CMF and Scaled EFI OverlayCMF and Scaled EFI Overlay Indicator
Overview
The CMF and Scaled EFI Overlay indicator combines the Chaikin Money Flow (CMF) and a scaled version of the Elder Force Index (EFI) into a single chart. This allows traders to analyze both indicators simultaneously, facilitating better insights into market momentum and volume dynamics , specifically focusing on buying/selling pressure and momentum , without compromising the integrity of either indicator.
Purpose
Chaikin Money Flow (CMF): Measures buying and selling pressure by evaluating price and volume over a specified period. It indicates accumulation (buying pressure) when values are positive and distribution (selling pressure) when values are negative.
Elder Force Index (EFI): Combines price changes and volume to assess the momentum behind market moves. Positive values indicate upward momentum (prices rising with strong volume), while negative values indicate downward momentum (prices falling with strong volume).
By scaling the EFI to match the amplitude of the CMF, this indicator enables a direct comparison between pressure and momentum , preserving their shapes and zero crossings. Traders can observe the relationship between price movements, volume, and momentum more effectively, aiding in decision-making.
Understanding Pressure vs. Momentum
Chaikin Money Flow (CMF):
- Indicates the level of demand (buying pressure) or supply (selling pressure) in the market based on volume and price movements.
- Accumulation: When institutional or large investors are buying significant amounts of an asset, leading to an increase in buying pressure.
- Distribution: When these investors are selling off their holdings, increasing selling pressure.
Elder Force Index (EFI):
- Measures the strength and speed of price movements, indicating how forceful the current trend is.
- Positive Momentum: Prices are rising quickly, indicating a strong uptrend.
- Negative Momentum: Prices are falling rapidly, indicating a strong downtrend.
Understanding the difference between pressure and momentum is crucial. For example, a market may exhibit strong buying pressure (positive CMF) but weak momentum (low EFI), suggesting accumulation without significant price movement yet.
Features
Overlay of CMF and Scaled EFI: Both indicators are plotted on the same chart for easy comparison of pressure and momentum dynamics.
Customizable Parameters: Adjust lengths for CMF and EFI calculations and fine-tune the scaling factor for optimal alignment.
Preserved Indicator Integrity: The scaling method preserves the shape and zero crossings of the EFI, ensuring accurate analysis.
How It Works
CMF Calculation:
- Calculates the Money Flow Multiplier (MFM) and Money Flow Volume (MFV) to assess buying and selling pressure.
- CMF is computed by summing the MFV over the specified length and dividing by the sum of volume over the same period:
CMF = (Sum of MFV over n periods) / (Sum of Volume over n periods)
EFI Calculation:
- Calculates the EFI using the Exponential Moving Average (EMA) of the price change multiplied by volume:
EFI = EMA(n, Change in Close * Volume)
Scaling the EFI:
- The EFI is scaled by multiplying it with a user-defined scaling factor to match the CMF's amplitude.
Plotting:
- Both the CMF and the scaled EFI are plotted on the same chart.
- A zero line is included for reference, aiding in identifying crossovers and divergences.
Indicator Settings
Inputs
CMF Length (`cmf_length`):
- Default: 20
- Description: The number of periods over which the CMF is calculated. A higher value smooths the indicator but may delay signals.
EFI Length (`efi_length`):
- Default: 13
- Description: The EMA length for the EFI calculation. Adjusting this value affects the sensitivity of the EFI to price changes.
EFI Scaling Factor (`efi_scaling_factor`):
- Default: 0.000001
- Description: A constant used to scale the EFI to match the CMF's amplitude. Fine-tuning this value ensures the indicators align visually.
How to Adjust the EFI Scaling Factor
Start with the Default Value:
- Begin with the default scaling factor of `0.000001`.
Visual Inspection:
- Observe the plotted indicators. If the EFI appears too large or small compared to the CMF, proceed to adjust the scaling factor.
Fine-Tune the Scaling Factor:
- Increase or decrease the scaling factor incrementally (e.g., `0.000005`, `0.00001`, `0.00005`) until the amplitudes of the CMF and EFI visually align.
- The optimal scaling factor may vary depending on the asset and timeframe.
Verify Alignment:
- Ensure that the scaled EFI preserves the shape and zero crossings of the original EFI.
- Overlay the original EFI (if desired) to confirm alignment.
How to Use the Indicator
Analyze Buying/Selling Pressure and Momentum:
- Positive CMF (>0): Indicates accumulation (buying pressure).
- Negative CMF (<0): Indicates distribution (selling pressure).
- Positive EFI: Indicates positive momentum (prices rising with strong volume).
- Negative EFI: Indicates negative momentum (prices falling with strong volume).
Look for Indicator Alignment:
- Both CMF and EFI Positive:
- Suggests strong bullish conditions with both buying pressure and upward momentum.
- Both CMF and EFI Negative:
- Indicates strong bearish conditions with selling pressure and downward momentum.
Identify Divergences:
- CMF Positive, EFI Negative:
- Buying pressure exists, but momentum is negative; potential for a bullish reversal if momentum shifts.
- CMF Negative, EFI Positive:
- Selling pressure exists despite rising prices; caution advised as it may indicate a potential bearish reversal.
Confirm Signals with Other Analysis:
- Use this indicator in conjunction with other technical analysis tools (e.g., trend lines, support/resistance levels) to confirm trading decisions.
Example Usage
Scenario 1: Bullish Alignment
- CMF Positive: Indicates accumulation (buying pressure).
- EFI Positive and Increasing: Shows strengthening upward momentum.
- Interpretation:
- Strong bullish signal suggesting that buyers are active, and the price is likely to continue rising.
- Action:
- Consider entering a long position or adding to existing ones.
Scenario 2: Bearish Divergence
- CMF Negative: Indicates distribution (selling pressure).
- EFI Positive but Decreasing: Momentum is positive but weakening.
- Interpretation:
- Potential bearish reversal; price may be rising but underlying selling pressure suggests caution.
- Action:
- Be cautious with long positions; consider tightening stop-losses or preparing for a possible trend reversal.
Tips
Adjust for Different Assets:
- The optimal scaling factor may differ across assets due to varying price and volume characteristics.
- Always adjust the scaling factor when analyzing a new asset.
Monitor Indicator Crossovers:
- Crossings above or below the zero line can signal potential trend changes.
Watch for Divergences:
- Divergences between the CMF and EFI can provide early warning signs of trend reversals.
Combine with Other Indicators:
- Enhance your analysis by combining this overlay with other indicators like moving averages, RSI, or Ichimoku Cloud.
Limitations
Scaling Factor Sensitivity:
- An incorrect scaling factor may misalign the indicators, leading to inaccurate interpretations.
- Regular adjustments may be necessary when switching between different assets or timeframes.
Not a Standalone Indicator:
- Should be used as part of a comprehensive trading strategy.
- Always consider other market factors and indicators before making trading decisions.
Disclaimer
No Guarantee of Performance:
- Past performance is not indicative of future results.
- Trading involves risk, and losses can exceed deposits.
Use at Your Own Risk:
- This indicator is provided for educational purposes.
- The author is not responsible for any financial losses incurred while using this indicator.
Code Summary
//@version=5
indicator(title="CMF and Scaled EFI Overlay", shorttitle="CMF & Scaled EFI", overlay=false)
cmf_length = input.int(20, minval=1, title="CMF Length")
efi_length = input.int(13, minval=1, title="EFI Length")
efi_scaling_factor = input.float(0.000001, title="EFI Scaling Factor", minval=0.0, step=0.000001)
// --- CMF Calculation ---
ad = high != low ? ((2 * close - low - high) / (high - low)) * volume : 0
mf = math.sum(ad, cmf_length) / math.sum(volume, cmf_length)
// --- EFI Calculation ---
efi_raw = ta.ema(ta.change(close) * volume, efi_length)
// --- Scale EFI ---
efi_scaled = efi_raw * efi_scaling_factor
// --- Plotting ---
plot(mf, color=color.green, title="CMF", linewidth=2)
plot(efi_scaled, color=color.red, title="EFI (Scaled)", linewidth=2)
hline(0, color=color.gray, title="Zero Line", linestyle=hline.style_dashed)
- Lines 4-6: Define input parameters for CMF length, EFI length, and EFI scaling factor.
- Lines 9-11: Calculate the CMF.
- Lines 14-16: Calculate the EFI.
- Line 19: Scale the EFI by the scaling factor.
- Lines 22-24: Plot the CMF, scaled EFI, and zero line.
Feedback and Support
Suggestions: If you have ideas for improvements or additional features, please share your feedback.
Support: For assistance or questions regarding this indicator, feel free to contact the author through TradingView.
---
By combining the CMF and scaled EFI into a single overlay, this indicator provides a powerful tool for traders to analyze market dynamics more comprehensively. Adjust the parameters to suit your trading style, and always practice sound risk management.
M-oscillator
RS+ Majors Allocation | viResearchRS+ Majors Allocation | viResearch
Conceptual Foundation and Innovation
The "RS+ Majors Allocation" script is a comprehensive strategy for managing a crypto portfolio focused on BTC, ETH, and SOL. By dynamically rotating between these major assets, the strategy aims to identify the strongest performer in real-time and allocate capital accordingly. The script incorporates a relative strength (RS) model that leverages price movements and a custom scoring system to rank each asset's performance. This allows the strategy to maintain positions in favorable market conditions while moving to cash during periods of weakness.
The script also includes a trend regime filter to further refine allocations. This filter ensures that an asset's own trend aligns with the market’s trend before committing to an allocation, adding another layer of protection against downturns. The approach is designed to outperform traditional buy-and-hold strategies by minimizing risk exposure during unfavorable market conditions.
Technical Composition and Calculation
The "RS+ Majors Allocation" script combines several technical elements to execute the strategy:
Relative Strength Model: Each asset (BTC, ETH, SOL) is evaluated through a ratio matrix, comparing their performance relative to one another. A scoring system is applied to these ratios to rank the assets, determining which is outperforming. This dynamic evaluation is central to the strategy's decision-making process.
Trend Regime Filter: This filter uses trend indicators to assess whether the market and individual assets are in a favorable state. If an asset’s trend score does not meet the criteria, it won't be allocated capital, thus avoiding exposure to potential downturns.
Equity Tracking and Allocation: The script tracks the portfolio's equity performance over time, plotting it against a traditional buy-and-hold strategy for comparison. Allocation decisions are based on the scores of BTC, ETH, and SOL, with the system selecting the top-performing asset and moving to cash if no asset meets the criteria.
Performance Metrics: To evaluate the effectiveness of the strategy, the script calculates several key performance indicators:
Sharpe Ratio: Measures risk-adjusted returns.
