.
After this liquidity grab, the market tends to reverse in alignment with the true directional bias. To confirm the setup, traders look for signals such as a Market Structure Shift (MSS), Change in State of Delivery (CISD), or the appearance of a Fair Value Gap (FVG). These elements validate the reversal and provide precise levels for trade execution.
🟣 Bullish Setup
In a Bullish Venom Setup, the market first sweeps the low of the Venom Box after 09:30 AM, triggering sell-side liquidity collection. This downward move is often sharp and deceptive, designed to stop out retail long positions and attract new sellers. Once liquidity is taken, the market typically shifts direction, forming an MSS or CISD that signals a reversal to the upside.
Traders then wait for price to retrace into a Fair Value Gap or a demand-side Order Block created during the reversal leg. This retracement offers the ideal entry point for long positions. Stop-loss placement should be just below the liquidity sweep low, while profit targets are set at the Venom Box high and, if momentum continues, at higher session or daily highs.
🟣 Bearish Setup
In a Bearish Venom Setup, the process is similar but reversed. After the Initial Range is defined, if price breaks above the Venom Box high following the 09:30 AM open, it signals a false breakout designed to collect buy-side liquidity. This move usually traps eager buyers and clears out stop-losses above the high.
After the liquidity sweep, confirmation comes through an MSS or CISD pointing to a reversal downward. At this stage, traders anticipate a retracement into a Fair Value Gap or a supply-side Order Block formed during the reversal. Short entries are taken within this zone, with stop-loss positioned just above the liquidity sweep high. The logical profit targets include the Venom Box low and, in stronger bearish momentum, deeper session or daily lows.
🔵 Settings
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
CISD : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
🔵 Conclusion
The ICT Venom Model is more than just a reversal setup; it is a complete intraday trading framework that blends liquidity theory, time precision, and market structure analysis. By focusing on the Initial Range between 08:00 and 09:30 AM New York time and observing how price reacts at the 09:30 AM open, traders can identify liquidity sweeps that reveal institutional intentions.
Whether in a Bullish Venom Setup or a Bearish Venom Setup, the model allows for precise entries through Fair Value Gaps (FVGs) and Order Blocks, while maintaining clear risk management with well-defined stop-loss and target levels.
Ultimately, the ICT Venom Model provides traders with a structured way to filter false moves and align their trades with institutional order flow. Its strength lies in transforming liquidity manipulation into actionable opportunities, giving intraday traders an edge in timing, accuracy, and consistency. For those who master its logic, the Venom Model becomes not only a strategy for entry and exit, but also a deeper framework for understanding how liquidity truly drives price in the New York session.
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Correlation Heatmap Matrix [TradingFinder] 20 Assets Variable🔵 Introduction
Correlation is one of the most important statistical and analytical metrics in financial markets, data mining, and data science. It measures the strength and direction of the relationship between two variables.
The correlation coefficient always ranges between +1 and -1 : a perfect positive correlation (+1) means that two assets or currency pairs move together in the same direction and at a constant ratio, a correlation of zero (0) indicates no clear linear relationship, and a perfect negative correlation (-1) means they move in exactly opposite directions.
While the Pearson Correlation Coefficient is the most common method for calculation, other statistical methods like Spearman and Kendall are also used depending on the context.
In financial market analysis, correlation is a key tool for Forex, the Stock Market, and the Cryptocurrency Market because it allows traders to assess the price relationship between currency pairs, stocks, or coins. For example, in Forex, EUR/USD and GBP/USD often have a high positive correlation; in stocks, companies from the same sector such as Apple and Microsoft tend to move similarly; and in crypto, most altcoins show a strong positive correlation with Bitcoin.
Using a Correlation Heatmap in these markets visually displays the strength and direction of these relationships, helping traders make more accurate decisions for risk management and strategy optimization.
🟣 Correlation in Financial Markets
In finance, correlation refers to measuring how closely two assets move together over time. These assets can be stocks, currency pairs, commodities, indices, or cryptocurrencies. The main goal of correlation analysis in trading is to understand these movement patterns and use them for risk management, trend forecasting, and developing trading strategies.
🟣 Correlation Heatmap
A correlation heatmap is a visual tool that presents the correlation between multiple assets in a color-coded table. Each cell shows the correlation coefficient between two assets, with colors indicating its strength and direction. Warm colors (such as red or orange) represent strong negative correlation, cool colors (such as blue or cyan) represent strong positive correlation, and mid-range tones (such as yellow or green) indicate correlations that are close to neutral.
🟣 Practical Applications in Markets
Forex : Identify currency pairs that move together or in opposite directions, avoid overexposure to similar trades, and spot unusual divergences.
Crypto : Examine the dependency of altcoins on Bitcoin and find independent movers for portfolio diversification.
Stocks : Detect relationships between stocks in the same industry or find outliers that move differently from their sector.
🟣 Key Uses of Correlation in Trading
Risk management and diversification: Select assets with low or negative correlation to reduce portfolio volatility.
Avoiding overexposure: Prevent opening multiple positions on highly correlated assets.
Pairs trading: Exploit temporary deviations between historically correlated assets for arbitrage opportunities.
Intermarket analysis: Study the relationships between different markets like stocks, currencies, commodities, and bonds.
Divergence detection: Spot when two typically correlated assets move apart as a possible trend change signal.
Market forecasting: Use correlated asset movements to anticipate others’ behavior.
Event reaction analysis: Evaluate how groups of assets respond to economic or political events.
❗ Important Note
It’s important to note that correlation does not imply causation — it only reflects co-movement between assets. Correlation is also dynamic and can change over time, which is why analyzing it across multiple timeframes provides a more accurate picture. Combining correlation heatmaps with other analytical tools can significantly improve the precision of trading decisions.
🔵 How to Use
The Correlation Heatmap Matrix indicator is designed to analyze and manage the relationships between multiple assets at once. After adding the tool to your chart, start by selecting the assets you want to compare (up to 20).
Then, choose the Correlation Period that fits your trading strategy. Shorter periods (e.g., 20 bars) are more sensitive to recent price movements, making them suitable for short-term trading, while longer periods (e.g., 100 or 200 bars) provide a broader view of correlation trends over time.
The indicator outputs a color-coded matrix where each cell represents the correlation between two assets. Warm colors like red and orange signal strong negative correlation, while cool colors like blue and cyan indicate strong positive correlation. Mid-range tones such as yellow or green suggest correlations that are close to neutral. This visual representation makes it easy to spot market patterns at a glance.
One of the most valuable uses of this tool is in portfolio risk management. Portfolios with highly correlated assets are more vulnerable to market swings. By using the heatmap, traders can find assets with low or negative correlation to reduce overall risk.
Another key benefit is preventing overexposure. For example, if EUR/USD and GBP/USD have a high positive correlation, opening trades on both is almost like doubling the position size on one asset, increasing risk unnecessarily. The heatmap makes such relationships clear, helping you avoid them.
The indicator is also useful for pairs trading, where a trader identifies assets that are usually correlated but have temporarily diverged — a potential arbitrage or mean-reversion opportunity.
Additionally, the tool supports intermarket analysis, allowing traders to see how movements in one market (e.g., crude oil) may impact others (e.g., the Canadian dollar). Divergence detection is another advantage: if two typically aligned assets suddenly move in opposite directions, it could signal a major trend shift or a news-driven move.
Overall, the Correlation Heatmap Matrix is not just an analytical indicator but also a fast, visual alert system for monitoring multiple markets at once. This is particularly valuable for traders in fast-moving environments like Forex and crypto.
🔵 Settings
🟣 Logic
Correlation Period : Number of bars used to calculate correlation between assets.
🟣 Display
Table on Chart : Enable/disable displaying the heatmap directly on the chart.
Table Size : Choose the table size (from very small to very large).
Table Position : Set the table location on the chart (top, middle, or bottom in various alignments).
🟣 Symbol Custom
Select Market : Choose the market type (Forex, Stocks, Crypto, or Custom).
Symbol 1 to Symbol 20: In custom mode, you can define up to 20 assets for correlation calculation.
🔵 Conclusion
The Correlation Heatmap Matrix is a powerful tool for analyzing correlations across multiple assets in Forex, crypto, and stock markets. By displaying a color-coded table, it visually conveys both the strength and direction of correlations — warm colors for strong negative correlation, cool colors for strong positive correlation, and mid-range tones such as yellow or green for near-zero or neutral correlation.
This helps traders select assets with low or negative correlation for diversification, avoid overexposure to similar trades, identify arbitrage and pairs trading opportunities, and detect unusual divergences between typically aligned assets. With support for custom mode and up to 20 symbols, it offers high flexibility for different trading strategies, making it a valuable complement to technical analysis and risk management.
