MomentumSignal Kit RSI-MACD-ADX-CCI-CMF-TSI-EStoch// ----------------------------------------
// Description:
// ----------------------------------------
// MomentumKit RSI/MACD-ADX-CCI-CMF-TSI-EStoch Suite is a comprehensive momentum indicator suite designed to provide robust buy and sell signals through the consensus of multiple normalized momentum indicators. This suite integrates the following indicators:
// - **Relative Strength Index (RSI)**
// - **Stochastic RSI**
// - **Moving Average Convergence Divergence (MACD)** with enhanced logic
// - **True Strength Index (TSI)**
// - **Commodity Channel Index (CCI)**
// - **Chaikin Money Flow (CMF)**
// - **Average Directional Index (ADX)**
// - **Ehlers' Stochastic**
//
// **Key Features:**
// 1. **Normalization:** Each indicator is normalized to a consistent scale, facilitating easier comparison and interpretation across different momentum metrics. This uniform scaling allows traders to seamlessly analyze multiple indicators simultaneously without the confusion of differing value ranges.
//
// 2. **Consensus-Based Signals:** By combining multiple indicators, MomentumKit generates buy and sell signals based on the agreement among various momentum measurements. This multi-indicator consensus approach enhances signal reliability and reduces the likelihood of false positives.
//
// 3. **Overlap Analysis:** The normalization process aids in identifying overlapping signals, where multiple indicators point towards a potential change in price or momentum. Such overlaps are strong indicators of significant market movements, providing traders with timely and actionable insights.
//
// 4. **Enhanced Logic for MACD:** The MACD component within MomentumKit utilizes enhanced logic to improve its responsiveness and accuracy in detecting trend changes.
//
// 5. **Debugging Features:** MomentumKit includes advanced debugging tools that display individual buy and sell signals generated by each indicator. These features are intended for users with technical and programming skills, allowing them to:
// - **Visualize Signal Generation:** See real-time buy and sell signals for each integrated indicator directly on the chart.
// - **Adjust Signal Thresholds:** Modify the criteria for what constitutes a buy or sell signal for each indicator, enabling tailored analysis based on specific trading strategies.
// - **Filter and Manipulate Signals:** Enable or disable specific indicators' contributions to the overall buy and sell signals, providing flexibility in signal generation.
// - **Monitor Indicator Behavior:** Utilize debug plots and labels to understand how each indicator reacts to market movements, aiding in strategy optimization.
//
// **Work in Progress:**
// MomentumKit is continuously evolving, with ongoing enhancements to its algorithms and user interface. Current debugging features are designed to offer deep insights for technically adept users, allowing for extensive customization and fine-tuning. Future updates aim to introduce more user-friendly interfaces and automated optimization tools to cater to a broader audience.
//
// **Usage Instructions:**
// - **Visibility Controls:** Users can toggle the visibility of individual indicators to focus on specific momentum metrics as needed.
// - **Parameter Adjustments:** Each indicator comes with customizable parameters, allowing traders to fine-tune the suite according to their trading strategies and market conditions.
// - **Debugging Features:** Enable the debugging mode to visualize individual indicator signals and adjust their contribution to the overall buy/sell signals. This requires a basic understanding of the underlying indicators and their operational thresholds.
//
// **Benefits:**
// - **Simplified Analysis:** Normalization simplifies the process of analyzing multiple indicators, making it easier to identify consistent signals across different momentum measurements.
// - **Improved Decision-Making:** Consensus-based signals backed by multiple normalized indicators provide a higher level of confidence in trading decisions.
// - **Versatility:** Suitable for various trading styles and market conditions, MomentumKit offers a versatile toolset for both novice and experienced traders.
//
// **Technical Requirements:**
// - **Programming Knowledge:** To fully leverage the debugging and signal manipulation features, users should possess a foundational understanding of Pine Script and the mechanics of momentum indicators.
// - **Customization Skills:** Ability to adjust indicator parameters and debug filters to align with specific trading strategies.
//
// **Disclaimer:**
// This indicator suite is intended for educational and analytical purposes only and does not constitute financial advice. Trading involves significant risk, and past performance is not indicative of future results. Always conduct your own analysis or consult a qualified financial advisor before making trading decisions.
M-oscillator
Stochastics Confluences 4 in 1Description of the Pine Script:
This script plots the Full Stochastic indicator for four different time periods, and highlights conditions where potential buy or sell signals can be identified. The Stochastic indicator measures the position of the current closing price relative to the range of high and low prices over a defined period, helping traders identify overbought and oversold conditions.
Key Features:
Stochastic Calculation for 4 Different Periods:
The script calculates the Stochastic for four separate lookback periods: 9, 14, 40, and 60 bars.
Each Stochastic value is smoothed by a Simple Moving Average (SMA) to reduce noise and provide a clearer signal.
Visual Representation:
It plots each Stochastic value on the chart using different colors, allowing the user to see how the different periods of the indicator behave relative to each other.
Horizontal lines are drawn at 80 (Upper Bound) and 20 (Lower Bound), commonly used to identify overbought and oversold regions.
Highlighting Buy and Sell Conditions:
Green Highlight (Potential Buy Signal):
When all four Stochastic values (for the four different periods) are below 20, this suggests that the asset is in an oversold condition across multiple timeframes. The green background highlight appears when the Stochastic lines converge below 20, indicating a potential buy signal, as the price may be preparing to move upward from an oversold state.
Red Highlight (Potential Sell Signal):
When all four Stochastic values are above 80, the asset is in an overbought condition across multiple timeframes. The red background highlight appears when the Stochastic lines converge above 80, indicating a potential sell signal, as the price may soon reverse downward from an overbought state.
How to Interpret the Signals:
Buy Signals (Green Highlight):
When the chart is highlighted in green, it means the Stochastic indicators for all four periods are below 20, signaling that the asset is oversold and may be nearing a potential upward reversal. This condition suggests a possible buying opportunity, especially when other indicators confirm the potential for an upward trend.
Sell Signals (Red Highlight):
When the chart is highlighted in red, it indicates that the Stochastic indicators for all four periods are above 80, meaning the asset is overbought. This condition signals a possible downward reversal, suggesting a potential selling opportunity if the price begins to show signs of weakness.
By using this script, traders can visually identify periods of strong confluence across different timeframes when the Stochastic indicators are in extreme oversold or overbought conditions, which are traditionally seen as strong buy or sell signals.
This approach helps filter out weaker signals and focuses on moments when all timeframes align, increasing the probability of a successful trade.
Money Wave Script (Visual Adaptive MFI)This Script is a visual modification of the Money Flow Index (MFI)
//@version=5
indicator(title="Money Flow Index", shorttitle="MFI", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
length = input.int(title="Length", defval=14, minval=1, maxval=2000)
src = hlc3
mf = ta.mfi(src, length)
plot(mf, "MF", color=#7E57C2)
overbought=hline(80, title="Overbought", color=#787B86)
hline(50, "Middle Band", color=color.new(#787B86, 50))
oversold=hline(20, title="Oversold", color=#787B86)
fill(overbought, oversold, color=color.rgb(126, 87, 194, 90), title="Background")
This Money Wave Script is culled from. the Money Flow Index with visual representation to help traders identify money flow. In addition, the waves can be smoothened. Here’s a detailed overview based on its functionality, color coding, usage, risk management, and a concluding summary.
Functionality
The Money Wave Script operates as an oscillator that measures the inflow and outflow of money into an asset over a specified period. It calculates the MFI by considering both price and volume, which allows it to assess buying and selling pressures more accurately than traditional indicators that rely solely on price data.
Color Coding
The indicator employs a color-coded scheme to enhance visual interpretation:
Green Area: Indicates bullish conditions when the normalized Money wave is above zero, suggesting buying pressure.