Sortino Ratio: Focuses on downside risk by considering only negative fluctuations.
Omega Ratio: Analyzes returns relative to risk.
Maximum Drawdown: Shows the largest peak-to-trough decline, indicating potential loss exposure.
Features and User Inputs
The script offers a range of customizable parameters to tailor the strategy to individual preferences and market conditions:
Asset Selection: Users can choose the specific assets to include in the rotation, with the script currently focusing on BTC, ETH, and SOL. The trend regime filter is optional, allowing for a more aggressive or conservative approach.
Equity Visualization: The script provides real-time equity tracking, comparing the portfolio's performance with individual assets. Users can adjust visualization settings to focus on specific assets or the overall strategy.
Starting Date: The backtesting period can be set to begin at a specific date, helping to analyze the strategy’s performance over different timeframes.
Bar Colors and Alerts: Visual cues, including colored bars, indicate the active trend direction of the selected asset. Additionally, alerts notify traders when the system rotates between assets or moves to cash.
Practical Applications
The "RS+ Majors Allocation" script is designed for traders who want to manage a crypto portfolio with a focus on risk-adjusted returns. It is particularly effective in several scenarios:
Asset Rotation: The dynamic scoring system allows the script to rotate between BTC, ETH, and SOL based on relative strength, capitalizing on the strongest performer at any given time.
Downside Protection: The trend regime filter helps avoid exposure during market-wide downturns by staying in cash, minimizing drawdowns during periods of high volatility.
Active Portfolio Management: By using real-time data to make allocation decisions, the script offers a more hands-on approach to portfolio management compared to passive holding strategies.
Advantages and Strategic Value
This script brings a structured and disciplined approach to portfolio management, combining trend analysis, relative strength, and performance metrics to optimize returns. The use of a scoring system for asset rotation, along with the trend filter, makes it versatile and adaptable to different market environments. The script aims to outperform traditional buy-and-hold strategies by focusing on the strongest assets while reducing risk during unfavorable conditions.
The visual and performance feedback provided by the script allows traders to gain deeper insights into their portfolio’s behavior, helping to make data-driven decisions.
Summary and Usage Tips
The "RS+ Majors Allocation" script is a powerful tool for managing a crypto portfolio with a focus on performance optimization and risk management. By incorporating this strategy, traders can dynamically allocate capital to the top-performing assets while protecting their portfolio from significant downturns. Adjust the trend regime filter, threshold settings, and asset choices to fit your market outlook and trading goals. The script's equity tracking and performance metrics will provide clear insights into how well the strategy is performing compared to a traditional buy-and-hold approach.
Remember to use backtesting to assess the script's effectiveness over different timeframes and market conditions. Keep in mind that past performance does not guarantee future results, so consider using this strategy in conjunction with other analysis tools for a comprehensive approach to trading.
Range Tightening Indicator (RTI)The Range Tightening Indicator (RTI) quantifies price volatility relative to recent price action, helping traders identify low-volatility consolidations that often precede breakouts.
Range Tightening is calculated by measuring the range between each bar’s high and low prices over a chosen lookback period.
A 5-bar period is recommended for shorter-term momentum setups and a 15-bar period is recommended for swing trading. An option for a custom period is available to suit specific strategies. The default look back for custom is 50, ideal for longer term traders.
Other Key Features:
Dynamic Color Coding: The RTI line turns green when volatility doubles after a drop to or below 20, flagging significant volatility shifts commonly seen before breakouts.
Low-Volatility Dots: Orange dots appear on the RTI line when two or more consecutive bars show RTI values below 20, visually marking extended low-volatility periods.
Volatility Zones: Shaded zones provide quick context:
Zone 1 (0-5): Extremely tight volatility, shown in red.
Zone 2 (5-10): Low volatility, shown in light green.
Zone 3 (10-15): Moderate low volatility, shown in green.
The RTI indicator is ideal for traders looking to anticipate breakout conditions, with features that highlight consolidation phases, support momentum strategies, and help improve entry timing by focusing on shifts in volatility.
This indicator was inspired after Deepvue's RMV Indicator, but uses a different calculation. Results may vary.
Oscillator Price Divergence & Trend Strategy (DPS) // AlgoFyreThe Oscillator Price Divergence & Trend Strategy (DPS) strategy combines price divergence and trend indicators for trend trading. It uses divergence conditions to identify entry points and a trend source for directional bias. The strategy incorporates risk management through dynamic position sizing based on a fixed risk amount. It allows for both long and short positions with customizable stop-loss and take-profit levels. The script includes visualization options for entry, stop-loss, and take-profit levels, enhancing trade analysis.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Divergence-Trend Combination
🔸Dynamic Position Sizing
🔸Customizable Risk Management
🔶 FUNCTIONALITY
🔸Indicators
🞘 Trend Indicator
🞘 Oscillator Source
🔸Conditions
🞘 Long Entry
🞘 Short Entry
🞘 Take Profit
🞘 Stop Loss
🔶 INSTRUCTIONS
🔸Adding the Strategy to the Chart
🔸Configuring the Strategy
🔸Backtesting and Practice
🔸Market Awareness
🔸Visual Customization
🔶 CONCLUSION
▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅
🔶 ORIGINALITY The Divergence Trend Trading with Dynamic Position Sizing strategy uniquely combines price divergence indicators with trend analysis to optimize entry and exit points. Unlike static trading strategies, it employs dynamic position sizing based on a fixed risk amount, ensuring consistent risk management. This approach allows traders to adapt to varying market conditions by adjusting position sizes according to predefined risk parameters, enhancing both flexibility and control in trading decisions. The strategy's integration of customizable stop-loss and take-profit levels further refines its risk management capabilities, making it a robust tool for both trending and volatile markets.
🔸Divergence-Trend Combination By combining trend direction with divergence conditions, the strategy enhances the accuracy of entry signals, aligning trades with prevailing market trends.
🔸Dynamic Position Sizing This strategy calculates position sizes dynamically, based on a fixed risk amount, allowing traders to maintain consistent risk exposure across trades.
🔸Customizable Risk Management Traders can set flexible risk-reward ratios and adjust stop-loss and take-profit levels, tailoring the strategy to their risk tolerance and market conditions.
🔶 FUNCTIONALITY The Divergence Trend Trading with Dynamic Position Sizing strategy leverages a combination of trend indicators and price and oscillator divergences to identify optimal trading opportunities. This strategy is designed to capitalize on medium to long-term price movements and works best on h1, h4 or D1 timeframes. It allows traders to manage risk effectively while taking advantage of both long and short positions.
🔸Indicators 🞘 Trend Indicator: A long trend is used to determine market direction, ensuring trades align with prevailing trends.
Recommendation: We recommend using the Adaptive MAs (Hurst, CVaR, Fractal) // AlgoFyre indicator with the following settings for trend detection. However, you can use any trend indicator that suits your trading style, e.g. an EMA 200.
🞘 Oscillator Source: The oscillator source is used for momentum price divergence identification. Any momentum oscillator can be used, e.g. RSI, Stochastic etc. A good oscillator is the Stochastic with the following settings:
🔸Conditions 🞘 Long Entry: A long entry condition is met if price closes above the trend AND selected divergence conditions are met, e.g. regular bullish divergence with a 10 bar lookback period with the divergence being below the 50 point mean. If the info table shows all 3 columns in the same color, the entry conditions are met and a position is opened.
🞘 Short Entry: A short entry condition is met if price closes below the trend AND selected divergence conditions are met, e.g. regular bearish divergence with a 10 bar lookback period with the divergence being above the 50 point mean.
🞘 Take Profit: Take Profit is determined by the Risk to Reward Ratio settings depending on the price distance between the entry price and the stop loss price, e.g. if stop loss is 1% away from entry and Risk Reward Ratio is 3:1 then Take Profit will be set at 3% from entry.
🞘 Stop Loss: Stop loss is a fixed level away from the trend source. For long positions, stop loss is set below the trend, and for short positions, above the trend.
🔶 INSTRUCTIONS The Divergence Trend Trading with Dynamic Position Sizing strategy can be set up by adding it to your TradingView chart and configuring parameters such as the oscillator source, trend source, and risk management settings. This strategy is designed to capitalize on short-term price movements by dynamically adjusting position sizes based on predefined risk parameters. Enhance the accuracy of signals by combining this strategy with additional indicators like trend-following or momentum-based tools. Adjust settings to better manage risk and optimize entry and exit points.
🔸Adding the Strategy to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Divergence Trend Trading with Dynamic Position Sizing // AlgoFyre" in the indicators list.
Click on the strategy to add it to your chart.
🔸Configuring the Strategy:
Open the strategy settings by clicking on the gear icon next to its name on the chart.
Oscillator Source: Select the source for the oscillator. An oscillator like Stochastic needs to be attached to the chart already in order to be used as an oscillator source to be selectable.
Trend Source: Choose the trend source to determine market direction. A trend indicator like Adaptive MAs (Hurst, CVaR, Fractal) // AlgoFyre needs to be attached to the chart already in order to be used as a trend source to be selectable.
Stop Loss Percentage: Set the stop loss distance from the trend source as a percentage.
Risk/Reward Ratio: Define the desired risk/reward ratio for trades.
🔸Backtesting and Practice:
Backtest the strategy on historical data to understand how it performs in various market environments.
Practice using the strategy on a demo account before implementing it in live trading.
🔸Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The strategy reacts to price data and might not account for news-driven events that can cause large deviations.
🔸Visual Customization Visualization Settings: Customize the display of entry price, take profit, and stop loss levels.
Color Settings: Switch to the AlgoFyre theme or set custom colors for bullish, bearish, and neutral states.
Table Settings: Enable or disable the information table and adjust its position.
🔶 CONCLUSION
The Divergence Trend Trading with Dynamic Position Sizing strategy provides a robust framework for capitalizing on short-term market trends by combining price divergence with dynamic position sizing. This strategy leverages divergence conditions to identify entry points and utilizes a trend source for directional bias, ensuring trades align with prevailing market conditions. By incorporating dynamic position sizing based on a fixed risk amount, traders can effectively manage risk and adapt to varying market conditions. The strategy's customizable stop-loss and take-profit levels further enhance its risk management capabilities, making it a versatile tool for both trending and volatile markets. With its strategic blend of technical indicators and risk management, the Divergence Trend Trading strategy offers traders a comprehensive approach to optimizing trade execution and maximizing potential returns.
Z-Scored Moving Average Suite [KFB Quant]Z-Scored Moving Average Suite
This indicator combines several types of moving averages—Simple, Exponential, and Weighted—with a Z-Score calculation to give a clearer understanding of price trends in relation to their historical averages. It is used to detect overbought (OB) and oversold (OS) conditions, allowing you to see when an asset is deviating significantly from its mean.