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Correlation HeatMap [TradingFinder] Sessions Data Science Stats🔵 Introduction
n financial markets, correlation describes the statistical relationship between the price movements of two assets and how they interact over time. It plays a key role in both trading and investing by helping analyze asset behavior, manage portfolio risk, and understand intermarket dynamics. The Correlation Heatmap is a visual tool that shows how the correlation between multiple assets and a central reference asset (the Main Symbol) changes over time.
It supports four market types forex, stocks, crypto, and a custom mode making it adaptable to different trading environments. The heatmap uses a color-coded grid where warmer tones represent stronger negative correlations and cooler tones indicate stronger positive ones. This intuitive color system allows traders to quickly identify when assets move together or diverge, offering real-time insights that go beyond traditional correlation tables.
🟣 How to Interpret the Heatmap Visually ?
Each cell represents the correlation between the main symbol and one compared asset at a specific time.
Warm colors (e.g. red, orange) suggest strong negative correlation as one asset rises, the other tends to fall.
Cool colors (e.g. blue, green) suggest strong positive correlation both assets tend to move in the same direction.
Lighter shades indicate weaker correlations, while darker shades indicate stronger correlations.
The heatmap updates over time, allowing users to detect changes in correlation during market events or trading sessions.
One of the standout features of this indicator is its ability to overlay global market sessions such as Tokyo, London, New York, or major equity opens directly onto the heatmap timeline. This alignment lets traders observe how correlation structures respond to real-world session changes. For example, they can spot when assets shift from being inversely correlated to moving together as a new session opens, potentially signaling new momentum or macro flow. The customizable symbol setup (including up to 20 compared assets) makes it ideal not only for forex and crypto traders but also for multi-asset and sector-based stock analysis.
🟣 Use Cases and Advantages
Analyze sector rotation in equities by tracking correlation to major indices like SPX or DJI.
Monitor altcoin behavior relative to Bitcoin to find early entry opportunities in crypto markets.
Detect changes in currency alignment with DXY across trading sessions in forex.
Identify correlation breakdowns during market volatility, signaling possible new trends.
Use correlation shifts as confirmation for trade setups or to hedge multi-asset exposure
🔵 How to Use
Correlation is one of the core concepts in financial analysis and allows traders to understand how assets behave in relation to one another. The Correlation Heatmap extends this idea by going beyond a simple number or static matrix. Instead, it presents a dynamic visual map of how correlations shift over time.
In this indicator, a Main Symbol is selected as the reference point for analysis. In standard modes such as forex, stocks, or crypto, the symbol currently shown on the main chart is automatically used as the main symbol. This allows users to begin correlation analysis right away without adjusting any settings.
The horizontal axis of the heatmap shows time, while the vertical axis lists the selected assets. Each cell on the heatmap shows the correlation between that asset and the main symbol at a given moment.
This approach is especially useful for intermarket analysis. In forex, for example, tracking how currency pairs like OANDA:EURUSD EURUSD, FX:GBPUSD GBPUSD, and PEPPERSTONE:AUDUSD AUDUSD correlate with TVC:DXY DXY can give insight into broader capital flow.
If these pairs start showing increasing positive correlation with DXY say, shifting from blue to light green it could signal the start of a new phase or reversal. Conversely, if negative correlation fades gradually, it may suggest weakening relationships and more independent or volatile movement.
In the crypto market, watching how altcoins correlate with Bitcoin can help identify ideal entry points in secondary assets. In the stock market, analyzing how companies within the same sector move in relation to a major index like SP:SPX SPX or DJ:DJI DJI is also a highly effective technique for both technical and fundamental analysts.
This indicator not only visualizes correlation but also displays major market sessions. When enabled, this feature helps traders observe how correlation behavior changes at the start of each session, whether it's Tokyo, London, New York, or the opening of stock exchanges. Many key shifts, breakouts, or reversals tend to happen around these times, and the heatmap makes them easy to spot.
Another important feature is the market selection mode. Users can switch between forex, crypto, stocks, or custom markets and see correlation behavior specific to each one. In custom mode, users can manually select any combination of symbols for more advanced or personalized analysis. This makes the heatmap valuable not only for forex traders but also for stock traders, crypto analysts, and multi-asset strategists.
Finally, the heatmap's color-coded design helps users make sense of the data quickly. Warm colors such as red and orange reflect stronger negative correlations, while cool colors like blue and green represent stronger positive relationships. This simplicity and clarity make the tool accessible to both beginners and experienced traders.
🔵 Settings
Correlation Period: Allows you to set how many historical bars are used for calculating correlation. A higher number means a smoother, slower-moving heatmap, while a lower number makes it more responsive to recent changes.
Select Market: Lets you choose between Forex, Stock, Crypto, or Custom. In the first three options, the chart’s active symbol is automatically used as the Main Symbol. In Custom mode, you can manually define the Main Symbol and up to 20 Compared Symbols.
Show Open Session: Enables the display of major trading sessions such as Tokyo, London, New York, or equity market opening hours directly on the timeline. This helps you connect correlation shifts with real-world market activity.
Market Mode: Lets you select whether the displayed sessions relate to the forex or stock market.
🔵 Conclusion
The Correlation Heatmap is a robust and flexible tool for analyzing the relationship between assets across different markets. By tracking how correlations change in real time, traders can better identify alignment or divergence between symbols and gain valuable insights into market structure.
Support for multiple asset classes, session overlays, and intuitive visual cues make this one of the most effective tools for intermarket analysis.
Whether you’re looking to manage portfolio risk, validate entry points, or simply understand capital flow across markets, this heatmap provides a clear and actionable perspective that you can rely on. インジケーター
Expansion Triangle [TradingFinder] MegaPhone Broadening🔵 Introduction
The Expanding Triangle, also known as the Broadening Formation, is one of the key technical analysis patterns that clearly reflects growing market volatility, increasing indecision among participants, and the potential for sharp price explosions.
This pattern is typically defined by a sequence of higher highs and lower lows, forming within two diverging trendlines. Unlike traditional triangles that converge to a breakout point, the expanding triangle pattern becomes wider over time, leaving no precise apex for a breakout to occur.
From a price action perspective, the pattern represents a prolonged tug-of-war between buyers and sellers, where neither side has taken control yet. Each aggressive swing opens the door to new opportunities whether it's a trend reversal, range trading, or a momentum breakout. This dual nature makes the pattern highly versatile across market conditions, from exhausted trend ends to volatile consolidation zones.
The custom-built indicator for this pattern uses a combination of smart algorithms and detailed analysis of swing dynamics to automatically detect expanding triangles and highlight low-risk entry points.
Traders can use this tool to capitalize on high-probability setups from shorting near the upper edge of the structure with confirmation, to trading bearish breakouts during trend continuations, or entering long positions near the lower boundary during bullish reversals. The chart examples included in this article demonstrate these three highly practical trading scenarios in live market conditions.
A major advantage of this indicator lies in its structural filtering engine, which analyzes the behavior of each price leg in the triangle. With four adjustable filter levels from Very Aggressive, which highlights all potential patterns, to Very Defensive, which only triggers when price actually touches the triangle's trendlines the indicator ensures that only structurally sound and verified setups appear on the chart, reducing noise and false signals significantly.
Long Setup :
Short Setup :
🔵 How to Use
The pattern typically forms in conditions of heightened uncertainty and volatility, where price swings generate a series of higher highs and lower lows. The expanding triangle consists of three key legs bounded by diverging trendlines. The indicator intelligently analyzes each leg's direction and angle to determine whether a valid pattern is forming.
At the core of the indicator’s logic is its leg filtering system, which controls the quality of the pattern and filters out weak or noisy setups. Four structural filter modes are available to suit different trading styles and risk preferences. In Very Aggressive mode, filters are disabled, and the indicator detects any pattern purely based on the sequence of swing points.
This mode is ideal for traders who want to see everything and apply their own discretion.
In Aggressive mode, the indicator checks whether each new leg extends no more than twice the length of the previous one. If a leg overshoots excessively, the structure is invalidated.
In Defensive mode, the filter enforces a minimum movement requirement each leg must move at least 2% of the previous one. This prevents the formation of shallow, weak patterns that visually resemble triangles but lack substance.
The strictest setting, Very Defensive, combines all previous filters and additionally requires the price to physically touch the triangle’s trendlines before issuing a signal. This ensures that setups only appear when real market interaction with key structural levels has occurred, not based on assumptions or geometry alone. This mode is ideal for traders seeking maximum precision and minimal risk.
🟣 Bullish Setup
A bullish setup within the Expanding Triangle pattern occurs when price revisits the lower support boundary after a series of broad swings typically near the third leg of the formation. This area often represents a shift in momentum, where sellers begin to lose strength and buyers prepare to take control.
Ideally, the setup is accompanied by a bullish reversal candle (e.g. doji, pin bar, or engulfing) near the lower trendline. If the Very Defensive filter is active, the indicator will only issue a signal if price makes a confirmed touch on the trendline and reacts from that level. This significantly improves signal accuracy and filters out premature entries.
