Project Monday Strategy [AlgoAI System]Overview
Project Monday is a sophisticated trading strategy designed for active market participants. This strategy can be used alongside other forms of technical analysis, providing traders with additional tools to enhance their market insights. While it offers a flexible approach for identifying and exploiting market inefficiencies, Project Monday does not fit every market condition and requires adjustments. Its core principles include technical analysis and risk management, all aimed at making informed trading decisions and managing risk effectively.
Features
Project Monday Strategy works in any market and includes many features:
Efficient Trading Presets: Offers ready-to-use presets that allow traders to start efficient trading with one click.
Confirmation Signals: Provides signals to help traders validate trends, emphasizing informed decision-making (not to be followed blindly).
Reversal Signals: Identifies signals to alert traders to potential reversals, encouraging careful analysis (not to be followed blindly).
Adaptability: Can be adjusted to fit different market conditions, ensuring ongoing effectiveness.
Multi-Market Application: Suitable for use across various asset classes including stocks, forex, commodities, and cryptocurrencies.
Integration: Can be used alongside other technical analysis tools for enhanced decision-making.
Position Sizing: Allows traders to determine optimal trade size using backtesting and trading performance dashboard.
Backtesting: Supports historical testing to refine and validate the strategy.
Continuous Monitoring: Includes features for ongoing performance evaluation and strategy adjustments.
Unique Project Monday Strategy Features on TradingView:
Adaptive Position Sizing: Dynamically adjusts the size of each position based on market conditions and predefined risk management criteria, ensuring optimal trade sizing and risk exposure.
Preliminary Position Opening: Allows traders to enter a position in anticipation of a signal confirmation, enabling them to capture early market movements and improve entry points.
Preliminary Position Closing: Enables traders to exit a position before a signal reversal, helping to lock in profits and minimize potential losses during volatile market conditions.
Adjusting Strategy Parameters:
Price Band Inputs:
Project Monday Strategy uses a set of configurable inputs to tailor its behavior according to the trader's preferences. The following are the key inputs for the price band calculations. Signals are not generated when the price remains within these bands.
“Length of Calculation” determines how many historical data points are used in the trend calculation. A shorter “Length of Calculation” will make the Price Band more responsive to recent price changes but may also increase the noise and the likelihood of false signals. A longer “Length of Calculation” will make the Price Band smoother, with less noise, but may cause more lag in reacting to price changes.
“Offset” determines the position of the Gaussian filter, which is used to weight the data points in the trend calculation. The offset is expressed as a fraction of the “Length of Calculation”, with a value between 0 and 1. A higher “Offset” will shift the Gaussian filter closer to the more recent data points, making the Price Band more responsive to recent price changes but potentially increasing noise. A lower “Offset” will shift the Gaussian filter closer to the centre of the window, resulting in a smoother Price Band but potentially introducing more lag.
“Sigma” refers to the standard deviation used in the Gaussian distribution function. This parameter determines the smoothness of the curve and the degree to which data points close to the centre of the “Length of Calculation” are weighted more heavily than those further away. A smaller “Sigma” will result in a narrower Gaussian filter, leading to a more responsive Price Band but with a higher chance of noise and false signals. A larger “Sigma” will result in a wider Gaussian filter, creating a smoother Price Band but with more lag.
Adjust the “Source” inputs to specify which type of price data should be used for strategy calculations and signal generation.
“Width of Band” input determines the multiplier for the band width. A higher value of “Width of Band” makes the price band wider, which generates fewer signals due to the lower probability of the price moving outside the band. Conversely, a lower multiplier makes the band narrower, generating more signals but also increasing the likelihood of false signals.
Direction input:
The Project Monday strategy includes an input to specify the direction of trades, allowing traders to control whether the strategy should consider long positions, short positions, or both. The following input parameter is used for this purpose:
This input parameter allows traders to define the type of positions the strategy will take. It has three options:
Only Long: The strategy will generate signals exclusively for buying or closing short positions, focusing on potential uptrends.
Only Short: The strategy will generate signals exclusively for selling or closing long positions, focusing on potential downtrends.
Both: The strategy will generate signals for both buying (long positions) and selling (short positions), allowing for a more comprehensive trading approach that captures opportunities in both rising and falling markets.
Signals Filter:
The Project Monday strategy includes inputs to filter signals based on higher timeframes and the length of the data used for filtering. These inputs help traders refine the strategy's performance by considering broader market trends and smoothing out short-term fluctuations.
Filter Timeframe input specifies the timeframe used for filtering signals. By choosing a higher timeframe, traders can filter out noise from shorter timeframes and focus on more significant trends. The options range from intraday minutes (e.g., 1, 5, 15 minutes) to daily (1D, 2D, etc.), weekly (1W, 2W, etc.), and monthly (1M) timeframes. This allows traders to align their strategy with their preferred trading horizon and market perspective.
Filter Length input defines the number of data points used for filtering signals on the selected timeframe. A longer filter length will smooth out the data more, helping to identify sustained trends and reduce the impact of short-term fluctuations. Conversely, a shorter filter length will make the filter more responsive to recent price changes, potentially generating more signals but also increasing sensitivity to market noise.
Adaptive Position Size:
The Project Monday strategy incorporates inputs for unique feature Adaptive Position Sizing (APS), which dynamically adjusts the size of trades based on market conditions and specified parameters. This feature helps optimize risk management and trading performance.
Enable Adaptive Position Size: Users can check or uncheck this box to enable or disable the Adaptive Position Size feature. When checked, the strategy dynamically adjusts position sizes based on the defined parameters. This allows traders to scale their positions according to market volatility and other factors, enhancing risk management and potentially improving returns. When unchecked, the strategy will not adjust position sizes adaptively, and positions will remain fixed as per other settings.
“Timeframe for Adaptive Position Size “input specifies the timeframe used for calculating the position size. Options range from intraday minutes (e.g., 30, 60 minutes) to daily (1D, 3D), weekly (1W), and monthly (1M) timeframes. Selecting an appropriate timeframe helps align position sizing calculations with the trader’s overall strategy and market perspective, ensuring that position sizes are adjusted based on relevant market data.
“APS Length” input defines the number of data points used to calculate the adaptive position size. A longer APS length will result in higher position sizes. Conversely, a shorter APS length will result in smaller position sizes.
Anticipatory Trading:
Project Monday Strategy includes inputs for unique feature Anticipatory Trading, allowing traders to open and close positions preliminarily based on certain conditions. This feature aims to provide an edge by taking action before traditional signals confirm.
Enable Preliminary Position Opening: Users can check or uncheck this box to enable or disable Preliminary Position Opening. When enabled, the strategy will open positions based on preliminary conditions before the standard signals are confirmed. This can help traders capitalize on early trend movements and potentially gain a better entry point.
Enable Preliminary Position Closing: Users can check or uncheck this box to enable or disable Preliminary Position Closing. When enabled, the strategy will close positions based on preliminary conditions before the standard exit signals are confirmed. This can help traders lock in profits or limit losses by exiting positions at the early signs of trend reversals.
“Position Size in %” input specifies the position size as a percentage of the trading capital. By setting this value, traders can control the amount of capital allocated to each trade. For example, a risk value of 40% means that 40% of the available trading capital will be used for each anticipatory trade. This helps in managing risk and ensuring that the position size aligns with the trader's risk tolerance and overall strategy.
Usage:
Signal Generation
Long signal indicates a potential uptrend, suggesting either buying or closing a short position. Short signal indicates a potential downtrend, suggesting either selling or closing a long position. Signals are generated on your chart when the price moves beyond a calculated price band based on the current trend.
Signal Filtering
The strategy includes a filtering mechanism based on the current or another timeframe. Filtering works best with higher timeframes. This component calculates the trend on a higher timeframe and predicts the trend, ensuring trades on the current timeframe are only opened if they align with the higher timeframe trend. Setting the right filter timeframe is crucial for obtaining the best signals.
Position Direction
Users can choose the direction of positions to open via the settings box. Options include only long positions, only short positions, or both.
Adaptive Position Size (APS)
Users can enable the Adaptive Position Size feature to adjust position sizes based on trend strength. The strategy evaluates the strength of the current trend based on a higher timeframe. The stronger the trend, the larger the position size for opening a position.
Anticipatory Trading
Users can activate this unique feature to enhance trading decisions. The strategy assesses the likelihood of receiving a main signal. If the opportunity appears strong, it opens a partial position, as specified in the settings box. As the probability of the signal strengthens, the strategy gradually increases the position size.
