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.
Bands and Channels
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.
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.
Empirical Kaspa Power Law Full Model v3.1🔶 First we need to understand what Power Laws are.
Power laws are mathematical relationships where one quantity varies as a power of another. They are prevalent in both natural and social systems, describing phenomena such as earthquake magnitudes, word frequencies, and wealth distributions. In a power-law relationship, a change in one quantity results in a proportional change in another, typically following a consistent and predictable mathematical pattern.
🔶 Why Do Power Laws work for Bitcoin and Kaspa?
Power laws work for Bitcoin and Kaspa due to the underlying principles of network dynamics and growth patterns that these cryptocurrencies exhibit. Here's how:
1. Network Growth and User Adoption:
Both Bitcoin and Kaspa grow as more users join their networks. The value of these networks often increases in a manner consistent with Metcalfe’s Law, which states that the value of a network is proportional to the square of its number of users. This relationship is a form of a power law, where network effects lead to exponential growth as more users participate.
2. Mining and Hash Rate:
The mining difficulty and hash rate in cryptocurrencies like Bitcoin and Kaspa adjust based on network activity. As more miners join, the difficulty increases to maintain a stable rate of block production. This self-adjusting mechanism creates feedback loops that can be described by power laws, ensuring the stability and security of the network over time.
3. Price Behavior:
Astrophysicist Giovanni Santostasi discovered that Bitcoin’s price follows a power-law distribution over time. This means that despite short-term volatility, Bitcoin’s long-term price behavior is predictable and adheres to specific mathematical patterns. Santostasi's model provides a framework for understanding Bitcoin’s price movements and forecasting future trends. He also discovered that Kaspa might be following a power-law aswell but it might be to early to tell because Kaspa hasn't been around for too long(2years).
4. Resource Allocation and System Stability:
As the price of Bitcoin or Kaspa increases, more resources are allocated to mining, leading to more sophisticated mining operations. This iterative process of investment and technological advancement follows a power-law pattern, driving the growth and stability of the network.
In summary, the application of power laws to Bitcoin and Kaspa offers a structured framework for understanding their price movements, network growth, and overall stability. These principles provide valuable predictive tools for long-term forecasting, helping to explain the dynamic behavior of these cryptocurrencies.
🔶 What does it look like on a chart?
Here is the Kaspa power law plotted on the KaspaUSD chart. Notice that the y-axis is in logarithmic scale. Unfortunately, TradingView does not allow the x-axis to be in logarithmic scale, which would otherwise make the power law appear as a straight line.
🔶 All the features of the Empirical Kaspa Power Law Full Model
This indicator includes a variety of scripts and tools, meticulously designed and developed to navigate the Kaspa market effectively.
🔹 Power Law & Deviation bands
The decision to use the lower two bands, marking an area between -40% to -50% below the power law, is based on historical analysis. Historically, this range has proven to be a great buying opportunity. In the case of Bitcoin, the bottom typically lies around -60% from the power law. However, for Kaspa, the bottom appears to be less distant from the power law. This discrepancy can be attributed to the differing supply dynamics of the two. Bitcoin undergoes a halving event approximately every four years, significantly reducing the rate at which new coins are introduced into circulation. This cyclical halving can lead to larger price fluctuations and a greater deviation from the power law. In contrast, Kaspa employs a more gradual reduction in its emission rate, with a 5% decrease each month. This consistent and incremental reduction helps Kaspa's price follow the power law more closely, resulting in less pronounced deviations. Consequently, the bottom for Kaspa tends to be closer to the power law, typically around -40% to -50%, rather than the -60% observed with Bitcoin.
The top two deviation bands are fitted to a few bubble data points, which are honestly not very reliable compared to the bottom bands that are based on a larger number of data points. When examining Bitcoin, we see that the bottoms are quite predictable due to the availability of thousands of data points, making it easier to identify patterns and trends.