Red Area: Indicates bearish conditions when the normalized Money wave is below zero, suggesting selling pressure.
Background Colors: The background changes to green when the MoneyWave exceeds the upper threshold (overbought) and red when it falls below the lower threshold (oversold), providing immediate visual cues about market conditions.
Usage
Traders utilize the Money Wave indicator in various ways:
Identifying Overbought and Oversold Levels: By observing the MFI readings, traders can determine when an asset may be overbought or oversold, prompting potential entry or exit points.
Spotting Divergences: Traders look for divergences between price and the MFI to anticipate potential reversals. For example, if prices are making new highs but the MFI is not, it could indicate weakening momentum.
Trend Confirmation: The indicator can help confirm trends by showing whether buying or selling pressure is dominating.
Customizable Settings: Users can adjust parameters such as the MFI length , Smoothen index and overbought/oversold thresholds to tailor the indicator to their trading strategies.
Conclusion
The Money Wave indicator is a powerful tool for traders seeking to analyze market conditions based on the flow of money into and out of assets. Its combination of price and volume analysis, along with clear visual cues, makes it an effective choice for identifying overbought and oversold conditions, spotting divergences, and confirming trends.
TEMA For Loop [Mattes]The TEMA For Loop indicator is a powerful tool designed for technical analysis, combining the Triple Exponential Moving Average (TEMA) with a custom scoring mechanism based on a for loop. It evaluates price trends over a specified period, allowing traders to identify potential entry and exit points in the market. This indicator enhances decision-making by providing visual cues through dynamic candle coloring, reflecting market sentiment and trends effectively.
Technical Details:
Triple Exponential Moving Average (TEMA):
- TEMA is known for its responsiveness to price changes, as it reduces lag compared to traditional moving averages. The TEMA calculation employs three nested Exponential Moving Averages (EMAs) to produce a smoother trend line, which helps traders identify the direction and momentum of the market.
Scoring Mechanism:
- The scoring mechanism is based on a custom for loop that compares the current TEMA value to previous values over a specified range. The loop counts how many previous values are less than the current value, generating a score that reflects the strength of the trend:
- A higher score indicates a stronger upward trend.
- A lower (negative) score suggests a downward trend.
Threshold Levels:
- Upper Threshold: A score above this level signals a potential long entry, indicating strong bullish momentum.
- Lower Threshold: A score below this level indicates a potential short entry, suggesting bearish sentiment.
>>>These thresholds are adjustable, allowing traders to fine-tune their strategy according to their risk tolerance and market conditions.
Signal Logic:
- The indicator provides clear signals for entering long or short positions based on the score crossing the defined thresholds.
>>Long Entry Signal: When the smoothed score crosses above the upper threshold.
>>Short Entry Signal: When the smoothed score crosses below the lower threshold.
Why This Indicator Is Useful:
>>> Enhanced Decision-Making: The TEMA For Loop indicator offers traders a clear and objective view of market trends, reducing the emotional aspect of trading. By visualizing bullish and bearish conditions, it assists traders in making timely decisions.
>>> Customizable Parameters: The ability to adjust TEMA period, thresholds, and other settings allows traders to tailor the indicator to their specific trading strategies and market conditions.
Visual Clarity: The integration of dynamic candle coloring provides immediate visual cues about the prevailing trend, making it easier for traders to spot potential trade opportunities at a glance.
The TEMA For Loop - Smoothed with Candle Colors indicator is a sophisticated trading tool that utilizes TEMA and a custom scoring mechanism to identify and visualize market trends effectively. By employing dynamic candle coloring, traders gain immediate insights into market sentiment, enabling informed decision-making for entry and exit strategies. This indicator is designed for traders seeking a systematic approach to trend analysis, enhancing their trading performance through clear, actionable signals.
Relative Strength Price Oscillator Indicator (RS PPO)Percentage Price Oscillator (PPO)
The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences.
PPO readings are not subject to the price level of the security and the PPO values for different securities can be compared, regardless of the price of the security.
Relative Strength (RS)
Relative strength is a strategy used in momentum investing and focuses on investing in stocks or other securities that have performed well relative to the market as a whole or to a relevant benchmark.
Chart
In the chart, Microsoft stock (MSFT) is plotted against the VanEck Semiconductor ETF (SMH).
In the example on the left, from the negative values of the RS PPO it can be seen that MSFT, although trending upward, is losing out in negative terms to the SMH etf.
In the example on the right, during a correction phase with a downward price trend, Microsoft held up relatively well compared to the Van Eck Semiconductor etf.
Momentum Nexus Oscillator [UAlgo]The "Momentum Nexus Oscillator " indicator is a comprehensive momentum-based tool designed to provide traders with visual cues on market conditions using multiple oscillators. By combining four popular technical indicators—RSI (Relative Strength Index), VZO (Volume Zone Oscillator), MFI (Money Flow Index), and CCI (Commodity Channel Index)—this heatmap offers a holistic view of the market's momentum.
The indicator plots two lines: one representing the current chart’s combined momentum score and the other representing a higher timeframe’s (HTF) score, if enabled. Through smooth gradient color transitions and easy-to-read signals, the Momentum Nexus Heatmap allows traders to easily identify potential trend reversals or continuation patterns.
Traders can use this tool to detect overbought or oversold conditions, helping them anticipate possible long or short trade opportunities. The option to use a higher timeframe enhances the flexibility of the indicator for longer-term trend analysis.
🔶 Key Features
Multi-Oscillator Approach: Combines four popular momentum oscillators (RSI, VZO, MFI, and CCI) to generate a weighted score, providing a comprehensive picture of market momentum.
Dynamic Color Heatmap: Utilizes a smooth gradient transition between bullish and bearish colors, reflecting market momentum across different thresholds.
Higher Timeframe (HTF) Compatibility: Includes an optional higher timeframe input that displays a separate score line based on the same momentum metrics, allowing for multi-timeframe analysis.
Customizable Parameters: Adjustable RSI, VZO, MFI, and CCI lengths, as well as overbought and oversold levels, to match the trader’s strategy or preference.
Signal Alerts: Built-in alert conditions for both the current chart and higher timeframe scores, notifying traders when long or short entry signals are triggered.
Buy/Sell Signals: Displays visual signals (▲ and ▼) on the chart when combined scores reach overbought or oversold levels, providing clear entry cues.
User-Friendly Visualization: The heatmap is separated into four sections representing each indicator, providing a transparent view of how each contributes to the overall momentum score.
🔶 Interpreting Indicator:
Combined Score
The indicator generates a combined score by weighing the individual contributions of RSI, VZO, MFI, and CCI. This score ranges from 0 to 100 and is plotted as a line on the chart. Lower values suggest potential oversold conditions, while higher values indicate overbought conditions.
Color Heatmap
The indicator divides the combined score into four distinct sections, each representing one of the underlying momentum oscillators (RSI, VZO, MFI, and CCI). Bullish (greenish) colors indicate upward momentum, while bearish (grayish) colors suggest downward momentum.
Long/Short Signals
When the combined score drops below the oversold threshold (default is 26), a long signal (▲) is displayed on the chart, indicating a potential buying opportunity.
When the combined score exceeds the overbought threshold (default is 74), a short signal (▼) is shown, signaling a potential sell or short opportunity.
Higher Timeframe Analysis
If enabled, the indicator also plots a line representing the combined score for a higher timeframe. This can be used to align lower timeframe trades with the broader trend of a higher timeframe, providing added confirmation.
Signals for long and short entries are also plotted for the higher timeframe when its combined score reaches overbought or oversold levels.
