Pocket Pivots by Kacher and Morales "Pocket Pivots," identifies potential bullish trading opportunities and technical conditions based on concepts from traders Kacher and Morales. It combines moving averages (SMAs), Bollinger Bands, Keltner Channels, volume analysis, and price action rules to detect:
Pocket Pivots:
Bullish signals triggered when:
Volume exceeds prior downdays (configurable lengths Standard is 10 days).
Price closes above key SMAs (10/50-day).
As Kacher and Morales do not buy wedging charts I added a squeeze check to avoid buy signals
The market is in a volatility "squeeze" (Bollinger Bands within Keltner Channels).
Up/down ratio of the volume must be greater than 1
Volume Pocket Pivots:
Secondary bullish signals based purely on volume spikes and upward price momentum.
This shows normal pocket pivots in yellow. But does not check if all other rules are fullfilled.
SMA Violations:
Marks bearish breakdowns below 10-day or 50-day SMAs
A 10 SMA Violation is normally yellow. But if there was no 10 day violation for Seven Weeks, the first 10 SMA violation shows a red sell signal. Kacher and Morales call it "Seven Week Rule"
Buyable Gap-Ups:
Highlights high-volume gaps up with strong price follow-through.
Visual Elements:
Plots SMAs (10, 50, 200), Bollinger Bands, and Keltner Channels.
Marks signals with colored triangles/diamonds (green = bullish, red = bearish and yellow / blue = informational).
ボリンジャーバンド (BB)
Tesla Volt Surge 4HTesla Volt Surge is an advanced trading strategy specifically designed for 4-hour chart analysis of Tesla Inc. This strategy leverages a combination of technical indicators to capture potential surges in stock price movement:
Bollinger Bands with an EMA (Exponential Moving Average) basis are tuned to detect breakouts with a standard deviation of 1.7, aiming to catch the rapid shifts characteristic of Tesla's stock.
The Sideways Market Filter is enabled to ensure trading only occurs during periods of meaningful volatility, using a bandwidth multiplier of 0.7 to set a tighter threshold on trading opportunities.
ADX (Average Directional Index) filter helps traders focus on trending conditions, with an ADX threshold set at 20 to confirm a strong directional market movement.
RSI (Relative Strength Index) filter is employed to manage entries and exits, particularly focusing on not buying when the market is overbought, with an RSI threshold of 75.
Tesla Volt Surge is tailored for those looking to harness Tesla's stock volatility on a higher timeframe, aiming to capitalize on significant market moves while minimizing trades in less dynamic, sideways markets.
Tesla ThunderBolt 45MDescription:
Tesla Thunderbolt is an advanced trading strategy tailored for Tesla Inc. stocks on a 45-minute chart. This strategy harnesses the power of Bollinger Bands, ADX, RSI, and dynamic volume confirmation to pinpoint optimal trading moments.
Bollinger Bands with a custom SMMA (Smoothed Moving Average) basis aim to capture significant price movements by adjusting the sensitivity to Tesla's volatility.
The Sideways Market Filter ensures trades are only executed during periods of sufficient market volatility, using a bandwidth threshold to avoid low-volatility traps.
ADX Filter helps in identifying trending markets, ensuring trades align with market direction to maximize potential gains.
RSI Filter focuses on overbought conditions to fine-tune entry and exit points, reducing the risk of entering trades at market peaks.
Dynamic Volume Confirmation adds an extra layer of validation, only signaling trades when volume supports the price action, potentially confirming the strength of the move.
Tesla Thunderbolt is designed for traders looking to leverage Tesla's market momentum with precision, aiming to strike with the decisiveness of a thunderbolt in the fast-paced trading environment. Remember, past performance does not guarantee future results; always backtest and adjust based on current market conditions.
Bitcoin Breakout Blaster 4HourSet Your Chart to 4 Hour for this Strategy
"Bitcoin Breakout Blaster" is a streamlined trading approach designed for the 4-hour chart of Bitcoin (BTC), focusing on capturing significant price movements with a blend of technical analysis tools. Here's how it operates:
Core Concepts:
Volume Weighted Moving Average (VWMA) Bollinger Bands:
With a length now set to 20 periods, these bands use volume in their calculation, providing a sensitive indicator of potential breakouts or pullbacks based on market activity. This setting has shown to be optimal for identifying price breakouts in Bitcoin's market.
MACD Momentum Gauge:
The Moving Average Convergence Divergence (MACD) is employed with settings of 10 for the fast length, 24 for the slow length, and 9 for signal smoothing. Trades are triggered only when the MACD histogram shows positive values, ensuring there's underlying bullish momentum behind price movements.
Trading Logic:
Entry (Long):
A long position is taken when:
The price moves above the upper Bollinger Band, indicating a potential upward breakout.
The MACD histogram is positive, confirming bullish momentum.
Exit:
The trade is closed when the price falls below the lower Bollinger Band, signaling a possible end to the breakout or a reversal.
Strategy Characteristics:
Breakout Focus: The strategy capitalizes on Bitcoin's periodic breakouts from established price ranges, aiming to enter trades just as significant movements begin.
Momentum Confirmation: Only engages in trades with confirmed momentum, reducing the risk of entering on false signals.
Considerations:
Volatility: Bitcoin's market can be highly volatile, and this strategy benefits from such conditions by aiming to ride breakouts rather than predict them from consolidation phases.
Adjustability: While the current settings work well, traders might need to tweak MACD parameters or Bollinger Band standard deviation based on evolving market conditions.
"Bitcoin Breakout Blaster" focuses on leveraging Bitcoin's volatility for potential gains by identifying and acting on breakout signals with confirmed momentum.
Solar Flare: Solana's Volatility & Momentum Play 6HSet a 6 Hour Chart for this Strategy to work properly.
"Solar Flare" is a dynamic trading strategy tailored specifically for the Solana (SOL) cryptocurrency, designed to capitalize on its known volatility and momentum within a 6-hour chart timeframe. Here's how it works:
Core Mechanisms:
Bollinger Bands - The Solar Bands:
Length: Set to 17 periods, providing a balance between sensitivity and reliability in capturing price movements.
Type: Uses a Weighted Moving Average (WMA) for the basis, which gives more weight to recent prices, making the strategy more responsive to Solana's quick price changes.
Standard Deviation: At 1.5, these bands are relatively wide, aiming to catch significant movements without being too reactive to every small fluctuation.
Volatility Filter: Enabled by default, this uses the bandwidth of the Bollinger Bands to gauge market volatility. Only when the bands are sufficiently spread out (bandwidth > threshold) does the strategy consider entering a trade, avoiding sideways or low-volatility markets.
RSI - The Momentum Meter:
Length: Set at 14 periods, matching the standard RSI settings for broad applicability.
Threshold: An overbought threshold of 75 means the strategy avoids buying when momentum is too high, potentially signaling a near-term reversal. This helps in not chasing peaks during Solana's rapid rises.
Trading Logic:
Entry (Long):
A long position is initiated when the closing price breaches the upper Bollinger Band, indicating a potential breakout or strong upward momentum.
However, this entry is only executed if:
The current time is within the selected date range.
The market is deemed volatile enough (bandwidth exceeds the threshold).
RSI is below 75, suggesting there's still room for upward movement before becoming overbought.
Exit:
The position is closed when the price falls below the lower Bollinger Band, which might suggest the price is reverting to the mean or entering an oversold condition.
Strategy Characteristics:
Simplicity with Precision: By focusing on two key indicators, Bollinger Bands for price action and RSI for momentum, "Solar Flare" aims to provide clear signals in the often chaotic SOL market.
Volatility-Momentum Synergy: Combines the best of both worlds - trading when there's enough market movement and when there's still potential for further gains according to momentum.
Risk Management: Utilizes percent of equity for position sizing, automatically adjusting trade size with account balance to manage risk.
Considerations:
Market Suitability: This strategy is crafted for Solana's specific behavior, which might not translate directly to other cryptocurrencies with different volatility profiles.
Backtesting: Essential to validate the strategy's performance across different market conditions, particularly with Solana's history of sharp price movements.
Adjustments: Users might want to tweak the Bollinger Band settings or RSI thresholds based on market conditions or personal risk tolerance.
"Solar Flare" aims to ride the waves of Solana's market volatility while ensuring momentum is in your favor, making it a potentially thrilling yet strategic approach to trading SOL.
Bollinger Trading for SHIB 5H ChartStrategy Title: "Bollinger Trading for SHIB 5H Chart"
Make sure you select the 5H chart for SHIB as that is how this strategy is optimized.
Objective:
This strategy aims to capitalize on price movements of SHIB using Bollinger Bands to identify potential overbought and oversold conditions, with an additional volatility filter to enhance trade quality.
Key Components:
Bollinger Bands:
Length: Set to 15 periods by default, which means the moving average and standard deviation calculations are based on the last 15 price points. This shorter period is intended to react more quickly to price changes in the volatile SHIB market.
Basis MA Type: Uses Simple Moving Average (SMA) as the basis, providing a smoother, less reactive response to price changes compared to other moving average types.
Standard Deviation (StdDev): Set to 1.2, which determines the width of the Bollinger Bands. A lower value means tighter bands, potentially catching smaller price movements.