Exit Strategy
The strategy exits positions based on receiving a reverse signal. Positions opened through “Anticipatory trading” are exited incrementally as each preliminary signal reverses.
By following these steps, traders can implement the strategy to navigate various market scenarios, manage risk, and adjust trading performance over time. Adjusting parameters and monitoring signals diligently are key to adapting the strategy to individual trading styles and market conditions.
You will get
By purchasing the Project Monday strategy, you not only gain access to a cutting-edge system but also receive ready-to-use presets designed to help you start trading immediately and achieve optimal results. Additionally, you benefit from comprehensive support and the option to request custom presets for your desired financial instruments through our dedicated support team, ensuring you have the tools and assistance needed for successful trading.
Risk Disclaimer
This information is not a personalized investment recommendation, and the financial instruments or transactions mentioned in it may not be appropriate for your financial situation, investment objective(s), risk tolerance, and/or expected return. AlgoAI shall not be liable for any losses incurred in the event of transactions or investments in financial instruments mentioned in this information.
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NOVO ALGO - Starry SkyGeneral Description:
This indicator provides the possible buy and sell entry with the estimated risk and its corresponding Stop Loss (SL) value.
It has originally developed for 1-min chart and works the best on this time-frame. It may work on the other time-frames, but its profitability has not been checked. So, I would rather recommend to use and apply it only on 1-min chart.
Novelty of the indicator:
Trading in 1-min chart consists of dealing with so many small swings and price variations which are very local and does not affect the general trend even in the 5-min time frame.
We call these small price variations and swings 'Noise'.
The novelty of the indicator is in a parameter which we call the Noise Level and filtering length.
It has been widely used in the Fluid Dynamics and in the Large Eddy Simulations where small noises of flow is removed by a dynamic filter.
In this indicator, we have tried to incorporate the same idea but in the price trend detection.
For the current version, we have used a less tolerance for noise level which results in much less signals compared to the full capacity of the indicator. It roughly sends out around 10-15% of the total confirmed positions.
How it detects the entry positions
To define the entry point, 5 main properties are considered and checked at 3 main time frames including 1-min, 5-min, and 15-min.
These time-frames are selected based on the fact that the target chart is in 1-min.
The 5 properties evaluated are:
1- Smooth Moving Average
2- Bollinger Band
3- Price Regression
4- Candle Pattern
5- Volume
Detailed Description:
Detect a possible entry by Smooth Moving Average:
- At each time frame, 3 lengths are considered to calculate the price moving average values; i.e. short, medium and long lengths.
- The interaction of these MAs, of course, defines the local trend of the price generally. It also provides an idea about the strength of the trend.
- The information calculated at 1-min time frame triggers the possible buy/sell. However, it waits until getting confirmation from the upper time frame (5-min).
- We use the MAs of 15-min time frame to define the general dominant price trend and stop reverse signals when the trend is fully dominant in one direction.
When a possible entry position is triggered by the MAs, at that very price bar we calculate the noise level.
If the noise level is higher than a certain predefined value, then the signal is rejected. Otherwise the signal gets out.
The threshold we use to define if a signal is noisy or not is normalized so it can be used without any concern at different markets.
We believe the calculations and ideas behind the Noise Level is what makes this indicator unique and practical.
We define the noise level parameter based on the following properties:
1- Smooth Moving Average at upper time frame (basically 15-min):
If a possible signal is against the trend of the upper time-frame, the noise level is increased.
If it is in the direction of the upper time-frame trend, then the noise level is untouched.
As already mentioned, different lengths are used. So, as the length of MA is larger its impact on the noise level is considered higher.
2- Bollinger Band of upper time frames (5-min and 15-min)
We employ bollinger bands to define 4 regions.
1. Above the upper band
2. Between middle and upper band
3. Between Lower and middle bands
4. Below the lower band
Then use these 4 regions along with the candle position and price regression.
For example, if the price regression line and candle position are on the same region of BB, then we assume less possibility for reverse or strong trend.
Consequently, we increase the noise level parameter. On the other hand, if they belong to two different region, we assume more possibility for big price change, and so we lower the noise level.
3- Price Regression
We use average price regression line to filter out very small swings in the price. We have also set a criterion of continuity for the regression line that ensures small price variation and swings are left out and filtered.
This will come with the sot of delay in the confirmation of signal, but we found it very important to remove very small swings of price that, for example, consists of only few bars in 1-min chart.
We have also used the position of the regression line along with the regions defied by BBs to evaluate the strength of a newly detected trend.
As candles will always reach to the regression at some point, if a possible entry is detected and the regression line and candles belong to two different region, we assume a strong price change. But if they belong to the same region, we increase the noise level and will assume that it might be a small swing.
4- Candle Pattern
We assumed several rules for candles shape and prices to define if a price movement is strong or it is just a small swing. For example we expect the price to be increase in the last 2-3 candles if we should call a entry for long position.
These set of self-made rules have been extracted by using the visual inspections of the price movement. This has been done much more advanced for long entry position which has resulted in more long signals by the indicator.
5- Volume
We use volume of trades in 1-min, 5-min, and 15-min to evaluate the strength of the trend. We use both absolute and what we call directional volume! The directional volume is the volume with the sign of the candle. This helps us to know if the reverse trend supported by enough volume or it is just a small swing.
For example, if the directional volume of 1-min can surpass the 5-min directional volume, this indicates to us that the importance of 5-min data and its validity is less. So, more focus will be put on the 1-min volume data and the direction it indicates.
Money Management:
Profit calculation: the profit is calculated based on the user defined leverage (default 100x). The user has the option to change the buy/sell leverages to the desired values.
Risk assessment: The user has the option to adjust the risk of the trades. Then the SL value will be calculated for each trade according to the defined risk value.
If a value of zero is set for the risk, then the indicator will define the local SL of each trade based on the pivot point.
As in 1-min trading, the prices are noise and include several small swings and consequently several minor pivot points, we filtered the pivot points that belong to the super small swings detected by our noise level indicator.
Suggestion
I found it more profitable to make the trades risk-free when their profits passes 10% (with leverage 100x). Then, readjust the TP of trades if the trend is in the direction of the position.
I would recommend to observe the performance of the indicator for a day or two, before actually trading with its signals. This will help to have a better understanding of the leverage and risk you may apply.
Adaptive Bollinger-RSI Trend Signal [CHE]Adaptive Bollinger-RSI Trend Signal
Indicator Overview:
The "Adaptive Bollinger-RSI Trend Signal " (ABRT Signal ) is a sophisticated trading tool designed to provide clear and actionable buy and sell signals by combining the power of Bollinger Bands and the Relative Strength Index (RSI). This indicator aims to help traders identify potential trend reversals and confirm entry and exit points with greater accuracy.
Key Features:
1. Bollinger Bands Integration:
- Utilizes Bollinger Bands to detect price volatility and identify overbought or oversold conditions.
- Configurable parameters: Length, Source, and Multiplier for precise adjustments based on trading preferences.
- Color customization: Change the colors of the basis line, upper band, lower band, and the fill color between bands.
2. RSI Integration:
- Incorporates the Relative Strength Index (RSI) to validate potential buy and sell signals.
- Configurable parameters: Length, Source, Upper Threshold, and Lower Threshold for customized signal generation.
3. Signal Generation:
- Buy Signal: Generated when the price crosses below the lower Bollinger Band and the RSI crosses above the lower threshold, indicating a potential upward trend.
- Sell Signal: Generated when the price crosses above the upper Bollinger Band and the RSI crosses below the upper threshold, indicating a potential downward trend.
- Color customization: Change the colors of the buy and sell signal labels.
4. State Tracking:
- Tracks and records crossover and crossunder states of the price and RSI to ensure signals are only generated under the right conditions.
- Monitors the basis trend (SMA of the Bollinger Bands) to provide context for signal validation.
5. Counters and Labels:
- Labels each buy and sell signal with a counter to indicate the number of consecutive signals.
- Counters reset upon the generation of an opposite signal, ensuring clarity and preventing signal clutter.
6. DCA (Dollar-Cost Averaging) Calculation:
- Stores the close price at each signal and calculates the average entry price (DCA) for both buy and sell signals.
- Displays the number of positions and DCA values in a label on the chart.
7. Customizable Inputs:
- Easily adjustable parameters for Bollinger Bands, RSI, and colors to suit various trading strategies and timeframes.
