BTC Trend Momentum (BTM) with VWMOBTC Trend Momentum (BTM) with VWMO – A Smarter Way to Trade Bitcoin 🚀
Overview
Bitcoin price movements can be volatile, often leading to fake breakouts and whipsaws that mislead traders. BTC Trend Momentum (BTM), combined with Volume Weighted Moving Average (VWMO), helps smooth out market noise and provide clearer trend signals.
This script integrates momentum analysis, trend strength detection, and zero-line crossovers, allowing traders to make smarter entries and exits while avoiding false signals.
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Why Use This Indicator?
✅ Momentum Histogram – Easily visualize trend strength with color-coded bars.
✅ Volume-Weighted Analysis – Uses VWMO to filter out weak price movements.
✅ Zero Line Crossover Alerts – Identifies major trend shifts in real-time.
✅ Dynamic Color Coding – Stronger trends highlighted in brighter colors.
✅ Background Shading – Differentiates bullish & bearish zones for easy trend reading.
✅ Built-in Alerts – Get notified of trade opportunities instantly.
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How to Trade Using BTC Trend Momentum (BTM)
🔹 Buy Signal: When the momentum histogram (green bars) crosses above the EMA (orange line).
🔹 Sell Signal: When the momentum histogram (red bars) crosses below the EMA.
🔹 Strong Trend Confirmation: If histogram bars turn lime (bullish) or maroon (bearish), it indicates strong momentum.
🔹 Zero Line Crossovers: A bullish crossover above zero confirms an uptrend, while a bearish crossover below zero confirms a downtrend.
For better results, combine with RSI, MACD, or VWAP to confirm trend strength before entering trades.
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Best Timeframes for Trading
📌 1H & 4H – Ideal for swing trading Bitcoin.
📌 5M & 15M – Perfect for scalping BTC with precision.
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💡 Would you integrate BTC Trend Momentum (BTM) into your trading strategy? Let us know your thoughts below!
Cari dalam skrip untuk "momentum"
Volatility Momentum Breakout StrategyDescription:
Overview:
The Volatility Momentum Breakout Strategy is designed to capture significant price moves by combining a volatility breakout approach with trend and momentum filters. This strategy dynamically calculates breakout levels based on market volatility and uses these levels along with trend and momentum conditions to identify trade opportunities.
How It Works:
1. Volatility Breakout:
• Methodology:
The strategy computes the highest high and lowest low over a defined lookback period (excluding the current bar to avoid look-ahead bias). A multiple of the Average True Range (ATR) is then added to (or subtracted from) these levels to form dynamic breakout thresholds.
• Purpose:
This method helps capture significant price movements (breakouts) while ensuring that only past data is used, thereby maintaining realistic signal generation.
2. Trend Filtering:
• Methodology:
A short-term Exponential Moving Average (EMA) is applied to determine the prevailing trend.
• Purpose:
Long trades are considered only when the current price is above the EMA, indicating an uptrend, while short trades are taken only when the price is below the EMA, indicating a downtrend.
3. Momentum Confirmation:
• Methodology:
The Relative Strength Index (RSI) is used to gauge market momentum.
• Purpose:
For long entries, the RSI must be above a mid-level (e.g., above 50) to confirm upward momentum, and for short entries, it must be below a similar threshold. This helps filter out signals during overextended conditions.
Entry Conditions:
• Long Entry:
A long position is triggered when the current closing price exceeds the calculated long breakout level, the price is above the short-term EMA, and the RSI confirms momentum (e.g., above 50).
• Short Entry:
A short position is triggered when the closing price falls below the calculated short breakout level, the price is below the EMA, and the RSI confirms momentum (e.g., below 50).
Risk Management:
• Position Sizing:
Trades are sized to risk a fixed percentage of account equity (set here to 5% per trade in the code, with each trade’s stop loss defined so that risk is limited to approximately 2% of the entry price).
• Stop Loss & Take Profit:
A stop loss is placed a fixed ATR multiple away from the entry price, and a take profit target is set to achieve a 1:2 risk-reward ratio.
• Realistic Backtesting:
The strategy is backtested using an initial capital of $10,000, with a commission of 0.1% per trade and slippage of 1 tick per bar—parameters chosen to reflect conditions faced by the average trader.
Important Disclaimers:
• No Look-Ahead Bias:
All breakout levels are calculated using only past data (excluding the current bar) to ensure that the strategy does not “peek” into future data.
• Educational Purpose:
This strategy is experimental and provided solely for educational purposes. Past performance is not indicative of future results.
• User Responsibility:
Traders should thoroughly backtest and paper trade the strategy under various market conditions and adjust parameters to fit their own risk tolerance and trading style before live deployment.
Conclusion:
By integrating volatility-based breakout signals with trend and momentum filters, the Volatility Momentum Breakout Strategy offers a unique method to capture significant price moves in a disciplined manner. This publication provides a transparent explanation of the strategy’s components and realistic backtesting parameters, making it a useful tool for educational purposes and further customization by the TradingView community.
BTC-SPX Momentum Gauge + EMA SignalHere's an explanation of the market dynamics and signal benefits of this script:
Momentum and Sentiment Indicator:
The script uses the momentum of the S&P 500 to change the chart's background color, providing a quick visual cue of market sentiment. Green indicates potential bullish momentum in the broader market, while red suggests bearish momentum. This can help traders gauge overall market direction at a glance.