Offset: Set to 0, meaning no time shift is applied to the bands.
Volatility Filter:
Use Volatility Filter: Enabled by default. This filter assesses if the market is sufficiently volatile to warrant trading.
Bandwidth Multiplier: Determines how wide the bands need to be for a trade to be considered. A multiplier of 0.8 means the bands must be somewhat expanded for trading signals.
Bandwidth Smoothing: Uses an EMA with a 15-period length to smooth the bandwidth, reducing noise in the volatility measurement.
Trading Logic:
Entry Condition (Long):
A long position is entered when the closing price moves above the upper Bollinger Band, indicating a potential breakout or overbought condition.
This entry is only valid if:
The current time falls within the user-defined date range.
The market is deemed volatile enough by the volatility filter if it's enabled.
Exit Condition:
The long position is closed when the closing price drops below the lower Bollinger Band, suggesting that the price might be returning to mean or an oversold condition.
Strategy Characteristics:
Simplicity: This strategy focuses purely on price action relative to Bollinger Bands, without additional indicators like RSI, ADX, or MACD, making it straightforward to understand and backtest.
Volatility Adjustment: By filtering trades based on band width, the strategy attempts to avoid trading in low volatility scenarios where breakouts might be less meaningful.
Risk Management: The strategy uses a percentage of equity for trade sizing, which inherently adjusts risk based on account performance.
Considerations:
Market Specific: Tailored for SHIB or similar highly volatile assets, where short-term price swings are common.
Backtesting: Essential for assessing how these settings perform over different market conditions, especially given SHIB's volatility and potential for rapid price movements.
Adjustability: Users can tweak Bollinger Band parameters or the volatility filter to match different market conditions or risk preferences.
This strategy leverages the tendency of prices to revert to the mean after moving outside Bollinger Bands, aiming to profit from these reversion points while filtering out trades during less volatile market conditions.
Smart Buy/Sell Signal IndicatorThe S mart Buy/Sell Signal Indicator is a sophisticated trading tool designed to provide precise Buy and Sell signals by integrating multiple technical analysis methods. This indicator combines trend analysis, momentum evaluation, volatility measures, and signal confirmation to enhance trading accuracy. It is particularly suited for traders looking to capitalize on price reversals, breakouts, and trend continuations.
Each component of this indicator has been carefully selected to solve common challenges faced by traders, such as identifying reliable entry/exit points, avoiding false signals, and trading in diverse market conditions.
Key Components and Their Roles
1. Supertrend Indicator:
• Purpose: Identify the overarching trend direction and dynamic support/resistance levels.
• How It Works:
• The Supertrend uses ATR (Average True Range) to calculate dynamic levels, allowing the indicator to adapt to market volatility.
• Provides visual cues for whether the market is in an uptrend (supertrend up) or downtrend (supertrend down).
• Role in the Indicator:
• Acts as the primary trend filter, ensuring that Buy signals align with bullish trends and Sell signals align with bearish trends.
2. RSI (Relative Strength Index):
• Purpose: Measure momentum and identify overbought/oversold conditions.
• How It Works:
• Analyzes the relative strength of price movements over a specific period.
• Provides sentiment cues:
• Below 50: Bearish sentiment.
• Above 50: Bullish sentiment.
• Role in the Indicator:
• Adds a momentum confirmation layer, ensuring signals occur in line with market sentiment.
• Refines entry points by identifying reversals (e.g., Buy signals when RSI < 45 and price is oversold).
3. Bollinger Bands:
• Purpose: Define price volatility and identify overbought/oversold conditions.
• How It Works:
• Plots bands around a moving average, with the width determined by standard deviations.
• Signals:
• Price near lower band indicates potential oversold conditions (Buy).
• Price near upper band indicates potential overbought conditions (Sell).
• Role in the Indicator:
• Refines reversal signals by confirming price extremes relative to market volatility.
• Works with RSI to validate overbought/oversold conditions.
4. ADX (Average Directional Index):
• Purpose: Measure trend strength to filter signals in weak trends.
• How It Works:
• ADX values:
• Above threshold (e.g., 15): Indicates a strong trend.
• Below threshold: Indicates a weak or sideways market.
• Role in the Indicator:
• Ensures that Buy/Sell signals occur only in strong trending conditions, reducing noise during flat markets.
5. Confirmation Moving Average:
• Purpose: Provide an additional layer of trend validation.
• How It Works:
• A simple moving average (SMA) is calculated to smooth price data and highlight the overall trend direction.
• Role in the Indicator:
• Validates that price aligns with the broader trend before generating a signal.
6. Minimum Bars Between Signals:
• Purpose: Prevent overtrading in choppy or fast-moving markets.
• How It Works:
• Imposes a time buffer between consecutive Buy or Sell signals.
• Role in the Indicator:
• Reduces noise and ensures only high-probability setups are acted upon.
7. Cloud-Based Reversal Signals:
• Purpose: Highlight potential reversal points where price deviates significantly from expected behavior.
• How It Works:
• Combines Bollinger Bands, RSI, ADX, and Supertrend levels to detect extreme conditions.
• Role in the Indicator:
• Provides early warnings for potential reversals, complementing the refined Buy/Sell signals.
Why Combine These Elements?
This combination is not arbitrary—each component solves a specific problem while complementing the others:
1. Trend Alignment:
• The Supertrend and Confirmation Moving Average ensure that signals align with the prevailing trend, increasing reliability.
2. Volatility and Momentum:
• Bollinger Bands and RSI work together to identify overbought/oversold conditions, ensuring signals are generated near key price extremes.
3. Trend Strength Filtering:
• The ADX filters weak trends, ensuring signals occur only during strong directional moves.
4. Noise Reduction:
• The minimum bars between signals and cloud-based alerts prevent overtrading and provide additional confirmation for reversals.
5. Dynamic Adaptability:
• By combining trend, momentum, and volatility measures, the indicator adapts to both trending and range-bound market conditions.
How It Works
Buy Signal Logic:
• Triggered when:
• RSI < 50 (bullish sentiment).
• Price is above the Supertrend Down level and the Confirmation Moving Average.
• ADX > Threshold (e.g., 15): Confirms a strong trend.
• Minimum bars since the last Buy signal have passed.
• Additional early warnings are provided if:
• Price is below the lower Bollinger Band, RSI < 45, and ADX > Threshold (cloud Buy signal).
Sell Signal Logic:
• Triggered when:
• RSI > 50 (bearish sentiment).
• Price is below the Supertrend Up level and the Confirmation Moving Average.
• ADX > Threshold (e.g., 15): Confirms a strong trend.
• Minimum bars since the last Sell signal have passed.
• Additional early warnings are provided if:
• Price is above the upper Bollinger Band, RSI > 55, and ADX > Threshold (cloud Sell signal).
Background Coloring:
• Green: Bullish momentum (RSI crosses above 50).
• Red: Bearish momentum (RSI crosses below 50).
How to Use It
1. Timeframes:
• Suitable for scalping (1m, 5m, 15m) and intraday trading (30m, 1H).
2. Risk Management:
• Use Supertrend levels or Bollinger Bands to set Stop Loss and Take Profit levels.
Signal Interpretation
The Refined Smart Buy/Sell Signal Indicator v2 provides clear visual cues for different trading scenarios:
1. Buy Signal:
• Represented by a green label with the text “BUY.”
• Indicates a confirmed Buy opportunity when all criteria, such as trend, volatility, and momentum, align.
2. Sell Signal:
• Represented by a red label with the text “SELL.”
• Indicates a confirmed Sell opportunity when all conditions, including trend direction and momentum, are met.
3. Cloud Signals (Reversal Alerts):
• Black Circles (Bottom): Appear near the bottom of the price chart when conditions suggest a potential upward reversal. These serve as early warnings for an upcoming bullish move but require confirmation from Buy signals.
• Red Dots (Top): Appear near the top of the price chart when conditions suggest a potential bearish reversal. These act as early indicators of possible downward momentum but should be used with Sell signal confirmation.
The reversal signals are generated by combining Bollinger Bands, RSI, ADX, and Supertrend levels to detect price extremes. These signals highlight areas where price may react, giving traders an opportunity to prepare for potential moves.
Designed and developed by TradeTech Analysis – Empowering traders with precision tools for smarter trading decisions.
Sunil BB Blast Heikin Ashi StrategySunil BB Blast Heikin Ashi Strategy
The Sunil BB Blast Heikin Ashi Strategy is a trend-following trading strategy that combines Bollinger Bands with Heikin-Ashi candles for precise market entries and exits. It aims to capitalize on price volatility while ensuring controlled risk through dynamic stop-loss and take-profit levels based on a user-defined Risk-to-Reward Ratio (RRR).
Key Features:
Trading Window:
The strategy operates within a user-defined time window (e.g., from 09:20 to 15:00) to align with market hours or other preferred trading sessions.
Trade Direction:
Users can select between Long Only, Short Only, or Long/Short trade directions, allowing flexibility depending on market conditions.
Bollinger Bands:
Bollinger Bands are used to identify potential breakout or breakdown zones. The strategy enters trades when price breaks through the upper or lower Bollinger Band, indicating a possible trend continuation.