- Boolean input to show or hide the table label displaying position counts and DCA values.
- Intuitive and user-friendly configuration options for traders of all experience levels.
How to Use:
1. Setup:
- Add the "Adaptive Bollinger-RSI Trend Signal " to your TradingView chart.
- Customize the input parameters to match your trading style and preferred timeframe.
- Adjust the colors of the indicator elements to your preference for better visibility and clarity.
2. Interpreting Signals:
- Buy Signal: Look for a "Buy" label on the chart, indicating a potential entry point when the price is oversold and RSI signals upward momentum.
- Sell Signal: Look for a "Sell" label on the chart, indicating a potential exit point when the price is overbought and RSI signals downward momentum.
3. Trade Execution:
- Use the buy and sell signals to guide your trade entries and exits, aligning them with your overall trading strategy.
- Monitor the counter labels to understand the strength and frequency of signals, helping you make informed decisions.
4. Adjust and Optimize:
- Regularly review and adjust the indicator parameters based on market conditions and backtesting results.
- Combine this indicator with other technical analysis tools to enhance your trading accuracy and performance.
5. Monitor DCA Values:
- Enable the table label to display the number of positions and average entry prices (DCA) for both buy and sell signals.
- Use this information to assess the cost basis of your trades and make strategic adjustments as needed.
Conclusion:
The Adaptive Bollinger-RSI Trend Signal is a powerful and versatile trading tool designed to help traders identify and capitalize on trend reversals with confidence. By combining the strengths of Bollinger Bands and RSI, this indicator provides clear and reliable signals, making it an essential addition to any trader's toolkit. Customize the settings, interpret the signals, and execute your trades with precision using this comprehensive indicator.
Draw Dealers Levels LinesThis Pine Script is a comprehensive tool for TradingView users, allowing them to display and customize multiple significant horizontal lines on a chart. These lines represent various important price levels, each of which can be configured with specific colors, widths, styles, and labels. This script is particularly useful for traders who rely on technical analysis to identify key support and resistance levels, control zones, and other critical price points.
Key Features:
Dynamic Level Calculation:
The script calculates default levels based on the previous day's closing price (yesterday_close). These levels include:
Max1D: Calculated as yesterday_close * 1.01, representing a 1% increase over the previous close.
Min1D: Calculated as yesterday_close * 0.99, representing a 1% decrease.
BuyControl: Slightly below the Max1D at yesterday_close * 1.0099.
SellControl: Slightly above the Min1D at yesterday_close * 0.991.
PutSup0dte: Another variation with yesterday_close * 1.0098.
CallRes0dte: Based on yesterday_close * 0.98.
CallResAll: Set to yesterday_close * 1.015, showing a 1.5% increase.
PutResAll: Set to yesterday_close * 0.985, showing a 1.5% decrease.
These calculations are rounded to the nearest integer for clarity.
User Customization:
Visibility Controls: Users can enable or disable each line using boolean input controls, allowing for a focused analysis of specific levels.
Level Adjustment: Float inputs allow users to manually set the levels if they differ from the default calculations.
Label Customization: Each line can have a custom label, with default labels provided (e.g., "Max1D", "Min1D", "BuyControl").
Color and Style Options: Users can select specific colors, line widths, and styles (dotted, dashed, solid) for each line, making the chart visually distinctive and easier to read.
Labeling and Placement:
Each line is labeled with the provided custom name and the exact value, displayed to the right of the line. This ensures that the information is readily visible and easy to interpret.
The labels use label.style_label_right to position text at the end of the lines, aiding in clear identification.
Integration with TradingView:
The script uses the request.security() function to access the previous day's closing price, ensuring that the calculations are based on the latest data available.
Practical Applications:
Technical Analysis: The script helps traders mark and monitor key price levels that might act as support or resistance. It is particularly useful in identifying areas where the price might react or reverse.
Strategy Development: By visualizing these critical levels, traders can develop and refine their trading strategies, including setting entry and exit points, stop-loss levels, and target prices.
Customization for Different Markets: The extensive customization options allow the script to be adapted to different markets and trading styles, providing flexibility in technical analysis.
How It Works:
Initialization:
The script starts by fetching the previous day's closing price and calculating the default levels for each line.
It then sets up the user interface inputs, including controls for visibility, levels, colors, and labels.
Drawing and Labeling:
The script dynamically draws each line on the chart at the specified levels, with the corresponding label displayed to the right.
The lines and labels are updated in real-time as new data becomes available or as the user changes the input settings.
This script enhances the ability of traders to perform technical analysis by providing a clear and customizable visualization of key price levels on TradingView charts.
Consolidation Range Detector [Pt]█ Author's Note:
After extensively reviewing the existing consolidation detection tools in the TradingView library, I found that none fully met my expectations. Some tools were overly sensitive, producing too many invalid ranges, while others lacked the necessary sensitivity. Consequently, I decided to develop my own tool. I hope that you, fellow traders, find it valuable and enjoy using it.
█ Description:
The Consolidation Range Detector is a sophisticated TradingView tool designed to identify and visualize periods of price consolidation on any financial chart. This indicator employs advanced algorithms to detect ranges where price movements are confined, helping traders spot potential breakout zones and make informed trading decisions.
█ Key Features:
► Customizable Detection Sensitivity: Adjust the sensitivity of the detection algorithm to suit your trading strategy, ensuring a precise fit within the consolidation range.
► Dynamic Coloring: Choose between random or fixed colors for the consolidation ranges, with options to match different background color schemes (Dark, Light, Neutral).
► Visual Clarity: Highlight detected consolidation ranges directly on the chart with customizable color schemes to enhance visibility and provide clear visual cues.
► ATR-Based Validation: Ensures detected consolidation ranges are significant and reliable by using the Average True Range (ATR) for validation.
█ User-Defined Inputs:
► Minimum Detection Bars: Set the minimum number of bars required to detect a consolidation range.
► Max Range Multiplier: Define the maximum range for detection as a multiple of the ATR.
► Detection Sensitivity: Adjust the sensitivity of the detection algorithm. Higher values mean a tighter fit within the consolidation range.
► Color Options: Choose the color for the consolidation range boxes and decide whether to use random colors.
► Color Scheme (Background): Select a color scheme for the chart background (Dark, Light, Neutral).
█ How It Works:
► Range Detection: The indicator scans the chart for potential consolidation ranges based on user-defined parameters. It calculates the average price and ATR to determine the significance of the range.
► Validation: Each detected range is validated based on criteria such as ATR threshold, range validity, average price comparison, and the number of touches at the range boundaries.
► Visualization: Validated ranges are highlighted on the chart with colored boxes, providing a clear visual cue of potential consolidation zones.
█ Usage Examples:
► Example 1:
The image below showcases the Consolidation Range Detector in action on a chart of S&P 500 E-mini Futures. The indicator highlights several consolidation ranges with different colors, demonstrating its ability to adapt to varying market conditions and visually emphasize key areas of price consolidation. The annotations for breakouts and price reactions are manually marked to illustrate the practical application of the tool in identifying potential trading opportunities based on these key areas.
█ Practical Applications:
► Identify Breakout Zones: Use the detected consolidation ranges to identify potential breakout zones, helping to anticipate significant price movements.
► Identify Key Price Levels: The tool helps in pinpointing key price levels where there is a high probability of significant price reactions, providing crucial insights for trading strategies.
► Enhance Technical Analysis: Integrate the Consolidation Range Detector into your existing technical analysis toolkit to improve the accuracy of your trading decisions.
█ Conclusion:
The Consolidation Range Detector is a powerful tool for traders looking to identify periods of price consolidation and potential breakout zones. With its customizable settings and advanced detection algorithms, it provides a reliable and visual method to enhance your trading strategy. Whether you're a beginner or an experienced trader, this indicator can add significant value to your technical analysis.
█ Cautionary Note:
While the Consolidation Range Detector is a powerful tool, it's important to combine it with other indicators and analysis methods for comprehensive trading decisions. Always consider market context and external factors when interpreting detected consolidation ranges.
Rolling Price Activity Heatmap [AlgoAlpha]📈 Rolling Price Activity Heatmap 🔥
Enhance your trading experience with the Rolling Price Activity Heatmap , designed by AlgoAlpha to provide a dynamic view of price activity over a rolling lookback period. This indicator overlays a heatmap on your chart, highlighting areas of significant price activity, allowing traders to spot key price levels at a glance.