Bitcoin Trend Analysis:
By plotting the scaled TEMA of Bitcoin (BTC), traders can see how Bitcoin's trend correlates or diverges from the current asset being analyzed. Since Bitcoin is often viewed as a hedge against traditional financial systems or inflation, its trend can signal broader economic shifts or investor sentiment towards alternative investments.
Dual Trend Confirmation:
The script offers two trend lines: one for Bitcoin and one for the current ticker. When these lines move in tandem, it might indicate a strong market trend across both traditional and crypto markets. Divergence between these lines can highlight potential market anomalies or opportunities for arbitrage or hedging.
Smoothness vs. Reactivity:
The use of TEMA for Bitcoin provides a smoother signal than a simple moving average, reducing lag while still reacting to price changes. This can be particularly useful for identifying longer-term trends in Bitcoin's volatile market. The 20-period EMA for the current ticker, on the other hand, gives a quicker response to price changes in the asset you're directly trading.
Cross-Asset Correlation:
By overlaying Bitcoin's trend on another asset's chart, traders can analyze how these markets might influence each other. For instance, if Bitcoin is in an uptrend while a traditional asset is declining, it might suggest capital rotation into cryptocurrencies.
Trading Signals:
Crossovers or divergences between the TEMA of Bitcoin and the EMA of the current ticker could be used as signals for entry or exit points. For example, if the BTC TEMA crosses above the current ticker's EMA, it might suggest a shift towards crypto assets.
Risk Management:
The visual cues from the background color and moving averages can aid in risk management. For example, trading in the direction of the momentum indicated by the background color might be seen as going with the market flow, potentially reducing risk.
Macro-Economic Insights:
The relationship between Bitcoin and traditional markets can offer insights into macroeconomic conditions, particularly related to inflation, monetary policy, and investor sentiment towards fiat currencies.
Headwind and tailwind:
Currently BTC correlated trade instruments experience headwind or tailwind from the broader market. This indicator lets the user see it to help their trade decision process.
Additional Statement:
As the market realizes the dangers of the fiat that its construct is built upon and evolves and migrates into stable money, incorruptible by inflation, this indicator will reveal the external influence of that corruptible and the internal influence of the incorruptible; having diminishing returns as the rise of stable money overtakes the treasuries of the fiat construct.
Adaptive Momentum Cycle Oscillator (AMCO)1. Concept and Foundation
The Adaptive Momentum Cycle Oscillator (AMCO) is an advanced indicator designed to dynamically adjust to varying market conditions while identifying price cycles and trends. It combines momentum and volatility into a single, oscillating signal that helps traders detect turning points in price movements. By incorporating adaptive periods and trend filtering, AMCO ensures relevance across different asset classes and timeframes. This innovation bridges the gap between traditional oscillators and trending indicators, providing a comprehensive tool for both cycle identification and trend confirmation.
2. Dynamic Adaptation to Market Conditions
A standout feature of AMCO is its ability to adapt its sensitivity based on market volatility. Using the ATR (Average True Range) as a measure of current volatility, AMCO adjusts its calculation periods dynamically. During periods of high volatility, it extends its lookback periods to smooth out noise and avoid false signals. Conversely, in low-volatility environments, it shortens its periods to remain responsive to smaller price fluctuations. This adaptability ensures that AMCO remains effective and reliable in both trending and ranging markets.
3. Trend Awareness and Directional Weighting
AMCO integrates a trend filter based on a long-term moving average, such as SMA(200), to align its signals with the broader market direction. This filter ensures that buy signals are prioritized during uptrends and sell signals during downtrends, reducing counter-trend trades. Additionally, a directional weighting mechanism amplifies momentum signals that align with the prevailing trend. This dual-layer approach significantly enhances the accuracy of signals, making AMCO especially useful in markets with clear directional bias.
4. Normalized Visualization for Clarity
The AMCO includes a normalized histogram that provides a clear visual representation of momentum strength relative to recent volatility. By dividing the raw AMCO value by the ATR, the histogram ensures consistency across assets with varying price ranges and volatility levels. Positive bars indicate bullish momentum, while negative bars signify bearish momentum. This intuitive visualization makes it easier for traders to interpret market dynamics and act on actionable signals, regardless of asset type or timeframe.
5. Practical and Actionable Signals
AMCO generates practical signals based on zero-line crossovers, allowing traders to easily identify shifts between bullish and bearish cycles. Positive values above the zero line suggest upward momentum, signaling potential buying opportunities, while negative values below the zero line indicate downward momentum, signaling potential sell opportunities. By combining adaptive behavior, trend filtering, and momentum-strength normalization, AMCO offers traders a robust framework for navigating complex markets with confidence. Its versatility makes it suitable for scalping, swing trading, and even longer-term investing.
LRI Momentum Cycles [AlgoAlpha]Discover the LRI Momentum Cycles indicator by AlgoAlpha, a cutting-edge tool designed to identify market momentum shifts using trend normalization and linear regression analysis. This advanced indicator helps traders detect bullish and bearish cycles with enhanced accuracy, making it ideal for swing traders and intraday enthusiasts alike.