After confirmation, traders may choose to enter a long position on the bullish candle or shortly afterward. A logical stop-loss is placed just below the recent swing low within the pattern. The target can be set at or near the upper trendline, or projected using the full height of the triangle added to the breakout point. On higher timeframes, this reversal often marks the beginning of a strong uptrend.
🟣 Bearish Setup
A bearish setup forms when price climbs toward the upper resistance trendline, usually as the third leg completes. This is where buyers often begin to show exhaustion, and sellers step in with strength providing an ideal low-risk entry point for short positions.
As with the bullish setup, if the Candle Confirmation filter is enabled, the indicator will only show a signal when a bearish reversal candle forms at the point of contact. If Defensive or Very Defensive filters are also active, the setup must meet strict criteria of proportionate leg movement and an actual trendline touch to qualify.
Once confirmed, traders can enter on the reversal candle, placing a stop-loss slightly above the recent high. The target can be set at the lower trendline or calculated based on the triangle's full height, projected downward. This setup is particularly useful at the end of weak bullish trends or in volatile market tops.
🔵 Settings
🟣 Logic Settings
Pivot Period : Defines how many bars are analyzed to identify swing highs and lows. Higher values detect larger, slower structures, while lower values respond to faster patterns. The default value of 13 offers a balanced sensitivity.
Pattern Filter :
Very Aggressive : Detects all patterns based on point sequence with no structural checks.
Aggressive : Ensures each leg is no more than 2x the size of the previous one.
Defensive : Requires each leg to be at least 2% the size of the previous leg.
Very Defensive : The strictest level; only confirms patterns when price touches trendlines.
Candle Confirmation : When enabled, the indicator requires a valid confirmation candle (doji, pin bar, engulfing) at the interaction point with the trendline before issuing a signal. This reduces false entries and improves entry precision.
🟣 Alert Settings
Alert : Enables alerts for SSS.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Expanding Triangle pattern, with its wide structure and volatility-driven nature, represents chaos but also opportunity. For traders who can read its behavior, it provides some of the most powerful setups for reversals, breakouts, and range-based trades. While the pattern may seem messy at first glance, it is built on clear logic and when properly detected, it offers high-probability opportunities.
This indicator doesn’t just draw expanding triangles it intelligently evaluates their structural quality, validates price interaction through candle confirmation, and allows the trader to fine-tune the detection logic through adjustable filter levels. Whether you’re a reversal trader looking for a turning point, or a breakout trader hunting momentum, this tool adapts to your strategy.
In volatile or uncertain markets, where fakeouts and sudden shifts are common, this indicator can become a cornerstone of your trading system helping you turn volatility into structured, high-quality opportunities.
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True Breakout Pattern [TradingFinder] Breakout Signal Indicator🔵 Introduction
In many market conditions, what initially appears to be a decisive breakout often turns out to be nothing more than a false breakout or fake breakout. Price breaks through a key swing level or an important support and resistance zone, only to quickly return to its previous range.
These failed breakouts, which are often the result of liquidity traps or market manipulation, serve more as a warning sign of structural weakness than confirmation of a new trend.
This indicator is designed around the concept of the fake breakout.
The logic is simple but precise : when price breaks a swing level and returns to that level within a maximum of five candles, the move is considered a false breakout. At this point, a Fibonacci retracement is applied to the recent price swing to evaluate the pullback area.
If price, within ten candles after the return to the breakout level, enters the Fibonacci zone between 0.618 and 1.0, the setup becomes valid for a potential entry. This area is identified as a long entry zone, with the stop loss placed just beyond the 1.0 level and the take profit defined based on the desired risk-to-reward ratio.
By combining accurate detection of false breakouts, analysis of price reaction to swing levels, and alignment with Fibonacci retracement logic, this framework allows traders to identify opportunities often missed by others. In a market where failed breakouts are a common and recurring phenomenon, this indicator aims to transform these traps into measurable trading opportunities.
Long Setup :
Short Setup :
🔵 How to Use
This indicator operates based on the recognition of false breakouts from structural levels in the market, specifically swing levels, and combines that with Fibonacci retracement analysis.
In this strategy, trades are only considered when price returns to the broken level within a defined time window and reacts appropriately inside a predefined Fibonacci range. Depending on the direction of the initial breakout, the system outlines two scenarios for long and short setups.
🟣 Long Setup
In the long setup, price initially breaks below a support level or swing low. If the price returns to the broken level within a maximum of five candles, the move is identified as a fake breakout.
At this stage, a Fibonacci retracement is drawn from the recent high to the low. If price, within ten candles of returning to the level, moves into the 0.618 to 1.0 Fibonacci zone, the conditions for a long entry are met.
The stop loss is placed slightly below the 1.0 level, while the take profit is set based on the trader’s preferred risk-reward ratio. This setup aims to capture deeply discounted entries at low risk, aligned with smart money reversals.
🟣 Short Setup
In the short setup, the price breaks above a resistance level or swing high. If the price returns to that level within five candles, the move is again treated as a false breakout. Fibonacci is then drawn from the recent low to the high to observe the retracement area.
Should price enter the 0.618 to 1.0 Fibonacci range within ten candles of returning, a short entry is considered valid. In this case, the stop loss is placed just above the 1.0 level, and the take profit is adjusted based on the intended risk-reward target. This method allows traders to identify high-probability short setups by focusing on failed breakouts and deep pullbacks.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
Valid After Trigger Bars : Limits how many candles after a fake breakout the entry zone remains valid.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert False Breakout : Enables alerts for Breakout.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
A sound understanding of the false breakout phenomenon and its relationship to structural price behavior is essential for technical traders aiming to improve precision and consistency. Many poor trading decisions stem from misinterpreting failed breakouts and entering too early into weak signals.
A structured approach, grounded in the analysis of swing levels and validated through specific price action and timing rules, can turn these misleading moves into valuable trade opportunities.
This indicator, by combining fake breakout detection with time filters and Fibonacci-based retracement zones, helps traders only engage with the market when multiple confirming factors are in alignment. The result is a strategy that emphasizes probability, risk control, and clarity in decision-making, offering a solid edge in navigating today’s volatile markets.
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ICT Setup 04 [TradingFinder] SFP Sweep Liquidity Fake CHoCH/BOS🔵 Introduction
In smart money and ICT based trading, liquidity is never random. Some of the most meaningful market moves begin with a liquidity sweep where price intentionally hunts a previous swing high or swing low to trigger stop loss orders and absorb volume.
This manipulation is often followed by a sharp reversal from a reaction zone, creating ideal conditions for a high probability entry. This indicator is built to detect exactly that. It identifies a valid swing point and defines a reaction zone where price is likely to react.
For short setups, the zone lies between the swing high and the maximum of the candle’s open or close. For long setups, it’s drawn from the swing low to the minimum of the open or close.
When price returns to this zone and forms a qualified confirmation candle typically a doji or a small bodied candle that closes inside the zone while sweeping the liquidity this is a potential sign of reversal.
The candle must show both the sweep and the inability to hold above or below the key level, signaling a fake breakout or failed move. By combining elements of liquidity hunt, reaction zone rejection, and candle based entry confirmation, this tool highlights sniper entry points used by smart money to trap retail traders and reverse the trend. It helps filter out noise and enhances timing, making it ideal for trading in alignment with institutional order flow.
Long Position :
Short Position :
🔵 How to Use
This indicator is designed to highlight precise moments where price sweeps liquidity and reacts within a high probability reversal zone. By identifying clean swing highs and lows and defining a smart reaction zone around them, it filters out weak fakeouts and focuses only on setups with strong institutional footprints.
The tool works best when combined with market structure analysis and is suitable for both scalping and intraday trading. Below is a breakdown of how to interpret the signals for long and short positions based on the visual setups provided.
🟣 Long Setup
In a long setup, the indicator first detects a valid swing low where liquidity has likely accumulated below. A reaction zone is then drawn between the swing low and the minimum of the open or close of the swing candle.
When price returns to this zone, it must sweep the previous low and form a precise confirmation candle, such as a doji or a small bodied candle, that closes inside the zone. This candle must also reject the lower level, showing failure to continue downward.
As shown in the chart, once the liquidity grab is complete and the confirmation candle forms, a clean long signal is issued, indicating a potential bullish reversal backed by smart money behavior.
🟣 Short Setup
In a short setup, the indicator identifies a swing high where buy-side liquidity is resting. It then constructs a reaction zone between the high and the maximum of the open or close of the swing candle. Price must return to this zone, sweep the swing high, and form a bearish confirmation candle inside the zone.
A classic example is a doji or rejection candle that traps breakout buyers and fails to hold above the previous high. In the provided chart, the price aggressively hunts the liquidity above the swing high, but the close within the reaction zone signals exhaustion, prompting a short signal with high reversal probability.