🌟 Key Features
📊 Rolling Heatmap: Visualize historical price activity intensity over a user-defined lookback period.
🔄 Customizable Lookback: Adjust the heatmap lookback period to suit your trading style.
🌫️ Transparency Filter: Fine-tune the heatmap’s transparency to filter out less significant areas.
🎨 Color Customization: Choose colors for up, down, and highlight areas to fit your chart’s theme.
🔄 Inverse Heatmap Option: Flip the heatmap to highlight less active areas if needed.
🛠 Add the Indicator: Add the Indicator to favorites. Customize settings like lookback period, transparency filter, and colors to fit your trading style.
📊 Market Analysis: Watch for areas of high price activity indicated by the heatmap to identify potential support and resistance levels.
🔧 How it Works
This script calculates the highest and lowest prices within a specified lookback period and divides the price range into 15 segments. It counts the number of candles that fall within each segment to determine areas of high and low price activity. The script then plots the heatmap on the chart, using varying levels of transparency to indicate the strength of price activity in each segment, providing a clear visual representation of where significant trading occurs.
Stay ahead of the market with this powerful visualization tool and make informed trading decisions! 📈💼
Simple FVGSimple FVG - Fair Value Gap Indicator
Overview:
The "Simple FVG" script is designed for use with TradingView to identify and visually display Fair Value Gaps (FVG) on a trading chart. This indicator highlights both bullish and bearish imbalances based on specific candlestick patterns, helping traders to quickly identify potential trading opportunities.
Key Features:
Bullish and Bearish Imbalances:
Bullish Imbalances: This script identifies bullish imbalances where the price exhibits a gap upward. The conditions for detecting a bullish imbalance are:
The high of the second candle is greater than the high of the first candle.
The low of the third candle is greater than the high of the first candle.
Bearish Imbalances: This script identifies bearish imbalances where the price exhibits a gap downward. The conditions for detecting a bearish imbalance are:
The low of the second candle is less than the low of the first candle.
The high of the third candle is less than the low of the first candle.
Customizable Display:
Bullish Blocks: Users can toggle the display of bullish imbalance blocks with customizable colors and border settings.
Bearish Blocks: Users can toggle the display of bearish imbalance blocks with customizable colors and border settings.
Color and Border Settings: Adjust the color, border color, and border width of the blocks for both bullish and bearish imbalances according to user preferences.
Visual Representation:
Drawing Blocks: The script draws filled boxes on the chart to represent identified imbalances. These blocks span from the start of the first candlestick to the end of the third candlestick, providing a clear visual indicator of the price gap.
How It Works:
Identification Logic:
The script analyzes three consecutive candles to determine if an imbalance exists.
It compares the highs and lows of these candles to establish bullish or bearish conditions.
Drawing Mechanism:
Once an imbalance condition is met, the script calculates the top and bottom levels of the imbalance block based on the high of the first candle and the low of the third candle for bullish imbalances, and vice versa for bearish imbalances.
It then draws these blocks on the chart using the specified colors and border settings.
Usage Instructions:
Add the Indicator:
Apply the "Simple FVG" indicator to your TradingView chart.
Customize Settings:
Use the input options to enable or disable the display of bullish and bearish blocks.
Adjust the colors and border settings for the imbalance blocks as needed.
Interpret Imbalances:
Look for the drawn blocks to identify potential areas where price imbalances have occurred.
Use this information to inform your trading decisions.
Originality and Value:
The "Simple FVG" script offers a unique approach to visualizing Fair Value Gaps by focusing on specific candlestick patterns. It provides traders with a tool to easily identify and analyze price imbalances, enhancing chart analysis and trading strategy development.
Chart Information:
Ensure to show the complete symbol, timeframe, and script name information on your chart for clarity and reference.
For further details and usage guidelines, refer to the TradingView House Rules.
Note: This script adheres to TradingView's guidelines for originality and usefulness, offering a practical tool for traders seeking to enhance their chart analysis.
This description adheres to TradingView's requirements by providing a detailed explanation of the script's functionality, how it works, and how users can benefit from it.
Buffett Valuation Indicator [TradeDots]The Buffett Valuation Indicator (also known as the Buffett Index or Buffett Ratio) measures the ratio of the total United States stock market to GDP.
This indicator helps determine whether the valuation changes in US stocks are justified by the GDP level.
For example, the ratio is calculated based on the standard deviations from the historical trend line. If the value exceeds +2 standard deviations, it suggests that the stock market is overvalued relative to GDP, and vice versa.
This "Buffett Valuation Indicator" is an enhanced version of the original indicator. It applies a Bollinger Band over the Valuation/GDP ratio to identify overvaluation and undervaluation across different timeframes, making it efficient for use in smaller timeframes, e.g. daily or even hourly intervals.
HOW DOES IT WORK
The Buffett Valuation Indicator measures the ratio between US stock valuation and US GDP, evaluating whether stock valuations are overvalued or undervalued in GDP terms.
In this version, the total valuation of the US stock market is represented by considering the top 10 market capitalization stocks.
Users can customize this list to include other stocks for a more balanced valuation ratio. Alternatively, users may use S&P 500 ETFs, such as SPY or VOO, as inputs.
The ratio is plotted as a line chart in a separate panel below the main chart. A Bollinger Band with a default 100-period and multiples of 1 and 2 is used to identify overvaluation and undervaluation.
For instance, if the ratio line moves above the +2 standard deviation line, it indicates that stocks are overvalued, signaling a potential selling opportunity.
APPLICATION
When the indicator is applied to a chart, we observe the ratio line's movements relative to the standard deviation lines. The further the line deviates from the standard deviation lines, the more extreme the overvaluation or undervaluation.
We look for buying opportunities when the Buffett Index moves below the first and second standard deviation lines and sell opportunities when it moves above these lines. This indicator is used as a microeconomic confirmation tool, in combination with other indicators, to achieve higher win-rate setups.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
TrendMaster ProTrendMaster Pro: A Comprehensive Trend Analysis Tool for Long-Term Investors
TrendMaster Pro is an advanced technical indicator designed to provide long-term investors with a robust and comprehensive analysis of market trends. This sophisticated tool operates exclusively on daily timeframes, making it ideal for those focused on long-term investment strategies. By combining multiple analytical approaches, TrendMaster Pro offers investors a powerful means to assess trend quality and make informed decisions.
Automatic Trend Detection
At the heart of TrendMaster Pro lies its ability to automatically identify the most statistically significant trend. The indicator analyzes various timeframes ranging from 1000 to 5000 days, selecting the one that exhibits the highest correlation. This feature ensures that investors are always working with the most relevant trend data, eliminating the subjectivity often associated with manual trend identification.
The trend detection algorithm employs a regression analysis approach, evaluating approximately 80,000 different trend alternatives each day. Each potential trend is assigned a score based on criteria such as trend density, deviation from regression, and the number of price points near the trend's floor and ceiling. The trend with the highest score is then selected and displayed on the chart.
Comprehensive Scoring System
TrendMaster Pro employs a multi-faceted scoring system that evaluates four key aspects of a trend, providing a holistic view of its quality and potential. Each aspect is scored on a scale of 0 to 10, with the overall trend quality score being a weighted average of these individual scores.
1. Length Score
The Length Score measures the duration of the detected trend. Longer trends receive higher scores, reflecting increased reliability and significance. This score is calculated by normalizing the auto-selected period (which ranges from 1000 to 5000 days) to a scale of 5 to 10.
For example, if the auto-selected period is 3000 days, it would receive a score of around 7.5. This emphasizes the importance of long-term trends in investment decision-making, as they tend to be more stable and indicative of underlying market forces.
2. Strength Score
The Strength Score utilizes Pearson's Correlation Coefficient to assess trend strength. This statistical measure gauges the linear relationship between price and trend projection. A value closer to 1 indicates a strong positive correlation, reinforcing confidence in the trend direction based on historical price movements.
The indicator translates the Pearson's Correlation Coefficient into a score from 0 to 10. For instance, a correlation coefficient of 0.95 might translate to a Strength Score of 8, indicating a strong and reliable trend.
3. Performance Score
The Performance Score compares the asset's Compound Annual Growth Rate (CAGR) to a chosen benchmark, typically a major index like the S&P 500. This score provides insight into how well the asset is performing relative to the broader market.