🔶Purpose of Using Multiple Technical Indicators
The combination of RSI, VZO, MFI, and CCI in the Momentum Nexus Heatmap provides a comprehensive approach to analyzing market momentum by leveraging the unique strengths of each indicator. This multi-indicator method minimizes the limitations of using just one tool, resulting in more reliable signals and a clearer understanding of market conditions.
RSI (Relative Strength Index)
RSI contributes by measuring the strength and speed of recent price movements. It helps identify overbought or oversold levels, signaling potential trend reversals or corrections. Its simplicity and effectiveness make it one of the most widely used indicators in technical analysis, contributing to momentum assessment in a straightforward manner.
VZO (Volume Zone Oscillator)
VZO adds the critical element of volume to the analysis. By assessing whether price movements are supported by significant volume, VZO distinguishes between price changes that are driven by real market conviction and those that might be short-lived. It helps validate the strength of a trend or alert the trader to potential weakness when price moves are unsupported by volume.
MFI (Money Flow Index)
MFI enhances the analysis by combining price and volume to gauge money flow into and out of an asset. This indicator provides insight into the participation of large players in the market, showing if money is pouring into or exiting the asset. MFI acts as a volume-weighted version of RSI, giving more weight to volume shifts and helping traders understand the sustainability of price trends.
CCI (Commodity Channel Index)
CCI contributes by measuring how far the price deviates from its statistical average. This helps in identifying extreme conditions where the market might be overextended in either direction. CCI is especially useful for spotting trend reversals or continuations, particularly during market extremes, and for identifying divergence signals.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
RSI & Volume Impact Analyzer Ver.1.00Description:
The RSI VOL Score indicator combines the Relative Strength Index (RSI) and volume data through a mathematical calculation to assist traders in identifying and confirming potential trend reversals and continuations. By leveraging both momentum (RSI) and volume data, this indicator provides a more comprehensive view of market strength compared to using RSI or volume alone.
How It Works:
This indicator calculates a score by comparing the RSI against its moving average, adjusted by the volume data. The resulting score quantifies market momentum and strength. When the score crosses its signal line, it may indicate key moments where the market shifts between bullish and bearish trends, potentially helping traders spot these changes earlier.
Calculation Methods:
The RSI VOL Score allows users to select between several calculation methods to suit their strategy:
SMA (Simple Moving Average): Provides a balanced smoothing approach.
EMA (Exponential Moving Average): Reacts more quickly to recent price changes, offering faster signals.
VWMA (Volume Weighted Moving Average): Emphasizes high-volume periods, focusing on stronger market moves.
WMA (Weighted Moving Average): Applies greater weight to recent data for a more responsive signal.
What the Indicator Plots:
Score Line: Represents a combined metric based on RSI and volume, helping traders gauge the overall strength of the trend.
Signal Line: A smoothed version of the score that helps traders identify potential trend changes. Bullish signals occur when the score crosses above the signal line, while bearish signals occur when the score drops below.
Key Features:
Trend Identification: The score and signal line crossovers can help confirm emerging bullish or bearish trends, allowing traders to act on upward or downward momentum.
Customizable Settings: Traders can adjust the lengths of the RSI and signal line and choose between different moving averages (SMA, EMA, VWMA, WMA) to tailor the indicator to their trading style.
Timeframe-Specific: The indicator works within the selected timeframe, ensuring accurate trend analysis based on the current market context.
Practical Use Cases:
Trending Markets: In trending markets, this indicator helps confirm bullish or bearish signals by validating price moves with volume. Traders can use the crossover of the score and signal line as a guide for entering or exiting trades based on trend strength.
Ranging Markets: In ranging markets, the indicator helps filter out false signals by confirming if price movements are backed by volume, making it a useful tool for traders looking to avoid entering during weak or uncertain market conditions.
Interpreting the Score and Signal Lines:
Bullish Signal: A bullish signal occurs when the score crosses above the signal line, indicating a potential upward trend in momentum and price.
Bearish Signal: A bearish signal is generated when the score crosses below the signal line, suggesting a potential downward trend or weakening market momentum.
By mathematically combining RSI and volume data into a single trend score, the RSI VOL Score indicator provides traders with a powerful tool for identifying trend shifts early and making more confident trading decisions.
Important Note:
The signals generated by this indicator should be interpreted in conjunction with other analysis tools. It is always advisable to confirm signals before making any trading decisions.
Disclaimer:
This indicator is designed to assist traders in their decision-making process and does not provide financial advice. The creators of this tool are not responsible for any financial losses or trading decisions made based on its signals. Trading involves significant risk, and users should seek professional advice or conduct their own research before making any trading decisions.
Stochastic RMIThe Relative Momentum Index (RMI) is a technical analysis indicator used to analyze the price movements of assets in a financial market. Similar to the RSI (Relative Strength Index), it helps measure the momentum and strength of the asset's price movements over the recent period. However, the RMI offers a "smoother" view, unlike the RSI. This means that there is less "noise" in the indicator.
As is known, the Stochastic RSI indicator is based on the RSI. What I did was to create a stochastic based on the RMI. If you compare this indicator with the "Stochastic RSI", you will see that there is no difference between them, except that the "Stochastic RMI" is more "smooth" and noiseless.
BRT MACD CustomBRT MACD Custom — Adaptive and Flexible MACD for Multi-Timeframe Analysis
The BRT MACD Custom is an advanced version of the traditional MACD indicator, offering additional flexibility and adaptability for multi-timeframe trading. This custom script allows traders to adjust the calculation parameters for MACD to suit their specific trading strategy, timeframe, and market conditions.
Key Features
Multi-Timeframe Support
Unlike the standard MACD, this indicator lets you choose a specific timeframe (different from the chart timeframe) for calculating MACD values. This feature provides more flexibility in analyzing market trends on multiple timeframes without changing the main chart.
Example: You can analyze MACD on a 15-minute timeframe even when your chart is set to 1-minute, giving you broader market insights.
Customizable EMA and Signal Settings
Users can adjust the fast and slow EMA lengths as well as the signal smoothing to better align with their preferred trading strategies. The script allows switching between the two popular types of moving averages — SMA or EMA — for both the MACD and the signal line.
Volatility-Based Adaptive EMA
The script includes an adaptive mechanism for EMA calculation. When the selected timeframe closes, the indicator dynamically adjusts the calculation, ensuring the MACD values respond quickly to market volatility. This makes the indicator more reactive compared to static MACD implementations.
Shift Options for MACD, Signal, and Histogram
The indicator allows shifting the MACD, signal line, and histogram values by one or more bars. This can be useful for backtesting and simulating strategies where you anticipate future price movements.
Signal Alerts for Long and Short Trades
The script generates visual signals when certain conditions are met, indicating potential long or short trade opportunities. These signals are based on MACD and histogram crossovers:
Long Signal: Triggered when MACD is above the signal line and both are rising.
Short Signal: Triggered when MACD is below the signal line and both are falling.
Custom Plotting
The MACD line, signal line, and histogram are plotted on the chart for easy visualization. The histogram changes colors to reflect positive or negative momentum:
Green shades when MACD is above the signal line.
Red shades when MACD is below the signal line.
Applications in Trading
The BRT MACD Custom is ideal for traders who need flexibility in their technical analysis. Its multi-timeframe capabilities and customizable moving averages make it suitable for day trading, swing trading, and long-term investing across a variety of markets.
Scalping: Use the 1-minute or 5-minute timeframe to identify short-term trends while calculating MACD on a higher timeframe such as 15 or 30 minutes.
Swing Trading: Apply the indicator on 1-hour or 4-hour charts to detect mid-term trends.
Long-Term Investing: Analyze daily or weekly charts with longer EMA periods to confirm market direction before making large investments.
Cubic Bezier Curve RSI [CBCR]Overview :
Introducing the Cubic Bézier Curve RSI – an innovative approach to smoothing the traditional RSI using cubic Bézier curves. This indicator provides traders with a smoother, adaptive version of the RSI that can help filter out noise and better highlight market trends.