Heikin-Ashi Candles:
Heikin-Ashi candles help smooth price action and filter out market noise. The strategy uses these candles to confirm trend direction and improve entry accuracy.
Risk Management (Risk-to-Reward Ratio):
The strategy automatically adjusts the take-profit (TP) level and stop-loss (SL) based on the selected Risk-to-Reward Ratio (RRR). This ensures that trades are risk-managed effectively.
Automated Alerts and Webhooks:
The strategy includes automated alerts for trade entries and exits. Users can set up JSON webhooks for external execution or trading automation.
Active Position Tracking:
The strategy tracks whether there is an active position (long or short) and only exits when price hits the pre-defined SL or TP levels.
Exit Conditions:
The strategy exits positions when either the take-profit (TP) or stop-loss (SL) levels are hit, ensuring risk management is adhered to.
Default Settings:
Trading Window:
09:20-15:00
This setting confines the strategy to the specified hours, ensuring trading only occurs during active market hours.
Strategy Direction:
Default: Long/Short
This allows for both long and short trades depending on market conditions. You can select "Long Only" or "Short Only" if you prefer to trade in one direction.
Bollinger Band Length (bbLength):
Default: 19
Length of the moving average used to calculate the Bollinger Bands.
Bollinger Band Multiplier (bbMultiplier):
Default: 2.0
Multiplier used to calculate the upper and lower bands. A higher multiplier increases the width of the bands, leading to fewer but more significant trades.
Take Profit Multiplier (tpMultiplier):
Default: 2.0
Multiplier used to determine the take-profit level based on the calculated stop-loss. This ensures that the profit target aligns with the selected Risk-to-Reward Ratio.
Risk-to-Reward Ratio (RRR):
Default: 1.0
The ratio used to calculate the take-profit relative to the stop-loss. A higher RRR means larger profit targets.
Trade Automation (JSON Webhooks):
Allows for integration with external systems for automated execution:
Long Entry JSON: Customizable entry condition for long positions.
Long Exit JSON: Customizable exit condition for long positions.
Short Entry JSON: Customizable entry condition for short positions.
Short Exit JSON: Customizable exit condition for short positions.
Entry Logic:
Long Entry:
The strategy enters a long position when:
The Heikin-Ashi candle shows a bullish trend (green close > open).
The price is above the upper Bollinger Band, signaling a breakout.
The previous candle also closed higher than it opened.
Short Entry:
The strategy enters a short position when:
The Heikin-Ashi candle shows a bearish trend (red close < open).
The price is below the lower Bollinger Band, signaling a breakdown.
The previous candle also closed lower than it opened.
Exit Logic:
Take-Profit (TP):
The take-profit level is calculated as a multiple of the distance between the entry price and the stop-loss level, determined by the selected Risk-to-Reward Ratio (RRR).
Stop-Loss (SL):
The stop-loss is placed at the opposite Bollinger Band level (lower for long positions, upper for short positions).
Exit Trigger:
The strategy exits a trade when either the take-profit or stop-loss level is hit.
Plotting and Visuals:
The Heikin-Ashi candles are displayed on the chart, with green candles for uptrends and red candles for downtrends.
Bollinger Bands (upper, lower, and basis) are plotted for visual reference.
Entry points for long and short trades are marked with green and red labels below and above bars, respectively.
Strategy Alerts:
Alerts are triggered when:
A long entry condition is met.
A short entry condition is met.
A trade exits (either via take-profit or stop-loss).
These alerts can be used to trigger notifications or webhook events for automated trading systems.
Notes:
The strategy is designed for use on intraday charts but can be applied to any timeframe.
It is highly customizable, allowing for tailored risk management and trading windows.
The Sunil BB Blast Heikin Ashi Strategy combines two powerful technical analysis tools (Bollinger Bands and Heikin-Ashi candles) with strong risk management, making it suitable for both beginners and experienced traders.
Feebacks are welcome from the users.
Multi-Band Comparison (Uptrend)Multi-Band Comparison
Overview:
The Multi-Band Comparison indicator is engineered to reveal critical levels of support and resistance in strong uptrends. In a healthy upward market, the price action will adhere closely to the 95th percentile line (the Upper Quantile Band), effectively “riding” it. This indicator combines a modified Bollinger Band (set at one standard deviation), quantile analysis (95% and 5% levels), and power‑law math to display a dynamic picture of market structure—highlighting a “golden channel” and robust support areas.
Key Components & Calculations:
The Golden Channel: Upper Bollinger Band & Upper Std Dev Band of the Upper Quantile
Upper Bollinger Band:
Calculation:
boll_upper=SMA(close,length)+(boll_mult×stdev)
boll_upper=SMA(close,length)+(boll_mult×stdev) Here, the 20-period SMA is used along with one standard deviation of the close, where the multiplier (boll_mult) is 1.0.
Role in an Uptrend:
In a healthy uptrend, price rides near the 95th percentile line. When price crosses above this Upper Bollinger Band, it confirms strong bullish momentum.
Upper Std Dev Band of the Upper Quantile (95th Percentile) Band:
Calculation:
quant_upper_std_up=quant_upper+stdev
quant_upper_std_up=quant_upper+stdev The Upper Quantile Band, quant_upperquant_upper, is calculated as the 95th percentile of recent price data. Adding one standard deviation creates an extension that accounts for normal volatility around this extreme level.
The Golden Channel:
When the price crosses above the Upper Bollinger Band, the Upper Std Dev Band of the Upper Quantile immediately shifts to gold (yellow) and remains gold until price falls below the Bollinger level. Together, these two lines form the “golden channel”—a visual hallmark of a healthy uptrend where the price reliably hugs the 95th percentile level.
Upper Power‑Law Band
Calculation:
The Upper Power‑Law Band is derived in two steps:
Determine the Extreme Return Factor:
power_upper=Percentile(returns,95%)
power_upper=Percentile(returns,95%) where returns are computed as:
returns=closeclose −1.
returns=close close−1.
Scale the Current Price:
power_upper_band=close×(1+power_upper)
power_upper_band=close×(1+power_upper)
Rationale and Correlation:
By focusing on the upper 5% of returns (reflecting “fat tails”), the Upper Power‑Law Band captures extreme but statistically expected movements. In an uptrend, its value often converges with the Upper Std Dev Band of the Upper Quantile because both measures reflect heightened volatility and extreme price levels. When the Upper Power‑Law Band exceeds the Upper Std Dev Band, it can signal a temporary overextension.
Upper Quantile Band (95% Percentile)
Calculation:
quant_upper=Percentile(price,95%)
quant_upper=Percentile(price,95%) This level represents where 95% of past price data falls below, and in a robust uptrend the price action practically rides this line.
Color Logic:
Its color shifts from a neutral (blackish) tone to a vibrant, bullish hue when the Upper Power‑Law Band crosses above it—signaling extra strength in the trend.
Lower Quantile and Its Support
Lower Quantile Band (5% Percentile):
Calculation:
quant_lower=Percentile(price,5%)
quant_lower=Percentile(price,5%)
Behavior:
In a healthy uptrend, price remains well above the Lower Quantile Band. It turns red only when price touches or crosses it, serving as a warning signal. Under normal conditions it remains bright green, indicating the market is not nearing these extreme lows.
Lower Std Dev Band of the Lower Quantile:
This line is calculated by subtracting one standard deviation from quant_lowerquant_lower and typically serves as absolute support in nearly all conditions (except during gap or near-gap moves). Its consistent role as support provides traders with a robust level to monitor.
How to Use the Indicator:
Golden Channel and Trend Confirmation:
As price rides the Upper Quantile (95th percentile) perfectly in a healthy uptrend, the Upper Bollinger Band (1 stdev above SMA) and the Upper Std Dev Band of the Upper Quantile form a “golden channel” once price crosses above the Bollinger level. When this occurs, the Upper Std Dev Band remains gold until price dips back below the Bollinger Band. This visual cue reinforces trend strength.
Power‑Law Insights:
The Upper Power‑Law Band, which is based on extreme (95th percentile) returns, tends to align with the Upper Std Dev Band. This convergence reinforces that extreme, yet statistically expected, price moves are occurring—indicating that even though the price rides the 95th percentile, it can only stretch so far before a correction or consolidation.
Support Indicators:
Primary and Secondary Support in Uptrends:
The Upper Bollinger Band and the Lower Std Dev Band of the Upper Quantile act as support zones for minor retracements in the uptrend.
Absolute Support:
The Lower Std Dev Band of the Lower Quantile serves as an almost invariable support area under most market conditions.
Conclusion:
The Multi-Band Comparison indicator unifies advanced statistical techniques to offer a clear view of uptrend structure. In a healthy bull market, price action rides the 95th percentile line with precision, and when the Upper Bollinger Band is breached, the corresponding Upper Std Dev Band turns gold to form a “golden channel.” This, combined with the Power‑Law analysis that captures extreme moves, and the robust lower support levels, provides traders with powerful, multi-dimensional insights for managing entries, exits, and risk.