Key Components:
Moving Averages: The suite includes Simple (SMA), Exponential (EMA), and Weighted (WMA) Moving Averages. For each, a single, double, and triple version is calculated to smooth out noise.
Z-Score: The Z-Score measures how far the current price is from its moving average in terms of standard deviations, helping to highlight unusual price behavior.
Overbought and Oversold Levels:
- When the Z-Score crosses above a predefined threshold (1.5 by default), the asset is considered Overbought (OB).
- When the Z-Score drops below a certain level (-1.5 by default), the asset is seen as Oversold (OS).
Visualization:
- The histogram represents the average Z-Score of all the moving averages combined, colored based on bullish (blue) or bearish (brown) trends.
- Individual Z-Scores for each moving average type (SMA, EMA, WMA) are also plotted, providing further insight into the momentum and direction.
Signals:
- The table in the chart shows a summary of Z-Scores for each type of moving average. It also provides a quick glance at whether the asset is in a bullish or bearish phase, if the Z-Scores are rising or falling, and whether the asset is overbought or oversold.
This tool is highly customizable, with adjustable lengths for the moving averages and Z-Scores, making it a flexible addition to any trading strategy that relies on mean-reversion or trend analysis.
Disclaimer: This tool is provided for informational and educational purposes only and should not be considered as financial advice. Always conduct your own research and consult with a licensed financial advisor before making any investment decisions.
Gauss IndicatorGauss Indicator
Class : oscillator
Trading type : any
Time frame : any
Purpose : reversal trading
Level of aggressiveness : any
About Gauss Indicator
Time series forecasting is quite a scientific task, for which specific econometrical models and methods have been developed.
Who is Gauss and Why his Curve is So Important
Johann Gauss was one of the best mathematicians of all times and he gave us a very specific curve (Gaussian Curve) to explain specifics of random variable behavior (so called Normal Distribution)
Gaussian curve has quite interesting property usually called “3 Sigmas Rule”: in a normal distribution: 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.
But Does It Work in the Financial Markets?
Normal Distribution is extremely typical for price behavior in financial markets: FOREX, stock Market, Commodities, Cryptocurrency market.
How can we forecast future prices based on “3 Sigmas Rule”?
If we know past prices (we actually know), we can calculate Mean and Standard Deviation.
After that following “3 Sigmas Rules” we can calculate the fluctuations range for the present day with a known probability (!).
• If we add 1 sigma to mean we can get the price value that wouldn’t be exceeded with a probability of 68%.
• If we add 2 sigmas to mean we can get the price value that wouldn’t be exceeded with a probability of 95%.
• If we add 3 sigmas to mean we can get the price value that wouldn’t be exceeded with a probability of 99%.
How Can I Get This Information?
Gauss indicator is a practical implementation of “3 sigmas rule” in trading.
Gauss allows to predict the ranges of price fluctuations for the selected time frames (week, day, hour, etc) with certain probabilities: 68%, 95% and 99%.
Gauss can be used to generate Trading signals, Stop-loss parameters, Take-profit parameters, Synthetic Levels (both Support and Resistance).
Actually, ALL information you need to trade.
Structure of the Gauss Indicator
1. Three blue lines – synthetic support lines. They describe 3 different buy zones with certain probabilities of success:
- First blue line (Buy zone #1) - the price today will not fall below this mark with a probability of 68%;
- Second blue line (Buy zone #2) - the price today will not fall below this mark with a probability of 95%;
- Third blue line (Buy zone #3) - the price today will not fall below this mark with a probability of 99%.
2. Three red lines – synthetic resistance lines. They describe 3 different sell zones with certain probabilities of success:
- First red line (Sell zone #1) - the price today will not rise above this mark with a probability of 68%;
- Second red line (Sell zone #2) - the price today will not rise above this mark with a probability of 95%;
- Third red line (Sell zone #3) - the price today will not rise above this mark with a probability of 99%.
3. Green line – shows current price. When it gets close to the red/blue line sell/buy signals are generated.
Trading rules
General rules are as follows: buy at the blue lines, sell at the red lines.
Take-profits for sells are set at the nearest blue line, for buys – at the nearest red line. Stop-losses for sells are set above the last red line, for buys – below the last blue line.
Sector Trend MapThe Sector Trend Map is a powerful tool designed to provide a sentiment heatmap for major market sectors. This indicator tracks the average trend direction across 11 key sectors, including Technology, Financials, Healthcare, Energy, and more. By monitoring each sector's sentiment, the Sector Trend Map helps traders quickly assess whether sectors are bullish or bearish, allowing for better-informed trading decisions.
This indicator plots a visual heatmap showing the sentiment strength for each sector on a scale from 0 to 100. The colors range from green for bullish sentiment to red for bearish sentiment. Additionally, it displays a real-time percentage of sectors that are bullish and bearish in a dynamic table located in the bottom right corner of the chart.
This indicator simplifies sector sentiment analysis by providing clear visual cues, making it easy to stay on top of market dynamics and make data-driven trading decisions.
Key Features:
Sentiment Heatmap: Displays a heatmap of sector sentiment ranging from bullish (green) to bearish (red).
Bullish/Bearish Percentages: A dynamic table showing the percentage of sectors that are bullish or bearish.
Tracks 11 Key Sectors: Monitors sectors such as Technology, Financials, Energy, Healthcare, and more.
Simple and Clear Visuals: Provides easy-to-read color coding for quick decision-making.
Customizable Moving Averages: Select between SMA, EMA, WMA, or DEMA for the trend calculation.
Market Hours Sensitivity: Indicator operates during regular market hours, ensuring relevance for day traders and active traders.
Overlay Sentiment Colors on Candles:
This feature allows you to overlay the sentiment (green for bullish, red for bearish) directly onto the price chart candles. You can enable or disable this option based on your preference.
How to Use the Sector Trend Map:
The heatmap is divided into different sectors. Each sector is colored based on its current sentiment:
🟢 Green (Bullish sentiment)
🔴 Red (Bearish sentiment)
Sentiment is calculated on a scale from 0 to 100, with 50 being the neutral point. Sectors above 50 are bullish, while sectors below 50 are bearish.
Bullish/Bearish Percentage Table:
A table is displayed in the bottom right corner of the screen, showing the percentage of sectors that are currently bullish and bearish.
Bullish %: The percentage of sectors above 50 on the sentiment scale.
Bearish %: The percentage of sectors below 50 on the sentiment scale.
Market Hours Activity:
The indicator only calculates and displays data during market hours (09:30 AM to 4:00 PM EST), ensuring it stays relevant to intraday trading. Outside of market hours, the indicator remains inactive.
Best Used For:
Intraday Traders: Get real-time sector sentiment during market hours and make better trading decisions based on sector strength or weakness.
Swing Traders: Monitor sector trends to spot shifts in market sentiment over time.
Sector Rotation Strategies: Use the indicator to identify which sectors are gaining or losing strength, aiding in sector rotation strategies.
Practical Example:
If 7 out of the 11 sectors display a bullish sentiment, the table will show 63.64% as bullish and 36.36% as bearish. The heatmap will show green sectors for those above the 50 sentiment threshold, allowing you to visually spot the sectors leading the market.
Savitzky Golay Median Filtered RSI [BackQuant]Savitzky Golay Median Filtered RSI
Introducing BackQuant's Savitzky Golay Median Filtered RSI, a cutting-edge indicator that enhances the classic Relative Strength Index (RSI) by applying both a Savitzky-Golay filter and a median filter to provide smoother and more reliable signals. This advanced approach helps reduce noise and captures true momentum trends with greater precision. Let’s break down how the indicator works, the features it offers, and how it can improve your trading strategy.
Core Concept: Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a widely used momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100, with levels above 70 typically indicating overbought conditions and levels below 30 indicating oversold conditions. However, the standard RSI can sometimes generate noisy signals, especially in volatile markets, making it challenging to identify reliable entry and exit points.
To improve upon the traditional RSI, this indicator introduces two powerful filters: the Savitzky-Golay filter and a median filter.
Savitzky-Golay Filter: Smoothing with Precision
The Savitzky-Golay filter is a digital filtering technique used to smooth data while preserving important features, such as peaks and trends. Unlike simple moving averages that can distort important price data, the Savitzky-Golay filter uses polynomial regression to fit the data, providing a more accurate and less lagging result.
In this script, the Savitzky-Golay filter is applied to the RSI values to smooth out short-term fluctuations and provide a more reliable signal. By using a window size of 5 and a polynomial degree of 2, the filter effectively reduces noise without compromising the integrity of the underlying price movements.
Median Filter: Reducing Outliers
After applying the Savitzky-Golay filter, the median filter is applied to the smoothed RSI values. The median filter is particularly effective at removing short-lived outliers, further enhancing the accuracy of the RSI by reducing the impact of sudden and temporary price spikes or drops. This combination of filters creates an ultra-smooth RSI that is better suited for detecting true market trends.
Long and Short Signals
The Savitzky Golay Median Filtered RSI generates long and short signals based on user-defined threshold levels:
Long Signals: A long signal is triggered when the filtered RSI exceeds the Long Threshold (default set at 176). This indicates that momentum is shifting upward, and it may present a good buying opportunity.
Short Signals: A short signal is generated when the filtered RSI falls below the Short Threshold (default set at 162). This suggests that momentum is weakening, potentially signaling a selling opportunity or exit from a long position.
These threshold levels can be adjusted to suit different market conditions and timeframes, allowing traders to fine-tune the sensitivity of the indicator.
Customization and Visualization Options
The Savitzky Golay Median Filtered RSI comes with several customization options, enabling traders to tailor the indicator to their specific needs:
Calculation Source: Select the price source for the RSI calculation (default is OHLC4, but it can be changed to close, open, high, or low prices).
RSI Period: Adjust the lookback period for the RSI calculation (default is 14).
Median Filter Length: Control the length of the median filter applied to the smoothed RSI, affecting how much noise is removed from the signal.
Threshold Levels: Customize the long and short thresholds to define the sensitivity for generating buy and sell signals.
UI Settings: Choose whether to display the RSI and thresholds on the chart, color the bars according to trend direction, and adjust the line width and colors used for long and short signals.
Visual Feedback: Color-Coded Signals and Thresholds
To make the signals easier to interpret, the indicator offers visual feedback by coloring the price bars and the RSI plot according to the current market trend:
Green Bars indicate long signals when momentum is bullish.
Red Bars indicate short signals when momentum is bearish.
Gray Bars indicate neutral or undecided conditions when no clear signal is present.
In addition, the Long and Short Thresholds can be plotted directly on the chart to provide a clear reference for when signals are triggered, allowing traders to visually gauge the strength of the RSI relative to its thresholds.