Key Features:
Bézier Curve : the script uses cubic Bézier curves to create a smoothed version of the RSI, offering a more visually appealing and potentially more insightful representation of market momentum.
Customizable Settings: Users can adjust the Bézier Curve Length, Impact Factor, and color modes, allowing full customization of the smoothing effect and visualization.
Color-coded Trend Indicator: The smoothed RSI is displayed with colors that indicate potential bullish or bearish trends, helping traders quickly assess market conditions.
Overbought/Oversold Lines: Option to display overbought and oversold levels for better identification of market extremes.
Parameters:
RSI Length: Set the length for the traditional RSI calculation (default is 14).
Bézier Curve Length: Adjust the length of the Bézier curve used to smooth the RSI (default is 20).
Impact Factor: Control the influence of the Bézier smoothed values versus the original RSI values (default is 0.5, ranging from 0.0 to 1.0).
Overbought/Oversold Lines: Option to show overbought (default: 70) and oversold (default: 30) lines for easier identification of extreme conditions.
Color Mode: Choose between "Trend Following" and "Overbought/Oversold" modes for line color indication.
Display Settings: Color customization for bullish and bearish phases allows better visual differentiation.
How It Works:
The CBCR uses four control points derived from historical RSI values over a user-defined length. It then applies the cubic Bezier formula to generate a sequence of points representing a smoothed version of the RSI over this range.
The Bezier curve is recalculated each time a specific number of bars (as defined by the Bezier Curve Length) have passed, helping reduce noise while retaining key trend information.
The result is a smoothed RSI that combines the adaptability of cubic Bezier curves with the familiar oscillation of the RSI, making it potentially more robust for identifying shifts in market sentiment.
Visuals:
Smoothed RSI Line: Plotted on the indicator pane, the line changes color depending on the chosen color mode:
Trend Following Mode: Color changes based on whether the smoothed RSI is above or below the 50-level.
Overbought/Oversold Mode: Color changes based on whether the smoothed RSI is above the overbought level or below the oversold level.
Bullish Color: Configurable (default: cyan).
Bearish Color: Configurable (default: red).
Overbought/Oversold Lines: Horizontal lines at user-defined levels (default: 70 for overbought, 30 for oversold) for easy identification of market extremes.
Usage:
The CBCR can be used like a traditional RSI but with a smoother output that may help traders avoid false signals generated by sudden price spikes. For instance:
Look for crossovers around the 50 level as a signal for changing momentum.
Use the overbought and oversold levels to identify potential reversal zones.
Observe the color change of the line for an immediate visual cue on current sentiment.
Magnificent 7 Overall Percentage Change with MA and Angle LabelsMagnificent 7 Overall Percentage Change with MA and Angle Labels
Overview:
The "Magnificent 7 Overall Percentage Change with MA and Angle Labels" indicator tracks the percentage change of seven key tech stocks (Apple, Microsoft, Amazon, NVIDIA, Tesla, Meta, and Alphabet) and displays their overall average percentage change on the chart. It also provides a moving average of this overall change and calculates the angle of the moving average to help traders gauge the momentum and direction of the overall trend.
How it works:
Real-Time Percentage Change: The indicator calculates the percentage change of each of the "Magnificent 7" stocks compared to their previous day's closing price, giving a snapshot of the market's performance.
Overall Average: It then computes the average of the seven stocks' percentage changes to reflect the broader movement of these major tech companies.
Moving Average: The indicator offers a choice of four types of moving averages (SMA, EMA, WMA, or VWMA) to smooth the overall percentage change, allowing traders to focus on the trend rather than short-term fluctuations.
Slope and Angle Calculation: To provide additional insights, the indicator calculates the slope of the moving average and converts it into an angle (in degrees). This can help traders determine the strength of the trend—steeper angles often indicate stronger momentum.
Key Features:
Percentage Change of the "Magnificent 7":
Tracks the percentage change of Apple (AAPL), Microsoft (MSFT), Amazon (AMZN), NVIDIA (NVDA), Tesla (TSLA), Meta (META), and Alphabet (GOOGL) on the current chart's timeframe.
Overall Average Change:
Computes the average percentage change across all seven stocks, giving a combined view of how the most influential tech stocks are performing.
Customizable Moving Averages:
Offers four types of moving averages (SMA, EMA, WMA, VWMA) to provide flexibility in tracking the trend of the overall percentage change.
Angle Calculation:
Measures the angle of the moving average in degrees, which helps assess the strength of the market’s momentum. Alerts and visual cues can be triggered based on the angle's steepness.
Visual Cues:
The percentage change is plotted in green when positive and red when negative, with a background color that changes accordingly. A zero line is plotted for reference.
Use Case:
This indicator is ideal for traders and investors looking to track the collective performance of the most dominant tech companies in the market. It provides real-time insights into how the "Magnificent 7" stocks are moving together and offers clues about potential market momentum based on the direction and angle of their average percentage change.
Customization:
Moving Average Type and Length: Choose between different types of moving averages (SMA, EMA, WMA, VWMA) and adjust the length to suit your preferred timeframe.
Angle Threshold: Set an angle threshold to trigger alerts when the moving average slope becomes too steep, indicating strong momentum.
Alerts:
Alerts can be created based on the crossing of the moving average or when the angle of the moving average exceeds a specified threshold. This ensures traders are notified when the trend is accelerating or decelerating significantly.
Conclusion:
The "Magnificent 7 Overall Percentage Change with MA and Angle Labels" indicator is a powerful tool for those wanting to monitor the performance of the most influential tech stocks, analyze their overall trend, and receive timely alerts when market conditions shift.
Elliott Wave Oscillator with Peak DetectionThe Elliott Wave Oscillator with Derivative Peak Detection and Breakout Bands is a technical indicator that blends traditional Elliott Wave theory with modern derivative-based peak detection and breakout bands for a clearer view of market trends.
Key Components:
Elliott Wave Oscillator (EWO):
The core of the indicator is based on the difference between two simple moving averages (SMA): a short-term SMA (default length: 5) and a long-term SMA (default length: 35).
This difference is expressed either as an absolute value or a percentage of the current price, depending on the user’s input.
Smoothing:
The EWO is smoothed using an Exponential Moving Average (EMA) to filter out noise and provide a clearer trend direction.
The smoothing length is adaptive based on the current chart's timeframe (e.g., longer smoothing for daily charts).
Derivative Peak Detection:
The smoothed EWO is analyzed for peaks (positive) and troughs (negative) by calculating the derivative (rate of change) between consecutive values.
Peaks are detected when the derivative transitions from positive to negative, while troughs are identified when the derivative switches from negative to positive.
Tolerance levels are adjustable and vary by timeframe to avoid false signals.
Breakout Bands:
Upper and lower breakout bands are dynamically generated based on the smoothed EWO.
The bands help to filter significant peaks and troughs, only highlighting those that occur beyond the breakout levels.
Users can choose to display these bands and use them to filter out less significant peaks and troughs.
Visualization:
The original, unsmoothed EWO is plotted as a histogram, with positive values in green and negative values in red.
The smoothed EWO is plotted as a blue line, providing a clearer view of the underlying trend.
The breakout bands, if enabled, are plotted as white lines to visualize the upper and lower bounds of the oscillator's movement.
Positive peaks and negative troughs that meet the filtering criteria are marked with purple triangles (for peaks) and red triangles (for troughs) on the chart.
Customization Options:
Timeframe-based Smoothing and Tolerance: Different smoothing lengths and tolerance levels can be set for daily, hourly, and 5-minute charts.
Breakout Bands: Users can toggle the display of breakout bands and adjust their visual properties.