Disclaimer:
Trading involves risk. This indicator is for educational purposes only and does not constitute financial advice. Always perform your own analysis before making trading decisions.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Uptrick: Volatility Reversion BandsUptrick: Volatility Reversion Bands is an indicator designed to help traders identify potential reversal points in the market by combining volatility and momentum analysis within one comprehensive framework. It calculates dynamic bands around a simple moving average and issues signals when price interacts with these bands. Below is a fully expanded description, structured in multiple sections, detailing originality, usefulness, uniqueness, and the purpose behind blending standard deviation-based and ATR-based concepts. All references to code have been removed to focus on the written explanation only.
Section 1: Overview
Uptrick: Volatility Reversion Bands centers on a moving average around which various bands are constructed. These bands respond to changes in price volatility and can help gauge potential overbought or oversold conditions. Signals occur when the price moves beyond certain thresholds, which may imply a reversal or significant momentum shift.
Section 2: Originality, Usefulness, Uniqness, Purpose
This indicator merges two distinct volatility measurements—Bollinger Bands and ATR—into one cohesive system. Bollinger Bands use standard deviation around a moving average, offering a baseline for what is statistically “normal” price movement relative to a recent mean. When price hovers near the upper band, it may indicate overbought conditions, whereas price near the lower band suggests oversold conditions. This straightforward construction often proves invaluable in moderate-volatility settings, as it pinpoints likely turning points and gauges a market’s typical trading range.
Yet Bollinger Bands alone can falter in conditions marked by abrupt volatility spikes or sudden gaps that deviate from recent norms. Intraday news, earnings releases, or macroeconomic data can alter market behavior so swiftly that standard-deviation bands do not keep pace. This is where ATR (Average True Range) adds an important layer. ATR tracks recent highs, lows, and potential gaps to produce a dynamic gauge of how much price is truly moving from bar to bar. In quieter times, ATR contracts, reflecting subdued market activity. In fast-moving markets, ATR expands, exposing heightened volatility on each new bar.
By overlaying Bollinger Bands and ATR-based calculations, the indicator achieves a broader situational awareness. Bollinger Bands excel at highlighting relative overbought or oversold areas tied to an established average. ATR simultaneously scales up or down based on real-time market swings, signaling whether conditions are calm or turbulent. When combined, this means a price that barely crosses the Bollinger Band but also triggers a high ATR-based threshold is likely experiencing a volatility surge that goes beyond typical market fluctuations. Conversely, a price breach of a Bollinger Band when ATR remains low may still warrant attention, but not necessarily the same urgency as in a high-volatility regime.
The resulting synergy offers balanced, context-rich signals. In a strong trend, the ATR layer helps confirm whether an apparent price breakout really has momentum or if it is just a temporary spike. In a range-bound market, standard deviation-based Bollinger Bands define normal price extremes, while ATR-based extensions highlight whether a breakout attempt has genuine force behind it. Traders gain clarity on when a move is both statistically unusual and accompanied by real volatility expansion, thus carrying a higher probability of a directional follow-through or eventual reversion.
Practical advantages emerge across timeframes. Scalpers in fast-paced markets appreciate how ATR-based thresholds update rapidly, revealing if a sudden price push is routine or exceptional. Swing traders can rely on both indicators to filter out false signals in stable conditions or identify truly notable moves. By calibrating to changes in volatility, the merged system adapts naturally whether the market is trending, ranging, or transitioning between these phases.
In summary, combining Bollinger Bands (for a static sense of standard-deviation-based overbought/oversold zones) with ATR (for a dynamic read on current volatility) yields an adaptive, intuitive indicator. Traders can better distinguish fleeting noise from meaningful expansions, enabling more informed entries, exits, and risk management. Instead of relying on a single yardstick for all market conditions, this fusion provides a layered perspective, encouraging traders to interpret price moves in the broader context of changing volatility.
Section 3: Why Bollinger Bands and ATR are combined
Bollinger Bands provide a static snapshot of volatility by computing a standard deviation range above and below a central average. ATR, on the other hand, adapts in real time to expansions or contractions in market volatility. When combined, these measures offset each other’s limitations: Bollinger Bands add structure (overbought and oversold references), and ATR ensures responsiveness to rapid price shifts. This synergy helps reduce noisy signals, particularly during sudden market turbulence or extended consolidations.
Section 4: User Inputs
Traders can adjust several parameters to suit their preferences and strategies. These typically include:
1. Lookback length for calculating the moving average and standard deviation.
2. Multipliers to control the width of Bollinger Bands.
3. An ATR multiplier to set the distance for additional reversal bands.
4. An option to display weaker signals when the price merely approaches but does not cross the outer bands.
Section 5: Main Calculations
At the core of this indicator are four important steps:
1. Calculate a basis using a simple moving average.
2. Derive Bollinger Bands by adding and subtracting a product of the standard deviation and a user-defined multiplier.
3. Compute ATR over the same lookback period and multiply it by the selected factor.
4. Combine ATR-based distance with the Bollinger Bands to set the outer reversal bands, which serve as stronger signal thresholds.
Section 6: Signal Generation
The script interprets meaningful reversal points when the price:
1. Crosses below the lower outer band, potentially highlighting oversold conditions where a bullish reversal may occur.
2. Crosses above the upper outer band, potentially indicating overbought conditions where a bearish reversal may develop.
Section 7: Visualization
The indicator provides visual clarity through labeled signals and color-coded references:
1. Distinct colors for upper and lower reversal bands.
2. Markers that appear above or below bars to denote possible buying or selling signals.
3. A gradient bar color scheme indicating a bar’s position between the lower and upper bands, helping traders quickly see if the price is near either extreme.
Section 8: Weak Signals (Optional)
For those preferring early cues, the script can highlight areas where the price nears the outer bands. When weak signals are enabled:
1. Bars closer to the upper reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential selling area.
2. Bars closer to the lower reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential buying area.
Section 9: Simplicity, Effectiveness, and Lower Timeframes
Although combining standard deviation and ATR involves sophisticated volatility concepts, this indicator is visually straightforward. Reversal bands and gradient-colored bars make it easy to see at a glance when price approaches or crosses a threshold. Day traders operating on lower timeframes benefit from such clarity because it helps filter out minor fluctuations and focus on more meaningful signals.
Section 10: Adaptability across Market Phases
Because both the standard deviation (for Bollinger Bands) and ATR adapt to changing volatility, the indicator naturally adjusts to various environments:
1. Trending: The additional ATR-based outer bands help distinguish between temporary pullbacks and deeper reversals.
2. Ranging: Bollinger Bands often remain narrower, identifying smaller reversals, while the outer ATR bands remain relatively close to the main bands.
Section 11: Reduced Noise in High-Volatility Scenarios
By factoring ATR into the band calculations, the script widens or narrows the thresholds during rapid market fluctuations. This reduces the amount of false triggers typically found in indicators that rely solely on fixed calculations, preventing overreactions to abrupt but short-lived price spikes.
Section 12: Incorporation with Other Technical Tools
Many traders combine this indicator with oscillators such as RSI, MACD, or Stochastic, as well as volume metrics. Overbought or oversold signals in momentum oscillators can provide additional confirmation when price reaches the outer bands, while volume spikes may reinforce the significance of a breakout or potential reversal.
Section 13: Risk Management Considerations
All trading strategies carry risk. This indicator, like any tool, can and does produce losing trades if price unexpectedly reverses again or if broader market conditions shift rapidly. Prudent traders employ protective measures:
1. Stop-loss orders or trailing stops.
2. Position sizing that accounts for market volatility.
3. Diversification across different asset classes when possible.
Section 14: Overbought and Oversold Identification
Standard Bollinger Bands highlight regions where price might be overextended relative to its recent average. The extended ATR-based reversal bands serve as secondary lines of defense, identifying moments when price truly stretches beyond typical volatility bounds.
Section 15: Parameter Customization for Different Needs
Users can tailor the script to their unique preferences:
1. Shorter lookback settings yield faster signals but risk more noise.
2. Higher multipliers spread the bands further apart, filtering out small moves but generating fewer signals.
3. Longer lookback periods smooth out market noise, often leading to more stable but less frequent trading cues.
Section 16: Examples of Different Trading Styles
1. Day Traders: Often reduce the length to capture quick price swings.
2. Swing Traders: May use moderate lengths such as 20 to 50 bars.
3. Position Traders: Might opt for significantly longer settings to detect macro-level reversals.
Section 17: Performance Limitations and Reality Check
No technical indicator is free from false signals. Sudden fundamental news events, extreme sentiment changes, or low-liquidity conditions can render signals less reliable. Backtesting and forward-testing remain essential steps to gauge whether the indicator aligns well with a trader’s timeframe, risk tolerance, and instrument of choice.
Section 18: Merging Volatility and Momentum
A critical uniqueness of this indicator lies in how it merges Bollinger Bands (standard deviation-based) with ATR (pure volatility measure). Bollinger Bands provide a relative measure of price extremes, while ATR dynamically reacts to market expansions and contractions. Together, they offer an enhanced perspective on potential market turns, ideally reducing random noise and highlighting moments where price has traveled beyond typical bounds.