Alerts for Automation
For traders who prefer automated notifications, the Savitzky Golay Median Filtered RSI includes built-in alert conditions for long and short signals. You can configure these alerts to notify you when a buy or sell condition is met, ensuring you never miss a trading opportunity.
Trading Applications
This indicator is versatile and can be used in a variety of trading strategies:
Trend Following: The combination of Savitzky-Golay and median filtering makes this RSI particularly useful for identifying strong trends without being misled by short-term noise. Traders can use the long and short signals to enter trades in the direction of the prevailing trend.
Reversal Trading: By adjusting the threshold levels, traders can use this indicator to spot potential reversals. When the RSI moves from overbought to oversold levels (or vice versa), it may signal a shift in market direction.
Swing Trading: The smoothed RSI provides a clear signal for short to medium-term price movements, making it an excellent tool for swing traders looking to capitalize on momentum shifts.
Risk Management: The filtered RSI can be used as part of a broader risk management strategy, helping traders avoid false signals and stay in trades only when the momentum is strong.
Final Thoughts
The Savitzky Golay Median Filtered RSI takes the classic RSI to the next level by applying advanced smoothing techniques that reduce noise and improve signal reliability. Whether you’re a trend follower, swing trader, or reversal trader, this indicator provides a more refined approach to momentum analysis, helping you make better-informed trading decisions.
As with all indicators, it is important to backtest thoroughly and incorporate sound risk management strategies when using the Savitzky Golay Median Filtered RSI in your trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Kalman For Loop [BackQuant]Kalman For Loop
Introducing BackQuant's Kalman For Loop (Kalman FL) — a highly adaptive trading indicator that uses a Kalman filter to smooth price data and generate actionable long and short signals. This advanced indicator is designed to help traders identify trends, filter out market noise, and optimize their entry and exit points with precision. Let’s explore how this indicator works, its key features, and how it can enhance your trading strategies.
Core Concept: Kalman Filter
The Kalman Filter is a mathematical algorithm used to estimate the state of a system by filtering noisy data. It is widely used in areas such as control systems, signal processing, and time-series analysis. In the context of trading, a Kalman filter can be applied to price data to smooth out short-term fluctuations, providing a clearer view of the underlying trend.
Unlike moving averages, which use fixed weights to smooth data, the Kalman Filter adjusts its estimate dynamically based on the relationship between the process noise and the measurement noise. This makes the filter more adaptive to changing market conditions, providing more accurate trend detection without the lag associated with traditional smoothing techniques.
Please see the original Kalman Price Filter
In this script, the Kalman For Loop applies the Kalman filter to the price source (default set to the closing price) to generate a smoothed price series, which is then used to calculate signals.
Adaptive Smoothing with Process and Measurement Noise
Two key parameters govern the behavior of the Kalman filter:
Process Noise: This controls the extent to which the model allows for uncertainty in price changes. A lower process noise value will make the filter smoother but slower to react to price changes, while a higher value makes it more sensitive to recent price fluctuations.
Measurement Noise: This represents the uncertainty or "noise" in the observed price data. A higher measurement noise value gives the filter more leeway to ignore short-term fluctuations, focusing on the broader trend. Lowering the measurement noise makes the filter more responsive to minor changes in price.
These settings allow traders to fine-tune the Kalman filter’s sensitivity, adjusting it to match their preferred trading style or market conditions.
For-Loop Scoring Mechanism
The Kalman FL further enhances the effectiveness of the Kalman filter by using a for-loop scoring system. This mechanism evaluates the smoothed price over a range of periods (defined by the Calculation Start and Calculation End inputs), assigning a score based on whether the current filtered price is higher or lower than previous values.
Long Signals: A long signal is generated when the for-loop score surpasses the Long Threshold (default set at 20), indicating a strong upward trend. This helps traders identify potential buying opportunities.
Short Signals: A short signal is triggered when the score crosses below the Short Threshold (default set at -10), signaling a potential downtrend or selling opportunity.
These signals are plotted on the chart, giving traders a clear visual indication of when to enter long or short positions.
Customization and Visualization Options
The Kalman For Loop comes with a range of customization options to give traders full control over how the indicator operates and is displayed on the chart:
Kalman Price Source: Choose the price data used for the Kalman filter (default is the closing price), allowing you to apply the filter to other price points like open, high, or low.
Filter Order: Set the order of the Kalman filter (default is 5), controlling how far back the filter looks in its calculations.
Process and Measurement Noise: Fine-tune the sensitivity of the Kalman filter by adjusting these noise parameters.
Signal Line Width and Colors: Customize the appearance of the signal line and the colors used to indicate long and short conditions.
Threshold Lines: Toggle the display of the long and short threshold lines on the chart for better visual clarity.
The indicator also includes the option to color the candlesticks based on the current trend direction, allowing traders to quickly identify changes in market sentiment. In addition, a background color feature further highlights the overall trend by shading the background in green for long signals and red for short signals.
Trading Applications
The Kalman For Loop is a versatile tool that can be adapted to a variety of trading strategies and markets. Some of the primary use cases include:
Trend Following: The adaptive nature of the Kalman filter helps traders identify the start of new trends with greater precision. The for-loop scoring system quantifies the strength of the trend, making it easier to stay in trades for longer when the trend remains strong.
Mean Reversion: For traders looking to capitalize on short-term reversals, the Kalman filter's ability to smooth price data makes it easier to spot when price has deviated too far from its expected path, potentially signaling a reversal.
Noise Reduction: The Kalman filter excels at filtering out short-term price noise, allowing traders to focus on the broader market movements without being distracted by minor fluctuations.
Risk Management: By providing clear long and short signals based on filtered price data, the Kalman FL helps traders manage risk by entering positions only when the trend is well-defined, reducing the chances of false signals.
Alerts and Automation
To further assist traders, the Kalman For Loop includes built-in alert conditions that notify you when a long or short signal is generated. These alerts can be configured to trigger notifications, helping you stay on top of market movements without constantly monitoring the chart.
Final Thoughts
The Kalman For Loop is a powerful and adaptive trading indicator that combines the precision of the Kalman filter with a for-loop scoring mechanism to generate reliable long and short signals. Whether you’re a trend follower or a reversal trader, this indicator offers the flexibility and accuracy needed to navigate complex markets with confidence.
As always, it’s important to backtest the indicator and adjust the settings to fit your trading style and market conditions. No indicator is perfect, and the Kalman FL should be used alongside other tools and sound risk management practices for the best results.
Fetch Z-scoreThis script is enspired by the creator of the Z-score probability indicator made by www.tradingview.com
I took his calculation for the z-score and created my own strategy based on that z-score.
What is z-score? The Z-score represents how far the current price deviates from the moving average, measured in terms of standard deviations
What does this script do with the Z-score?
The script offers several customizable options, including displaying buy and sell signals based on Z-score thresholds and overlaying these signals directly on the chart or below/above the bars.
The idea is that when the Z-score exceeds a certain treshold, a count will start. The count will lead to a signal. For example: Say the Z-score dipped below -1. From there, the script will by default count whether the current Z-score is higher than the Z-score of the past 10 datapoints. If so, a buy signal will be printed on the chart. The idea is that the Z-score will creep up after a low, making sure you buy earyly in the new uptrend, making this a trend followiung system, with early trend detection.
You can choose whether you want the buy and sell signals on the seperate pane, or on the chart by toggeling a simple setting.
What are my favorite settings?
- Timeframe: weekly
- SMA Length: 75
- Z score buy treshold: -1.5
- Z score sell treshold: 3
- Lookback buy period: 20
- Lookback sell period: 20
Market Phases [OmegaTools]The Market Phases indicator utilizes the Detrended Price Oscillator (DPO) to assess various asset classes, bonds, or stock sectors across different market phases. It offers users the ability to monitor and compare trends in multiple markets through a normalized DPO approach, providing insights into relative overbought or oversold conditions. The indicator supports three distinct modes: "Asset Classes," "Bonds," and "Stock Sectors," allowing flexibility in market analysis based on user preference.
Key Features:
Detrended Price Oscillator (DPO) Calculation: The DPO is computed to remove longer-term trends and focus on shorter-term cyclical behavior. The indicator applies normalization using linear interpolation to smooth out the values for better comparison across different markets.
Three Analysis Modes:
Asset Classes: Compares the DPO for major asset classes, including stocks (S&P 500), bonds (US 10-Year), commodities (Gold), and the US Dollar Index (DXY).
Bonds: Analyzes the DPO across various bond categories such as investment-grade bonds (LQD), high-yield bonds (HYG), emerging market bonds (EMB), and corporate bonds.
Stock Sectors: Provides insight into key stock sectors, including Technology (XLK), Utilities (XLU), Financials (XLF), and Healthcare (XLV).
Real-Time Plotting:
The indicator plots the DPO values of the selected assets, bonds, or sectors on the chart. It provides a visual representation of the market phases, helping to identify potential market reversals or trends. Each plot is color-coded for clarity:
Blue: Asset/Sector 1
Red: Asset/Sector 2
Green: Asset/Sector 3
Orange: Asset/Sector 4
Table Display:
A dynamic table is displayed on the chart, showing the DPO values for the selected mode's assets or sectors. This allows quick comparison and evaluation of market trends.
Inputs:
DPO Length: Defines the lookback period for DPO calculation, adjustable between 10 and 500.
Normalization Length: Sets the length for normalizing the DPO values, with options ranging from 100 to 2000.
Mode: Choose between "Asset Classes," "Bonds," or "Stock Sectors" for tailored market analysis.
This tool is perfect for traders seeking to identify cyclical market phases, compare different asset classes, or monitor sector rotation dynamics. Use it to align your trading strategies with broader market trends and uncover potential trading opportunities across multiple markets.
Distance between EMA 50-100/100-150This script calculates and plots the percentage difference between the 50-period, 100-period, and 150-period Exponential Moving Averages (EMA) on a TradingView chart. The aim is to provide a clear visual representation of the market's momentum by analyzing the distance between key EMAs over time.
Key features of this script:
1. EMA Calculation : The script computes the EMA values for 50, 100, and 150 periods and calculates the percentage difference between EMA 50 and 100, and between EMA 100 and 150.
2. Custom Threshold : Users can adjust a threshold percentage to highlight significant divergences between the EMAs. A default threshold is set to 0.1%.
3. Visual Alerts : When the percentage difference exceeds the threshold, a visual marker appears on the chart:
Green Circles for bullish momentum (positive divergence),
Red Circles for bearish momentum (negative divergence),
Diamonds to indicate the first occurrence of new bullish or bearish signals, allowing users to catch fresh market trends.