The CAGR is calculated using the formula: CAGR = (Ending Value / Beginning Value)^(1/n) - 1, where n is the number of years. The Performance Score is then determined by comparing this CAGR to the benchmark's CAGR over the same period. A higher score indicates outperformance relative to the benchmark.
4. Level Score
The Level Score evaluates the current price position within the trend channel. Lower prices within the channel receive higher scores, suggesting potential value or buying opportunities. This score helps identify possible entry points based on historical trend behavior.
For example, if the current price is near the lower boundary of the trend channel, it might receive a Level Score of 9, indicating a potentially attractive entry point.
Visual Representation
TrendMaster Pro provides a clear visual representation of the detected trend by displaying a regression channel on the chart. This channel consists of three lines: a middle line representing the main trend, and upper and lower lines representing standard deviations from the main trend.
The channel offers a quick visual reference for support and resistance levels, helping investors identify potential entry and exit points. The color and style of these lines can be customized to suit individual preferences.
Detailed Information Table
A comprehensive table presents all scores and relevant data, allowing for quick and easy interpretation of the trend analysis. This table includes:
The auto-selected trend length
The Pearson's Correlation Coefficient
The asset's CAGR and the benchmark's CAGR
Individual scores for Length, Strength, Performance, and Level
The overall Trend Quality Score
This table provides investors with a clear, at-a-glance summary of the trend's key characteristics and quality.
Practical Application
To use TrendMaster Pro effectively, investors should consider the following:
Focus on the overall Trend Quality Score as a primary indicator of trend strength and reliability.
Use the Length Score to gauge the trend's longevity and potential stability.
Pay attention to the Strength Score to assess how well the price action aligns with the identified trend.
Utilize the Performance Score to compare the asset's performance against the broader market.
Consider the Level Score when timing entries, looking for opportunities when prices are relatively low within the trend channel.
Use the visual trend channel as a guide for potential support and resistance levels.
Limitations and Considerations
While TrendMaster Pro offers powerful insights, it's important to remember that no indicator can predict future market movements with certainty. The tool should be used in conjunction with fundamental analysis and other market information.
Additionally, as the indicator is designed for daily charts and long-term analysis, it may not be suitable for short-term trading strategies. Users should also be aware that past performance does not guarantee future results, even with strong trend indications.
Conclusion
TrendMaster Pro represents a significant advancement in trend analysis for long-term investors. By combining automatic trend detection, comprehensive scoring, and benchmark comparison, it offers a powerful tool for those seeking to make informed, data-driven investment decisions. Its ability to objectively assess trend quality across multiple dimensions provides investors with a valuable edge in navigating complex market conditions.
For investors looking to deepen their understanding of market trends and enhance their long-term investment strategies, TrendMaster Pro offers a sophisticated yet accessible solution. As with any investment tool, users are encouraged to thoroughly familiarize themselves with its features and interpret its outputs in the context of their overall investment approach.
R-Squared Trend Strength and Direction [CHE] Introduction
TradingView is a web-based platform that allows traders and investors to conduct comprehensive technical analyses, develop trading strategies, and track market movements in real-time. One of the many features TradingView offers is the ability to create custom indicators using Pine Script. In this presentation, we will focus on the implementation and application of an R-Squared indicator for analyzing trend strength and direction, as well as using the T3 indicator for trend direction confirmation.
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What is R-Squared?
R-Squared (R²), also known as the coefficient of determination, is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable(s). In technical analysis, R-Squared is used to quantify the clarity of a trend. A higher R-Squared indicates a clearer trend, less affected by random price fluctuations.
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Pine Script: Implementing the R-Squared Indicator
Inputs:
- Source: The data source to be analyzed, such as the average of high and low prices.
- Period: The period length for calculating sums and R-Squared values.
Sum Calculations:
- Sum X and Sum XX: These sums relate to the indices of the selected period.
- Sum XY and Sum YY: These sums relate to the products of the indices and their respective price values.
- Sum Y: The sum of price values over the chosen period.
Q-Values Calculation:
- Q-values are used to calculate the R-Squared value, which indicates trend clarity.
Trend State:
- Based on the R-Squared value, a trend state is determined, indicating whether a clear trend is present. Specific threshold values are used to identify trend changes.
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Using the T3 Indicator
The T3 indicator is used exclusively for confirming the trend direction in this strategy. It helps verify the direction of the trend identified by the R-Squared indicator.
T3 Indicator Calculation:
- The T3 indicator uses a series of exponential smoothings to smooth price movements and provide a clearer view of the trend direction.
- The T3 indicator confirms the trend direction indicated by the R-Squared indicator.
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Functioning of the R-Squared and T3 Combination
1. Input Parameters:
- Define the data source and period length for calculating sums and R-Squared values.
2. Sum Calculations:
- Calculate various sums over the defined period needed to derive Q-values.
3. Q-Values Calculation:
- Derive Q1, Q2, and Q3 from the sums to calculate the R-Squared value.
4. Trend State:
- Use the R-Squared value to determine if a clear trend is present, utilizing threshold values to recognize trend changes.
5. Trend Direction Confirmation with T3:
- Calculate the T3 indicator to confirm the trend direction. The T3 is used solely for direction confirmation, not for clarity.
6. Long and Short Conditions:
- Define long and short entry conditions based on the combination of R-Squared and T3 indicators, and visualize them on the chart.
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Conclusion
The R-Squared indicator is a powerful tool for analyzing the clarity of a trend. By integrating it into TradingView using Pine Script, traders can make informed decisions and optimize their trading strategies. The T3 indicator is used exclusively in this strategy to confirm the trend direction, enhancing the accuracy of trading signals.
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Questions and Discussion
Are there any questions about the implementation or application of the R-Squared indicator in TradingView? How can we further improve this indicator or integrate it into existing strategies?
Best regards
Chervolino
Rafi's Trend Finder
This custom TradingView indicator measures the relative position of the current closing price within a specified lookback period, providing insights into overbought and oversold market conditions.
Key Features:
Period Input:
Users can define the lookback period for the calculation, with a default value of 250 periods.
Relative Position Calculation:
The indicator computes the difference between the current closing price and the lowest low over the lookback period.
It also calculates the difference between the highest high and the lowest low during the same period.
The resulting value is scaled to a range from 0 to 100.
Dynamic Levels:
Users can customize up to ten pairs of overbought and oversold levels.
Each pair consists of an upper level (default 90) and a lower level (default 10).
Horizontal lines are drawn at these levels on the chart for easy visual reference.
Color-Coded Plot:
The indicator’s plot color changes based on the calculated value’s position relative to the primary overbought and oversold levels:
Green if the value is above the primary upper level.
Red if the value is below the primary lower level.
Gray if the value is between the primary upper and lower levels.
Usage:
This indicator helps traders identify potential reversal points by highlighting when the market is potentially overbought or oversold. The customizable levels allow for fine-tuning based on different trading strategies or market conditions. The visual cues provided by the color-coded plot enhance the interpretability of the indicator, making it a valuable tool for technical analysis.
Risk Management Calculator with Fees and Take Profit [CHE]Risk Management Calculator with Fees and Take Profit
Welcome to the Risk Management Calculator with Fees and Take Profit script! This powerful tool is designed to help traders manage their risk effectively, calculate leverage, and set take profit targets. The script is inspired by and builds upon the ideas from the following TradingView script: ().
This script is inspired by and builds upon the ideas from the following TradingView script:
Features
1. Portfolio Size Input: Enter the size of your portfolio to accurately calculate your risk and leverage.
2. Max Loss Percent Input: Specify the maximum percentage of your portfolio that you are willing to risk on a single trade.
3. Max Leverage Input: Set the maximum leverage you are comfortable using.
4. Trading Fee Input: Include trading fees in your calculations to get a more realistic view of your potential losses and gains.
5. ATR Settings: Configure the ATR period and multiplier to calculate your stop loss and take profit levels.
6. RSI Settings: Adjust the RSI period for trend analysis.
How to Use
Portfolio Size
- Description: This is the total value of your trading account.
- Input: `portfolioSize`
- Default Value: 100
- Minimum Value: 0.001
Max Loss Percent
- Description: The maximum percentage of your portfolio you are willing to lose on a single trade.
- Input: `maxLossPercent`
- Default Value: 3%
- Range: 0.1% to 100%
Max Leverage
- Description: The maximum leverage you wish to use.
- Input: `maxLeverage`
- Default Value: 125
- Range: 1 to 125
Trading Fee
- Description: The fee percentage you pay per trade.