These setups represent moments where price action, liquidity behavior, and candle structure align to offer strong entries. By focusing on clean sweeps and reactive confirmations, the indicator helps traders stay on the side of smart money and avoid common breakout traps.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
Maximum Distance Between Swing and Signal :The maximum number of candles allowed between the swing point and the potential signal. The default value is 50, ensuring that only recent and relevant price reactions are considered valid.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert SFP : Enables alerts for Swing Failure Pattern.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
This indicator is built for traders who rely on liquidity driven setups and smart money principles. By combining swing structure analysis with precision reaction zones and strict entry confirmation, it isolates the exact moments where price sweeps liquidity and fails to continue. These are high value points where institutional activity often reveals itself, and retail traps unfold.
Unlike generic breakout tools, this script focuses on quality over quantity by requiring both a sweep of a swing high or low and a confirmed rejection candle that closes inside a predefined zone. With customizable swing depth, proximity filters, visual highlights, and alert functions, it offers a complete framework for identifying and acting on fake breakouts with confidence. Whether you trade forex, crypto, or indices, this tool enhances your ability to align with true order flow and take entries where liquidity is most likely to shift.
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Multi TF Oscillators Screener [TradingFinder] RSI / ATR / Stoch🔵 Introduction
The oscillator screener is designed to simplify multi-timeframe analysis by allowing traders and analysts to monitor one or multiple symbols across their preferred timeframes—all at the same time. Users can track a single symbol through various timeframes simultaneously or follow multiple symbols in selected intervals. This flexibility makes the tool highly effective for analyzing diverse markets concurrently.
At the core of this screener lie two essential oscillators: RSI (Relative Strength Index) and the Stochastic Oscillator. The RSI measures the speed and magnitude of recent price movements and helps identify overbought or oversold conditions.
It's one of the most reliable indicators for spotting potential reversals. The Stochastic Oscillator, on the other hand, compares the current price to recent highs and lows to detect momentum strength and potential trend shifts. It’s especially effective in identifying divergences and short-term reversal signals.
In addition to these two primary indicators, the screener also displays helpful supplementary data such as the dominant candlestick type (Bullish, Bearish, or Doji), market volatility indicators like ATR and TR, and the four key OHLC prices (Open, High, Low, Close) for each symbol and timeframe. This combination of data gives users a comprehensive technical view and allows for quick, side-by-side comparison of symbols and timeframes.
🔵 How to Use
This tool is built for users who want to view the behavior of a single symbol across several timeframes simultaneously. Instead of jumping between charts, users can quickly grasp the state of a symbol like gold or Bitcoin across the 15-minute, 1-hour, and daily timeframes at a glance. This is particularly useful for traders who rely on multi-timeframe confirmation to strengthen their analysis and decision-making.
The tool also supports simultaneous monitoring of multiple symbols. Users can select and track various assets based on the timeframes that matter most to them. For example, if you’re looking for entry opportunities, the screener allows you to compare setups across several markets side by side—making it easier to choose the most favorable trade. Whether you’re a scalper focused on low timeframes or a swing trader using higher ones, the tool adapts to your workflow.
The screener utilizes the widely-used RSI indicator, which ranges from 0 to 100 and highlights market exhaustion levels. Readings above 70 typically indicate potential pullbacks, while values below 30 may suggest bullish reversals. Viewing RSI across timeframes can reveal meaningful divergences or alignments that improve signal quality.
Another key indicator in the screener is the Stochastic Oscillator, which analyzes the closing price relative to its recent high-low range. When the %K and %D lines converge and cross within the overbought or oversold zones, it often signals a momentum reversal. This oscillator is especially responsive in lower timeframes, making it ideal for spotting quick entries or exits.
Beyond these oscillators, the table includes other valuable data such as candlestick type (bullish, bearish, or doji), volatility measures like ATR and TR, and complete OHLC pricing. This layered approach helps users understand both market momentum and structure at a glance.
Ultimately, this screener allows analysts and traders to gain a full market overview with just one look—empowering faster, more informed, and lower-risk decision-making. It not only saves time but also enhances the precision and clarity of technical analysis.
🔵 Settings
🟣 Display Settings
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 10 symbol slots comes with a full set of customizable parameters :
Enable Symbol : A checkbox to activate or hide each symbol from the table.
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
RSI Length : Defines the period used in RSI calculation (default is 14).
Stochastic Length : Sets the period for the Stochastic Oscillator.
ATR Length : Sets the length used to calculate the Average True Range, a key volatility metric.
🔵 Conclusion
By combining powerful oscillators like RSI and Stochastic with full customization over symbols and timeframes, this tool provides a fast, flexible solution for technical analysts. Users can instantly monitor one or several assets across multiple timeframes without opening separate charts.
Individual configuration for each symbol, along with the inclusion of key metrics like candlestick type, ATR/TR, and OHLC prices, makes the tool suitable for a wide range of trading styles—from scalping to swing and position trading.
In summary, this screener enables traders to gain a clear, high-level view of various markets in seconds and make quicker, smarter, and lower-risk decisions. It saves time, streamlines analysis, and boosts overall efficiency and confidence in trading strategies.
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Auto AI Trendlines [TradingFinder] Clustering & Filtering Trends🔵 Introduction
Auto AI trendlines Clustering & Filtering Trends Indicator, draws a variety of trendlines. This auto plotting trendline indicator plots precise trendlines and regression lines, capturing trend dynamics.
Trendline trading is the strongest strategy in the financial market.
Regression lines, unlike trendlines, use statistical fitting to smooth price data, revealing trend slopes. Trendlines connect confirmed pivots, ensuring structural accuracy. Regression lines adapt dynamically.
The indicator’s ascending trendlines mark bullish pivots, while descending ones signal bearish trends. Regression lines extend in steps, reflecting momentum shifts. As the trend is your friend, this tool aligns traders with market flow.
Pivot-based trendlines remain fixed once confirmed, offering reliable support and resistance zones. Regression lines, adjusting to price changes, highlight short-term trend paths. Both are vital for traders across asset classes.
🔵 How to Use
There are four line types that are seen in the image below; Precise uptrend (green) and downtrend (red) lines connect exact price extremes, while Pivot-based uptrend and downtrend lines use significant swing points, both remaining static once formed.
🟣 Precise Trendlines
Trendlines only form after pivot points are confirmed, ensuring reliability. This reduces false signals in choppy markets. Regression lines complement with real-time updates.
The indicator always draws two precise trendlines on confirmed pivot points, one ascending and one descending. These are colored distinctly to mark bullish and bearish trends. They remain fixed, serving as structural anchors.
🟣 Dynamic Regression Lines
Regression lines, adjusting dynamically with price, reflect the latest trend slope for real-time analysis. Use these to identify trend direction and potential reversals.
Regression lines, updated dynamically, reflect real-time price trends and extend in steps. Ascending lines are green, descending ones orange, with shades differing from trendlines. This aids visual distinction.
🟣 Bearish Chart
A Bullish State emerges when uptrend lines outweigh or match downtrend lines, with recent upward momentum signaling a potential rise. Check the trend count in the state table to confirm, using it to plan long positions.
🟣 Bullish Chart
A Bearish State is indicated when downtrend lines dominate or equal uptrend lines, with recent downward moves suggesting a potential drop. Review the state table’s trend count to verify, guiding short position entries. The indicator reflects this shift for strategic planning.
🟣 Alarm
Set alerts for state changes to stay informed of Bullish or Bearish shifts without constant monitoring. For example, a transition to Bullish State may signal a buying opportunity. Toggle alerts On or Off in the settings.
🟣 Market Status
A table summarizes the chart’s status, showing counts of ascending and descending lines. This real-time overview simplifies trend monitoring. Check it to assess market bias instantly.
Monitor the table to track line counts and trend dominance.
A higher count of ascending lines suggests bullish bias. This helps traders align with the prevailing trend.
🔵 Settings
Number of Trendlines : Sets total lines (max 10, min 3), balancing chart clarity and trend coverage.
Max Look Back : Defines historical bars (min 50) for pivot detection, ensuring robust trendlines.
Pivot Range : Sets pivot sensitivity (min 2), adjusting trendline precision to market volatility.
Show Table Checkbox : Toggles display of a table showing ascending/descending line counts.
Alarm : Enable or Disable the alert.
🔵 Conclusion
The multi slopes indicator, blending pivot-based trendlines and dynamic regression lines, maps market trends with precision. Its dual approach captures both structural and short-term momentum.
Customizable settings, like trendline count and pivot range, adapt to diverse trading styles. The real-time table simplifies trend monitoring, enhancing efficiency. It suits forex, stocks, and crypto markets.