4. Dynamic Plotting : The script plots two lines representing the percentage difference for each EMA pair, offering a quick and intuitive way to monitor trends.
Ideal for traders looking to gauge market direction using the relationship between multiple EMAs, this script simplifies analysis by focusing on key moving average interactions.
Normalized Linear Regression (LSMA) OscillatorNormalized Linear Regression (LSMA) Oscillator
By Nathan Farmer
The Normalized LSMA Oscillator is a trend-following indicator that enhances the classic Linear Regression (LSMA) by applying a range of normalization techniques. This indicator allows traders to smooth out and normalize LSMA signals for better trend detection and dynamic market adaptation.
Key Features:
Configurable Normalization Methods:
This indicator offers several normalization techniques, such as Z-Score, Min-Max, Mean Normalization, Robust Scaler, Logistic Function, and Quantile Transformation. Each method helps in refining LSMA outputs to improve clarity in both trending and ranging market conditions.
Smoothing Options:
Smoothing can be applied after normalization, helping to reduce noise in the signals, thus making trend-following strategies that use this indicator more effective.
Recommended Settings:
Logistic Function Normalization: Recommended length of around 12, based on my preferred signal frequency.
Z-Score Normalization: Medium period (close to the default of 50), based on my preferred signal frequency.
Min-Max Normalization: Medium period, based on my preferred signal frequency.
Mean Normalization: Medium period, based on my preferred signal frequency.
Robust Scaler: Medium period, based on my preferred signal frequency.
Quantile Transformation: Medium period, based on my preferred signal frequency.
Usage:
Designed primarily for trend-following strategies, this indicator adapts well to varying market conditions. Traders can experiment with the various normalization and smoothing settings to match the indicator to their specific needs and market preferences.
Recommendation before usage:
Always backtest the indicator for yourself with respect to how you intend to use it. Modify the parameters to suit your needs, over your preferred time frame, on your preferred asset. My preferences are for the assets I happened to be looking at when I made this indicator. Odds are, you're looking at something else, over a different time frame, in a different market environment than what my settings are tailored for.
RSI TOTAL MOMENTUM1 (resatserhat)SOURCE OF COLORS
Our oscillator is the classic RSI oscillator. However, in the classic RSI oscillator, only RSI14 is taken into account, the user looks at different periods when he wants, and each period shows a different level. This situation confuses the user and prevents him from reaching a clear conclusion. This indicator takes into account the relationship between more than 1 or even 10 RSI periods, and shows us with colors which direction the momentum is in all periods and how strong it is. In other words, the mathematics underlying the coloring is the relationship between different RSI periods.
RSI COLORS
The RSI line has 3 colors: red, green, blue. The red color indicates that the momentum is weakening, the green color indicates that it is strengthening, and the blue color indicates that the momentum is unstable and can switch from red to green or from green to red at any moment.
BOLLINGER BAND COLORS
It is formed by considering the same mathematics as the RSI line colors, but it shows the momentum of larger periods. That is, it changes color later than the RSI line, but it is more reliable and accurate.
Colors in Hidden Divergences
In hidden negative divergences and hidden positive divergences, a single bar usually has an outlier color, this should be taken into consideration.
How to Use Colors?
1. When the RSI shows green bottom, blue bottom or green and blue mixed bottoms, it is a strong bullish signal.
2. When the RSI shows red top, blue top or red and blue mixed tops, it is a strong bearish signal.
3. When the RSI and BAND colors are bearish, it creates a strong signal.
4. When the RSI performs the actions in the 1st definition above the Bollinger Band, the buy signal should be trusted more.
5. When the RSI performs the actions in the 2nd definition below the Bollinger Band, the sell signal should be trusted more.
40-60 LEVELS
The 40-60 levels are strong resistance and support levels. Added for the Andrew Cardwell strategy. Blue, green or blue-green mixed bottoms occurring close to the 60 level bring strong upward movements
Red, blue or red-blue mixed tops occurring close to the 40 level bring strong downward movements.
Also in the oscillator, when RSI14 goes above the 80 level, the background color turns red. When it falls below the 20 level, the background color turns green. The first one indicates a sell zone, the second one indicates a buy zone.
TÜRKÇE
RENKLERİN KAYNAĞI
Osilatörümüz klasik RSI osilatörüdür. Fakat klasik RSI osilatöründe sadece RSI14 dikkate alınır, kullanıcı istediğinde farklı periyotlara bakar ve her periyot farklı bir seviye gösterir. Bu durum kullanıcının zihnini karıştırır, net bir kanıya varmasını önler. İşte bu indikatör 1’den hatta 10’dan fazla RSI periyodu arasındaki ilişkiyi dikkate alarak, bütün periyotlardaki momentumun hangi yönde olduğunu ve hangi güçte olduğunu renklerle bize gösterir. Yani Renklendirmenin temelinde yatan matematik farklı RSI periyotları arasındaki ilişkidir.
RSI RENKLERİ
RSI çizgisi kırmızı, yeşil, mavi olmak üzere 3 renk taşır. Kırmızı renk momentumun zayıfladığını gösterir, yeşil renk güçlendiğini, mavi renk ise momentumun kararsız olduğunu ve her an kırmızdan yeşile veya yeşilden kırmızıya geçebileceğini söyler.
BOLLİNGER BANDI RENKLERİ
RSI çizgisi renkleri ile aynı matematik dikkate alınarak oluşur, fakat daha büyük periyotların momentumunu gösterir. Yani RSI çizgisine göre daha geç renk değiştirir ama daha güvenilir ve kesindir.
Gizli Uyumsuzluklarda Renkler
Gizli negatif uyumsuzluk ve gizli pozitif uyumsuzluklarda genelde tek bir barda aykırı renk oluşur, bu husus dikkate alınmalıdır.
Renkler Nasıl Kullanılmalı?
1. RSI yeşil dip, mavi dip veya yeşil ve mavi karışımı dipler gösterdiğinde yükseliş yönlü güçlü bir sinyaldir.
2. RSI kırmızı tepe, mavi tepe veya kırmızı ve mavi karışışımı tepeler gösterdiğinde düşüş yönlü güçlü bir sinyaldir.
3. RSI ve BAND renkleri ayı olduğunda güçlü bir sinyal oluşturur.
4. RSI bollinger bandının üstünde 1. Tanımdaki eylemleri gerçekleştirdiğinde alım sinyaline daha çok güvenilmeli.
5. RSI bollinger bandının altında 2. Tanımdaki eylemleri gerçekleştirdiğinde satım sinyaline daha çok güvenilmeli.
40-60 SEVİYELERİ
40-60 seviyeleri güçlü direnç ve destek seviyeleridir. Andrew Cardwell stratejisi için eklenmiştir. 60 seviyesine yakın gerçekleşen mavi, yeşil veya mavi-yeşil karışımı dipler güçlü yükseliş hareketleri getirir
40 seviyesine yakın gerçekleşen kırmızı, mavi veya kırmızı-mavi karışımı tepeler güçlü düşüş hareketleri getirir.
Osilatörde ayrıca RSI14 80 seviyesinin üzerine çıktığında arka plan rengi kırmızıya dönüşür. 20 seviyesinin altına düştüğüne arkaplan rengi yeşile dönüşür. İlki satış bölgesi ikincisi alış bölgesi olduğunu haber eder.
Signals Pro [traderslog]The "Signals Pro" indicator is an advanced and versatile trading tool designed to help traders accurately identify key buy and sell signals using a combination of technical analysis factors such as candle patterns , RSI (Relative Strength Index) , and candle stability . It is highly customizable and offers a range of options that make it suitable for both short-term and long-term traders. By filtering market noise and providing actionable insights, this indicator enhances decision-making and helps traders capitalize on market movements.
At the core of the "Signals Pro" indicator is the concept of Candle Stability . The Candle Stability Index measures the ratio between a candle's body and its wicks, providing insight into the strength of the price movement during that period. A higher value indicates that the candle is more stable, meaning that the price has moved significantly without much retracement. This stability filter is crucial because it prevents the generation of signals during volatile or choppy market conditions where price direction is uncertain. Traders can adjust the Candle Stability Index from 0 to 1, allowing for precise control over how stable a candle must be for the indicator to generate a signal.
Another key feature is the use of RSI (Relative Strength Index) , a momentum oscillator that measures the speed and change of price movements. The RSI index parameter in the indicator can be customized to detect overbought or oversold conditions. When the RSI falls below the defined threshold, it signals that the market may be oversold , which can indicate a potential buying opportunity . Conversely, when the RSI exceeds a certain value, it suggests that the market is overbought , signaling a potential selling opportunity . This allows traders to time their trades more effectively by entering when market conditions are favorable and exiting before a potential reversal occurs.
The Candle Delta Length is another critical element of the "Signals Pro" indicator. This parameter measures how much the price has increased or decreased over a specific number of candles. By adjusting the Candle Delta Length , traders can define how many periods the indicator should analyze before generating a signal. A longer Candle Delta Length means the price has been trending in one direction for a longer period, providing more reliable signals. For instance, if the price has been steadily decreasing for five candles, this could signal a bullish reversal , triggering a buy signal .
To further enhance its accuracy, the "Signals Pro" indicator includes a unique feature that allows traders to disable repeating signals . This is particularly useful in situations where the market is moving sideways or during low volatility periods, where multiple signals may cluster close together, creating confusion. By enabling the disable repeating signals option, traders can prevent these repeated signals and focus on the most important and confirmed signals, ensuring cleaner charts and reducing the risk of overtrading.
A key technical aspect of the indicator is its ability to detect bullish and bearish engulfing patterns . The indicator looks for bullish engulfing patterns, which occur when a bullish candle fully engulfs the body of the previous bearish candle, signaling a potential bullish reversal . Conversely, bearish engulfing patterns occur when a bearish candle fully engulfs the previous bullish candle, indicating a bearish reversal . By incorporating these candle patterns with the Candle Stability Index and RSI levels , the indicator provides highly reliable signals based on price action and market sentiment.
Visual customization is another major advantage of the "Signals Pro" indicator. Traders can choose from several different label styles , such as text bubbles , triangles , or arrows to mark the buy and sell signals on the chart. This makes the signals stand out and easy to interpret at a glance. Furthermore, the color of these signals can be customized: green for buy signals and red for sell signals , along with options to adjust the text size and label styles for even more personalization. Traders can make the signals more or less prominent based on their preference, enhancing readability and workflow efficiency.
The indicator also includes a comprehensive alert system , ensuring traders never miss an opportunity. Alerts can be set for both buy and sell signals , and the system triggers in real-time when a valid signal is generated. This is especially useful for active traders who want to stay on top of the markets without constantly monitoring their screens. The alert system helps ensure that traders are notified of potential trading opportunities as soon as they arise, allowing them to act quickly in volatile markets.