Key Features :
🎨 Customizable Appearance : Set personalized colors for bullish and bearish trends to match your charting style.
🔧 Dynamic Trend Analysis : Tracks market momentum using a unique trend normalization algorithm.
📊 Linear Regression Insight : Calculates real-time trend direction using linear regression for better precision.
🔔 Alert Notifications : Receive alerts when the market switches from bearish to bullish or vice versa.
How to Use :
🛠 Add the Indicator : Favorite and apply the indicator to your TradingView chart. Adjust the lookback period, linear regression source, and regression length to fit your strategy.
📊 Market Analysis : Watch for color changes on the trend line. Green signals bullish momentum, while red indicates bearish cycles. Use these shifts to time entries and exits.
🔔 Set Alerts : Enable notifications for momentum shifts, ensuring you never miss critical market moves.
How It Works :
The LRI Momentum Cycles indicator calculates trend direction by applying linear regression on a user-defined price source over a specified period. It compares historical trend values, detecting bullish or bearish momentum through a dynamic scoring system. This score is normalized to ensure consistent readings, regardless of market conditions. The indicator visually represents trends using gradient-colored plots and fills to highlight changes in momentum. Alerts trigger when the momentum state changes, providing actionable trading signals.
Adaptive Squeeze Momentum StrategyThe Adaptive Squeeze Momentum Strategy is a versatile trading algorithm designed to capitalize on periods of low volatility that often precede significant price movements. By integrating multiple technical indicators and customizable settings, this strategy aims to identify optimal entry and exit points for both long and short positions.
Key Features:
Long/Short Trade Control:
Toggle Options: Easily enable or disable long and short trades according to your trading preferences or market conditions.
Flexible Application: Adapt the strategy for bullish, bearish, or neutral market outlooks.
Squeeze Detection Mechanism:
Bollinger Bands and Keltner Channels: Utilizes the convergence of Bollinger Bands inside Keltner Channels to detect "squeeze" conditions, indicating a potential breakout.
Dynamic Squeeze Length: Calculates the average squeeze duration to adapt to changing market volatility.
Momentum Analysis:
Linear Regression: Applies linear regression to price changes over a specified momentum length to gauge the strength and direction of momentum.
Dynamic Thresholds: Sets momentum thresholds based on standard deviations, allowing for adaptive sensitivity to market movements.
Momentum Multiplier: Adjustable setting to fine-tune the aggressiveness of momentum detection.
Trend Filtering:
Exponential Moving Average (EMA): Implements a trend filter using an EMA to align trades with the prevailing market direction.
Customizable Length: Adjust the EMA length to suit different trading timeframes and assets.
Relative Strength Index (RSI) Filtering:
Overbought/Oversold Signals: Incorporates RSI to avoid entering trades during overextended market conditions.
Adjustable Levels: Set your own RSI oversold and overbought thresholds for personalized signal generation.
Advanced Risk Management:
ATR-Based Stop Loss and Take Profit:
Adaptive Levels: Uses the Average True Range (ATR) to set stop loss and take profit points that adjust to market volatility.
Custom Multipliers: Modify ATR multipliers for both stop loss and take profit to control risk and reward ratios.
Minimum Volatility Filter: Ensures trades are only taken when market volatility exceeds a user-defined minimum, avoiding periods of low activity.
Time-Based Exit:
Holding Period Multiplier: Defines a maximum holding period based on the momentum length to reduce exposure to adverse movements.
Automatic Position Closure: Closes positions after the specified holding period is reached.
Session Filtering:
Trading Session Control: Limits trading to predefined market hours, helping to avoid illiquid periods.
Custom Session Times: Set your preferred trading session to match market openings, closings, or specific timeframes.
Visualization Tools:
Indicator Plots: Displays Bollinger Bands, Keltner Channels, and trend EMA on the chart for visual analysis.
Squeeze Signals: Marks squeeze conditions on the chart, providing clear visual cues for potential trade setups.
Customization Options:
Indicator Parameters: Fine-tune lengths and multipliers for Bollinger Bands, Keltner Channels, momentum calculation, and ATR.
Entry Filters: Choose to use trend and RSI filters to refine trade entries based on your strategy.
Risk Management Settings: Adjust stop loss, take profit, and holding periods to match your risk tolerance.
Trade Direction Control: Enable or disable long and short trades independently to align with your market strategy or compliance requirements.
Time Settings: Modify the trading session times and enable or disable the time filter as needed.
Use Cases:
Trend Traders: Benefit from aligning entries with the broader market trend while capturing breakout movements.
Swing Traders: Exploit periods of low volatility leading to significant price swings.
Risk-Averse Traders: Utilize advanced risk management features to protect capital and manage exposure.
Disclaimer:
This strategy is a tool to assist in trading decisions and should be used in conjunction with other analyses and risk management practices. Past performance is not indicative of future results. Always test the strategy thoroughly and adjust settings to suit your specific trading style and market conditions.
Custom MACD Oscillator with Bar ColoringCustom MACD Oscillator with Bar Coloring
This custom MACD indicator is a fusion of two powerful MACD implementations, combining the best features of both the MACD Crossover by HPotter and the Multiple Time Frame Custom MACD Indicator by ChrisMoody. The indicator enhances the traditional MACD with customizable options and dynamic bar coloring based on the relationship between the MACD and Signal lines, providing a clear visual representation of momentum shifts in the market.