- Input: `feeRate`
- Default Value: 1%
- Range: 0% to 10%
ATR Settings
- ATR Period: Number of bars used to calculate the Average True Range.
- Input: `atrPeriod`
- Default Value: 5
- ATR Multiplier: Multiplier for ATR to set stop loss levels.
- Input: `atrMultiplier`
- Default Value: 2.0
Take Profit Multiplier
- Description: Multiplier for ATR to set take profit levels.
- Input: `takeProfitMultiplier`
- Default Value: 2.0
RSI Settings
- RSI Period: Period for the RSI calculation.
- Input: `rsiPeriod`
- Default Value: 14
Dashboard
The script includes a customizable dashboard that displays the following information:
- Portfolio Size
- Maximum Loss Amount
- Entry Price
- Stop Loss Price
- Stop Loss Percentage
- Calculated Leverage
- Order Value
- Order Quantity
- Trend Direction
- Adjusted Maximum Loss Percentage
- Take Profit Price
Dashboard Settings
- Location: Choose the position of the dashboard on the chart.
- Options: 'Top Right', 'Bottom Right', 'Top Left', 'Bottom Left'
- Size: Adjust the size of the dashboard text.
- Options: 'Tiny', 'Small', 'Normal', 'Large'
- Text/Frame Color: Set the color for the text and frame of the dashboard.
Underlying Principles and Assumptions
Leverage Calculation
The leverage calculation is fundamental to risk management in trading. It ensures that the risk per trade does not exceed a specified percentage of the portfolio. This calculation takes into account the potential loss from the entry price to the stop loss level, adjusted for trading fees. By dividing the maximum acceptable loss by the total potential loss (including fees), we derive a leverage that limits the exposure per trade. This approach helps traders avoid over-leveraging, which can lead to significant losses.
ATR and Stop Loss
The Average True Range (ATR) is used to set stop loss levels because it measures market volatility. A higher ATR indicates more volatility, which means wider stop losses are needed to avoid being prematurely stopped out by normal market fluctuations. By using an ATR multiplier, the stop loss is dynamically adjusted based on current market conditions, providing a more robust risk management strategy.
Take Profit Calculation
The take profit level is calculated as a multiple of the ATR, ensuring that it is set at a realistic level relative to market volatility. This method aims to capture significant price movements while avoiding the noise of smaller fluctuations. Setting take profit targets this way helps in locking in profits when the market moves favorably.
RSI for Trend Confirmation
The Relative Strength Index (RSI) is used to confirm the trend direction. An RSI above 50 typically indicates a bullish trend, while an RSI below 50 indicates a bearish trend. By aligning trades with the prevailing trend, the script increases the probability of successful trades. This trend confirmation helps in making informed decisions about leverage and position sizing.
Risk Color Coding
The script uses color coding to visually indicate the risk level and trend direction. Green indicates a favorable condition for long trades, red for short trades, and gray for neutral conditions. This intuitive color coding aids in quickly assessing the market conditions and making timely trading decisions.
Conclusion
This script aims to provide a comprehensive risk management tool for traders. By integrating portfolio size, leverage, fees, ATR, and RSI, it helps in making informed trading decisions. We hope you find this tool useful in your trading journey.
Happy Trading!
Percentages from 52 Week HighThis script is helpful for anyone that wants to monitor 5, 10, 20, 30, 40, 50% drops from the 52 week moving high.
I have been using a version of this script for a few years now and thought I would share it back with the community as I wrote it in 2021 to find quick deals when flipping through charts of stocks I've been watching. I never seemed to find anything doing this simple yet intuitive thing and I found myself regularly computing these lines manually on each chart. This will save you from having to do that as it automatically draws each level on your chart based on the recent 52 week or daily high.
I recently added the ability to turn on/off different levels and defaulted to setting 5, 10, and 20 % drops from the 52 week high. You can also change this to be a 52 day moving high if that's your preference.
Please let me know if you have ideas for modification as I wanted to share this with the community given I had not seen anything out there giving me what I wanted - which is why I wrote it.
All the best friends.
Support/Resistance v2 (ML) KmeanKmean with Standard Deviation Channel
1. Description of Kmean
Kmean (or K-means) is a popular clustering algorithm used to divide data into K groups based on their similarity. In the context of financial markets, Kmean can be applied to find the average price values over a specific period, allowing the identification of major trends and levels of support and resistance.
2. Application in Trading
In trading, Kmean is used to smooth out the price series and determine long-term trends. This helps traders make more informed decisions by avoiding noise and short-term fluctuations. Kmean can serve as a baseline around which other analytical tools, such as channels and bands, are constructed.
3. Description of Standard Deviation (stdev)
Standard deviation (stdev) is a statistical measure that indicates how much the values of data deviate from their mean value. In finance, standard deviation is often used to assess price volatility. A high standard deviation indicates strong price fluctuations, while a low standard deviation indicates stable movements.
4. Combining Kmean and Standard Deviation to Predict Short-Term Price Behavior
Combining Kmean and standard deviation creates a powerful tool for analyzing market conditions. Kmean shows the average price trend, while the standard deviation channels demonstrate the boundaries within which the price can fluctuate. This combination helps traders to:
Identify support and resistance levels.
Predict potential price reversals.
Assess risks and set stop-losses and take-profits.
Should you have any questions about code, please reach me at Tradingview directly.
Hope you find this script helpful!
Kernel SwitchThe indicator uses different kernel regression functions and filters to analyze and smooth the price data. It incorporates various technical analysis features like moving averages, ATR-based channels, and the Kalman filter to generate buy and sell signals. The purpose of this indicator is to help traders identify trends, reversals, and potential trade entry and exit points.
Key Components and Functionalities:
Kernel and Filter Selection:
Kernel: Options include RationalQuadratic, Gaussian, Periodic, and LocallyPeriodic.
Filter: Options include No Filter, Smooth, and Zero Lag.
Source: The source data for the calculations (default is close).
Lookback Period: The lookback period for the kernel calculations.
Relative Weight: Used for RationalQuadratic kernel.
Start at Bar: The starting bar index for the calculations.
Period: Used for Periodic and LocallyPeriodic kernels.
Additional Calculations:
Multiplier: Option to apply a multiplier to the kernel output.
Smoothing: Option to apply EMA smoothing to the kernel output.
Kalman Filter: Option to apply a Kalman filter to the smoothed output.
ATR Length: The length of the ATR used for calculating upper and lower bands.
Kernel Regression:
The code uses a switch statement to select and apply the chosen kernel function with the specified parameters.
Kalman Filter:
A custom function to apply a Kalman filter to the kernel output, providing additional smoothing and trend estimation.
ATR-based Channels:
Upper and lower bands are calculated using the kernel output and ATR, adjusted by a multiplier.
Buy/Sell Signals:
Buy signals are generated when the kernel output crosses above its previous value.
Sell signals are generated when the kernel output crosses below its previous value.
Plotting:
The main kernel output is plotted with color changes based on its direction (green for up, red for down).
Upper and lower bands are plotted based on the ATR-adjusted kernel output.
Buy and sell signals are marked on the chart with labels.
Additional markers are plotted when the high crosses above the upper band and the low crosses below the lower band.
Usage:
This indicator is used to analyze and smooth price data using various kernel regression functions and filters. It helps traders identify trends and potential reversal points, providing visual signals for buy and sell opportunities. By incorporating ATR-based channels and the Kalman filter, the indicator offers additional insights into price movements and volatility. Traders can customize the parameters to fit their specific trading strategies and preferences.
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Signals & Overlays [UAlgo]The Signals & Overlays indicator is a comprehensive trading tool designed to provide traders with a holistic view of market conditions. It combines multiple analysis techniques to offer insights into trend direction, potential reversal points, and optimal entry and exit levels. This versatile indicator is suitable for various trading styles and timeframes, also has Beginner-Friendly presets to enable multiple features at once within one-click.
🔶 Key Features:
🔹 Contrarian Signals:
This feature identifies potential trend reversals and market turning points. These contrarian signals are displayed as arrow markers on the chart, alerting traders to possible opportunities that go against the prevailing trend. The signals are based on a combination of price action, momentum, and volatility factors, providing a multi-faceted approach to market analysis.
Customizable Settings :
Signal Sensitivity: Adjustable from 0.1 to 10.0. This controls how sensitive the indicator is to potential reversal signals.