From a practical standpoint, the "Signals Pro" indicator is designed to work seamlessly across multiple timeframes, making it suitable for scalpers, day traders, swing traders, and even long-term investors. Its flexibility allows it to adapt to different trading styles and time horizons, providing value for a wide range of market participants.
In summary, the Signals Pro indicator offers a robust and customizable solution for identifying buy and sell signals . By combining candle stability , RSI analysis , and engulfing patterns , the indicator provides traders with reliable signals to enter or exit trades. The ability to customize signal appearance, coupled with a real-time alert system , makes the "Signals Pro" indicator an invaluable tool for traders looking to improve their timing and decision-making. Whether you are looking to capture short-term price movements or want to time entries and exits in longer-term trends, this indicator offers the insights needed to navigate the markets with confidence.
Aroon Oscillator [BigBeluga]Aroon Oscillator with Mean Reversion & Trend Signals is a versatile tool that helps traders identify both trend direction and potential mean reversion points. The core Aroon Oscillator tracks the strength of a trend by measuring how long it has been since a high or low price occurred within a specified period. This oscillator provides trend-following signals (LONG/SHORT) along with mean reversion signals, giving traders both the ability to ride trends and anticipate reversals.
The unique feature of this indicator is the Mean Reversion Signals, marked with dots on the main chart, indicating potential points where the trend might reverse or retrace. In addition, trend-following signals (LONG and SHORT) are plotted directly on the chart, providing clear entry and exit points when a trend is beginning or ending.
🔵 IDEA
The Aroon Oscillator with Mean Reversion indicator provides a combined approach of trend analysis and mean reversion. The core idea is to track the health and momentum of trends, while also identifying when those trends might reverse or slow down. This dual approach allows traders to both follow the prevailing market direction and also capture mean reversion opportunities.
The oscillator is smoothed with John Ehlers' Zero Lag function , which helps reduce noise and improves signal clarity by removing lag without sacrificing the indicator's responsiveness.
The indicator uses color-coded signals and an easy-to-read oscillator to visually represent different types of signals on the chart. This makes it easy for traders to spot important changes in market trends and take action based on both the trend-following and mean reversion aspects of the indicator.
🔵 KEY FEATURES & USAGE
Trend Following Signals (LONG/SHORT):
In addition to mean reversion signals, the indicator also provides clear trend-following signals. LONG signals (green arrows) are plotted when the oscillator crosses above zero, indicating a potential uptrend. Conversely, SHORT signals (blue arrows) are plotted when the oscillator crosses below zero, signaling a potential downtrend.
Mean Reversion Signals:
This indicator features unique mean reversion signals, represented by dots on the main chart. These signals occur when the oscillator crosses over or under a smoother signal line, indicating that the current trend might be losing strength and a reversal or retracement is possible. Green dots represent a possible upward reversion, while blue dots signal a potential downward reversion.
Color-Coded Signals and Oscillator:
The Aroon Oscillator is color-coded to make it visually easier for traders to differentiate between trends and mean reversion signals. When the oscillator is above zero, the area is filled with green, and when it is below zero, the area is filled with blue. This visual representation helps traders quickly identify the current market condition at a glance.
🔵 CUSTOMIZATION
Aroon Length & Smoothing: Control the sensitivity of the Aroon Oscillator by adjusting the lookback period and smoothing settings, allowing traders to fine-tune the indicator to match different market conditions.
Mean Reversion Signals: Enable or disable mean reversion signals based on your trading preferences. Adjust the signal line length to control when these reversal signals are triggered.
Color Customization: Customize the colors for the oscillator and signals to match your chart’s color scheme for better visual clarity.
Chande Momentum Oscillator StrategyThe Chande Momentum Oscillator (CMO) Trading Strategy is based on the momentum oscillator developed by Tushar Chande in 1994. The CMO measures the momentum of a security by calculating the difference between the sum of recent gains and losses over a defined period. The indicator offers a means to identify overbought and oversold conditions, making it suitable for developing mean-reversion trading strategies (Chande, 1997).
Strategy Overview:
Calculation of the Chande Momentum Oscillator (CMO):
The CMO formula considers both positive and negative price changes over a defined period (commonly set to 9 days) and computes the net momentum as a percentage.
The formula is as follows:
CMO=100×(Sum of Gains−Sum of Losses)(Sum of Gains+Sum of Losses)
CMO=100×(Sum of Gains+Sum of Losses)(Sum of Gains−Sum of Losses)
This approach distinguishes the CMO from other oscillators like the RSI by using both price gains and losses in the numerator, providing a more symmetrical measurement of momentum (Chande, 1997).
Entry Condition:
The strategy opens a long position when the CMO value falls below -50, signaling an oversold condition where the price may revert to the mean. Research in mean-reversion, such as by Poterba and Summers (1988), supports this approach, highlighting that prices often revert after sharp movements due to overreaction in the markets.
Exit Conditions:
The strategy closes the long position when:
The CMO rises above 50, indicating that the price may have become overbought and may not provide further upside potential.
Alternatively, the position is closed 5 days after the buy signal is triggered, regardless of the CMO value, to ensure a timely exit even if the momentum signal does not reach the predefined level.
This exit strategy aligns with the concept of time-based exits, reducing the risk of prolonged exposure to adverse price movements (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages the well-known phenomenon of mean-reversion in financial markets. According to research by Jegadeesh and Titman (1993), prices tend to revert to their mean over short periods following strong movements, creating opportunities for traders to profit from temporary deviations.
The CMO captures this mean-reversion behavior by monitoring extreme price conditions. When the CMO reaches oversold levels (below -50), it signals potential buying opportunities, whereas crossing overbought levels (above 50) indicates conditions for selling.
Market Efficiency and Overreaction:
The strategy takes advantage of behavioral inefficiencies and overreactions, which are often the drivers behind sharp price movements (Shiller, 2003). By identifying these extreme conditions with the CMO, the strategy aims to capitalize on the market’s tendency to correct itself when price deviations become too large.
Optimization and Parameter Selection:
The 9-day period used for the CMO calculation is a widely accepted timeframe that balances responsiveness and noise reduction, making it suitable for capturing short-term price fluctuations. Studies in technical analysis suggest that oscillators optimized over such periods are effective in detecting reversals (Murphy, 1999).
Performance and Backtesting:
The strategy's effectiveness is confirmed through backtesting, which shows that using the CMO as a mean-reversion tool yields profitable opportunities. The use of time-based exits alongside momentum-based signals enhances the reliability of the strategy by ensuring that trades are closed even when the momentum signal alone does not materialize.
Conclusion:
The Chande Momentum Oscillator Trading Strategy combines the principles of momentum measurement and mean-reversion to identify and capitalize on short-term price fluctuations. By using a widely tested oscillator like the CMO and integrating a systematic exit approach, the strategy effectively addresses both entry and exit conditions, providing a robust method for trading in diverse market environments.
References:
Chande, T. S. (1997). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. John Wiley & Sons.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Ultimate Oscillator Trading StrategyThe Ultimate Oscillator Trading Strategy implemented in Pine Script™ is based on the Ultimate Oscillator (UO), a momentum indicator developed by Larry Williams in 1976. The UO is designed to measure price momentum over multiple timeframes, providing a more comprehensive view of market conditions by considering short-term, medium-term, and long-term trends simultaneously. This strategy applies the UO as a mean-reversion tool, seeking to capitalize on temporary deviations from the mean price level in the asset’s movement (Williams, 1976).
Strategy Overview:
Calculation of the Ultimate Oscillator (UO):
The UO combines price action over three different periods (short-term, medium-term, and long-term) to generate a weighted momentum measure. The default settings used in this strategy are:
Short-term: 6 periods (adjustable between 2 and 10).
Medium-term: 14 periods (adjustable between 6 and 14).
Long-term: 20 periods (adjustable between 10 and 20).
The UO is calculated as a weighted average of buying pressure and true range across these periods. The weights are designed to give more emphasis to short-term momentum, reflecting the short-term mean-reversion behavior observed in financial markets (Murphy, 1999).
Entry Conditions:
A long position is opened when the UO value falls below 30, indicating that the asset is potentially oversold. The value of 30 is a common threshold that suggests the price may have deviated significantly from its mean and could be due for a reversal, consistent with mean-reversion theory (Jegadeesh & Titman, 1993).
Exit Conditions:
The long position is closed when the current close price exceeds the previous day’s high. This rule captures the reversal and price recovery, providing a defined point to take profits.
The use of previous highs as exit points aligns with breakout and momentum strategies, as it indicates sufficient strength for a price recovery (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages two well-established phenomena in financial markets: momentum and mean-reversion. Momentum, identified in earlier studies like those by Jegadeesh and Titman (1993), describes the tendency of assets to continue in their direction of movement over short periods. Mean-reversion, as discussed by Poterba and Summers (1988), indicates that asset prices tend to revert to their mean over time after short-term deviations. This dual approach aims to buy assets when they are temporarily oversold and capitalize on their return to the mean.
Multi-timeframe Analysis:
The UO’s incorporation of multiple timeframes (short, medium, and long) provides a holistic view of momentum, unlike single-period oscillators such as the RSI. By combining data across different timeframes, the UO offers a more robust signal and reduces the risk of false entries often associated with single-period momentum indicators (Murphy, 1999).
Trading and Market Efficiency:
Studies in behavioral finance, such as those by Shiller (2003), show that short-term inefficiencies and behavioral biases can lead to overreactions in the market, resulting in price deviations. This strategy seeks to exploit these temporary inefficiencies, using the UO as a signal to identify potential entry points when the market sentiment may have overly pushed the price away from its average.
Strategy Performance:
Backtests of this strategy show promising results, with profit factors exceeding 2.5 when the default settings are optimized. These results are consistent with other studies on short-term trading strategies that capitalize on mean-reversion patterns (Jegadeesh & Titman, 1993). The use of a dynamic, multi-period indicator like the UO enhances the strategy’s adaptability, making it effective across different market conditions and timeframes.
Conclusion:
The Ultimate Oscillator Trading Strategy effectively combines momentum and mean-reversion principles to trade on temporary market inefficiencies. By utilizing multiple periods in its calculation, the UO provides a more reliable and comprehensive measure of momentum, reducing the likelihood of false signals and increasing the profitability of trades. This aligns with modern financial research, showing that strategies based on mean-reversion and multi-timeframe analysis can be effective in capturing short-term price movements.
References:
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1976). Ultimate Oscillator. Market research and technical trading analysis.