Key Features:
MACD Oscillator: Built on the core MACD principle, showing the difference between two Exponential Moving Averages (EMA) for momentum tracking.
Signal Line: A Simple Moving Average (SMA) of the MACD, helping to identify potential entry/exit points through crossovers.
Multiple Time Frame Support: Allows users to view MACD and Signal data from different timeframes, giving a broader view of the market dynamics.
Bar Coloring: Bars are colored green when the MACD is above the Signal line (bullish), red when the MACD is below (bearish), and blue during neutral conditions.
Histogram with Custom Colors: A customizable histogram visualizes the difference between the MACD and Signal lines with color-coding to represent changes in momentum.
Cross Dots: Visual markers at points where the MACD crosses the Signal line for easy identification of potential trend shifts.
This indicator is a versatile tool for traders who want to visualize MACD-based momentum and crossover signals in multiple timeframes with clear visual cues on price bars.
Gaussian Acceleration ArrayIndicators play a role in analyzing price action, trends, and potential reversals. Among many of these, velocity and acceleration have held a significant place due to their ability to provide insight into momentum and rate of change. This indicator takes the old calculation and tweaks it with gaussian smoothing and logarithmic function to ensure proper scaling.
A Brief on Velocity and Acceleration: The concept of velocity in trading refers to the speed at which price changes over time, while acceleration is the rate of change(ROC) of velocity. Early momentum indicators like the RSI and MACD laid foundation for understanding price velocity. However, as markets evolve so do we as technical analysts, we seek the most advanced tools.
The Acceleration/Deceleration Oscillator, introduced by Bill Williams, was one of the early attempts to measure acceleration. It helped gauge whether the market was gaining or losing momentum. Over time more specific tools like the "Awesome Oscillator"(AO) emerged, which has a set length on the datasets measured.
Gaussian Functions: Named after the mathematician Carl Friedrich Gauss, the Gaussian function describes a bell-shaped curve, often referred to as the "normal distribution." In trading these functions are applied to smooth data and reduce noise, focusing on underlying patterns.
The Gaussian Acceleration Array leverages this function to create a smoothed representation of market acceleration.
How does it work?
This indicator calculates acceleration based the highs and lows of each dataset
Once the weighted average for velocity is determined, its rate of change essentially becomes the acceleration
It then plots multiple lines with customizable variance from the primary selected length
Practical Tips:
The Gaussian Acceleration Array offers various customizable parameters, including the sample period, smoothing function, and array variance. Experiment with these settings to tailor it to preferred timeframes and styles.
The color-coded lines and background zones make it easier to interpret the indicator at a glance. The backgrounds indicate increasing or decreasing momentum simply as a visual aid while the lines state how the velocity average is performing. Combining this with other tools can signal shifts in market dynamics.
RSI Momentum [CrossTrade]The RSI Momentum indicator generates buy and sell signals based on the Relative Strength Index (RSI) crossing specific thresholds. The Key difference is that we're using RSI overbought and oversold readings as the foundation for finding continuation signals in the same direction of that momentum. This solves the issue of trying to buy the bottom or sell the top and offsets any oscillators main weakness, divergence and false signals in a strong trend.
Key Parameters:
RSI Length: Determines the calculation period for the RSI.
Overbought Threshold: The RSI level above which the asset is considered overbought.
Momentum Loss Threshold for Buy: The RSI level below which a loss in upward momentum is indicated, triggering a potential buy signal.
Oversold Threshold: The RSI level below which the asset is considered oversold.
Momentum Loss Threshold for Sell: The RSI level above which a loss in downward momentum is indicated, triggering a potential sell signal.
Allow Additional Retracement Signals: A toggle to allow more than one signal within a certain number of bars after the first signal.
Max Additional Signals: The maximum number of additional signals allowed after the first signal.
Buy Signal Logic:
Initial Signal: Generated when the RSI first exceeds the overbought threshold and then falls below the momentum loss buy threshold. Defaults are 70 for the overbought threshold and 60 for the retracement level.
Additional Signals for Deeper Retracements: If enabled, the script shows additional buy signals within the maximum limit set by Max Additional Signals. These additional signals are shown only if each new signal's bar has a lower low than the previous signal's bar.
Sell Signal Logic:
Initial Signal: Similar to the buy signal, a sell signal is generated when the RSI first drops below the oversold threshold and then rises above the momentum loss sell threshold. Defaults are 30 for the oversold threshold and 40 for the retracement level.
Additional Signals for Deeper Retracements: If enabled, additional sell signals are shown, limited by Max Additional Signals, and only if each new signal's bar has a higher high than the previous signal's bar.
Continuation Signals in Strong Trends:
The script allows for a new series of signals (starting with the first signal again) when the RSI pattern repeats. For buy signals, this means going above the overbought and then below the momentum loss buy threshold. For sell signals, it's dropping below oversold and then above the momentum loss sell threshold.
Alerts:
The script includes alert conditions for both buy and sell signals, which can be configured in the TradingView alerts.