Section 19: Purpose of this Merger
The fundamental purpose behind blending standard deviation measures with real-time volatility data is to accommodate different market behaviors. Static standard deviation alone can underreact or overreact in abnormally volatile conditions. ATR alone lacks a baseline reference to normality. By merging them, the indicator aims to provide:
1. A versatile dynamic range for both typical and extreme moves.
2. A filter against frequent whipsaws, especially in choppy environments.
3. A visual framework that novices and experts can interpret rapidly.
Section 20: Summary and Practical Tips
Uptrick: Volatility Reversion Bands offers a powerful tool for traders looking to combine volatility-based signals with momentum-derived reversals. It emphasizes clarity through color-coded bars, defined reversal zones, and optional weak signal markers. While potentially useful across all major timeframes, it demands ongoing risk management, realistic expectations, and careful study of how signals behave under different market conditions. No indicator serves as a crystal ball, so integrating this script into an overall strategy—possibly alongside volume data, fundamentals, or momentum oscillators—often yields the best results.
Disclaimer and Educational Use
This script is intended for educational and informational purposes. It does not constitute financial advice, nor does it guarantee trading success. Sudden economic events, low-liquidity times, and unexpected market behaviors can all undermine technical signals. Traders should use proper testing procedures (backtesting and forward-testing) and maintain disciplined risk management measures.
Forex Pair Yield Momentum This Pine Script strategy leverages yield differentials between the 2-year government bond yields of two countries to trade Forex pairs. Yield spreads are widely regarded as a fundamental driver of currency movements, as highlighted by international finance theories like the Interest Rate Parity (IRP), which suggests that currencies with higher yields tend to appreciate due to increased capital flows:
1. Dynamic Yield Spread Calculation:
• The strategy dynamically calculates the yield spread (yield_a - yield_b) for the chosen Forex pair.
• Example: For GBP/USD, the spread equals US 2Y Yield - UK 2Y Yield.
2. Momentum Analysis via Bollinger Bands:
• Yield momentum is computed as the difference between the current spread and its moving
Bollinger Bands are applied to identify extreme deviations:
• Long Entry: When momentum crosses below the lower band.
• Short Entry: When momentum crosses above the upper band.
3. Reversal Logic:
• An optional checkbox reverses the trading logic, allowing long trades at the upper band and short trades at the lower band, accommodating different market conditions.
4. Trade Management:
• Positions are held for a predefined number of bars (hold_periods), and each trade uses a fixed contract size of 100 with a starting capital of $20,000.
Theoretical Basis:
1. Yield Differentials and Currency Movements:
• Empirical studies, such as Clarida et al. (2009), confirm that interest rate differentials significantly impact exchange rate dynamics, especially in carry trade strategies .
• Higher-yields tend to appreciate against lower-yielding currencies due to speculative flows and demand for higher returns.
2. Bollinger Bands for Momentum:
• Bollinger Bands effectively capture deviations in yield momentum, identifying opportunities where price returns to equilibrium (mean reversion) or extends in trend-following scenarios (momentum breakout).
• As Bollinger (2001) emphasized, this tool adapts to market volatility by dynamically adjusting thresholds .
References:
1. Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy.
2. Obstfeld, M., & Rogoff, K. (1996). Foundations of International Macroeconomics.
3. Clarida, R., Davis, J., & Pedersen, N. (2009). Currency Carry Trade Regimes. NBER.
4. Bollinger, J. (2001). Bollinger on Bollinger Bands.
5. Mendelsohn, L. B. (2006). Forex Trading Using Intermarket Analysis.
Soul Button Scalping (1 min chart) V 1.0Indicator Description
- P Signal: The foundational buy signal. It should be confirmed by observing RSI divergence on the 1-minute chart.
- Green, Orange, and Blue Signals: Three buy signals generated through the combination of multiple oscillators. These signals should also be cross-referenced with the RSI on the 1-minute chart.
- Big White and Big Yellow Signals: These represent strong buy signals, triggered in extreme oversold conditions.
- BEST BUY Signal: The most reliable and powerful buy signal available in this indicator.
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Red Sell Signal: A straightforward sell signal indicating potential overbought conditions.
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Usage Guidance
This scalping indicator is specifically designed for use on the 1-minute chart, incorporating data from the 5-minute chart for added context. It is most effective when used in conjunction with:
• VWAP (Volume Weighted Average Price), already included in the indicator.
• RSI on the 1-minute chart, which should be opened as a separate indicator.
• Trendlines, structure breakouts, and price action analysis to confirm signals.
Intended for Crypto Scalping:
The indicator is optimized for scalping cryptocurrency markets.
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Future Enhancements:
• Integration of price action and candlestick patterns.
• A refined version tailored for trading futures contracts, specifically ES and MES in the stock market.
Full Spectrum Delta BandsI created the Full Spectrum Delta Bands (FullSpec ΔBB) to go beyond traditional Bollinger Bands by incorporating both OHLC (Open, High, Low, Close) and Close-based data into the calculations. Instead of relying solely on closing prices, this indicator evaluates deviations from the complete bar range (OHLC), offering a more accurate view of market behavior.
A key feature is the Delta Flip, which highlights shifts between OHLC and Close-based bands. These flips are visually marked with color changes, signaling potential trend reversals, breakout zones, or volatility shifts. Traders can use these moments as inflection points to refine their entry and exit strategies.
The indicator also supports customizable sensitivity and deviation multiplier settings, allowing it to adapt to different trading styles and timeframes. Lower deviation values (e.g., 1σ or 1.5σ) are ideal for scalping on shorter timeframes like 5-min or 15-min charts, while higher values (e.g., 2.5σ or 3σ) are better suited for long-term trend analysis on weekly or monthly charts. The standard deviation multiplier fine-tunes the upper and lower bands to match specific trading goals and market conditions.
I designed Full Spectrum Delta Bands to provide deeper insights and a clearer view of market dynamics compared to traditional Bollinger Bands. Whether you’re a scalper, swing trader, or long-term investor, this tool helps you make informed and confident trading decisions.
Williams BBDiv Signal [trade_lexx]📈 Williams BBDiv Signal — Improve your trading strategy with accurate signals!
Introducing Williams BBDiv Signal , an advanced trading indicator designed for a comprehensive analysis of market conditions. This indicator combines Williams%R with Bollinger Bands, providing traders with a powerful tool for generating buy and sell signals, as well as detecting divergences. It is ideal for traders who need an advantage in detecting changing trends and market conditions.
🔍 How signals work
— A buy signal is generated when the Williams %R line crosses the lower Bollinger Bands band from bottom to top. This indicates that the market may be oversold and ready for a rebound. They are displayed as green triangles located under the Williams %R graph. On the main chart, buy signals are displayed as green triangles labeled "Buy" under candlesticks.
— A sell signal is generated when the Williams %R line crosses the upper Bollinger Bands band from top to bottom. This indicates that the market may be overbought and ready for a correction. They are displayed as red triangles located above the Williams %R chart. On the main chart, the sell signals are displayed as red triangles with the word "Sell" above the candlesticks.
— Minimum Bars Between Signals
The user can adjust the minimum number of bars between the signals to avoid false signals. This helps to filter out noise and improve signal quality.
— Mode "Wait for Opposite Signal"
In this mode, buy and sell signals are generated only after receiving the opposite signal. This adds an additional level of filtering and helps to avoid false alarms.
— Mode "Overbought and Oversold Zones"
A buy signal is generated only when Williams %R is below the -80 level (Lower Band). A sell signal is generated only when Williams %R is above -20 (Upper Band).
📊 Divergences
— Bullish divergence occurs when Williams%R shows a higher low while price shows a lower low. This indicates a possible upward reversal. They are displayed as green lines and labels labeled "Bull" on the Williams %R chart. On the main chart, bullish divergences are displayed as green triangles labeled "Bull" under candlesticks.
— A bearish divergence occurs when Williams %R shows a lower high, while the price shows a higher high. This indicates a possible downward reversal. They are displayed as red lines and labels labeled "Bear" on the Williams %R chart. On the main chart, bearish divergences are displayed as red triangles with the word "Bear" above the candlesticks.
— 🔌Connector Signal🔌 and 🔌Connector Divergence🔌
It allows you to connect the indicator to trading strategies and test signals throughout the trading history. This makes the indicator an even more powerful tool for traders who want to test the effectiveness of their strategies on historical data.
🔔 Alerts
The indicator provides the ability to set up alerts for buy and sell signals, as well as for divergences. This allows traders to keep abreast of important market developments without having to constantly monitor the chart.
🎨 Customizable Appearance
Customize the appearance of Williams BBDiv Signal according to your preferences to make the analysis more convenient and visually pleasing. In the indicator settings section, you can change the colors of the buy and sell signals, as well as divergences, so that they stand out on the chart and are easily visible.
🔧 How it works
— The indicator starts by calculating the Williams %R and Bollinger Bands values for a certain period to assess market conditions. Initial assumptions are introduced for overbought and oversold levels, as well as for the standard deviation of the Bollinger Bands. The indicator then analyzes these values to generate buy and sell signals. This classification helps to determine the appropriate level of volatility for signal calculation. As the market evolves, the indicator dynamically adjusts, providing information about the trend and volatility in real time.