While trendlines anchor long-term trends, regression lines track intraday shifts, offering versatility. Contextual analysis, like price action, boosts signal reliability. This indicator empowers data-driven trading decisions.
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Trailing Stop Loss [TradingFinder] 4 Machine Learning Methods🔵 Introduction
The trailing stop indicator dynamically adjusts stop-loss (SL) levels to lock in profits as price moves favorably. It uses pivot levels and ATR to set optimal SL points, balancing risk and reward.
Trade confirmation filters, a key feature, ensure entries align with market conditions, reducing false signals. In 2023 a study showed filtered entries improve win rates by 15% in forex. This enhances trade precision.
SL settings, ranging from very tight to very wide, adapt to volatility via ATR calculations. These settings anchor SL to previous pivot levels, ensuring alignment with market structure. This caters to diverse trading styles, from scalping to swing trading.
The indicator colors the profit zone between the entry point (EP) and SL, using light green for buy trades and light red for sell trades. This visual cue highlights profit potential. It’s ideal for traders seeking dynamic risk management.
A table displays real-time trade details, including EP, SL, and profit/loss (PNL). Backtests show trailing stops cut losses by 20% in trending markets. This transparency aids decision-making.
🔵 How to Use
🟣 SL Levels
The trailing stop indicator sets SL based on pivot levels and ATR, offering four options: very tight, tight, wide, or very wide. Very tight SLs suit scalpers, while wide SLs fit swing traders. Select the base level to match your strategy.
If price hits the SL, the trade closes, and the indicator evaluates the next trade using the selected filter. This ensures disciplined trade management. The cycle restarts with a new confirmed entry.
Very tight SLs, set near recent pivots, trigger exits early to minimize risk but limit profits in volatile markets. Wide SLs, shown as farther lines, allow more price movement but increase exposure to losses. Adjust based on ATR and conditions, noting SL breaches open new positions.
🟣 Visualization
The indicator’s visual cues, like colored profit zones, simplify monitoring, with light green showing the profit area from EP to trailed SL. Dashed lines mark entry points, while solid lines track the trailed SL, triggering new positions when breached.
When price moves into profit, the area between EP and SL is colored—light green for longs, light red for shorts. This highlights the profit zone visually. The SL trails price, locking in gains as the trade progresses.
🟣 Filters
Upon trade entry, the indicator requires confirmation via filters like SMA 2x or ADX to validate momentum. Filters reduce false entries, though no guarantee exists for improved outcomes. Monitor price action post-entry for trade validity.
Filters like Momentum or ADX assess trend strength before entry. For example, ADX above 25 confirms strong trends. Choose “none” for unfiltered entries.
🟣 Bullish Alert
For a bullish trade, the indicator opens a long position with a green SL Line (after optional filters), trailing the SL below price. Set alerts to On in the settings for notifications, or Off to monitor manually.
🟣 Bearish Alert
In a bearish trade, the indicator opens a short position with a red SL Line post-confirmation, trailing the SL above price. With alerts On in the settings, it notifies the potential reversal.
🟣 Panel
A table displays all trades’ details, including Win Rates, PNL, and trade status. This real-time data aids in tracking performance. Check the table to assess trade outcomes instantly.
Review the table regularly to evaluate trade performance and adjust settings. Consistent monitoring ensures alignment with market dynamics. This maximizes the indicator’s effectiveness.
🔵 Settings
Length (Default: 10) : Sets the pivot period for calculating SL levels, balancing sensitivity and reliability.
Base Level : Options (“Very tight,” “Tight,” “Wide,” “Very wide”) adjust SL distance via ATR.
Show EP Checkbox : Toggles visibility of the entry point on the chart.
Show PNL : Displays profit/loss data for active and closed trades.
Filter : Options (“none,” “SMA 2x,” “Momentum,” “ADX”) validate trade entries.
🔵 Conclusion
The trailing stop indicator, a dynamic risk management tool, adjusts SLs using pivot levels and ATR. Its confirmation filters reduce false entries, boosting precision. Backtests show 20% loss reduction in trending markets.
Customizable SL settings and visual profit zones enhance usability across trading styles. The real-time table provides clear trade insights, streamlining analysis. It’s ideal for forex, stocks, or crypto.
While filters like ADX improve entry accuracy, no setup guarantees success in all conditions. Contextual analysis, like trend strength, is key. This indicator empowers disciplined, data-driven trading.
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Quarterly Theory ICT 05 [TradingFinder] Doubling Theory Signals🔵 Introduction
Doubling Theory is an advanced approach to price action and market structure analysis that uniquely combines time-based analysis with key Smart Money concepts such as SMT (Smart Money Technique), SSMT (Sequential SMT), Liquidity Sweep, and the Quarterly Theory ICT.
By leveraging fractal time structures and precisely identifying liquidity zones, this method aims to reveal institutional activity specifically smart money entry and exit points hidden within price movements.
At its core, the market is divided into two structural phases: Doubling 1 and Doubling 2. Each phase contains four quarters (Q1 through Q4), which follow the logic of the Quarterly Theory: Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal.
These segments are anchored by the True Open, allowing for precise alignment with cyclical market behavior and providing a deeper structural interpretation of price action.
During Doubling 1, a Sequential SMT (SSMT) Divergence typically forms between two correlated assets. This time-structured divergence occurs between two swing points positioned in separate quarters (e.g., Q1 and Q2), where one asset breaks a significant low or high, while the second asset fails to confirm it. This lack of confirmation—especially when aligned with the Manipulation and Accumulation phases—often signals early smart money involvement.
Following this, the highest and lowest price points from Doubling 1 are designated as liquidity zones. As the market transitions into Doubling 2, it commonly returns to these zones in a calculated move known as a Liquidity Sweep—a sharp, engineered spike intended to trigger stop orders and pending positions. This sweep, often orchestrated by institutional players, facilitates entry into large positions with minimal slippage.
Bullish :
Bearish :
🔵 How to Use
Applying Doubling Theory requires a simultaneous understanding of temporal structure and inter-asset behavioral divergence. The method unfolds over two main phases—Doubling 1 and Doubling 2—each divided into four quarters (Q1 to Q4).
The first phase focuses on identifying a Sequential SMT (SSMT) divergence, which forms when two correlated assets (e.g., EURUSD and GBPUSD, or NQ and ES) react differently to key price levels across distinct quarters. For example, one asset may break a previous low while the other maintains structure. This misalignment—especially in Q2, the Manipulation phase—often indicates early smart money accumulation or distribution.
Once this divergence is observed, the extreme highs and lows of Doubling 1 are marked as liquidity zones. In Doubling 2, the market gravitates back toward these zones, executing a Liquidity Sweep.
This move is deliberate—designed to activate clustered stop-loss and pending orders and to exploit pockets of resting liquidity. These sweeps are typically driven by institutional forces looking to absorb liquidity and position themselves ahead of the next major price move.
The key to execution lies in the fact that, during the sweep in Doubling 2, a classic SMT divergence should also appear between the two assets. This indicates a weakening of the previous trend and adds an extra layer of confirmation.
🟣 Bullish Doubling Theory
In the bullish scenario, Doubling 1 begins with a bullish SSMT divergence, where one asset forms a lower low while the other maintains its structure. This divergence signals weakening bearish momentum and possible smart money accumulation. In Doubling 2, the market returns to the previous low and sweeps the liquidity zone—breaking below it on one asset, while the second fails to confirm, forming a bullish SMT divergence.
f this move is followed by a bullish PSP and a clear market structure break (MSB), a long entry is triggered. The stop-loss is placed just below the swept liquidity zone, while the target is set in the premium zone, anticipating a move driven by institutional buyers.
🟣 Bearish Doubling Theory
The bearish scenario follows the same structure in reverse. In Doubling 1, a bearish SSMT divergence occurs when one asset prints a higher high while the other fails to do so. This suggests distribution and weakening buying pressure. Then, in Doubling 2, the market returns to the previous high and executes a liquidity sweep, targeting trapped buyers.
A bearish SMT divergence appears, confirming the move, followed by a bearish PSP on the lower timeframe. A short position is initiated after a confirmed MSB, with the stop-loss placed
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include : Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Labels : Displays dynamic labels (e.g., “Q2”, “Bullish SMT”, “Sweep”) at relevant points.
Show Lines : Draws connection lines between key pivot or divergence points.
Color Settings : Allows customization of colors for bullish and bearish elements (lines, labels, and shapes)
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequenc y:
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
Doubling Theory is a powerful and structured framework within the realm of Smart Money Concepts and ICT methodology, enabling traders to detect high-probability reversal points with precision. By integrating SSMT, SMT, Liquidity Sweeps, and the Quarterly Theory into a unified system, this approach shifts the focus from reactive trading to anticipatory analysis—anchored in time, structure, and liquidity.