Approximate Spectral Entropy-Based Market Momentum (SEMM)Overview
The Approximate Spectral Entropy-Based Market Momentum (SEMM) indicator combines the concepts of spectral entropy and traditional momentum to provide traders with insights into both the strength and the complexity of market movements. By measuring the randomness or predictability of price changes, SEMM helps traders understand whether the market is in a trending or consolidating state and how strong that trend or consolidation might be.
Key Features
Entropy Measurement: Calculates the approximate spectral entropy of price movements to quantify market randomness.
Momentum Analysis: Integrates entropy with rate-of-change (ROC) to highlight periods of strong or weak momentum.
Dynamic Market Insight: Provides a dual perspective on market behavior—both the trend strength and the underlying complexity.
Customizable Parameters: Adjustable window length for entropy calculation, allowing for fine-tuning to suit different market conditions.
Concepts Underlying the Calculations
The indicator utilizes Shannon entropy, a concept from information theory, to approximate the spectral entropy of price returns. Spectral entropy traditionally involves a Fourier Transform to analyze the frequency components of a signal, but due to Pine Script limitations, this indicator uses a simplified approach. It calculates log returns over a rolling window, normalizes them, and then computes the Shannon entropy. This entropy value represents the level of disorder or complexity in the market, which is then multiplied by traditional momentum measures like the rate of change (ROC).
How It Works
Price Returns Calculation: The indicator first computes the log returns of price data over a specified window length.
Entropy Calculation: These log returns are normalized and used to calculate the Shannon entropy, representing market complexity.
Momentum Integration: The calculated entropy is then multiplied by the rate of change (ROC) of prices to generate the SEMM value.
Signal Generation: High SEMM values indicate strong momentum with higher randomness, while low SEMM values indicate lower momentum with more predictable trends.
How Traders Can Use It
Trend Identification: Use SEMM to identify strong trends or potential trend reversals. Low entropy values can indicate a trending market, whereas high entropy suggests choppy or consolidating conditions.
Market State Analysis: Combine SEMM with other indicators or chart patterns to confirm the market's state—whether it's trending, ranging, or transitioning between states.
Risk Management: Consider high SEMM values as a signal to be cautious, as they suggest increased market unpredictability.
Example Usage Instructions
Add the Indicator: Apply the "Approximate Spectral Entropy-Based Market Momentum (SEMM)" indicator to your chart.
Adjust Parameters: Modify the length parameter to suit your trading timeframe. Shorter lengths are more responsive, while longer lengths smooth out the signal.
Analyze the Output: Observe the blue line for entropy and the red line for SEMM. Look for divergences or confirmations with price action to guide your trades.
Combine with Other Tools: Use SEMM alongside moving averages, support/resistance levels, or other indicators to build a comprehensive trading strategy.
Volume, Volatility, and Momentum Metrics IndicatorVolume, Volatility, and Momentum Metrics Indicator
Welcome to our comprehensive TradingView indicator designed to provide traders with essential volume, volatility, and momentum metrics. This powerful tool is ideal for traders looking to enhance their market analysis by visualizing key indicators in a concise and easy-to-read format.
Key Features
1. Volume Metrics:
• Daily Dollar Volume: Understand the monetary value of the traded volume each day.
• Relative Volume (RVOL) Day: Compare the current volume to the previous day’s volume to gauge trading activity.
• Relative Volume (RVOL) 30D: Assess the average trading volume over the past 30 days.
• Relative Volume (RVOL) 90D: Evaluate the average trading volume over the past 90 days.
2. Volatility and Momentum Metrics:
• Average Daily Range (ADR) %: Measure the average daily price range as a percentage of the current price.
• Average True Range (ATR): Track the volatility by calculating the average true range over a specified period.
• Relative Strength Index (RSI): Determine the momentum by analyzing the speed and change of price movements.
3. Customizable Table Positions:
• Place the volume metrics table and the volatility/momentum metrics table in the bottom-left or bottom-right corners of your chart for optimal visibility and convenience.
Why Use This Indicator?
• Enhanced Market Analysis: Quickly assess volume trends, volatility, and momentum to make informed trading decisions.
• User-Friendly Interface: The clear and concise tables provide at-a-glance information without cluttering your chart.
• Customization Options: Choose where to display the tables to suit your trading style and preferences.
How It Works
This indicator uses advanced calculations to provide real-time data on trading volume, price range, and momentum. By displaying this information in separate, neatly organized tables, traders can easily monitor these critical metrics without diverting their focus from the main chart.
Who Can Benefit?
• Day Traders: Quickly gauge intraday trading activity and volatility.
• Swing Traders: Analyze longer-term volume trends and momentum to identify potential trade setups.
• Technical Analysts: Utilize comprehensive metrics to enhance technical analysis and trading strategies.
Get Started
To add this powerful indicator to your TradingView chart, simply search for “Volume, Volatility, and Momentum Metrics” in the TradingView public library, or use the provided link to add it directly to your chart. Enhance your trading analysis and make more informed decisions with our comprehensive TradingView indicator.
TASC 2024.01 Gap Momentum System█ OVERVIEW
TASC's January 2024 edition of Traders' Tips features an article titled “Gap Momentum” by Perry J. Kaufman. The article discusses how a trader might create a momentum strategy based on opening gap data. This script implements the Gap Momentum system presented therein.