Peak Filtering: Peaks and troughs can be filtered based on whether they break out beyond the bands, or all peaks can be shown.
This indicator provides a unique blend of trend detection through the Elliott Wave Oscillator and derivative analysis to highlight significant market reversals while offering breakout bands as a filtering mechanism for false signals.
Adaptive Gaussian MA For Loop [BackQuant]Adaptive Gaussian MA For Loop
PLEASE Read the following carefully before applying this indicator to your trading system. Knowing the core logic behind the tools you're using allows you to integrate them into your strategy with confidence and precision.
Introducing BackQuant's Adaptive Gaussian Moving Average For Loop (AGMA FL) — a sophisticated trading indicator that merges the Gaussian Moving Average (GMA) with adaptive volatility to provide dynamic trend analysis. This unique indicator further enhances its effectiveness by utilizing a for-loop scoring mechanism to detect potential shifts in market direction. Let's dive into the components, the rationale behind them, and how this indicator can be practically applied to your trading strategies.
Understanding the Gaussian Moving Average (GMA)
The Gaussian Moving Average (GMA) is a smoothed moving average that applies Gaussian weighting to price data. Gaussian weighting gives more significance to data points near the center of the lookback window, making the GMA particularly effective at reducing noise while maintaining sensitivity to changes in price direction. In contrast to simpler moving averages like the SMA or EMA, GMA provides a more refined smoothing function, which can help traders follow the true trend in volatile markets.
In this script, the GMA is calculated over a defined Calculation Period (default 14), applying a Gaussian filter to smooth out market fluctuations and provide a clearer view of underlying trends.
Adaptive Volatility: A Dynamic Edge
The Adaptive feature in this indicator gives it the ability to adjust its sensitivity based on current market volatility. If the Adaptive option is enabled, the GMA uses a standard deviation-based volatility measure (with a default period of 20) to dynamically adjust the width of the Gaussian filter, allowing the GMA to react faster in volatile markets and more slowly in calm conditions. This dynamic nature ensures that the GMA stays relevant across different market environments.
When the Adaptive setting is disabled, the script defaults to a constant standard deviation value (default 1.0), providing a more stable but less responsive smoothing function.
Why Use Adaptive Gaussian Moving Average?
The Gaussian Moving Average already provides smoother results than standard moving averages, but by adding an adaptive component, the indicator becomes even more responsive to real-time price changes. In fast-moving or highly volatile markets, this adaptation allows traders to react quicker to emerging trends. Conversely, in quieter markets, it reduces over-sensitivity to minor fluctuations, thus lowering the risk of false signals.
For-Loop Scoring Mechanism
The heart of this indicator lies in its for-loop scoring system, which evaluates the smoothed price data (the GMA) over a specified range, comparing it to previous values. This scoring system assigns a numerical value based on whether the current GMA is higher or lower than previous values, creating a trend score.
Long Signals: These are generated when the for-loop score surpasses the Long Threshold (default set at 40), signaling that the GMA is gaining upward momentum, potentially identifying a favorable buying opportunity.
Short Signals: These are triggered when the score crosses below the Short Threshold (default set at -10), indicating that the market may be losing strength and that a selling or shorting opportunity could be emerging.
Thresholds & Customization Options
This indicator offers a high degree of flexibility, allowing you to fine-tune the settings according to your trading style and risk preferences:
Calculation Period: Adjust the lookback period for the Gaussian filter, affecting how smooth or responsive the indicator is to price changes.
Adaptive Mode: Toggle the adaptive feature on or off, allowing the GMA to dynamically adjust based on market volatility or remain consistent with a fixed standard deviation.
Volatility Settings: Control the standard deviation period for adaptive mode, fine-tuning how quickly the GMA responds to shifts in volatility.
For-Loop Settings: Modify the start and end points for the for-loop score calculation, adjusting the depth of analysis for trend signals.
Thresholds for Signals: Set custom long and short thresholds to determine when buy or sell signals should be generated.
Visualization Options: Choose to color bars based on trend direction, plot signal lines, or adjust the background color to reflect current market sentiment visually.
Trading Applications
The Adaptive Gaussian MA For Loop can be applied to a variety of trading styles and markets. Here are some key ways you can use this indicator in practice:
Trend Following: The combination of Gaussian smoothing and adaptive volatility helps traders stay on top of market trends, identifying significant momentum shifts while filtering out noise. The for-loop scoring system enhances this by providing a numerical representation of trend strength, making it easier to spot when a new trend is emerging or when an existing one is gaining strength.
Mean Reversion: For traders looking to capitalize on short-term market corrections, the adaptive nature of this indicator makes it easier to identify when price action is deviating too far from its smoothed trend, allowing for strategic entries and exits based on overbought or oversold conditions.
Swing Trading: With its ability to capture medium-term price movements while avoiding the noise of short-term fluctuations, this indicator is well-suited for swing traders who aim to profit from market reversals or short-to-mid-term trends.
Volatility Management: The adaptive feature allows the indicator to adjust dynamically in volatile markets, ensuring that it remains responsive in times of increased uncertainty while avoiding unnecessary noise in calmer periods. This makes it an effective tool for traders who want to manage risk by staying in tune with changing market conditions.
Final Thoughts
The Adaptive Gaussian MA For Loop is a powerful and flexible indicator that merges the elegance of Gaussian smoothing with the adaptability of volatility-based adjustments. By incorporating a for-loop scoring mechanism, this indicator provides traders with a comprehensive view of market trends and potential trade opportunities.
It’s important to test the settings on historical data and adapt them to your specific trading style, timeframe, and market conditions. As with any technical tool, the AGMA For Loop should be used in conjunction with other indicators and solid risk management practices for the best results.
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
Two Pole Butterworth For Loop [BackQuant]Two Pole Butterworth For Loop
PLEASE read the following carefully, as understanding the underlying concepts and logic behind the indicator is key to incorporating it into your trading system in a sound and methodical manner.
Introducing BackQuant's Two Pole Butterworth For Loop (2P BW FL) — an advanced indicator that fuses the power of the Two Pole Butterworth filter with a dynamic for-loop scoring mechanism. This unique approach is designed to extract actionable trading signals by smoothing out price data and then analyzing it using a comparative scoring method. Let's delve into how this indicator works, why it was created, and how it can be used in various trading scenarios.
Understanding the Two Pole Butterworth Filter
The Butterworth filter is a signal processing tool known for its smooth response and minimal distortion. It's often used in electronic and communication systems to filter out unwanted noise. In trading, the Butterworth filter can be applied to price data to smooth out the volatility, providing traders with a clearer view of underlying trends without the whipsaws often associated with market noise.
The Two Pole Butterworth variant further enhances this effect by applying the filter with two poles, effectively creating a sharper transition between the passband and stopband. In simple terms, this allows the filter to follow the price action more closely, reacting to changes while maintaining smoothness.
In this script, the Two Pole Butterworth filter is applied to the Calculation Source (default is set to the closing price), creating a smoothed price series that serves as the foundation for further analysis.
Why Use a Two Pole Butterworth Filter?
The Two Pole Butterworth filter is chosen for its ability to reduce lag while maintaining a smooth output. This makes it an ideal choice for traders who want to capture trends without being misled by short-term volatility or market noise. By filtering the price data, the Two Pole Butterworth enables traders to focus on the broader market movements and avoid false signals.
The For-Loop Scoring Mechanism
In addition to the Butterworth filter, this script uses a for-loop scoring system to evaluate the smoothed price data. The for-loop compares the current value of the filtered price (referred to as "subject") to previous values over a defined range (set by the start and end input). The score is calculated based on whether the subject is higher or lower than the previous points, and the cumulative score is used to determine the strength of the trend.