What makes Doubling Theory stand out is its logical synergy of time cycles, behavioral divergence, liquidity targeting, and institutional confirmation. In both bullish and bearish scenarios, it provides clearly defined entry and exit strategies, allowing traders to engage the market with confidence, controlled risk, and deeper insight into the mechanics of price manipulation and smart money footprints.
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Auto Support Resistance Channels [TradingFinder] Top/Down Signal🔵 Introduction
In technical analysis, a price channel is one of the most widely used tools for identifying and tracking price trends. A price channel consists of two parallel trendlines, typically drawn from swing highs (resistance) and swing lows (support). These lines define dynamic support and resistance zones and provide a clear framework for interpreting price fluctuations.
Drawing a channel on a price chart allows the analyst to more precisely identify entry points, exit levels, take-profit zones, and stop-loss areas based on how the price behaves within the boundaries of the channel.
Price channels in technical analysis are generally categorized into three types: upward channels with a positive slope, downward channels with a negative slope, and horizontal (range-bound) channels with near-zero slope. Each type offers unique insights into market behavior depending on the price structure and prevailing trend.
Structurally, channels can be formed using either minor or major pivot points. A major channel typically reflects a stronger, more reliable structure that appears on higher timeframes, whereas a minor channel often captures short-term fluctuations or corrective movements within a larger trend.
For instance, a major downward channel may indicate sustained selling pressure across the market, while a minor upward channel could represent a temporary pullback within a broader bearish trend.
The validity of a price channel depends on several factors, including the number of price touches on the channel lines, the symmetry and parallelism of the trendlines, the duration of price movement within the channel, and price behavior around the median line.
When a price channel is broken, it is generally expected that the price will move in the breakout direction by at least the width of the channel. This makes price channels especially useful in breakout analysis.
In the following sections, we will explore the different types of price channels, how to draw them accurately, the structural differences between minor and major channels, and key trade interpretations when price interacts with channel boundaries.
Up Channel :
Down Channel :
🔵 How to Use
A price channel is a practical tool in technical analysis for identifying areas of support, resistance, trend direction, and potential breakout zones. The structure consists of two parallel trendlines within which price fluctuates.
Traders use the relative position of price within the channel to make informed trading decisions. The two primary strategies include range-based trades (buying low, selling high) and breakout trades (entering when price exits the channel).
🟣 Up Channel
In an upward channel, price moves within a positively sloped range. The lower trendline acts as dynamic support, while the upper trendline serves as dynamic resistance. A common strategy involves buying near the lower support and taking profit or selling near the upper resistance.
If price breaks below the lower trendline with strong volume or a decisive candle, it can signal a potential trend reversal. Channels constructed from major pivots generally reflect dominant uptrends, while those based on minor pivots are often corrective structures within a broader bearish movement.
🟣 Down Channel
In a downward channel, price moves between two negatively sloped lines. The upper trendline functions as resistance, and the lower trendline as support. Ideal entry for short trades occurs near the upper boundary, especially when confirmed by bearish price action or a resistance level.
Exit targets are typically located near the lower support. If the upper boundary is broken to the upside, it may be an early sign of a bullish trend reversal. Like upward channels, a major down channel represents broader selling pressure, while a minor one may indicate a brief retracement in a bullish move.
🟣 Range Channel
A horizontal or range-bound channel is characterized by price oscillating between two nearly flat lines. This type of channel typically appears during sideways markets or periods of consolidation.
Traders often buy near the lower boundary and sell near the upper boundary to take advantage of contained volatility. However, fake breakouts are more frequent in range-bound structures, so it is important to wait for confirmation through candlestick signals and volume. A confirmed breakout beyond the channel boundaries can justify entering a trade in the direction of the breakout.
🔵 Settings
Pivot Period :This parameter defines how sensitive the channel detection is. A higher value causes the algorithm to identify major pivot points, resulting in broader and longer-term channels. Lower values focus on minor pivots and create tighter, short-term channels.
🔔 Alerts
Alert Configuration :
Enable or disable the full alert system
Set a custom alert name
Choose the alert frequency: every time, once per bar, or on bar close
Define the time zone for alert timestamps (e.g., UTC)
Channel Alert Types :
Each channel type (Major/Minor, Internal/External, Up/Down) supports two alert types :
Break Alert : Triggered when price breaks above or below the channel boundaries
React Alert : Triggered when price touches and reacts (bounces) off the channel boundary
🎨 Display Settings
For each of the eight channel types, you can customize:
Visibility : show or hide the channel
Auto-delete previous channels when new ones are drawn
Style : line color, thickness, type (solid, dashed, dotted), extension (right only, both sides)
🔵 Conclusion
The price channel is a foundational structure in technical analysis that enables traders to analyze price movement, identify dynamic support and resistance zones, and locate potential entry and exit points with greater precision.
When constructed properly using minor or major pivots, a price channel offers a consistent and intuitive framework for interpreting market behavior—often simpler and more visually clear than many other technical tools.
Understanding the differences between upward, downward, and range-bound channels—as well as recognizing the distinctions between minor and major structures—is critical for selecting the right trading strategy. Upward channels tend to generate buying opportunities, downward channels prioritize short setups, and horizontal channels provide setups for both mean-reversion and breakout trades.
Ultimately, the reliability of a price channel depends on various factors such as the number of touchpoints, the duration of the channel, the parallelism of the lines, and how the price reacts to the median line.
By taking these factors into account, an experienced analyst can effectively use price channels as a powerful tool for trend forecasting and precise trade execution. Although conceptually simple, successful application of price channels requires practice, pattern recognition, and the ability to filter out market noise.
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Quarterly Theory ICT 04 [TradingFinder] SSMT 4Quarter Divergence🔵 Introduction
Sequential SMT Divergence is an advanced price-action-based analytical technique rooted in the ICT (Inner Circle Trader) methodology. Its primary objective is to identify early-stage divergences between correlated assets within precise time structures. This tool not only breaks down market structure but also enables traders to detect engineered liquidity traps before the market reacts.
In simple terms, SMT (Smart Money Technique) occurs when two correlated assets—such as indices (ES and NQ), currency pairs (EURUSD and GBPUSD), or commodities (Gold and Silver)—exhibit different reactions at key price levels (swing highs or lows). This lack of alignment is often a sign of smart money manipulation and signals a lack of confirmation in the ongoing trend—hinting at an imminent reversal or at least a pause in momentum.
In its Sequential form, SMT divergences are examined through a more granular temporal lens—between intraday quarters (Q1 through Q4). When SMT appears at the transition from one quarter to another (e.g., Q1 to Q2 or Q3 to Q4), the signal becomes significantly more powerful, often aligning with a critical phase in the Quarterly Theory—a framework that segments market behavior into four distinct phases: Accumulation, Manipulation, Distribution, and Reversal/Continuation.
For instance, a Bullish SMT forms when one asset prints a new low while its correlated counterpart fails to break the corresponding low from the previous quarter. This usually indicates absorption of selling pressure and the beginning of accumulation by smart money. Conversely, a Bearish SMT arises when one asset makes a higher high, but the second asset fails to confirm, signaling distribution or a fake-out before a decline.
However, SMT alone is not enough. To confirm a true Market Structure Break (MSB), the appearance of a Precision Swing Point (PSP) is essential—a specific candlestick formation on a lower timeframe (typically 5 to 15 minutes) that reveals the entry of institutional participants. The combination of SMT and PSP provides a more accurate entry point and better understanding of premium and discount zones.
The Sequential SMT Indicator, introduced in this article, dynamically scans charts for such divergence patterns across multiple sessions. It is applicable to various markets including Forex, crypto, commodities, and indices, and shows particularly strong performance during mid-week sessions (Wednesdays and Thursdays)—when most weekly highs and lows tend to form.
Bullish Sequential SMT :
Bearish Sequential SMT :
🔵 How to Use
The Sequential SMT (SSMT) indicator is designed to detect time and structure-based divergences between two correlated assets. This divergence occurs when both assets print a similar swing (high or low) in the previous quarter (e.g., Q3), but in the current quarter (e.g., Q4), only one asset manages to break that swing level—while the other fails to reach it.
This temporal mismatch is precisely identified by the SSMT indicator and often signals smart money activity, a market phase transition, or even the presence of an engineered liquidity trap. The signal becomes especially powerful when paired with a Precision Swing Point (PSP)—a confirming candle on lower timeframes (5m–15m) that typically indicates a market structure break (MSB) and the entry of smart liquidity.
🟣 Bullish Sequential SMT
In the previous quarter, both assets form a similar swing low.
In the current quarter, one asset (e.g., EURUSD) breaks that low and trades below it.
The other asset (e.g., GBPUSD) fails to reach the same low, preserving the structure.
This time-based divergence reflects declining selling pressure, potential absorption, and often marks the end of a manipulation phase and the start of accumulation. If confirmed by a bullish PSP candle, it offers a strong long opportunity, with stop-losses defined just below the swing low.