█ CONCEPTS
In the article, Perry J. Kaufman introduces Gap Momentum as a cumulative series constructed in the same way as On-Balance Volume (OBV) , but using gap openings (today’s open minus yesterday’s close).
To smoothen the resulting time series (i.e., obtain the " signal line "), the author applies a simple moving average . Subsequently, he proposes the following two trading rules for a long-only trading system:
• Enter a long position when the signal line is moving higher.
• Exit when the signal line is moving lower.
█ CALCULATIONS
The calculation of Gap Momentum involves the following steps:
1. Calculate the ratio of the sum of positive gaps over the past N days to the sum of negative gaps (absolute values) over the same time period.
2. Add the resulting gap ratio to the cumulative time series. This time series is the Gap Momentum.
3. Keep moving forward, as in an N-day moving average.
MADALGO`s Enhanced OBV DivergencesDescription:
MADALGO's Enhanced OBV Divergences indicator is a unique tool designed for traders to visualize the divergences between price action and On Balance Volume (OBV), a fundamental aspect often indicative of underlying strength or weakness in the market. By keenly identifying these divergences, traders are better positioned to anticipate potential trend reversals or trend continuations, making this script an invaluable addition to their technical analysis toolkit.
This script meticulously scans for both regular and hidden bullish/bearish divergences, providing a comprehensive view of market sentiment. The core of this indicator is built around the OBV, which cumulatively adds or subtracts volume based on the price movement per period, thus providing a running total of volume and portraying the force behind the price movements.
The regular divergences are classic indicators of a potential reversal in the current trend, while hidden divergences are often indicative of trend continuation. These divergences are pinpointed based on the relative positions of the OBV and price highs/lows, over customizable lookback periods and within specified lookback ranges.
Features:
Regular and Hidden Divergences: Clearly marked bullish and bearish divergences provide insights into potential market turning points.
On Balance Volume (OBV) Line: Visualize the continuous flow of buying and selling pressure, enabling the identification of accumulation or distribution phases essential for understanding the market's strength or weakness.
Moving Average of OBV: An optional feature to smooth the OBV line, aiding in the identification of the overarching trend.
Dynamic Statistics Label: A floating label provides real-time updates on essential statistics like the Rate of Percentage Change (RPC) of OBV, the last divergences, and bars since the last divergences.
Inputs:
Pivot Lookback Right and Pivot Lookback Left: Define the lookback periods for identifying pivot points in the OBV line.
Max of Lookback Range and Min of Lookback Range: Define the range for considering divergences.
RPC Period: Defines the period for calculating the Rate of Percentage Change of the OBV.
MA Period: Defines the period for the optional moving average of the OBV.
Plot Bullish, Plot Hidden Bullish, Plot Bearish, Plot Hidden Bearish: Toggle visibility of respective divergences.
Plot Moving Average: Toggle visibility of the OBV moving average.
Usage:
Add the script to your TradingView chart.
Tailor the input parameters in the settings panel to align with your analysis requirements.
The divergences, OBV line, and optional moving average will be plotted on your chart, with a dynamic label displaying real-time statistics.
Set up alerts to be notified of identified divergences, enabling timely decision-making.
Alerts:
Regular bullish/bearish divergence in OBV found: Triggered when a regular bullish or bearish divergence is identified.
Hidden bullish/bearish divergence in OBV found: Triggered when a hidden bullish or bearish divergence is identified.
Underlying Concepts:
The OBV Divergences indicator is rooted in the principle that volume precedes price movement. When prices are rising with increased volume, it suggests that buying pressure is prevailing and may lead to continued upward momentum. Conversely, rising prices with decreasing volume might indicate a lack of buying conviction and could signal a potential price reversal. The identification of divergences between price and OBV can therefore serve as a powerful signal for traders. These examples can be seen below in the image
The Moving Average of the OBV further aids in understanding the prevailing trend by smoothing out the OBV line, providing a clearer picture of the market's longer-term momentum. The Rate of Percentage Change (RPC) provides insight into the momentum of volume, offering an additional layer of analysis. Together, these additional features enhance the core OBV analysis, enabling a more nuanced understanding of volume dynamics fundamental for making more informed trading decisions.
License:
This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this file, you can obtain one at Mozilla Public License 2.0.
RSI MTF [Market Yogi]The Multi-Time Frame RSI with Money Flow Index and Average is a powerful trading indicator designed to help traders identify overbought and oversold conditions across multiple time frames. It combines the Relative Strength Index (RSI) with the Money Flow Index (MFI) and provides an average value for better accuracy.
The Relative Strength Index (RSI) is a popular momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100 and is used to identify overbought and oversold conditions in an asset. By incorporating the RSI across multiple time frames, this indicator offers a broader perspective on market sentiment.
In addition to the RSI, this indicator also includes the Money Flow Index (MFI). The MFI is a volume-based oscillator that measures the inflow and outflow of money into an asset. It takes into account both price and volume, providing insights into the strength and direction of buying and selling pressure.
By combining the RSI and MFI across multiple time frames, traders gain a comprehensive understanding of market dynamics. The indicator allows for comparing the RSI and MFI values across different time frames, enabling traders to identify divergences and potential trend reversals.
Furthermore, this indicator provides an average value of the multi-time frame RSI, offering a consolidated signal that helps filter out noise and enhance the accuracy of trading decisions.