However, predicting the tops is significantly more challenging because we lack a substantial amount of data for the peaks. This limited data makes it difficult to draw reliable conclusions about the upper deviation bands. As a result, while the bottom bands offer a robust framework for analysis, the top bands should be approached with caution due to their lesser reliability.
🔹 Alternating Sine wave
In observing the price behavior of Kaspa, an intriguing pattern emerges: it tends to follow a roughly four-month cycle. This cycle appears to alternate between smaller and larger waves. To capture this pattern, the sine wave in our indicator is designed to follow the power law, with both the top and bottom of the wave adjusting according to it.
Here's a simple explanation of how this works:
1. Four-Month Cycle: Empirically, Kaspa’s price seems to oscillate over approximately 120 days. This cycle includes periods of growth and decline, repeating every four months. Within these cycles, we observe alternating phases one smaller and one larger in amplitude.
2. Power Law Influence: The sine wave component of our indicator is not arbitrary; it follows a power law that predicts the general price trend of Kaspa. The power law essentially provides a baseline that reflects the longer-term price trajectory.
3. Diminishing Returns and Smoothing: To model diminishing returns, we adjust the amplitude of the sine wave over time, making it smaller as the cycle progresses. This helps to capture the natural tendency for price movements to become less volatile over longer periods. Additionally, the bottom of the sine wave adheres to the power law, ensuring it remains consistent with the overall trend.
🔹 Sine wave Cycle Start & End
Color transitions play a crucial role in visualizing different phases of the four-month cycle.
Based on empirical data, Kaspa experiences approximately 60 days of downward price action following each cycle peak, a period we refer to as the bear phase. This phase is followed by the bull phase, which also lasts around 60 days. To indicate the cycle peak, we have added a colored warning on the sine wave.
Cycle Start (Purple): The sine wave starts with a purple color, marking the beginning of a new cycle. This bull phase often represents a potential bottom or accumulation zone where prices are lower and stable, offering a strategic point for entering the market.
Cycle Top (Red): As the cycle progresses, the sine wave transitions through colors until it reaches red. This red phase indicates the top of the cycle, where the price is likely peaking. It's a critical area for investors to consider dollar-cost averaging (DCA) out of Kaspa, as it signifies a period of potential overvaluation and heightened risk.
These color transitions provide a visual guide to the market's cyclical nature, helping investors identify optimal entry and exit points. By following the sine wave's color changes, you can better time your investments, entering at the start of the cycle and considering exits as the cycle tops out.
🔹 Colored Deviation from the Power Law Bubbles
In trading, having a clear visual signal can significantly enhance decision-making, especially when dealing with complex models like power laws. This inspired the creation of the "deviation bubbles" in my indicator, which provides an intuitive, color-coded visual queue to help me, and other traders, better grasp market deviations and make timely trading decisions.
Here's a breakdown of how the deviation bubbles work:
1. Power Law Reference: The core of the indicator calculates a theoretical price level (the power law price) for Kaspa.
2. Deviation Calculation: For each day, the indicator computes the percentage deviation of the actual closing price from this power law price. This tells how much the market price diverges from the theoretically expected level.
3. Color-Coding Based on Deviation:
The deviation is categorized into various ranges (e.g., ≥ 100%, 90-100%, 80-90%, etc.).
Each range is assigned a distinct color, from red for extreme positive deviations to blue for extreme negative deviations.
This gradient helps in quickly identifying significant market deviations.
By integrating these bubbles into the chart, the indicator offers a simple yet powerful visual tool, aiding in recognizing critical market conditions without the need to delve into complex calculations manually. This approach not only enhances the ease of trading but also helps in overcoming the hesitation often faced when pulling the trigger on trades.
🔹 Projected Power Law Bands
Extends the current power law bands into the future using the same formula that defines the current power law.
Visual Representation: Dotted lines on the chart indicate the projected power law price and deviation bands.
Limitations: TradingView restricts how far these projections can extend, typically up to a reasonable future period.
These projected bands help anticipate future price movements, aiding in more informed trading decisions.