Long and Short Signal Logic
Long Signals: A long signal is triggered when the score surpasses the Long Threshold (default set at 40). This suggests that the price has built sufficient upward momentum, indicating a potential buying opportunity.
Short Signals: A short signal is triggered when the score crosses under the Short Threshold (default set at -10). This indicates weakening price action or a potential downtrend, signaling a possible selling or shorting opportunity.
By utilizing this scoring system, the indicator identifies moments when the price momentum is shifting, helping traders enter positions at opportune times.
Customization and Visualization Options
One of the strengths of this indicator is its flexibility. Traders can customize various settings to fit their personal trading style or adapt it to different markets and timeframes:
Calculation Periods: Adjust the lookback period for the Butterworth filter, allowing for shorter or longer smoothing depending on the desired sensitivity.
Threshold Levels: Set the long and short thresholds to define when signals should be triggered, giving you control over the balance between sensitivity and specificity.
Signal Line Width and Colors: Customize the visual presentation of the indicator on the chart, including the width of the signal line and the colors used for long and short conditions.
Candlestick and Background Colors: If desired, the indicator can color the candlesticks or the background according to the detected trend, offering additional clarity at a glance.
Trading Applications
This Two Pole Butterworth For Loop indicator is versatile and can be adapted to various market conditions and trading strategies. Here are a few use cases where this indicator shines:
Trend Following: The Butterworth filter smooths the price data, making it easier to follow trends and identify when they are gaining or losing strength. The for-loop scoring system enhances this by providing a clear indication of how strong the current trend is compared to recent history.
Mean Reversion: For traders looking to identify potential reversals, the indicator’s ability to compare the filtered price to previous values over a range of periods allows it to spot moments when the trend may be losing steam, potentially signaling a reversal.
Swing Trading: The combination of smoothing and scoring allows swing traders to capture short to medium-term price movements by filtering out the noise and focusing on significant shifts in momentum.
Risk Management: By providing clear long and short signals, this indicator helps traders manage their risk by offering well-defined entry and exit points. The smooth nature of the Butterworth filter also reduces the risk of getting caught in false signals due to market noise.
Final Thoughts
The Two Pole Butterworth For Loop indicator offers traders a powerful combination of smoothing and scoring to detect meaningful trends and shifts in price momentum. Whether you are a trend follower, swing trader, or someone looking to refine your entry and exit points, this indicator provides the tools to make more informed trading decisions.
As always, it's essential to backtest the indicator on historical data and tailor the settings to your specific trading style and market. While the Butterworth filter helps reduce noise and smooth trends, no indicator can predict the future with absolute certainty, so it should be used in conjunction with other tools and sound risk management practices.
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
Adaptive SuperTrend Oscillator [AlgoAlpha]Adaptive SuperTrend Oscillator 🤖📈
Introducing the Adaptive SuperTrend Oscillator , an innovative blend of volatility clustering and SuperTrend logic designed to identify market trends with precision! 🚀 This indicator uses K-Means clustering to dynamically adjust volatility levels, helping traders spot bullish and bearish trends. The oscillator smoothly tracks price movements, adapting to market conditions for reliable signals. Whether you're scalping or riding long-term trends, this tool has got you covered! 💹✨
🔑 Key Features:
📊 Volatility Clustering with K-Means: Segments volatility into three levels (high, medium, low) using a K-Means algorithm for precise trend detection.
📈 Normalized Oscillator : Allows for customizable smoothing and normalization, ensuring the oscillator remains within a fixed range for easy interpretation.
🔄 Heiken Ashi Candles : Optionally visualize smoothed trends with Heiken Ashi-style candlesticks to better capture market momentum.
🔔 Alert System : Get notified when key conditions like trend shifts or volatility changes occur.
🎨 Customizable Appearance : Fully customizable colors for bullish/bearish signals, along with adjustable smoothing methods and lengths.
📚 How to Use:
⭐ Add the indicator to favorites by pressing the star icon. Customize settings to your preference:
👀 Watch the chart for trend signals and reversals. The oscillator will change color when trends shift, offering visual confirmation.
🔔 Enable alerts to be notified of critical trend changes or volatility conditions
⚙️ How It Works:
This script integrates SuperTrend with volatility clustering by analyzing ATR (Average True Range) to dynamically identify high, medium, and low volatility clusters using a K-Means algorithm . The SuperTrend logic adjusts based on the assigned volatility level, creating adaptive trend signals. These signals are then smoothed and optionally normalized for clearer visual interpretation. The Heiken Ashi transformation adds an additional layer of smoothing, helping traders better identify the market's true momentum. Alerts are set to notify users of key trend shifts and volatility changes, allowing traders to react promptly.
ATR with Donchian Channels and SMAsThis script combines the Average True Range (ATR), Donchian Channels, and Simple Moving Averages (SMAs) to provide a comprehensive tool for volatility and trend analysis.
Key Components:
ATR Calculation: The ATR is used to measure market volatility. It is calculated as a moving average of the true range over a specified length, which you can customize using different smoothing methods: RMA, SMA, EMA, or WMA. ATR helps identify periods of high and low volatility, giving insights into potential breakout or consolidation phases in the market.
Donchian Channels on ATR: The Donchian Channels are calculated based on the highest and lowest values of the ATR over a user-defined period. The upper and lower bands provide a volatility range, and the middle line represents the average of the two. This can help visualize the range of market volatility and detect possible trend reversals or continuations.
SMAs on ATR: Two Simple Moving Averages (SMA) are applied to the ATR values. These SMAs act as a smoothed version of the ATR, providing additional insight into volatility trends. By adjusting the length of these SMAs, you can track short-term and long-term volatility movements, helping in decision-making for potential entries and exits.
Inputs:
ATR Length: Set the length for calculating the ATR.
Smoothing Method: Choose from RMA, SMA, EMA, or WMA for smoothing the ATR calculation.
Donchian Channel Length: Set the length for calculating the highest and lowest ATR values for Donchian Channels.
SMA Lengths: Two adjustable lengths for applying SMAs to the ATR.
Visualization:
ATR Plot: The ATR is plotted in red, allowing you to see the market's volatility at a glance.
Donchian Channels: Blue lines represent the upper and lower bands, while the green line represents the middle line of the Donchian Channels, helping you visualize the volatility range.
SMAs: Two SMAs (green and orange) are plotted to smooth out the ATR and identify trends in volatility.
Use Cases:
Breakout Detection: High ATR values breaking out of the Donchian Channels may signal increased volatility and a potential breakout.
Trend Analysis: SMAs on ATR help smooth volatility trends, aiding in determining if the market is entering a more volatile or stable period.
Stop-Loss Placement: ATR and Donchian Channels can be used to set dynamic stop-loss levels based on market volatility.
This script is versatile and can be used across different asset classes, such as stocks, forex, crypto, and commodities. It is especially useful for traders who want to incorporate volatility into their trading strategies for better risk management and trend detection.
RSI 30-50-70 moving averageDescription:
The RSI 30-50-70 Moving Average indicator plots three distinct moving averages based on different RSI ranges (30%, 50%, and 70%). Each moving average corresponds to different market conditions and provides potential entry and exit signals. Here's how it works:
• RSI_30 Range (25%-35%): The moving average of closing prices when the RSI is between 25% and 35%, representing potential oversold conditions.
• RSI_50 Range (45%-55%): The moving average of closing prices when the RSI is between 45% and 55%, providing a balanced perspective for trend-following strategies.
• RSI_70 Range (65%-75%): The moving average of closing prices when the RSI is between 65% and 75%, representing potential overbought conditions.
This indicator offers flexibility, as users can adjust key parameters such as RSI ranges, periods, and time frames to fine-tune the signals for their trading strategies.