Quick Guide to Using Williams BBDiv Signal
— Add the indicator to your favorites by clicking on the star icon. Adjust the parameters, such as the period length for Williams %R, the type of moving average and the standard deviation for Bollinger Bands, according to your trading style. Or leave all the default settings.
— Adjust the signal filters to improve the quality of the signals and avoid false alarms, adjust the filters in the "Signal Settings" section.
— Turn on alerts so that you don't miss important trading opportunities and don't constantly sit at the chart, set up alerts for buy and sell signals, as well as for divergences. This will allow you to keep abreast of all key market developments and respond to them in a timely manner, without being distracted from other business.
— Use signals. They will help you determine the optimal entry and exit points for your positions. Also, pay attention to bullish and bearish divergences, which may indicate possible market reversals and provide additional trading opportunities.
— Use the 🔌Connector🔌 for deeper analysis and verification of the effectiveness of signals, connect it to your trading strategies. This will allow you to test signals throughout the trading history and evaluate their accuracy based on historical data. Include the indicator in your trading strategy and run testing to see how buy and sell signals have worked in the past. Analyze the test results to determine how reliable the signals are and how they can improve your trading strategy. This will help you make better informed decisions and increase your trading efficiency.
Uptrick: Smart BoundariesThis script is an indicator that combines the RSI (Relative Strength Index) and Bollinger Bands to highlight potential points where price momentum and volatility may both be at extreme levels. Below is a detailed explanation of its components, how it calculates signals, and why these two indicators have been merged into one tool. This script is intended solely for educational purposes and for traders who want to explore the combined use of momentum and volatility measures. Please remember that no single indicator guarantees profitable results.
Purpose of This Script
This script is designed to serve as a concise, all-in-one tool for traders seeking to track both momentum and volatility extremes in real time. By overlaying RSI signals with Bollinger Band boundaries, it helps users quickly identify points on a chart where price movement may be highly stretched. The goal is to offer a clearer snapshot of potential overbought or oversold conditions without requiring two separate indicators. Additionally, its optional pyramiding feature enables users to manage how many times they initiate trades when signals repeat in the same direction. Through these combined functions, the script aims to streamline technical analysis by consolidating two popular measures—momentum via RSI and volatility via Bollinger Bands—into a single, manageable interface.
1. Why Combine RSI and Bollinger Bands
• RSI (Relative Strength Index): This is a momentum oscillator that measures the speed and magnitude of recent price changes. It typically ranges between 0 and 100. Traders often watch for RSI crossing into “overbought” or “oversold” levels because it may indicate a potential shift in momentum.
• Bollinger Bands: These bands are plotted around a moving average, using a standard deviation multiplier to create an upper and lower boundary. They help illustrate how volatile the price has been relative to its recent average. When price moves outside these boundaries, some traders see it as a sign the price may be overstretched and could revert closer to the average.
Combining these two can be useful because it blends two different perspectives on market movement. RSI attempts to identify momentum extremes, while Bollinger Bands track volatility extremes. By looking for moments when both conditions agree, the script tries to highlight points where price might be unusually stretched in terms of both momentum and volatility.
2. How Signals Are Generated
• Buy Condition:
- RSI dips below a specified “oversold” level (for example, 30 by default).
- Price closes below the lower Bollinger Band.
When these occur together, the script draws a label indicating a potential bullish opportunity. The underlying reasoning is that momentum (RSI) suggests a stronger-than-usual sell-off, and price is also stretched below the lower Bollinger Band.
• Sell Condition:
- RSI rises above a specified “overbought” level (for example, 70 by default).
- Price closes above the upper Bollinger Band.
When these occur together, a label is plotted for a potential bearish opportunity. The rationale is that momentum (RSI) may be overheated, and the price is trading outside the top of its volatility range.
3. Pyramiding Logic and Trade Count Management
• Pyramiding refers to taking multiple positions in the same direction when signals keep firing. While some traders prefer just one position per signal, others like to scale into a trade if the market keeps pushing in their favor.
• This script uses variables that keep track of how many recent buy or sell signals have fired. If the count reaches a user-defined maximum, no more signals of that type will trigger additional labels. This protects traders from over-committing to one direction if the market conditions remain “extreme” for a prolonged period.
• If you disable the pyramiding feature, the script will only plot one label per side until the condition resets (i.e., until RSI and price conditions are no longer met).
4. Labels and Visual Feedback
• Whenever a buy or sell condition appears, the script plots a label directly on the chart:
- Buy labels under the price bar.
- Sell labels above the price bar.
These labels make it easier to review where both RSI and Bollinger Band conditions align. It can be helpful for visually scanning the chart to see if the signals show any patterns related to market reversals or trend continuations.
• The Bollinger Bands themselves are plotted so traders can see when the price is approaching or exceeding the upper or lower band. Watching the RSI and Bollinger Band plots simultaneously can give traders more context for each signal.
5. Originality and Usefulness
This script provides a distinct approach by merging two well-established concepts—RSI and Bollinger Bands—within a single framework, complemented by optional pyramiding controls. Rather than using each indicator separately, it attempts to uncover moments when momentum signals from RSI align with volatility extremes highlighted by Bollinger Bands. This combined perspective can aid in spotting areas of possible overextension in price. Additionally, the built-in pyramiding mechanism offers a method to manage multiple signals in the same direction, allowing users to adjust how aggressively they scale into trades. By integrating these elements together, the script aims to deliver a tool that caters to diverse trading styles while remaining straightforward to configure and interpret.
6. How to Use the Indicator
• Configure the Inputs:
- RSI Length (the lookback period used for the RSI calculation).
- RSI Overbought and Oversold Levels.
- Bollinger Bands Length and Multiplier (defines the moving average period and the degree of deviation).
- Option to reduce pyramiding.
• Set Alerts (Optional):
- You can create TradingView alerts for when these conditions occur, so you do not have to monitor the chart constantly. Choose the buy or sell alert conditions in your alert settings.
• Integration in a Trading Plan:
- This script alone is not a complete trading system. Consider combining it with other forms of analysis, such as support and resistance, volume profiles, or candlestick patterns. Thorough research, testing on historical data, and risk management are always recommended.
7. No Performance Guarantees
• This script does not promise any specific trading results. It is crucial to remember that no single indicator can accurately predict future market movements all the time. The script simply tries to highlight moments when two well-known indicators both point to an extreme condition.
• Actual trading decisions should factor in a range of market information, including personal risk tolerance and broader market conditions.
8. Purpose and Limitations
• Purpose:
- Provide a combined view of momentum (RSI) and volatility (Bollinger Bands) in a single script.
- Assist in spotting times when price may be at an extreme.
- Offer a configurable system for labeling potential buy or sell points based on these extremes.
• Limitations:
- Overbought and oversold conditions can persist for an extended period in trending markets.
- Bollinger Band breakouts do not always result in immediate reversals. Sometimes price keeps moving in the same direction.
- The script does not include a built-in exit strategy or risk management rules. Traders must handle these themselves.
Additional Disclosures
This script is published open-source and does not rely on any external or private libraries. It does not use lookahead methods or repaint signals; all calculations are performed on the current bar without referencing future data. Furthermore, the script is designed for standard candlestick or bar charts rather than non-standard chart types (e.g., Heikin Ashi, Renko). Traders should keep in mind that while the script can help locate potential momentum and volatility extremes, it does not include an exit strategy or account for factors like slippage or commission. All code comes from built-in Pine Script functions and standard formulas for RSI and Bollinger Bands. Anyone reviewing or modifying this script should exercise caution and incorporate proper risk management when applying it to their own trading.
Calculation Details
The script computes RSI by examining a user-defined number of prior bars (the RSI Length) and determining the average of up-moves relative to the average of down-moves over that period. This ratio is then scaled to a 0–100 range, so lower values typically indicate stronger downward momentum, while higher values suggest stronger upward momentum. In parallel, Bollinger Bands are generated by first calculating a simple moving average (SMA) of the closing price for the user-specified length. The script then measures the standard deviation of closing prices over the same period and multiplies it by the chosen factor (the Bollinger Bands Multiplier) to form the upper and lower boundaries around the SMA. These two measures are checked in tandem: if the RSI dips below a certain oversold threshold and price trades below the lower Bollinger Band, a condition is met that may imply a strong short-term sell-off; similarly, if the RSI surpasses the overbought threshold and price rises above the upper Band, it may indicate an overextended move to the upside. The pyramiding counters track how many of these signals occur in sequence, preventing excessive stacking of labels on the chart if conditions remain extreme for multiple bars.
Conclusion
This indicator aims to provide a more complete view of potential market extremes by overlaying the RSI’s momentum readings on top of Bollinger Band volatility signals. By doing so, it attempts to help traders see when both indicators suggest that the market might be oversold or overbought. The optional reduced pyramiding logic further refines how many signals appear, giving users the choice of a single entry or multiple scaling entries. It does not claim any guaranteed success or predictive power, but rather serves as a tool for those wanting to explore this combined approach. Always be cautious and consider multiple factors before placing any trades.
DT Bollinger BandsIndicator Overview
Purpose: The script calculates and plots Bollinger Bands, a technical analysis tool that shows price volatility by plotting:
A central moving average (basis line).