🔹 Projected Sine Wave
This projection continues to calculate the phase and amplitude, adjusting for diminishing returns and cycle transitions. It also estimates the future power law price, ensuring the projection reflects potential market dynamics.
Visual Representation: The projected sine wave is shown with dotted blue lines, providing a clear visual of the expected trend, aiding traders in their decision-making process.
Limitations: Again, TradingView restricts how far these projections can extend, typically up to a reasonable future period.
🔶 Why are all these different scripts made into one indicator?
As a trader and crypto analyst, I needed specific tools and customizations that no other indicator offered. Being a visual person, I rely heavily on visual triggers such as colors and patterns to make trading decisions. Initially, I developed this indicator for my personal use to enhance my market analysis with these visual cues. However, after sharing my insights, other traders expressed interest in using it. In response, I expanded the functionality and added various options to cater to a broader range of users.
This comprehensive indicator integrates multiple features into one tool, providing a powerful and flexible solution for analyzing market trends and making informed trading decisions. The use of colors and visual elements helps in quickly identifying key signals and market phases. The customizable options allow you to fine-tune the indicator to suit your specific needs, making it a versatile tool for both novice and experienced traders.
🔶 Usage & Settings:
This indicator is best used on the Daily chart for KASUSD - crypto because it uses a power law formula based on days.
🔹 Using the Indicator for 4-Month Cycles:
For traders interested in playing the 4-month cycles, this indicator provides a straightforward strategy. When the bubbles turn purple or the sine wave shows the purple start color, it signals a good time to dollar-cost average (DCA) into the market. Conversely, when the bubbles turn red or the cycle top is near, indicated by a red color, it’s time to DCA out of the Kaspa market. This visual approach helps traders make timely decisions based on color-coded signals, simplifying the trading process.
Historically, it was nearly impossible to accurately time all the 4-month cycle tops because they alternate each time. Without the combination of multiple scripts in this indicator, identifying these cyclical patterns and their respective peaks was extremely challenging. This integrated tool now provides a clear and reliable method for detecting these critical points, enhancing trading effectiveness.
🔹 Combining the visual queues for market extremes
The chart above illustrates the alignment of visual cues indicating market extremes. Notably, these visual cues—marked by red and purple boxes—historically pinpoint areas of extreme value or opportunities. When red aligns with red and purple aligns with purple, these zones have consistently indicated significant market extremes.
Understanding and recognizing these patterns provides a strategic advantage. By identifying these visual triggers, traders can plan and execute informed trades with greater confidence whenever similar scenarios unfold in the future.
Kaspa is perhaps one of the most cyclical and predictable cryptocurrencies in the market. Given its consistent behavior, traders might wonder why they would trade anything else. As long as there are no signs indicating a change in Kaspa's cyclical nature, there is no reason to make significant alterations to our predictions. This makes Kaspa an attractive option for traders seeking reliable and repeatable trading opportunities.
🔹 Settings & customization:
As a visually-oriented trader, it is essential to customize the appearance of indicators to effectively navigate the Kaspa market. The Indicator offers extensive customization options, allowing users to modify the colors of various elements to suit their preferences. For example, users can adjust the colors of the deviation bubbles, deviation bands, sine wave, and power law to enhance visual clarity and focus on specific data points. This level of personalization not only enhances the overall user experience but also ensures that the visual representation aligns with unique trading strategies, making it easier to interpret complex market data.
Additionally, users can change the power law inputs and other parameters as shown in the image. For instance, the Power Law Intercept and Power Law Slope can be manually adjusted, allowing traders to update these values. This flexibility is crucial as the future power law for Kaspa may evolve/change.
🔶 Limitations
Like any technical analysis tool, the Empirical Kaspa Power Law Full Model indicator has limitations. It's based on historical data, which may not always accurately predict future market movements.
🔶 Credits
I want to thank Dr. Giovanni Santostasi · Professor of physics and Mathematics.