How it Works:
Like traditional moving averages, the RSI 30-50-70 Moving Averages can highlight dynamic levels of support and resistance. They offer additional insight by focusing on specific RSI ranges, providing early signals for trend reversals or continuation. The default settings can be used across various assets but should be optimized via backtesting.
Default Settings:
• RSI_30: 25% to 35% (Oversold Zone, yellow line)
• RSI_50: 45% to 55% (Neutral/Trend Zone, green line)
• RSI_70: 65% to 75% (Overbought Zone, red line)
• RSI Period: 14
Buy Conditions:
• Use the 5- or 15-minute time frame.
• Wait for the price to move below the RSI_30 line, indicating potential oversold conditions.
• Enter a buy order when the price closes above the RSI_30 line, signaling a recovery from the oversold zone.
• For a more conservative approach, use the RSI_50 line as the buy signal to confirm a trend reversal.
• Important: Before entering, ensure that the RSI_30 moving average has flattened or started to level off, signaling that the oversold momentum has slowed.
Sell Conditions:
• Use the 5- or 15-minute time frame.
• Wait for the price to close above the RSI_70 line, indicating potential overbought conditions.
• Enter a sell order when the price closes below the RSI_70 line, signaling a decline from the overbought zone.
• Important: Similar to buying, wait for the RSI_70 moving average to flatten or level off before selling, indicating the overbought conditions are stalling.
Key Features:
1. Dynamic Range Customization: The indicator allows users to modify the RSI ranges and periods, tailoring the moving averages to fit different market conditions or asset classes.
2. Trend-Following and Reversal Signals: The RSI 30-50-70 moving averages provide both reversal and trend-following signals, making it a versatile tool for short-term traders.
3. Visual Representation of Market Strength: By plotting moving averages based on RSI levels, traders can visually interpret the market’s strength and potential turning points.
4. Risk Management: The built-in flexibility allows traders to choose lower-risk entries by adjusting which RSI level (e.g., RSI_30 vs. RSI_50) they rely on for signals.
Practical Use:
Different assets respond uniquely to RSI-based moving averages, so it's recommended to backtest and adjust ranges for specific instruments. For example, volatile assets may require wider RSI ranges, while more stable assets could benefit from tighter ranges.
Checking for Buy conditions:
1st: Wait for current price to go below the RSI_30 (yellow line)
2nd: Wait and observe for bullish divergence
3rd: RSI_30 has flattened indicating potential gain of momentum after a bullish divergence.
4th: Enter a buy order when the price closed above the RSI_30, preferably when a green candle appeared.
Commitment of Trader %R StrategyThis Pine Script strategy utilizes the Commitment of Traders (COT) data to inform trading decisions based on the Williams %R indicator. The script operates in TradingView and includes various functionalities that allow users to customize their trading parameters.
Here’s a breakdown of its key components:
COT Data Import:
The script imports the COT library from TradingView to access historical COT data related to different trader groups (commercial hedgers, large traders, and small traders).
User Inputs:
COT data selection mode (e.g., Auto, Root, Base currency).
Whether to include futures, options, or both.
The trader group to analyze.
The lookback period for calculating the Williams %R.
Upper and lower thresholds for triggering trades.
An option to enable or disable a Simple Moving Average (SMA) filter.
Williams %R Calculation: The script calculates the Williams %R value, which is a momentum indicator that measures overbought or oversold levels based on the highest and lowest prices over a specified period.
SMA Filter: An optional SMA filter allows users to limit trades to conditions where the price is above or below the SMA, depending on the configuration.
Trade Logic: The strategy enters long positions when the Williams %R value exceeds the upper threshold and exits when the value falls below it. Conversely, it enters short positions when the Williams %R value is below the lower threshold and exits when the value rises above it.
Visual Elements: The script visually indicates the Williams %R values and thresholds on the chart, with the option to plot the SMA if enabled.
Commitment of Traders (COT) Data
The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides a breakdown of open interest positions held by different types of traders in the U.S. futures markets. It is widely used by traders and analysts to gauge market sentiment and potential price movements.
Data Collection: The COT data is collected from futures commission merchants and is published every Friday, reflecting positions as of the previous Tuesday. The report categorizes traders into three main groups:
Commercial Traders: These are typically hedgers (like producers and processors) who use futures to mitigate risk.
Non-Commercial Traders: Often referred to as speculators, these traders do not have a commercial interest in the underlying commodity but seek to profit from price changes.
Non-reportable Positions: Small traders who do not meet the reporting threshold set by the CFTC.
Interpretation:
Market Sentiment: By analyzing the positions of different trader groups, market participants can gauge sentiment. For instance, if commercial traders are heavily short, it may suggest they expect prices to decline.
Extreme Positions: Some traders look for extreme positions among non-commercial traders as potential reversal signals. For example, if speculators are overwhelmingly long, it might indicate an overbought condition.
Statistical Insights: COT data is often used in conjunction with technical analysis to inform trading decisions. Studies have shown that analyzing COT data can provide valuable insights into future price movements (Lund, 2018; Hurst et al., 2017).
Scientific References
Lund, J. (2018). Understanding the COT Report: An Analysis of Speculative Trading Strategies.
Journal of Derivatives and Hedge Funds, 24(1), 41-52. DOI:10.1057/s41260-018-00107-3
Hurst, B., O'Neill, R., & Roulston, M. (2017). The Impact of COT Reports on Futures Market Prices: An Empirical Analysis. Journal of Futures Markets, 37(8), 763-785.
DOI:10.1002/fut.21849
Commodity Futures Trading Commission (CFTC). (2024). Commitment of Traders. Retrieved from CFTC Official Website.
Momentum-Based Buy/Sell SignalsBuy Signal:
Triggered when ROC > threshold and the MACD line crosses above the Signal line.
Sell Signal:
Triggered when ROC < threshold and the MACD line crosses below the Signal line.
Visual Elements:
Green labels with "Buy" are displayed below the bars for buy signals.
Red labels with "Sell" are displayed above the bars for sell signals.
The background turns green during a buy signal and red during a sell signal for better visual clarity.
Open-Close Absolute Difference with Threshold CountsThe Open-Close Absolute Difference with Threshold Counts indicator is a versatile tool designed to help traders analyze the volatility and price movements within any given timeframe on their charts. This indicator calculates the absolute difference between the open and close prices for each bar, providing a clear visualization through a color-coded histogram.
Key features include:
• Timeframe Flexibility: Utilizes the current chart’s timeframe, whether it’s a 5-minute, hourly, or daily chart.
• Custom Thresholds: Allows you to set up to four custom threshold levels (Thresholds A, B, C, and D) with default values of 10, 15, 25, and 35, respectively.
• Period Customization: Enables you to define the number of bars (N) over which the indicator calculates the counts, with a default of 100 bars.
• Visual Threshold Lines: Plots horizontal dashed lines on the histogram representing each threshold for easy visual reference.
• Dynamic Counting: Counts and displays the number of times the absolute difference is less than or greater than each threshold within the specified period.
• Customizable Table Position: Offers the flexibility to position the results table anywhere on the chart (e.g., Top Right, Bottom Left).
How It Works:
1. Absolute Difference Calculation:
• For each bar on the chart, the indicator calculates the absolute difference between the open and close prices.
• This difference is plotted as a histogram:
• Green Bars: Close price is higher than the open price.
• Red Bars: Close price is lower than the open price.
2. Threshold Comparison and Counting:
• Compares the absolute difference to each of the four thresholds.
• Determines whether the difference is less than or greater than each threshold.
• Utilizes the ta.sum() function to count occurrences over the specified number of bars (N).
3. Results Table:
• Displays a table with three columns:
• Left Column: Counts where the absolute difference is less than the threshold.
• Middle Column: The threshold value.
• Right Column: Counts where the absolute difference is greater than the threshold.