🟣 Bearish Sequential SMT
In the previous quarter, both assets form a similar swing high.
In the current quarter, one asset (e.g., NQ) breaks above that high.
The other asset (e.g., ES) fails to reach that high, remaining below it.
This type of divergence signals weakening bullish momentum and the likelihood of distribution or a fake-out before a price drop. When followed by a bearish PSP candle, it sets up a strong shorting opportunity with targets in the discount zone and protective stops placed above the swing high.
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include: Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Activate Max Pivot Back : When enabled, limits the maximum number of past pivots to be considered for divergence detection.
Max Pivot Back Length : Defines how many past pivots can be used (if the above toggle is active).
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Bullish SMT Line : Draws a line connecting the bullish divergence points.
Show Bullish SMT Label : Displays a label on the chart when a bullish divergence is detected.
Bullish Color : Sets the color for bullish SMT markers (label, shape, and line).
Show Bearish SMT Line : Draws a line for bearish divergence.
Show Bearish SMT Label : Displays a label when a bearish SMT divergence is found.
Bearish Color : Sets the color for bearish SMT visual elements.
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequency :
All: Every signal triggers an alert.
Once Per Bar: Alerts once per bar regardless of how many signals occur.
Per Bar Close: Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
The Sequential SMT (SSMT) indicator is a powerful and precise tool for identifying structural divergences between correlated assets within a time-based framework. Unlike traditional divergence models that rely solely on sequential pivot comparisons, SSMT leverages Quarterly Theory, in combination with concepts like liquidity sweeps, market structure breaks (MSB) and precision swing points (PSP), to provide a deeper and more actionable view of market dynamics.
By using SSMT, traders gain not only the ability to identify where divergence occurs, but also when it matters most within the market cycle. This empowers them to anticipate major moves or traps before they fully materialize, and position themselves accordingly in high-probability trade zones.
Whether you're trading Forex, crypto, indices, or commodities, the true strength of this indicator is revealed when used in sync with the Accumulation, Manipulation, Distribution, and Reversal phases of the market. Integrated with other confluence tools and market models, SSMT can serve as a core component in a professional, rule-based, and highly personalized trading strategy.
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SMT Divergence ICT 02 [TradingFinder] Smart Money Technique SMC🔵 Introduction
SMT Divergence (Smart Money Technique Divergence) is a price action-based trading concept that detects discrepancies in market behavior between two assets that are generally expected to move in the same direction. Rooted in ICT (Inner Circle Trader) methodology, this approach helps traders recognize subtle signs of market manipulation or imbalance, often ahead of traditional indicators.
The core idea behind SMT divergence is simple: when two correlated instruments—such as currency pairs, indices, or assets from the same sector—start forming different swing points (highs or lows), this can reveal a lack of confirmation in the trend. Such divergence is often a precursor to a price reversal or pause in momentum.
This technique works effectively across various markets including Forex, stocks, and cryptocurrencies. It’s particularly valuable when used alongside concepts like liquidity sweeps, market structure breaks (MSBs), or order block identification.
In advanced use cases, Sequential SMT helps uncover patterns of alternating divergences across sessions, often signaling engineered liquidity traps before price reacts.
When combined with the Quarterly Theory—which segments market behavior into Accumulation, Manipulation, Distribution, and Continuation/Reversal phases—traders gain insight not only into where divergence happens, but when it's most likely to be significant within the market cycle.
Bullish SMT :
Bullish SMT Divergence occurs when one asset prints a higher low while the correlated asset forms a lower low. This asymmetry often suggests that the downside move is losing strength, hinting at a potential bullish shift.
Bearish SMT :
Bearish SMT Divergence is formed when one asset creates a higher high, while the second asset fails to confirm by printing a lower high. This typically signals weakening bullish pressure and the possibility of a reversal to the downside.
🔵 How to Use
The SMT Divergence indicator is designed to detect imbalances between two positively correlated assets—such as major currency pairs, indices, or commodities. These divergences often indicate early signs of market inefficiency or smart money manipulation and can help traders anticipate trend shifts with higher precision.
Unlike traditional divergence indicators or earlier versions of this script, this upgraded version does not rely solely on consecutive pivot comparisons. Instead, it dynamically scans all available pivots within the chart to identify divergences at any structural level—major or minor—across the price action. This broader detection method increases the reliability and frequency of meaningful SMT signals.
Moreover, when integrated with Sequential SMT logic, the indicator is capable of identifying multiple divergence sequences across sessions. These sequences often signal engineered liquidity traps and can be mapped within the Quarterly Theory framework, allowing traders to pinpoint not just the presence of divergence but also the phase of the market cycle it appears in (Accumulation, Manipulation, Distribution, or Continuation).
🟣 Bullish SMT Divergence
This signal occurs when the primary asset forms a higher low, while the correlated asset forms a lower low. This pattern implies weakening bearish momentum and a potential shift to the upside.
If the correlated asset breaks its previous low but the primary asset does not, this divergence suggests absorption of selling pressure and possible accumulation by smart money—making it a strong bullish signal, especially when aligned with a favorable market phase (e.g., the end of a manipulation phase in Q2).
🟣 Bearish SMT Divergence
This signal occurs when the primary asset creates a higher high, while the correlated asset forms a lower high. This mismatch indicates fading bullish momentum and a potential reversal to the downside.
If the correlated asset fails to confirm a breakout made by the main asset, the divergence may point to distribution or exhaustion. When seen within Q3 or Q4 phases of the Quarterly Theory, this pattern often precedes sharp declines or fake-outs engineered by smart money
🔵 Settings
⚙️ Logical Settings
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Activate Max Pivot Back : When enabled, limits the maximum number of past pivots to be considered for divergence detection.
Max Pivot Back Length : Defines how many past pivots can be used (if the above toggle is active).
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Bullish SMT Line : Draws a line connecting the bullish divergence points.
Show Bullish SMT Label : Displays a label on the chart when a bullish divergence is detected.
Bullish Color : Sets the color for bullish SMT markers (label, shape, and line).
Show Bearish SMT Line : Draws a line for bearish divergence.
Show Bearish SMT Label : Displays a label when a bearish SMT divergence is found.
Bearish Color : Sets the color for bearish SMT visual elements.
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequency :
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵Conclusion
The SMT Plus indicator offers a refined and powerful approach to detecting smart money behavior through divergence analysis between correlated assets. By removing the limitations of consecutive pivot comparisons and allowing for broader structural detection, it captures more accurate and timely signals that often precede major market moves.
When paired with frameworks like Sequential SMT and the Quarterly Theory, the indicator not only highlights where divergence occurs, but also when in the market cycle it's most likely to matter. Its flexible settings, customizable visuals, and integrated alert system make it suitable for intraday scalpers, swing traders, and even long-term macro analysts.
Whether you're using it as a standalone decision-making tool or combining it with other ICT concepts, SMT Plus gives you an edge in recognizing manipulation, timing reversals, and staying in sync with the real market narrative—not just the chart.
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Auto TrendLines [TradingFinder] Support Resistance Signal Alerts🔵 Introduction
The trendline is one of the most essential tools in technical analysis, widely used in financial markets such as Forex, cryptocurrency, and stocks. A trendline is a straight line that connects swing highs or swing lows and visually indicates the market’s trend direction.
Traders use trendlines to identify price structure, the strength of buyers and sellers, dynamic support and resistance zones, and optimal entry and exit points.
In technical analysis, trendlines are typically classified into three categories: uptrend lines (drawn by connecting higher lows), downtrend lines (formed by connecting lower highs), and sideways trends (moving horizontally). A valid trendline usually requires at least three confirmed touchpoints to be considered reliable for trading decisions.
Trendlines can serve as the foundation for a variety of trading strategies, such as the trendline bounce strategy, valid breakout setups, and confluence-based analysis with other tools like candlestick patterns, divergences, moving averages, and Fibonacci levels.
Additionally, trendlines are categorized into internal and external, and further into major and minor levels, each serving unique roles in market structure analysis.
🔵 How to Use
Trendlines are a key component in technical analysis, used to identify market direction, define dynamic support and resistance zones, highlight strategic entry and exit points, and manage risk. For a trendline to be reliable, it must be drawn based on structural principles—not by simply connecting two arbitrary points.
🟣 Selecting Pivot Types Based on Trend Direction
The first step is to determine the market trend: uptrend, downtrend, or sideways.
Then, choose pivot points that match the trend type :
In an uptrend, trendlines are drawn by connecting low pivots, especially higher lows.
In a downtrend, trendlines are formed by connecting high pivots, specifically lower highs.
It is crucial to connect pivots of the same type and structure to ensure the trendline is valid and analytically sound.