🔹 Reversal Zones:
This feature utilizes statistical methods that compute a smoothed average and associated bands around a data series using Gaussian weights. The Gaussian distribution helps to assign more weight to data points near the center of the window, and the bands represent the average plus/minus a scaled measure of deviation.
This technique is often used in financial analysis to detect trends and measure volatility to identify key areas where price reversals are more likely to occur. These zones providing a dynamic representation of potential support and resistance areas. Traders can use these zones to anticipate potential price reactions and plan their entries and exits accordingly.
Users can also customize the responsiveness of the Reversal Zones through the "Zone Speed" setting. This allows for fine-tuning the model's sensitivity to price changes:
Swift Mode: Quickly adapts to recent price movements, ideal for short-term trading.
Standard Mode: Balances recent and historical data for a medium-term perspective.
Slow Mode: Emphasizes longer-term trends, suitable for position trading.
Customizable Settings :
Zone Data Source: Users can select which price data (open, high, low, close, etc.) to use for zone calculations.
Zone Speed: Choosable between "Swift", "Standard", and "Slow", affecting how quickly the zones adapt to price changes.
🔹 Smart Trail:
The Smart Trail feature provides an adaptive trend-following mechanism. It plots a dynamic line that adjusts based on price action and volatility, helping traders stay in trending moves while providing a trailing stop-loss reference. This feature is particularly useful for managing open positions and optimizing exit points.
🔹 Trend Cloud:
Generates a specialized trend indicator using double-smoothed EMAs applied to closing prices and the high-low price range. It visualizes market trends and volatility by shading the area between different indicator values over time. The color of the shading changes to reflect whether the current trend is strengthening or weakening.
The Trend Cloud feature provides a visually intuitive representation of the overall market trend. It generates a dynamic colored cloud on the chart that helps traders quickly assess the current market direction and strength. Bullish trends represented by blue clouds and bearish trends by red clouds.
🔹 Trend Analyzer:
The Trend Analyzer component provides an in-depth analysis of the current market trend. It uses a customizable moving average system to determine the trend direction and strength. The analyzer can be configured to focus on short-term, medium-term, or long-term trends, allowing traders to align their strategy with their preferred trading timeframe.
Customizable Settings :
Analyzer Calculation Period: Adjustable period for trend analysis calculations.
Analyzer Mode: Selectable between "Short-Term", "Medium-Term", and "Long-Term".
Analyzer Calculation Source: Customizable price data source for trend analysis.
Use Heikin Ashi: Option to use Heikin Ashi candles instead of regular candles for calculations.
🔹 TP/Exit/Entry Levels:
The indicator calculates and displays potential take profit (TP), exit, and entry levels based on market structure and volatility. These levels are marked on the chart, offering traders guidance on optimal points for trade management. This feature can be particularly helpful for setting profit targets and managing risk.
🔹 Dashboard:
The customizable dashboard provides a quick overview of key market metrics. It displays information such as trend strength, volume analysis, market volatility, the current state of the Trend Catcher and the market is "Bearish" or "Bullish". This at-a-glance summary helps traders make informed decisions without the need to switch between multiple indicators.
Customizable Settings :
Toggle: Option to display or hide the dashboard.
Dashboard Position and Size: Selectable between "Top Right", "Bottom Right", and "Bottom Left". Adjustable size to "Tiny", "Small" or "Normal".
🔶 Disclaimer:
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Buy Sell Trend MonitorDescription
The purpose of this indicator is to create symbols that try to show the most accurate positions possible for trading. The formation of BUY/SELL symbols is based on the intersection of SYMBOL(Himself), BTC.D, BTC and DXY indices. The resulting signals take values between 0 and 16. These values represent the strength of the signal, and the higher its numerical value, the stronger the signal. Here, 2 different calculation methods are followed for BTC and Altcoins. In BTC, calculations are made according to the direction of BTC Market value and DXY averages, while in Altcoins, calculations are made according to the direction of BTC, BTC.D and DXY averages. If DXY for BTC is trending downwards and the BTC market value is trending upwards, the BUY symbol is formed depending on the level at which the trend occurs. For altcoins, if DXY is trending down, BTC is trending up and BTC.D is trending down, the BUY symbol is formed depending on the level at which the trend occurs. For the SELL signal, the opposite is true.
Symbols are drawn according to standard ticker and OHLC4 values.
The averages of the 1-length RSI value of these symbols are taken as the 6-length SMA.
Symbols
The symbols are explained one by one below.
Orange Line: Bitcoin Marketcap line.
White Line: DXY line.
Red Line: Bitcoin Dominance line.
Aqua Line: Current Symbol line.
Best Use
This indicator should be used for SPOT trades. Regardless, since it is not possible to know exactly the direction of the market, it should be considered to buy gradually at buy signals and sell gradually at sell signals.
It should be followed for at least a 4-hour period. We do not recommend its use as the margin of error will increase in shorter time periods.
Since the signals are not guaranteed to work 100%, we do not recommend you to trade with all your money.
No Repainting
Repainting is definitely not done. After the symbols appear, the closing should be expected. Once the closing occurs, the symbol will now be permanent.
Disclaimer
This indicator is for informational purposes only and should be used for educational purposes only. You may lose money if you rely on this to trade without additional information. Use at your own risk.
Version
v1.0
60-Day Cycle Long-Only IndicatorThe following indicator generates ‘Buy’ signals based on rotating 60-day cycles. The general theory is that when buying strong, growth-oriented assets, 60-day micro-cycles culminate into larger macro-cycles.
Summary:
Explaining the Upper and Lower Bounds in the 60-Day Cycle Strategy:
1. Cycle High (Upper Bound):
The cycle high is the highest closing price of the asset over the past 60 days. This value acts as the upper boundary of the 60-day cycle, indicating the peak price level during this period. When the current closing price is above this boundary, it suggests a potential distribution phase, where the asset might be overbought, and larger players may be selling off their positions. In the strategy, the cycle high is plotted as a red line on the chart, helping traders visually identify the upper limit of the 60-day trading range.
2. Cycle Low (Lower Bound):
The cycle low is the lowest closing price of the asset over the past 60 days. This value acts as the lower boundary of the 60-day cycle, indicating the trough price level during this period. When the current closing price is below this boundary, it suggests a potential accumulation phase, where the asset might be oversold, and larger players may be accumulating positions at lower prices. In the strategy, the cycle low is plotted as an orange line on the chart, helping traders visually identify the lower limit of the 60-day trading range.
How These Bounds Are Calculated:
• Cycle High: Calculated using the highest closing price over the last 60 trading days. In Pine Script, this is achieved with the function ta.highest(close, cycle_length), where cycle_length is set to 60 days.
• Cycle Low: Calculated using the lowest closing price over the last 60 trading days. In Pine Script, this is achieved with the function ta.lowest(close, cycle_length), where cycle_length is set to 60 days.
Interpretation and Application:
• Buy Signal: A buy signal is generated when the closing price crosses above the cycle low. This indicates a potential end to the bearish phase and the start of a bullish trend.
• Distribution Phase: When the closing price crosses above the cycle high, it suggests the market is in a distribution phase, potentially signaling a bearish trend or a sell-off period.
Example:
On a trading chart, the cycle high and cycle low are plotted as horizontal lines, with their colors distinguishing them (red for cycle high and orange for cycle low). These lines create a visual range within which the asset's price has moved over the last 60 days, helping traders quickly assess whether the current price is near the upper or lower bound.
By identifying and plotting these upper and lower bounds, traders can better understand the current market phase and make more informed trading decisions based on the 60-day cycle strategy. This indicator can be used across various assets.
Moving Average Exponential-DonCHI-SUPERTRENDThe "Moving Average Exponential-DonCHI-SUPERTREND" is a trading strategy or indicator that combines three distinct technical analysis tools:
Moving Average Exponential (EMA): This is a type of moving average that gives more weight to recent prices, making it more responsive to price changes compared to a simple moving average.
Donchian Channels (DonCHI): These are bands that are plotted above and below the recent price highs and lows. They help identify the current price volatility and potential breakout points.
SUPERTREND: This is a trend-following indicator that uses the average true range (ATR) to determine the direction of the trend. It provides signals similar to moving averages but with less lag.
United HUN CityPurpose and Usage
The purpose of this strategy is to create a composite indicator that combines the signals from the MFI, Fisher Transform, and Bollinger Bands %b indicators. By normalizing and averaging these indicators, the script aims to provide a smoother and more comprehensive signal that can be used to make trading decisions.