• The table updates dynamically and can be positioned anywhere on the chart according to your preference.
4. Threshold Lines on Histogram:
• Plots horizontal dashed lines at each threshold level.
• Each line is color-coded for distinction:
• Threshold A: Yellow
• Threshold B: Orange
• Threshold C: Purple
• Threshold D: Blue
How to Use:
1. Add the Indicator to Your Chart:
• Open the Pine Editor on TradingView.
• Copy and paste the provided code into the editor.
• Click “Add to Chart.”
2. Configure Settings:
• Number of Bars (N):
• Set the period over which you want to calculate the counts (default is 100).
• Thresholds A, B, C, D:
• Input your desired threshold values (defaults are 10, 15, 25, 35).
• Table Position:
• Choose where you want the results table to appear on the chart:
• Options include “Top Left,” “Top Center,” “Top Right,” “Bottom Left,” “Bottom Center,” “Bottom Right.”
3. Interpret the Histogram:
• Observe the absolute differences plotted as a histogram.
• Use the color-coded bars to quickly assess whether the close price was higher or lower than the open price.
4. Analyze the Counts Table:
• Review the counts of occurrences where the absolute difference was less than or greater than each threshold.
• Use this data to gauge volatility and price movement intensity over the specified period.
5. Visual Reference with Threshold Lines:
• Refer to the horizontal dashed lines on the histogram to see how the absolute differences align with your thresholds.
Example Use Case:
Suppose you’re analyzing a 5-minute chart for a particular stock and want to understand its short-term volatility:
• Set the Number of Bars (N) to 50 to analyze the recent 50 bars.
• Adjust Thresholds based on the typical price movements of the stock, e.g., Threshold A: 0.5, Threshold B: 1.0, Threshold C: 1.5, Threshold D: 2.0.
• Position the Table at the “Top Right” for easy viewing.
By doing so, you can:
• Quickly see how often the stock experiences significant price movements within 5-minute intervals.
• Make informed decisions about entry and exit points based on the volatility patterns.
• Customize the thresholds and periods as market conditions change.
Benefits:
• Customizable Analysis: Tailor the indicator to fit various trading styles and timeframes.
• Quick Visualization: Instantly assess market volatility and price movement direction.
• Enhanced Decision-Making: Use the counts and visual cues to make more informed trading decisions.
• User-Friendly Interface: Simple configuration and clear display of information.
Note: Always test the indicator with different settings to find the configuration that best suits your trading strategy. This indicator should be used as part of a comprehensive analysis and not as the sole basis for trading decisions.
Volume-Weighted Trend Strength indexVolume-Weighted Trend Strength index (VWTSI)
Introduction
The VWTSI is a custom indicator designed to combine trend strength, volume, and volatility to give traders a comprehensive view of market dynamics. It provides flexibility by allowing you to visualize the indicator as either an oscillator or a moving average.
Features
Dual Visualization: Can be displayed either as an oscillator or as a moving average on the chart.
Volume-Weighted: Adjusts trend strength based on current volume compared to its average.
Volatility-Adjusted: Incorporates market volatility into the trend strength calculation.
Customizable: Various parameters can be fine-tuned to suit different trading environments.
How It Works
1. Trend Strength Calculation
The difference between the fast (10-period) and slow (30-period) EMAs is used to calculate trend strength, which gives a percentage-based indication of the trend's strength
2. Volatility Adjustment
The ATR-based volatility is calculated and used to amplify or reduce the trend strength based on the current market conditions
3. Volume Adjustment
The ratio of current volume to the volume SMA adds another layer of adjustment to the final VWTSI value
4. Final VWTSI Calculation
The VWTSI value is the product of trend strength, volatility factor, and volume ratio
5. Normalization
The final VWTSI is normalized to fit within a range of -100 to 100 for better visualization in oscillator mode
Customization Inputs
Fast EMA Length: Default is 10.
Slow EMA Length: Default is 30.
Volume Length: Default is 14.
Volatility Length (ATR): Default is 20.
Oscillator or MA Mode: Toggle between displaying the indicator as an oscillator or moving average.
Distance From moving averageDistance From Moving Average is designed to help traders visualize the deviation of the current price from a specified moving average. Users can select from four different types of moving averages: Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), and Hull Moving Average (HMA).
Key Features:
User-Friendly Input Options:
Choose the type of moving average from a dropdown menu.
Set the length of the moving average, with a default value of 200.
Custom Moving Average Calculations:
The script computes the selected moving average using the appropriate mathematical formula, allowing for versatile analysis based on individual trading strategies.
Distance Calculation:
The indicator calculates the distance between the current price and the chosen moving average, providing insight into market momentum. A positive value indicates that the price is above the moving average, while a negative value shows it is below.
Visual Representation:
The distance is plotted on the chart, with color coding:
Lime: Indicates that the price is above the moving average (bullish sentiment).
Red: Indicates that the price is below the moving average (bearish sentiment).
Customization:
Users can further customize the appearance of the plotted line, enhancing clarity and visibility on the chart.
This indicator is particularly useful for traders looking to gauge market conditions and make informed decisions based on the relationship between current prices and key moving averages.
Pi Cycle Top & Bottom Indicator [InvestorUnknown]The Pi Cycle Top & Bottom Indicator is designed for long-term cycle analysis, particularly useful for detecting significant market tops and bottoms in assets like Bitcoin. By comparing the behavior of two moving averages, one with a shorter period (default 111) and the other with a longer period (default 350), the indicator helps investors identify potential turning points in the market.
Key Features:
Dual Moving Average System:
The indicator uses two moving averages (MA) to create a cyclic oscillator. The shorter moving average (Short Length MA) is more reactive to recent price changes, while the longer moving average (Long Length MA) smooths out long-term trends. Users can select between:
Simple Moving Average (SMA): A straightforward average of closing prices.
Exponential Moving Average (EMA): Places more weight on recent prices, making it more responsive to market changes.
Oscillator Mode Options:
The Pi Cycle Indicator offers two modes of oscillation to better suit different analysis styles:
RAW Mode: This mode calculates the raw ratio of the Short MA to the Long MA, offering a simple comparison of the two averages.
LOG(X) Mode: In this mode, the oscillator takes the natural logarithm of the Short MA to Long MA ratio. This transformation compresses extreme values and highlights relative changes more effectively, making it particularly useful for spotting shifts in long-term trends.
Cyclical Analysis:
The core of the Pi Cycle Indicator is its ability to visualize the relationship between the two moving averages. The ratio of the Short MA to the Long MA is plotted as an oscillator. When the oscillator crosses above or below a baseline (which is 1 for RAW mode and 0 for LOG(X) mode), it signals potential market turning points.
Visual Representation:
The indicator provides a clear visual display of market conditions:
Orange Line: Represents the Pi Cycle Oscillator, which shows the relationship between the short and long moving averages.
Gray Baseline: A reference line that dynamically adjusts based on the oscillator mode. Crosses above or below this line help indicate possible trend reversals.
Shaded Areas: Color-filled areas between the oscillator and the baseline, which are shaded green when the market is bullish (oscillator above baseline) and red when bearish (oscillator below baseline). This provides a visual cue to assist in identifying potential market tops and bottoms.
Use Cases:
The Pi Cycle Top & Bottom Indicator is primarily used in long-term market analysis, such as Bitcoin cycles, to identify significant tops and bottoms. These moments often coincide with large cyclical shifts, making it valuable for those aiming to enter or exit positions at key moments in the market cycle.
By analyzing the interaction between short-term and long-term trends, investors can gain insight into broader market dynamics and make more informed decisions regarding entry and exit points. The ability to switch between moving average types (SMA/EMA) and oscillator modes (RAW/LOG) adds flexibility for adapting to different market environments.