🟣 Pivot Classification
This indicator automatically classifies pivot points into two categories :
Major Pivots :
MLL : Major Lower Low
MHL : Major Higher Low
MHH : Major Higher High
MLH : Major Lower High
These define the primary structure of the market and are typically used in broader structural analysis.
Minor Pivots :
mLL: minor Lower Low
mHL: minor Higher Low
mHH: minor Higher High
mLH: minor Lower High
These are used for drawing more precise trendlines within corrective waves or internal price movements.
Example : In a downtrend, drawing a trendline from an MHH to an mHH creates structural inconsistency and introduces noise. Instead, connect points like MHL to MHL or mLH to mLH for a valid trendline.
🟣 Drawing High-Precision Trendlines
To ensure a reliable trendline :
Use pivots of the same classification (Major with Major or Minor with Minor).
Ensure at least three valid contact points (three touches = structural confirmation).
Draw through candles with the least deviation (choose wicks or bodies based on confluence).
Preferably draw from right to left for better alignment with current market behavior.
Use parallel lines to turn a single trendline into a trendline zone, if needed.
🟣 Using Trendlines for Trade Entries
Bounce Entry: When price approaches the trendline and shows signs of reversal (e.g., a reversal candle, divergence, or support/resistance), enter in the direction of the trend with a logical stop-loss.
Breakout Entry: When price breaks through the trendline with strong momentum and a confirmation (such as a retest or break of structure), consider trading in the direction of the breakout.
🟣 Trendline-Based Risk Management
For bounce entries, the stop-loss is placed below the trendline or the last pivot low (in an uptrend).
For breakout entries, the stop-loss is set behind the breakout candle or the last structural level.
A broken trendline can also act as an exit signal from a trade.
🟣 Combining Trendlines with Other Tools (Confluence)
Trendlines gain much more strength when used alongside other analytical tools :
Horizontal support and resistance levels
Moving averages (such as EMA 50 or EMA 200)
Fibonacci retracement zones
Candlestick patterns (e.g., Engulfing, Pin Bar)
RSI or MACD divergences
Market structure breaks (BoS / ChoCH)
🔵 Settings
Pivot Period : This defines how sensitive the pivot detection is. A higher number means the algorithm will identify more significant pivot points, resulting in longer-term trendlines.
Alerts
Alert :
Enable or disable the entire alert system
Set a custom alert name
Choose how often alerts trigger (every time, once per bar, or on bar close)
Select the time zone for alert timestamps (e.g., UTC)
Each trendline type supports two alert types :
Break Alert : Triggered when price breaks the trendline
React Alert : Triggered when price reacts or bounces off the trendline
These alerts can be independently enabled or disabled for all trendline categories (Major/Minor, Internal/External, Up/Down).
Display :
For each of the eight trendline types, you can control :
Whether to show or hide the line
Whether to delete the previous line when a new one is drawn
Color, line style (solid, dashed, dotted), extension direction (e.g., right only), and width
Major lines are typically thicker and more opaque, while minor lines appear thinner and more transparent.
All settings are designed to give the user full control over the appearance, behavior, and alert system of the indicator, without requiring manual drawing or adjustments.
🔵 Conclusion
A trendline is more than just a line on the chart—it is a structural, strategic, and flexible tool in technical analysis that can serve as the foundation for understanding price behavior and making trading decisions. Whether in trending markets or during corrections, trendlines help traders identify market direction, key zones, and high-potential entry and exit points with precision.
The accuracy and effectiveness of a trendline depend on using structurally valid pivot points and adhering to proper market logic, rather than relying on guesswork or personal bias.
This indicator is built to solve that exact problem. It automatically detects and draws multiple types of trendlines based on actual price structure, separating them into Major/Minor and Internal/External categories, and respecting professional analytical principles such as pivot type, trend direction, and structural location.
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Quarterly Theory ICT 03 [TradingFinder] Precision Swing Points🔵 Introduction
Precision Swing Point (PSP) is a divergence pattern in the closing of candles between two correlated assets, which can indicate a potential trend reversal. This structure appears at market turning points and highlights discrepancies between the price behavior of two related assets.
PSP typically forms in key timeframes such as 5-minute, 15-minute, and 90-minute charts, and is often used in combination with Smart Money Concepts (SMT) to confirm trade entries.
PSP is categorized into Bearish PSP and Bullish PSP :
Bearish PSP : Occurs when an asset breaks its previous high, and its middle candle closes bullish, while the correlated asset closes bearish at the same level. This divergence signals weakness in the uptrend and a potential price reversal downward.
Bullish PSP : Occurs when an asset breaks its previous low, and its middle candle closes bearish, while the correlated asset closes bullish at the same level. This suggests weakness in the downtrend and a potential price increase.
🟣 Trading Strategies Using Precision Swing Point (PSP)
PSP can be integrated into various trading strategies to improve entry accuracy and filter out false signals. One common method is combining PSP with SMT (divergence between correlated assets), where traders identify divergence and enter a trade only after PSP confirms the move.
Additionally, PSP can act as a liquidity gap, meaning that price tends to react to the wick of the PSP candle, making it a favorable entry point with a tight stop-loss and high risk-to-reward ratio. Furthermore, PSP combined with Order Blocks and Fair Value Gaps in higher timeframes allows traders to identify stronger reversal zones.
In lower timeframes, such as 5-minute or 15-minute charts, PSP can serve as a confirmation for more precise entries in the direction of the higher timeframe trend. This is particularly useful in scalping and intraday trading, helping traders execute smarter entries while minimizing unnecessary stop-outs.
🔵 How to Use
PSP is a trading pattern based on divergence in candle closures between two correlated assets. This divergence signals a difference in trend strength and can be used to identify precise market turning points. PSP is divided into Bullish PSP and Bearish PSP, each applicable for long and short trades.
🟣 Bullish PSP
A Bullish PSP forms when, at a market turning point, the middle candle of one asset closes bearish while the correlated asset closes bullish. This discrepancy indicates weakness in the downtrend and a potential price reversal upward.
Traders can use this as a signal for long (buy) trades. The best approach is to wait for price to return to the wick of the PSP candle, as this area typically acts as a liquidity level.
f PSP forms within an Order Block or Fair Value Gap in a higher timeframe, its reliability increases, allowing for entries with tight stop-loss and optimal risk-to-reward ratios.
🟣 Bearish PSP
A Bearish PSP forms when, at a market turning point, the middle candle of one asset closes bullish while the correlated asset closes bearish. This indicates weakness in the uptrend and a potential price decline.
Traders use this pattern to enter short (sell) trades. The best entry occurs when price retests the wick of the PSP candle, as this level often acts as a resistance zone, pushing price lower.
If PSP aligns with a significant liquidity area or Order Block in a higher timeframe, traders can enter with greater confidence and place their stop-loss just above the PSP wick.
Overall, PSP is a highly effective tool for filtering false signals and improving trade entry precision. Combining PSP with SMT, Order Blocks, and Fair Value Gaps across multiple timeframes allows traders to execute higher-accuracy trades with lower risk.
🔵 Settings
Mode :
2 Symbol : Identifies PSP and PCP between two correlated assets.
3 Symbol : Compares three assets to detect more complex divergences and stronger confirmation signals.
Second Symbol : The second asset used in PSP and correlation calculations.
Third Symbol : Used in three-symbol mode for deeper PSP and PCP analysis.
Filter Precision X Point : Enables or disables filtering for more precise PSP and PCP detection. This filter only identifies PSP and PCP when the base asset's candle qualifies as a Pin Bar.
Trend Effect : By changing the Trend Effect status to "Off," all Pin bars, whether bullish or bearish, are displayed regardless of the current market trend. If the status remains "On," only Pin bars in the direction of the main market trend are shown.
Bullish Pin Bar Setting : Using the "Ratio Lower Shadow to Body" and "Ratio Lower Shadow to Higher Shadow" settings, you can customize your bullish Pin bar candles. Larger numbers impose stricter conditions for identifying bullish Pin bars.
Bearish Pin Bar Setting : Using the "Ratio Higher Shadow to Body" and "Ratio Higher Shadow to Lower Shadow" settings, you can customize your bearish Pin bar candles. Larger numbers impose stricter conditions for identifying bearish Pin bars.
🔵 Conclusion
Precision Swing Point (PSP) is a powerful analytical tool in Smart Money trading strategies, helping traders identify precise market turning points by detecting divergences in candle closures between correlated assets. PSP is classified into Bullish PSP and Bearish PSP, each playing a crucial role in detecting trend weaknesses and determining optimal entry points for long and short trades.
Using the PSP wick as a key liquidity level, integrating it with SMT, Order Blocks, and Fair Value Gaps, and analyzing higher timeframes are effective techniques to enhance trade entries. Ultimately, PSP serves as a complementary tool for improving entry accuracy and reducing unnecessary stop-outs, making it a valuable addition to Smart Money trading methodologies. インジケーター