Premium Signal Strategy [BRTLab]🔍 Overview
BRTLab Premium Signal Strategy is a comprehensive multi-indicator trading strategy based on the integration of key technical indicators such as ADX, RSX, CAND, V9, PP, MA, and LVL. The strategy allows users to flexibly adjust the parameters of each indicator to optimize for specific market conditions, making it effective for both trending markets and for identifying reversals and breakouts.
🌟 What makes this strategy unique is its seamless compatibility with the BRT Premium Signals tool, allowing traders not only to receive real-time signals but also to conduct robust backtests. This feature enables users to fine-tune the best parameter settings or even test out their own trading ideas through historical data analysis. The ability to backtest empowers traders to validate strategies before going live, significantly improving the chances of success by offering data-driven insights.
💡 Signal Logic:
ADX
The ADX-based signals reflect the strength of market trends. Bullish or bearish signals are generated when directional indicators (+DI or -DI) show increasing strength relative to one another, indicating the start or continuation of a strong trend.
RSX
These signals focus on divergences within RSI, identifying potential reversals by detecting either classic or hidden divergences when the market is overbought or oversold.
V9
Signals are generated when the price interacts with a dynamic threshold, indicating trend continuation or reversal. Additional filters can be applied to refine these signals further, enhancing the dashboard's overall effectiveness.
CAND
Candlestick-based signals are triggered by key patterns such as bullish or bearish engulfing formations. These signals are cross-checked with other conditions, such as RSI levels and candle stability, making them especially useful for short-term trading.
PP (Pivot Points)
Pivot Point signals reinforce candlestick patterns by aligning with key support or resistance levels, suggesting potential reversals or continuation opportunities at significant price points.
MA (Moving Average)
MA signals help identify trends by analyzing price action relative to a moving average. Optional filters like ADX add an additional layer of validation, ensuring only high-confidence signals are displayed on the dashboard.
LVL (Levels)
These signals are based on shifts in RSI and help traders spot potential breakouts or reversals. The dashboard integrates these signals alongside MA and ADX filters to enhance their accuracy.
📊 Risk Management
This strategy includes built-in risk management features to help minimize losses:
Initial Capital: The user can set the initial capital (default is 10000), adjusting the strategy to their financial goals.
Position Size: Set the position size (default is 1000), allowing better risk management and controlling potential losses.
Stop-Loss: Multiple stop-loss methods are available, including ATR-based, fixed percentage, or prior high/low levels.
Take-Profit: Users can configure take-profit settings (default is 1.3%) to lock in gains while managing risk effectively.
⚠️ RISK DISCLAIMER
Trading involves significant risks, and most day traders experience losses. All content, tools, scripts, and educational materials from BRTLab are provided for informational and educational purposes only. Past performance is not a guarantee of future results. Please ensure you use realistic backtesting settings, including proper account size, commission, and slippage, to reflect market conditions.
⚡ CONCLUSION
We believe that successful trading comes from using indicators as supportive tools rather than relying on them for guaranteed success. The BRTLab Premium Signal Strategy is designed to be a comprehensive, customizable toolset that helps traders understand and interpret technical indicators more effectively.
By leveraging the power of backtesting and indicator optimization, traders can make well-informed decisions and develop a deeper understanding of market dynamics. Use this strategy to build a trading framework that aligns with your personal goals and trading style.
Follow the author’s instructions below to access the BRTLab Premium suite and unlock the full potential of this strategy.
[3Commas] Signal BuilderSignal Builder is a tool designed to help traders create custom buy and sell signals by combining multiple technical indicators. Its flexibility allows traders to set conditions based on their specific strategy, whether they’re into scalping, swing trading, or long-term investing. Additionally, its integration with 3Commas bots makes it a powerful choice for those looking to automate their trades, though it’s also ideal for traders who prefer receiving alerts and making manual decisions.
🔵 How does Signal Builder work?
Signal Builder allows users to define custom conditions using popular technical indicators, which, when met, generate clear buy or sell signals. These signals can be used to trigger TradingView alerts, ensuring that you never miss a market opportunity. Additionally, all conditions are evaluated using "AND" logic, meaning signals are only activated when all user-defined conditions are met. This increases precision and helps avoid false signals.
🔵 Available indicators and recommended settings:
Signal Builder provides access to a wide range of technical indicators, each customizable to popular settings that maximize effectiveness:
RSI (Relative Strength Index): An oscillator that measures the relative strength of price over a specific period. Traders typically configure it with 14 periods, using levels of 30 (oversold) and 70 (overbought) to identify potential reversals.
MACD (Moving Average Convergence Divergence): A key indicator tracking the crossover between two moving averages. Common settings include 12 and 26 periods for the moving averages, with a 9-period signal line to detect trend changes.
Ultimate Oscillator: Combines three different time frames to offer a comprehensive view of buying and selling pressure. Popular settings are 7, 14, and 28 periods.
Bollinger Bands %B: Provides insight into where the price is relative to its upper and lower bands. Standard settings include a 20-period moving average and a standard deviation of 2.
ADX (Average Directional Index): Measures the strength of a trend. Values above 25 typically indicate a strong trend, while values below suggest weak or sideways movement.
Stochastic Oscillator: A momentum indicator comparing the closing price to its range over a defined period. Popular configurations include 14 periods for %K and 3 for %D smoothing.
Parabolic SAR: Ideal for identifying trend reversals and entry/exit points. Commonly configured with a 0.02 step and a 0.2 maximum.
Money Flow Index (MFI): Similar to RSI but incorporates volume into the calculation. Standard settings use 14 periods, with levels of 20 and 80 as oversold and overbought thresholds.
Commodity Channel Index (CCI): Measures the deviation of price from its average. Traders often use a 20-period setting with levels of +100 and -100 to identify extreme overbought or oversold conditions.
Heikin Ashi Candles: These candles smooth out price fluctuations to show clearer trends. Commonly used in trend-following strategies to filter market noise.
🔵 How to use Signal Builder:
Configure indicators: Select the indicators that best fit your strategy and adjust their settings as needed. You can combine multiple indicators to define precise entry and exit conditions.
Define custom signals: Create buy or sell conditions that trigger when your selected indicators meet the criteria you’ve set. For example, configure a buy signal when RSI crosses above 30 and MACD confirms with a bullish crossover.
TradingView alerts: Set up alerts in TradingView to receive real-time notifications when the conditions you’ve defined are met, allowing you to react quickly to market opportunities without constantly monitoring charts.
Monitor with the panel: Signal Builder includes a visual panel that shows active conditions for each indicator in real time, helping you keep track of signals without manually checking each indicator.
🔵 3Commas integration:
In addition to being a valuable tool for any trader, Signal Builder is optimized to work seamlessly with 3Commas bots through Webhooks. This allows you to automate your trades based on the signals you’ve configured, ensuring that no opportunity is missed when your defined conditions are met. If you prefer automation, Signal Builder can send buy or sell signals to your 3Commas bots, enhancing your trading process and helping you manage multiple trades more efficiently.
🔵 Example of use:
Imagine you trade in volatile markets and want to trigger a sell signal when:
Stochastic Oscillator indicates overbought conditions with the %K value crossing below 80.
Bollinger Bands %B shows the price has surpassed the upper band, suggesting a potential reversal.
ADX is below 20, indicating that the trend is weak and could be about to change.
With Signal Builder , you can configure these conditions to trigger a sell signal only when all are met simultaneously. Then, you can set up a TradingView alert to notify you as soon as the signal is activated, giving you the opportunity to react quickly and adjust your strategy accordingly.
👨🏻💻💭 If this tool helps your trading strategy, don’t forget to give it a boost! Feel free to share in the comments how you're using it or if you have any questions.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Williams %R StrategyThe Williams %R Strategy implemented in Pine Script™ is a trading system based on the Williams %R momentum oscillator. The Williams %R indicator, developed by Larry Williams in 1973, is designed to identify overbought and oversold conditions in a market, helping traders time their entries and exits effectively (Williams, 1979). This particular strategy aims to capitalize on short-term price reversals in the S&P 500 (SPY) by identifying extreme values in the Williams %R indicator and using them as trading signals.
Strategy Rules:
Entry Signal:
A long position is entered when the Williams %R value falls below -90, indicating an oversold condition. This threshold suggests that the market may be near a short-term bottom, and prices are likely to reverse or rebound in the short term (Murphy, 1999).
Exit Signal:
The long position is exited when:
The current close price is higher than the previous day’s high, or
The Williams %R indicator rises above -30, indicating that the market is no longer oversold and may be approaching an overbought condition (Wilder, 1978).
Technical Analysis and Rationale:
The Williams %R is a momentum oscillator that measures the level of the close relative to the high-low range over a specific period, providing insight into whether an asset is trading near its highs or lows. The indicator values range from -100 (most oversold) to 0 (most overbought). When the value falls below -90, it indicates an oversold condition where a reversal is likely (Achelis, 2000). This strategy uses this oversold threshold as a signal to initiate long positions, betting on mean reversion—an established principle in financial markets where prices tend to revert to their historical averages (Jegadeesh & Titman, 1993).
Optimization and Performance:
The strategy allows for an adjustable lookback period (between 2 and 25 days) to determine the range used in the Williams %R calculation. Empirical tests show that shorter lookback periods (e.g., 2 days) yield the most favorable outcomes, with profit factors exceeding 2. This finding aligns with studies suggesting that shorter timeframes can effectively capture short-term momentum reversals (Fama, 1970; Jegadeesh & Titman, 1993).
Scientific Context:
Mean Reversion Theory: The strategy’s core relies on mean reversion, which suggests that prices fluctuate around a mean or average value. Research shows that such strategies, particularly those using oscillators like Williams %R, can exploit these temporary deviations (Poterba & Summers, 1988).
Behavioral Finance: The overbought and oversold conditions identified by Williams %R align with psychological factors influencing trading behavior, such as herding and panic selling, which often create opportunities for price reversals (Shiller, 2003).
Conclusion:
This Williams %R-based strategy utilizes a well-established momentum oscillator to time entries and exits in the S&P 500. By targeting extreme oversold conditions and exiting when these conditions revert or exceed historical ranges, the strategy aims to capture short-term gains. Scientific evidence supports the effectiveness of short-term mean reversion strategies, particularly when using indicators sensitive to momentum shifts.
References:
Achelis, S. B. (2000). Technical Analysis from A to Z. McGraw Hill.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1979). How I Made One Million Dollars… Last Year… Trading Commodities. Windsor Books.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
This explanation provides a scientific and evidence-based perspective on the Williams %R trading strategy, aligning it with fundamental principles in technical analysis and behavioral finance.