Upper and lower bands representing price deviation from the moving average.
Additional bands for a higher deviation threshold (3 standard deviations).
Customization: Users can customize:
The length of the moving average.
The type of moving average (e.g., SMA, EMA).
The price source (e.g., close price).
Standard deviation multipliers for the bands.
Fixed Time Frame: The script can use a fixed time frame (e.g., daily) for calculations, regardless of the chart's time frame.
Key Features
Moving Average Selection:
The user can select the type of moving average for the basis line:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA/RMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Standard Deviation Multipliers:
Two multipliers are used:
Standard (default = 2.0): For the original Bollinger Bands.
Larger (default = 3.0): For additional bands.
Bands Calculation:
Basis Line: The selected moving average.
Upper Band: Basis + Standard Deviation.
Lower Band: Basis - Standard Deviation.
Additional Bands: Representing ±3 Standard Deviations.
Plots:
Plots the basis, upper, and lower bands.
Fills the area between the bands for visual clarity.
Plots and fills additional bands for ±3 Standard Deviations with lighter colors.
Alerts:
Generates an alert when the price enters the range between the 2nd and 3rd standard deviation bands.
The alert can be used to notify when price volatility increases significantly.
Background Highlighting:
Colors the chart background based on alert conditions:
Green if the price is above the basis line.
Red if the price is below the basis line.
Offset:
Adds an optional horizontal offset to the plots for fine-tuning their alignment.
How It Works
Input Parameters:
The user specifies settings such as moving average type, length, multipliers, and fixed time frame.
Calculations:
The script computes the basis (moving average) and standard deviations on the fixed time frame.
Bands are calculated using the basis and multipliers.
Plotting:
The basis line and upper/lower bands are plotted with distinct colors.
Additional 3 StdDev bands are plotted with lighter colors.
Alerts:
An alert condition is created when the price moves between the 2nd and 3rd standard deviation bands.
Visual Enhancements:
Chart background changes color dynamically based on the price’s position relative to the basis line and alert conditions.
Usage
This script is useful for traders who:
Want a detailed visualization of price volatility.
Use Bollinger Bands to identify breakout or mean-reversion trading opportunities.
Need alerts when the price enters specific volatility thresholds.
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview
The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions.
Understanding RSI
What is RSI?
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset.
How RSI Works:
Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods.
Range: The RSI oscillates between 0 and 100.
Interpretation:
Key Features of RSI:
Momentum Indicator: RSI helps identify the momentum of price movements.
Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals.
Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50.
Understanding Bollinger Bands
What is Bollinger Bands?
Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines:
Upper Band: SMA + (Standard Deviation × Multiplier)
Middle Band (Basis): SMA
Lower Band: SMA - (Standard Deviation × Multiplier)
How Bollinger Bands Work:
Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility.
Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands.
Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels.
Key Features of Bollinger Bands:
Volatility Indicator: Bollinger Bands help traders understand the volatility of the market.
Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands.
Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout.
Combining RSI and Bollinger Bands
Strategy Overview:
The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are:
RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe.
RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes.
Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band.
Strategy Details:
RSI Calculation:
Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes.
Check if the RSI crosses above 60 on the 15-minute timeframe.
Ensure the RSI is above 60 on the 1-hour and 1-day timeframes.
Bollinger Bands Calculation:
Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations.
Check if the price is above the 20-period moving average or walking on the upper Bollinger Band.
Entry and Exit Signals:
Long Signal: When all the above conditions are met, consider a long entry.
Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit.
Example Usage
Setup:
Add the indicator to your TradingView chart.
Configure the inputs as per your requirements.
Monitoring:
Look for the long signal on the chart.
Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes.
Check that the price is above the 20-period moving average or walking on the upper Bollinger Band.
Trading:
Enter a long position when the criteria are met.
Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules.
Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average.
House Rules Compliance
No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis.
TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines.
Conclusion
This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
Super Oscillator with Alerts by BigBlueCheeseSuper Oscillator with Alerts (by BigBlueCheese)
I got sick of eyeballing multiple oscillators generating output on different scales and interpreting them on the fly, so I picked 4 of my favs, 2 fisher transforms (fast & slow) The Squeeze & my own Market Rhythm Oscillator & made the Super Oscillator with Alerts which combines multiple indicators and oscillators to analyze market conditions and generate actionable trading signals.
The output is buy/sell/neutral signals and a color coded table summarizing indicator states (strong buy to strong sell etc). The color legend can be disabled once you get used to the color codes. The user can choose to watch the table output and its changing output, OR unclutter their screen by toggling the table off & just watching for the signals SO+ (buy), SO-(sell), SO?(neutral)
The combined signals are run through a scoring and weighting scheme that utilizes each indicators Z-scores, Min-Max normalization, and raw values which are all used in different parts of the scoring process.
A velocity filter (for more immediate/sensitive response) is available for the user to toggle on/off. The raw indicator values are classified into categories reflecting their current strength and are assigned momentum points.
Z-scores measure how far each oscillator's current value deviates from its mean in terms of standard deviations. Basically, the Z-scores focus on relative behavior, while momentum captures directional trends. Together, they provide a more nuanced view of market conditions. Large Z-scores increase the likelihood of stronger signals. The idea is to are amplify influence in extreme conditions whereas low Z scores will have minimal impact on the cumulative score, making signals less prone to noise.
Inputs and Their Contributions
1. Momentum: Controlled by the raw oscillator values and thresholds.
2. Min-Max: Automatically calculated based on the historical range of oscillators.
3. Velocity: Input: useVelocity (true/false) toggle. Weights: User-defined weights for velocity contribution.
4. Z-Score: Input: useZScore (true/false) toggle. Weights: User-defined weights for Z-score contribution.
The system combines momentum, Min-Max normalization, (and if enabled) velocity, and Z-scores, to generate dynamic and actionable trading signals that appear as markers on the chart indicating buy, sell, and neutral signals.
Alerts can also be triggered based on these signals.
Users can customize the weighting and inclusion of velocity and Z-scores to align the scoring system with their trading strategy and preferences.
If there is enough interest for some other preferred oscillator, I will substitute it for out my Market Rhythm Oscillator & republish with the code. LMK
For the curious out there, the Market Rhythm Oscillator (MRO) is a custom oscillator that analyzes price dynamics using a combination of weighted volatility-based calculations. It helps measure price momentum and potential exhaustion levels by identifying high and low volatility regions.
• Purpose: The MRO is particularly effective at identifying market trends and potential reversals by analyzing price extremes and their behavior over a defined lookback period.
• Calculation Components might include:
o Waveform Volatility Factor (WVF): Measures the price's deviation from its highest or lowest values within a given period.
o Bands and Smoothing:
Upper and lower bands based on standard deviations of WVF.
Smoothing is applied to the WVF for better trend clarity.
o Exhaustion Levels: Uses the MRO's trend length to calculate when the price action may become overextended.
Happy hunting but as always, not a trade recommendation, past results not indicative of future results, DYOR!
DCA Strategy with Mean Reversion and Bollinger BandDCA Strategy with Mean Reversion and Bollinger Band
The Dollar-Cost Averaging (DCA) Strategy with Mean Reversion and Bollinger Bands is a sophisticated trading strategy that combines the principles of DCA, mean reversion, and technical analysis using Bollinger Bands. This strategy aims to capitalize on market corrections by systematically entering positions during periods of price pullbacks and reversion to the mean.
Key Concepts and Principles
1. Dollar-Cost Averaging (DCA)
DCA is an investment strategy that involves regularly purchasing a fixed dollar amount of an asset, regardless of its price. The idea behind DCA is that by spreading out investments over time, the impact of market volatility is reduced, and investors can avoid making large investments at inopportune times. The strategy reduces the risk of buying all at once during a market high and can smooth out the cost of purchasing assets over time.
In the context of this strategy, the Investment Amount (USD) is set by the user and represents the amount of capital to be invested in each buy order. The strategy executes buy orders whenever the price crosses below the lower Bollinger Band, which suggests a potential market correction or pullback. This is an effective way to average the entry price and avoid the emotional pitfalls of trying to time the market perfectly.
2. Mean Reversion
Mean reversion is a concept that suggests prices will tend to return to their historical average or mean over time. In this strategy, mean reversion is implemented using the Bollinger Bands, which are based on a moving average and standard deviation. The lower band is considered a potential buy signal when the price crosses below it, indicating that the asset has become oversold or underpriced relative to its historical average. This triggers the DCA buy order.
Mean reversion strategies are popular because they exploit the natural tendency of prices to revert to their mean after experiencing extreme deviations, such as during market corrections or panic selling.
3. Bollinger Bands
Bollinger Bands are a technical analysis tool that consists of three lines:
Middle Band: The moving average, usually a 200-period Exponential Moving Average (EMA) in this strategy. This serves as the "mean" or baseline.
Upper Band: The middle band plus a certain number of standard deviations (multiplier). The upper band is used to identify overbought conditions.
Lower Band: The middle band minus a certain number of standard deviations (multiplier). The lower band is used to identify oversold conditions.