Key Features:
1. Multi-Time Frame RSI: Combines the RSI across different time frames to provide a comprehensive view of market sentiment.
2. Money Flow Index (MFI): Incorporates the MFI to gauge buying and selling pressure based on both price and volume.
3. Average Calculation: Computes the average value of the multi-time frame RSI to generate a consolidated trading signal.
4. Divergence Detection: Enables traders to spot divergences between the RSI and MFI values, indicating potential trend reversals.
5. Overbought and Oversold Levels: Highlights overbought and oversold levels on the RSI, aiding in timing entry and exit points.
The Multi-Time Frame RSI with Money Flow Index and Average is a versatile tool that can be applied to various trading strategies, including trend following, swing trading, and mean reversion. Traders can adjust the time frame settings to suit their preferences and trading style.
Note: It's important to use this indicator in conjunction with other technical analysis tools and indicators to validate signals and make informed trading decisions.
Stochastic Momentum Index (SMI) of Money Flow Index (MFI)"He who does not know how to make predictions and makes light of his opponents, underestimating his ability, will certainly be defeated by them."
(Sun Tzu - The Art of War)
▮ Introduction
The Stochastic Momentum Index (SMI) is a technical analysis indicator that uses the difference between the current closing price and the high or low price over a specific time period to measure price momentum.
On the other hand, the Money Flow Index (MFI) is an indicator that uses volume and price to measure buying and selling pressure.
When these two indicators are combined, they can provide a more comprehensive view of price direction and market strength.
▮ Improvements
By combining SMI with MFI, we can gain even more insights into the market. One way to do this is to use the MFI as an input to the SMI, rather than just using price.
This means we are measuring momentum based on buying and selling pressure rather than just price.
Another way to improve this indicator is to adjust the periods to suit your specific trading needs.
▮ What to look
When using the SMI MFI indicator, there are a few things to look out for.
First, look at the SMI signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMI MFI and the price.
If price is rising but the SMI MFI is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMI MFI is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
In the examples below, I show the use in conjunction with the price SMI, in which the MFI SMI helps to anticipate divergences:
In summary, the SMI MFI is a useful indicator that can provide valuable insights into market direction and price strength.
By adjusting the timeframes and paying attention to divergences and signal line crossovers, traders can use it as part of a broader trading strategy.
However, remember that no indicator is a magic bullet and should always be used in conjunction with other analytics and indicators to make informed trading decisions.
"The Stocashi" - Stochastic RSI + Heikin-AshiWhat up guys and welcome to the coffee shop. I have a special little tool for you today to throw in your toolbox. This one is a freebie.
This is the Stochastic RS-Heiken-Ashi "The Stocashi"
This is the stochastic RSI built to look like Heikin-Ashi candles.
a lot of people have trouble using the stochastic indicator because of its ability to look very choppy at its edges instead of having nice curves or arcs to its form when you use it on scalping time frames it ends up being very pointed and you can't really tell when the bands turn over if you're using a stochastic Ribbon or you can't tell when it's actually moving in a particular direction if you're just using the K and the D line.
This new format of Presentation seeks to get you to have a better visual representation of what the stochastic is actually doing.
It's long been noted that Heikin-Ashi do a very good job of representing momentum in a price so using it on something that is erratic as the stochastic indicator seems like a plausible idea.
The strategy is simple because you use it exactly the same way you've always used the stochastic indicator except now you can look for the full color of the candle.
this one uses a gradient color setup for the candle so when the candle is fully red then you have a confirmed downtrend and when the candle is fully green you have a confirmed up trend of the stochastic however if, you a combination of the two colors inside of one candle then you do not have a confirmed direction of the stochastic.
the strategy is simple for the stochastic and that you need to know your overall trend. if you are in an uptrend you are waiting for the stochastic to reach bottom and start curving up.
if you are in a downtrend you are waiting for the stochastic to reach its top or its peak and curve down.
In an uptrend you want to make sure that the stochastic is making consistently higher lows just like price should be. if at any moment it makes a lower low then you know you have a problem with your Trend and you should consider exiting.
The opposite is true for a downtrend. In a downtrend you want to make sure you have lower highs. if at any given moment you end up with a higher high than you know you have a problem with your Trend and it's probably ending so you should consider exiting.
The stochastic indicator done as he can actually candles also does a very good job of telling you when there is a change of character. In that moment when the change of character shows up you simply wait until your trend and your price start to match up.
You can also use the stochastic indicator in this format to find divergences the same way you would on the relative strength index against your price highs and price lows so Divergence trading is visually a little bit easier with this tool.
The settings for the K percent D percent RSI length and stochastic length can be adjusted at will so be sure to study the history of the stochastic and find the good settings for your trading strategy.
Open DriveOpen Drive is a market profile concept introduced by Jim Dalton. It occurs when the price moves directionally and persistently for the first 30 minutes from the cash market open.
It is necessary to use 30-minute bars as there needs to be enough time to measure an extreme move of the cash open. This means there will be fewer trades than other strategies using faster time periodicities.
The script finds open drives from these time points 0700/ 0800 and 1300/1430.