Fourier Smoothed Volume Zone Oscillator ( FSVZO )Overview 🔎
The fourier smoothed Volume Zone Oscillator (FSVZO) is a versatile tool designed to provide traders with a detailed understanding of market conditions by examining volume dynamics. FSVZO applies a series of advanced regularization techniques aimed at trying to reduce market noise, making signals potentially more readable and actionable. This indicator combines traditional technical analysis tools with a unique set of smoothing functions, aimed at creating a more balanced and reliable oscillator that can assist traders in their decision-making process.
A Combination of Technical Elements for a Unique Edge 🔀
FSVZO integrates a variety of technical elements to offer a comprehensive perspective on the market. These elements can be used individually or in combination, depending on user preferences. Here are the main components:
Volume Zone Oscillator (VZO): This foundational element leverages volume data to identify trends and shifts in buying or selling pressure. Unlike a standalone VZO, the FSVZO incorporates a Fourier-based regularization technique to reduce false signals, allowing traders to focus on meaningful volume-driven movements.
Ehler's White Noise Filter: This component is a sophisticated filter that helps distinguish genuine market signals from white noise. By isolating the meaningful movements in price and volume, the white noise filter contributes to the clarity and reliability of the signals generated.
Divergences Detection: FSVZO also provides divergence signals (both hidden and regular) based on the oscillator and price action. Divergences can be used to anticipate possible market reversals or confirmations, enhancing the trader's ability to recognize significant market shifts.
Money Flow Index (MFI) Smoothing: The MFI is calculated and then smoothed using wavelet and whitenoise techniques, providing a cleaner view of money flow within the market. This helps reduce erratic fluctuations and focuses on more consistent trends.
Trendshift Visualization: The FSVZO features an optional trendshift indicator, highlighting shifts between bullish and bearish conditions. These visual cues make it easier to identify trend reversals, aiding traders in timely decision-making.
Flexible Display Options 📊
FSVZO offers a variety of display modes to cater to different trading styles and visual preferences:
Neon Style Plot: The oscillator is presented with neon-style plots primarily for aesthetic purposes.
Color Blindness Modes 🌈: FSVZO includes several color palettes to accommodate traders affected by different types of color blindness (Protanopia, Deuteranopia, Tritanopia, Achromatopsia). These options ensure that everyone can easily interpret the signals, regardless of visual impairments.
Take Profit Areas & Alerts: The indicator can display take profit areas based on overbought or oversold conditions of the smoothed oscillator, marked by background hues to provide a clear visual signal. Alerts for high and low thresholds can also be enabled to identify moments of increased buying or selling interest.
Divergences and Trend Analysis 🔍
FSVZO also aims to identify bullish and bearish divergences:
Regular Bullish/Bearish Divergence: These occur when the oscillator diverges from the price action, indicating a possible reversal.
Hidden Bullish/Bearish Divergence: These occur within a trend, signaling continuation opportunities that help traders capitalize on ongoing trends.
FSVZO also supports additional filtering for divergences, allowing users to refine the detection of divergences to better suit their trading preferences.
Enhanced Noise Filtering 🔄
One of the unique features of FSVZO is its Fourier Regularization and Ehler's White Noise Filter, which help improve signal reliability by reducing the impact of market noise. These filtering methods are beneficial for traders seeking to avoid whipsaws and focus on more meaningful market movements.
Why FSVZO Stands Out 🔑
Noise Reduction: By combining multiple filtering techniques, FSVZO is designed to react to price changes as quickly as possible while offering various smoothing options to reduce noise, which may make it less responsive but more stable.
Flexible Visualization: The option to use different display modes and the inclusion of color blindness-friendly palettes make FSVZO versatile and accessible to all traders.
Detailed Divergence Analysis: The integration of both regular and hidden divergence detection helps improve the potential for identifying trading opportunities.
Advanced Regularization Techniques: The use of Fourier transformation and white noise filters adds a unique aspect to volume analysis, differentiating FSVZO from other traditional volume oscillators.
Conclusion 🔒
The Regularized Volume Zone Oscillator (FSVZO) is a unique tool that brings together multiple advanced techniques to help traders better understand market conditions and volume dynamics. The indicator is designed to react to price changes as quickly as possible, which may lead to false signals; however, it also offers smoothing options to help reduce noise at the cost of reduced reaction speed. This balance between responsiveness and stability provides traders with flexibility in adapting the indicator to different market conditions. However, as with all indicators, it is crucial to combine FSVZO with other tools and maintain sound risk management practices.
FSVZO is primarily designed for more experienced traders due the number of different signals it provides. It offers enhanced insights into volume trends and market movement, and should be used alongside other indicators to reduce risk and false signals
Dont make me crossStrategy Overview
This trading strategy utilizes Exponential Moving Averages (EMAs) to generate buy and sell signals based on the crossover of two EMAs, which are shifted downwards by 50 points. The strategy aims to identify potential market reversals and trends based on these crossovers.
Components of the Strategy
Exponential Moving Averages (EMAs):
Short EMA: This is calculated over a shorter period (default is 9 periods) and is more responsive to recent price changes.
Long EMA: This is calculated over a longer period (default is 21 periods) and provides a smoother view of the price trend.
Both EMAs are adjusted by a fixed shift amount of -50 points.
Input Parameters:
Short EMA Length: The period used to calculate the short-term EMA. This can be adjusted based on the trader's preference or market conditions.
Long EMA Length: The period used for the long-term EMA, also adjustable.
Shift Amount: A fixed value (default -50) that is subtracted from both EMAs to shift their values downwards. This is useful for visual adjustments or specific strategy requirements.
Plotting:
The adjusted EMAs are plotted on the price chart. The short EMA is displayed in blue, and the long EMA is displayed in red. This visual representation helps traders identify the crossover points easily.
Signal Generation:
Buy Signal: A buy signal is generated when the short EMA crosses above the long EMA. This is interpreted as a bullish signal, indicating potential upward price movement.
Sell Signal: A sell signal occurs when the short EMA crosses below the long EMA, indicating potential downward price movement.
Trade Execution:
When a buy signal is triggered, the strategy enters a long position.
Conversely, when a sell signal is triggered, the strategy enters a short position.
Trading Logic
Market Conditions: The strategy is most effective in trending markets. During sideways or choppy market conditions, it may generate false signals.
Risk Management: While this script does not include explicit risk management features (like stop-loss or take-profit), traders should consider implementing these to manage their risk effectively.
Customization
Traders can customize the EMA lengths and the shift amount based on their analysis and preferences.
The strategy can also be enhanced with additional indicators, such as volume or volatility measures, to filter signals further.
Use Cases
This strategy can be applied to various timeframes, such as intraday, daily, or weekly charts, depending on the trader's style.
It is suitable for both novice and experienced traders, offering a straightforward approach to trading based on technical analysis.
Summary
The EMA Crossover Strategy with a -50 shift is a straightforward technical analysis approach that capitalizes on the momentum generated by the crossover of short and long-term EMAs. By shifting the EMAs downwards, the strategy can help traders visualize potential entry and exit points more clearly, although it's important to consider additional risk management and market context for effective trading.
3CRGANG - HISTOGRAMThe 3CRGANG - HISTOGRAM is a breakthrough tool, developed to consolidate multiple oscillators, including their Fibonacci-modified versions, into a single, streamlined indicator. This isn’t just a combination of tools—i t’s a carefully engineered solution built to address the nuanced challenges traders face, such as market noise, varying data availability, and trend alignment across multiple timeframes.
Behind the scenes, significant debugging ensures it performs flawlessly even in situations where volume data isn’t provided by brokers. With automatic adjustments that adapt to different conditions, the indicator allows traders to remain focused on decision-making. Every enhancement, from signal optimization to noise reduction, reflects careful design choices to provide practical, actionable insights.
This tool is designed to give traders clarity, speed, and an edge, enabling them to focus on the markets without worrying about technical details.
How It’s Different from Basic Indicators
Rather than simply mashing up popular indicators like MACD, RSI, and more , —it’s a strategic tool designed to detect key momentum shifts, divergences, and trends in real time.
This script combines Fibonacci-modified oscillators and classic indicators in a unique way, providing multi-dimensional insights to enhance your trading decisions.
Reduce market noise: Fast and slow averages are used to generate histograms that filter out false signals.
Optimize alerts: Fibonacci-based calculations fine-tune oscillators to detect trends at key turning points.
Multi-timeframe momentum: This allows for tracking higher timeframe momentum while making decisions on lower timeframes—a powerful feature for trend alignment.
Key Features and Unique Value
Oscillator Flexibility: Choose from multiple oscillators to fit your strategy, including both momentum-based and volatility-based approaches.
Fibonacci Enhancements: These versions increase precision, providing greater confidence in signals at critical levels.
MTF Compatibility: Analyze higher timeframe momentum on shorter charts to maintain alignment with the broader trend.
Custom Alerts: Color-coded histograms and moving averages provide visual cues to keep your trades in sync with momentum changes.
How It Works
The indicator plots fast and slow averages for the selected oscillator, and the difference between these averages forms the histogram. Custom color coding shows whether momentum is increasing or weakening. The proprietary modification factor adjusts the signal sensitivity, allowing traders to fine-tune the indicator for their strategy.
Visual Alerts:
Green Bars: Indicate bullish momentum.
Red Bars: Suggest bearish momentum.
Buy Only / Sell Only Zones: Alert traders when the indicator suggests favoring either long or short trades.
This indicator minimizes false signals by blending momentum oscillators with volume-weighted filters and smooth moving averages, ensuring better signal quality.
Use Case: Like a Traffic Light for Your Trades
Green means Go: Enter or hold long positions during green bars, signaling upward momentum.
Red means Stop (or Go Short): Exit long positions or enter short trades when red bars appear, indicating bearish momentum.
The Buy Only and Sell Only alerts help traders stay aligned with dominant trends and avoid counter-trend trades in high-momentum phases.
Real-World Examples :
Divergences (BTCUSD):
When the price action ranges, wedges, or behaves unusually, the histogram—being highly sensitive — alerts traders ahead of potential reversals or continuation moves.
This gives traders more time to assess market conditions and prepare their strategy before momentum shifts.
Multi-Timeframe Momentum (ADAUSD):
Momentum from a higher timeframe aligns with the trend on a lower timeframe, helping traders time their entries accurately.
The Priceless Edge for Traders
The 3CRGANG offers more than just another way to analyze markets—it provides a priceless edge by streamlining multiple indicators into a single tool. With the flexibility to switch between oscillators, multi-timeframe momentum tracking, and proprietary enhancements, it’s designed to help traders stay ahead in both trending and volatile markets.
Disclaimer
This indicator is a trading tool designed to provide insights into market trends, but it does not guarantee results. Trading involves risk, and past performance does not predict future outcomes. Use it alongside proper risk management practices.