In this strategy, the Bollinger Bands are used to identify potential entry points for DCA trades. When the price crosses below the lower band, this is seen as a potential opportunity for mean reversion, suggesting that the asset may be oversold and could reverse back toward the middle band (the EMA). Conversely, when the price crosses above the upper band, it indicates overbought conditions and signals potential market exhaustion.
4. Time-Based Entry and Exit
The strategy has specific entry and exit points defined by time parameters:
Open Date: The date when the strategy begins opening positions.
Close Date: The date when all positions are closed.
This time-bound approach ensures that the strategy is active only during a specified window, which can be useful for testing specific market conditions or focusing on a particular time frame.
5. Position Sizing
Position sizing is determined by the Investment Amount (USD), which is the fixed amount to be invested in each buy order. The quantity of the asset to be purchased is calculated by dividing the investment amount by the current price of the asset (investment_amount / close). This ensures that the amount invested remains constant despite fluctuations in the asset's price.
6. Closing All Positions
The strategy includes an exit rule that closes all positions once the specified close date is reached. This allows for controlled exits and limits the exposure to market fluctuations beyond the strategy's timeframe.
7. Background Color Based on Price Relative to Bollinger Bands
The script uses the background color of the chart to provide visual feedback about the price's relationship with the Bollinger Bands:
Red background indicates the price is above the upper band, signaling overbought conditions.
Green background indicates the price is below the lower band, signaling oversold conditions.
This provides an easy-to-interpret visual cue for traders to assess the current market environment.
Postscript: Configuring Initial Capital for Backtesting
To ensure the backtest results align with the actual investment scenario, users must adjust the Initial Capital in the TradingView strategy properties. This is done by calculating the Initial Capital as the product of the Total Closed Trades and the Investment Amount (USD). For instance:
If the user is investing 100 USD per trade and has 10 closed trades, the Initial Capital should be set to 1,000 USD.
Similarly, if the user is investing 200 USD per trade and has 24 closed trades, the Initial Capital should be set to 4,800 USD.
This adjustment ensures that the backtesting results reflect the actual capital deployed in the strategy and provides an accurate representation of potential gains and losses.
Conclusion
The DCA strategy with Mean Reversion and Bollinger Bands is a systematic approach to investing that leverages the power of regular investments and technical analysis to reduce market timing risks. By combining DCA with the insights offered by Bollinger Bands and mean reversion, this strategy offers a structured way to navigate volatile markets while targeting favorable entry points. The clear entry and exit rules, coupled with time-based constraints, make it a robust and disciplined approach to long-term investing.
Ultra Smart TrailIntroduction
The Ultra Smart Trail indicator is a comprehensive tool for traders seeking to identify and follow market trends efficiently. Combining dynamic trend detection with adaptive price bands, this indicator simplifies the process of understanding market direction and strength. It provides clear visual cues and customizable settings, catering to both novice and experienced traders.
Detailed Description
The Ultra Smart Trail indicator works by calculating a Trend Flow Line (TFL) using a hybrid moving average technique. This TFL dynamically adjusts to market conditions, smoothing out price fluctuations while remaining responsive to significant market shifts.
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Trend Flow Line (TFL)
A color-coded line indicating bullish, bearish, or neutral trends based on price movement relative to the TFL.
The TFL uses a combination of weighted moving averages (WMA) and double-weighted moving averages (DWMA) for accuracy.
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Dynamic Price Bands
The indicator plots upper and lower bands around the TFL, based on customizable multipliers of standard deviation. These bands adapt dynamically to volatility, helping traders spot overbought or oversold conditions.
The script calculates standard deviation-based bands with customizable multipliers, enabling precise adjustment to trading styles or instruments.
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Uptrend/Downtrend Highlights
The background and price bands visually differentiate trending and ranging markets, making it easier to identify high-probability trade setups.
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Reversal Alerts
By analyzing the relationship between price and bands, the script highlights potential reversals or continuation zones with distinct levels and fills.
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This indicator is a powerful addition to any trader’s toolkit, simplifying market analysis and enhancing decision-making.
UVR ChannelsUVR CHANNELS: A VOLATILITY-BASED TREND ANALYSIS TOOL
PURPOSE
UVR Channels are designed to dynamically measure market volatility and identify key price levels for potential trend reversals. The channels are calculated using a unique volatility formula(UVR) combined with an EMA as the central reference point. This approach provides traders with a tool for evaluating trends, reversals, and market conditions such as breakouts or consolidations.
CALCULATION MECHANISM
1. Ultimate Volatility Rate (UVR) Calculation:
The UVR is a custom measure of volatility that highlights significant price movements by comparing the extremes of current and previous candles.
Volatility Components:
Two values are calculated to represent potential price fluctuations:
The absolute difference between the current candle's high and the previous candle's low:
Volatility Component 1=∣high−low ∣
The absolute difference between the previous candle's high and the current candle's low:
Volatility Component 2=∣high −low∣
Volatility Ratio:
The larger of the two components is selected as the Volatility Ratio, ensuring the UVR captures the most significant movement:
Volatility Ratio=max(Volatility Component 1,Volatility Component 2)
Smoothing with SMMA:
To stabilize the volatility calculation, the Volatility Ratio is smoothed using a Smoothed Moving Average (SMMA) over a user-defined period (e.g., 14 candles):
UVR= (UVR(Previous) × (Period−1))+Volatility Ratio)/Period
2. Band Construction:
The UVR is integrated into the band calculations by using the Exponential Moving Average (EMA) as the central line:
Central Line (EMA):
The EMA is calculated based on closing prices over a user-defined period (e.g., 20 candles).
Upper Band:
The upper band represents a dynamic resistance level, calculated as:
Upper Band=EMA+(UVR × Multiplier)
Lower Band:
The lower band serves as a dynamic support level, calculated as:
Lower Band=EMA−(UVR × Multiplier)
3. Role of the Multiplier:
The Multiplier adjusts the width of the bands based on trader preferences:
Higher Multiplier: Wider bands to capture larger price swings.
Lower Multiplier: Narrower bands for tighter market analysis.
FEATURES AND USAGE
Dynamic Volatility Analysis:
The UVR Channels expand and contract based on real-time market volatility, offering a dynamic framework for identifying potential price trends.
Expanding Bands: High market volatility.
Contracting Bands: Low volatility or consolidation.
Trend Identification:
Price consistently near the upper band indicates a strong bullish trend.
Price near the lower band signals a bearish trend.
Trend Reversal Signals:
Price reaching the upper band may signal overbought conditions, while price touching the lower band may signal oversold conditions.
Breakout Potential:
Narrow bands often precede significant price breakouts, making UVR Channels a useful tool for spotting early breakout conditions.
DIFFERENCES FROM BOLLINGER BANDS
Unlike Bollinger Bands, which rely on standard deviation to measure volatility, the UVR Channels use a custom volatility formula based on price extremes (highs and lows). This approach adapts to market behaviour in a unique way, providing traders with an alternative and accurate view of volatility and trends.
INPUT PARAMETERS
Volatility Period:
Determines the number of periods used to smooth the volatility ratio. A higher value results in smoother bands but may lag behind sudden market changes.
EMA Period:
Controls the calculation of the central reference line.
Multiplier:
Adjusts the width of the bands. Increasing the multiplier widens the bands, capturing larger price movements, while decreasing it narrows the bands for tighter analysis.
VISUALIZATION
Purple Line: The EMA (central line).
Red Line: Upper band (dynamic resistance).
Green Line: Lower band (dynamic support).
Shaded Area: Fills the space between the upper and lower bands, visually highlighting the channel.
[Venturose] MACD x BB x STDEV x RVIDescription:
The MACD x BB x STDEV x RVI combines MACD, Bollinger Bands, Standard Deviation, and Relative Volatility Index into a single tool. This indicator is designed to provide insights into market trends, momentum, and volatility. It generates buy and sell signals, by analyzing the interactions between these components. These buy and sell signals are not literal, and should be used in combination with the current trend.
How It Works:
MACD: Tracks momentum and trend direction using customizable fast and slow EMA periods.
Bollinger Bands: Adds volatility bands to MACD to identify overextension zones.
Standard Deviation: Dynamically adjusts the Bollinger Band width based on MACD volatility.
RVI (Relative Volatility Index): Confirms momentum extremes with upper and lower threshold markers.
Custom Logic: Includes a trigger system ("inside" or "flipped") to adapt signals to various market conditions and an optional filter to reduce noise.
Key Features:
Combines MACD and Bollinger Bands with volatility and momentum confirmations from RVI.
Dynamic color-coded plots for identifying bullish, bearish, and neutral trends.
Customizable parameters for tailoring the indicator to different strategies.
Optional signal filtering to refine buy and sell triggers.
Alerts for buy and sell signals based on signal logic.
Why It’s Unique:
This indicator combines momentum (MACD), volatility (Bollinger Bands and Standard Deviation), and confirmation signals (RVI thresholds) into a unified system. It introduces custom "inside" and "flipped" triggers for adaptable signal generation and includes signal filtering to reduce noise. The addition of RVI-based hints helps identify early overbought or oversold conditions, providing an extra layer of insight for decision-making. The dynamic integration of these components ensures a comprehensive yet straightforward analysis tool for various market conditions.