MFI (Money Flow Index): Measures buying and selling pressure based on price and volume.
Fisher Transform: Highlights potential reversal points by transforming price data to a Gaussian normal distribution.
Bollinger Bands %b: Indicates where the price is relative to the Bollinger Bands, helping to identify overbought or oversold conditions.
The combined indicator can be used to identify potential buy or sell signals based on the smoothed composite value. For instance, a high combined indicator value might indicate overbought conditions, while a low value might indicate oversold conditions.
PEV Price BandThe PEV Price Band shows prices calculated using the high and low P/FQ EV of the previous period. (price to enterprise value per share for the last quarter) multiplied by FQ's current EVPS (similar to comparing marketcap to enterprise value but edit equations that are close to the theory of P/E)
If the current price is lower than the minimum P/EVPS, it is considered cheap. In other words, a current price is above the maximum is considered expensive.
PEV Price Band consists of 2 parts.
- First of all, the current P/EVPS value is "green" (if the markecap is less than the enterprise value) or "red" (if the marketcap is more than the enterprise value) or "gold" (if the market value is less than the enterprise value and less than equity)
- Second, the blue line is the closing price.
Bitcoin Logarithmic Regression
This indicator displays logarithmic regression channels for Bitcoin. A logarithmic regression is a function that increases or decreases rapidly at first, but then steadily slows as time moves. The original version of this indicator/model was created as an open source script by a user called Owain but is not available on TradingView anymore. So I decided to update the code to the latest version of pinescript and fine tune some of the parameters.
How to read and use the logarithmic regression:
There are 3 different regression lines or channels visible:
Green Channel: These lines represent different levels of support derived from the logarithmic regression model.
Purpose: The green channel is used to identify potential support levels where the price might find a bottom or bounce back upwards.
Interpretation:
If the price is approaching or touching the lower green lines, it might indicate a buying opportunity or an area where the price is considered undervalued.
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Red Channel: These lines represent different levels of resistance derived from the logarithmic regression model.
Purpose: The red channel is used to identify potential resistance levels where the price might encounter selling pressure or face difficulty moving higher.
Interpretation:
If the price is approaching or touching the upper red lines, it might indicate a selling opportunity or an area where the price is considered overvalued.
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Purple Line This line represents to so-called "fair price" of Bitcoin according to the regression model.
Purpose: The purple line can be used to identify if the current price of Bitcoin is under- or overvalued.
Interpretation: A simple interpretation here would be that over time the price will have the tendency to always return to its "fair price", so starting to DCA more when price is under the line and less when it is over the line could be a suitable investment strategy.
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Practical Application:
You can use this regression channel to build your own, long term, trading strategies. Notice how Bitcoin seems to always act in kind of the same 4 year cycle:
- Price likes to trade around the purple line at the time of the halvings
- After the halvings we see an extended sideways range for up to 300 days
- After the sideways range Bitcoin goes into a bull market frenzy (the area between the green and red channel)
- The price tops out at the upper red channel and then enters a prolonged bear market.
Buying around the purple line or lower line of the green channel and selling once the price reaches the red channel can be a suitable and very profitable strategy.
($ROSE Trader) Mean Multiple OscillatorThe ROSE Trader Mean Multiple Oscillator is an adaptation of The Mayer Multiple, using the 99-Day Simple Moving Average rather than the 200-Day (adjusted for ROSE's higher delta), setting distinct preset levels for ROSE overbought and oversold conditions.
Who is this indicator for?
While this indicator will function on any chart, it is setup for trading Oasis BINANCE:ROSEUSDT token specifically — the presets used are tailored to the ROSE chart.
While it is an open source public script, it has been released primarily for the ROSE community
What does this indicator offer?
This indicator follows the same concepts as the Mayer Multiple, popular with BTC. What makes it unique is that it the presets are setup specifically for the BINANCE:ROSEUSDT , based upon my trading experience.
About the Mayer Multiple:
The Mayer Multiple is a derivative of the 200-day MA, calculated by dividing the BTC market price by the 200-day MA. The 200-day MA is a widely recognised indicator for BTC in establishing macro bull or bear bias. The Mayer Multiple therefore represents a measure of distance away from this long-term average or mean price as a tool to gauge overbought and oversold conditions.
For BTC overbought, and oversold conditions, have historically coincided with Mayer Multiple values of 2.4, and 0.8 respectively.
Adapting this concept to the ROSE token:
The adaption of the Mayer Multiple offered here adjusts the 200-day MA to suit the higher delta or volatility of the BINANCE:ROSEUSDT token specifically. For ROSE I use the 99-day MA to establish macro bull or bear bias. The derived 'Mean Multiple', based on the 99-day MA therefore represents a measure of distance away from this long-term average or mean price as a tool to gauge overbought and oversold conditions.
For ROSE overbought, and oversold conditions, tend to coincide with values of 1.618, and 0.618 respectively. Further offsets have been preprogrammed to add nuance to the way this indicator may be used in different market conditions
The ROSE Trader Mean Multiple Oscillator:
The Oscillator version of this script is useful to determine possible levels that price is likely to reach overbought and over sold conditions by plotting the offsets and values directly on the price chart
Calculations:
99-Day Simple Moving Average (99D SMA) * by offset
This script is partnered with the "ROSE Trade Mean Multiple”: an adaptation of The Mayer Multiple, using the 99-Day Simple Moving Average rather than the 200-Day (adjusted for ROSE's higher delta), setting distinct preset levels for ROSE overbought and oversold conditions.
Note: this script is setup to work with any instrument, but the presets are built to provide actionable data on the Oasis BINANCE:ROSEUSDT token specifically. It is not a predicative model, it rather shows how price has behaved historically / statistically at these levels given past data.
($ROSE Trader) Mean MultipleThe ROSE Trader Mean Multiple is an adaptation of The Mayer Multiple, using the 99-Day Simple Moving Average rather than the 200-Day (adjusted for ROSE's higher delta), setting distinct preset levels for ROSE overbought and oversold conditions.
Who is this indicator for?
While this indicator will function on any chart, it is setup for trading Oasis BINANCE:ROSEUSDT token specifically — the presets used are tailored to the ROSE chart.
While it is an open source public script, it has been released primarily for the ROSE community
What does this indicator offer?
This indicator follows the same concepts as the Mayer Multiple, popular with BTC. What makes it unique is that it the presets are setup specifically for the BINANCE:ROSEUSDT , based upon my trading experience.
About the Mayer Multiple:
The Mayer Multiple is a derivative of the 200-day MA, calculated by dividing the BTC market price by the 200-day MA. The 200-day MA is a widely recognised indicator for BTC in establishing macro bull or bear bias. The Mayer Multiple therefore represents a measure of distance away from this long-term average or mean price as a tool to gauge overbought and oversold conditions.
For BTC overbought, and oversold conditions, have historically coincided with Mayer Multiple values of 2.4, and 0.8 respectively.
Adapting this concept to the ROSE token:
The adaption of the Mayer Multiple offered here adjusts the 200-day MA to suit the higher delta or volatility of the BINANCE:ROSEUSDT token specifically. For ROSE I use the 99-day MA to establish macro bull or bear bias. The derived 'Mean Multiple', based on the 99-day MA therefore represents a measure of distance away from this long-term average or mean price as a tool to gauge overbought and oversold conditions.
For ROSE overbought, and oversold conditions, tend to coincide with values of 1.618, and 0.618 respectively. Further offsets have been preprogrammed to add nuance to the way this indicator may be used in different market conditions
Calculations:
Mean Multiple is calculated by dividing the market price by the 99-Day Simple Moving Average (99D SMA). The indicator allows you to adjust the period if desired.
The indicator horizontals are set at regular offsets from Mean multiple (MM), these are calculated by multiplying the SMA from which the MM is derived by a set number to arrive at each offset, based upon historic price data.
The indicator horizontals may work as oversold and over bought levels, as they show the distance the price has moved from the mean, and how the Mean Multiple (as a derivation of price) has behaved at these levels historically
This script is partnered with the "ROSE Trade Mean Multiple Oscillator" which shows this data plotted on the price chart (This Oscillator is pictured in the chart but must be added separately, it can be found in my other public scripts)
Note: this script is setup to work with any instrument, but the presets are built to provide actionable data on the Oasis BINANCE:ROSEUSDT token specifically. It is not a predicative model, it rather shows how price has behaved historically / statistically at these levels given past data.