He was one of the first who applied the concept of the power law to Bitcoin's price movements, which has been instrumental in providing insights into the long-term growth and potential future value of Bitcoin. Giovanni also offers coding classes on his Discord, which I attended. He personally taught me how to code specific things in Pine Editor and Python, sparking my interest in developing my own indicator.
Additionally, I would like to extend my gratitude to the following individuals for their invaluable contributions in terms of ideas, theories, formulas, testing, and guidance:
Forgowork, PlanC, Miko Genno, Chancellor, SavingFace, Kaspapero, JJ Venema.
Uptrick : HMA Adaptive Trend and Volatility BandsThis proprietary trading indicator, named "Uptrick: HMA Adaptive Trend and Volatility Bands," offers a sophisticated blend of trend detection and volatility measurement for financial markets. Designed to overlay directly on the price chart, it leverages a variety of technical analysis tools to provide clear visual signals and comprehensive market insights.
Key Features:
Hull Moving Average (HMA) with Volatility Bands:
HMA Calculation: Utilizes the Hull Moving Average (HMA) for smooth trend identification, applied to the average price of high and low (hl2).
Adaptive Volatility Bands: Incorporates bands around the HMA based on a responsive standard deviation adjusted by an Exponential Moving Average (EMA). These bands dynamically expand and contract with market volatility.
Parameters:
Length: Configurable period for the HMA and standard deviation (default 14).
Multiplier: Determines the width of the bands (default 2.0).
MACD (Moving Average Convergence Divergence):
MACD Calculation: Includes fast and slow EMA periods with a signal line to detect trend direction and strength.
Histogram: Difference between MACD line and signal line to visualize momentum.
Parameters:
Fast Length: Short-term EMA period (default 6).
Slow Length: Long-term EMA period (default 13).
Signal Length: Signal line EMA period (default 5).
Relative Strength Index (RSI):
RSI Calculation: Measures the speed and change of price movements to identify overbought or oversold conditions.
Parameter:
RSI Length: Period for RSI calculation (default 10).
Average True Range (ATR):
ATR Calculation: Evaluates market volatility by considering the true range over a specified period.
Parameter:
ATR Length: Period for ATR calculation (default 7).
Volume and Liquidity Analysis:
Volume: Directly incorporated into the indicator to gauge market activity.
Liquidity: Assessed using the HMA of volume to determine the ease of trade execution.
Parameter:
Liquidity Length: Period for HMA of volume calculation (default 14).
Trend Identification:
Uptrend Conditions: A combination of positive MACD histogram, RSI above 50, ATR above its HMA, and volume exceeding liquidity.
Downtrend Conditions: Negative MACD histogram, RSI below 50, ATR above its HMA, and volume exceeding liquidity.
Visual Cues: Color-coded background (green for uptrend, red for downtrend) with corresponding labels on the price chart to indicate trend shifts.
Additional Moving Averages and Bollinger Bands:
SMA (Simple Moving Average): Includes 50 and 200-period SMAs for long-term trend analysis.
EMA (Exponential Moving Average): Includes a 20-period EMA for short-term trend analysis.
Bollinger Bands: Standard deviation bands around a 20-period SMA to measure market volatility and identify potential breakout points.
Information Table:
Real-Time Data Display: An optional table that provides current values for key metrics such as price, volume, liquidity, ATR, RSI, MACD histogram, SMAs, EMA, Buy+Sell Pressure, ATH, Global liquidity, Distance from ATH and Bollinger Bands, offering traders a comprehensive snapshot of market conditions.
Visualization:
Upper and Lower Bands: Clearly plotted with distinct colors (blue for upper, red for lower) to highlight volatility boundaries.
Trend Labels: Automatic annotations on the chart to signal uptrend and downtrend conditions.
Background Highlighting: Subtle shading to visually emphasize prevailing trend conditions.
This indicator is designed for traders seeking an advanced tool to detect trends, measure volatility, and make informed trading decisions based on comprehensive technical analysis. By integrating multiple technical indicators and providing clear visual signals, it aims to enhance trading accuracy and market insight.