The entry signal also has a breakout threshold using the 5-bar high and 5-bar low to only take trades moving away from the prior 5-bar range. This weeds out most mid-range trades and small range expansion bars.
If the price has had a strong move from the open and has broken either below the prior 5-bar low or above the prior 5-bar high by an amount equal to the prior 5-bar range a trade is entered in the direction of the move.
The Exit criteria; exit after 3 bars which is 90mins when using a 30min periodicity.
Note, this script is shared to show that momentum generated on or around the cash open tends to persist. The entry and exits of this strategy are quite naive but there are plenty of ways to take more aggressive entries on faster time frames when an open drive occurs. The times chosen for this strategy will suit stock index futures mainly. The user can experiment with other futures products and their corresponding pit/ cash open hours.
Google "open drive market profile" for more information on open drives and market profile concepts.
Happy trading!
Chef MomentumChef momentum is a simple stochastic indicator that uses the hull moving average (hma). The oscillator can be used like most oscillators available.
Default setting:
%K length: 25
%K smoothing: 100
The user can adapt the parameters to study other values.
how to use :
When the length of the stoch K crossover hline 25 , a green circle appears which indicates the potential arrival of momentum.
When the length of the stock K crossover hline 80 , a red circle appears indicating the potential end of the momentum.
Moving Average Convergence Divergence and MomentumMACD line is difference between 20 EMA and 100 EMA which measures the Longterm trend. If MACD line is above Zero trend is positive. If MACD line is below zero trend is negative. Strategy is classic Buy in uptrend Sell in Downtrend.
To Improve the entry timing MACD histogram is used as Momentum. Histogram is the difference between MACD line and 20 EMA of MACD line. And Hist Momentum is the 20 SMA of histogram.
Advantage of histogram is Smoothness and better reliability than other momentum indicators like RSI which is volatile.
If MACD line is above zero = Trend is positive
and Histogram is above its SMA = Momentum is also positive.
Buy Signal.
If MACD line is above zero = Trend is positive
and Histogram is below its SMA = Trend is positive but Momentum is losing.
Look for Support levels or Break out of support level.
If MACD line is below zero = Trend is Negative
and Histogram is Below its SMA = Momentum is also Negative.
Sell Signal.
If MACD line is Below zero = Trend is Negative
and Histogram is above its SMA = Trend is negative but momentum is improving
Look for Resistance levels or Break out of resistance level.
Electrified Aggressive Momentum SignalWhat this can be used for:
If you've already decided you want to trade a symbol, this can identify points of momentum alignment.
If a strong move has recently happened and you're looking for a change in momentum.
How it works:
This is a weighted combination of a Stochastic RSI and two modified SuperTrend (ATR Trailing Stop) indicators:
The Stochastic RSI signal is based upon aligned momentum and is negated at the overbought and oversold points.
The SuperTrend formula uses high and low values for calculation and both fast and slow can be adjusted for sensitivity.
Philosophy:
Signals have to be useful to humans. If a signal occurs to late, you've missed it. The intent of this indicator is to assist in timing a trade at very short time-frames. It assumes your conviction about a trade already exists, but you are trying to get an optimal entry.
Opposing momentum (weak signal) within an uptrend can be a sign that you should wait before entering. The frequency of a signal can indicate the strength of the trend. As the frequency of the aligned signal value decreases so does the reward vs risk.
Delta-RSI Oscillator StrategyDelta-RSI Oscillator Strategy:
This strategy illustrates the use of the recently published Delta-RSI Oscillator as a stand-alone indicator.
Delta-RSI represents a smoothed time derivative of the RSI, plotted as a histogram and serving as a momentum indicator.
There are three optional conditions to generate trading signals (set separately for Buy, Sell and Exit signals):
Zero-crossing : bullish when D-RSI crosses zero from negative to positive values (bearish otherwise)
Signal Line Crossing : bullish when D-RSI crosses from below to above the signal line (bearish otherwise)
Direction Change : bullish when D-RSI was negative and starts ascending (bearish otherwise)
Since D-RSI oscillator is based on polynomial fitting of the RSI curve, there is also an option to filter trade signal by means of the root mean-square error of the fit (normalized by the sample average).
My original D-RSI Oscillator script can be found here:
[blackcat] L2 Ehlers Smoothed Adaptive MomentumLevel: 2
Background
John F. Ehlers introuced Smoothed Adaptive Momentum in his "Cybernetic Analysis for Stocks and Futures" chapter 12 on 2004.
Function
Smoothed Adaptive Momentum is to measure the Dominant Cycle period and then use that measured period to take a onecycle momentum. It really does matter if you measure the Dominant Cycle. The trend component is measured by taking the momentum across one full Dominant Cycle.
Key Signal
Mom ---> Smoothed Adaptive Momentum fast line
Trigger ---> Smoothed Adaptive Momentum slow line
Pros and Cons
100% John F. Ehlers definition translation of original work, even variable names are the same. This help readers who would like to use pine to read his book. If you had read his works, then you will be quite familiar with my code style.
Remarks
The 28th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
RSI + DivergencesHi Guys,
This indicator gives you the trend changes (Designed with the basics of Vash's RSI advanced and the Fikira divergence indicator)
This indicator will only give you regular divergences.
Please keep in mind that a trading plan is not only built with momentum but also with location and structure.
Good trading,
