Volume & Trend Confluence OscillatorVolume & Trend Confluence Oscillator (VTCO)
Overview:
The Volume & Trend Confluence Oscillator (VTCO) is a technical analysis tool designed to help traders assess market conditions by integrating volume analysis, momentum, and trend direction into a single oscillator. This indicator provides traders with additional confirmation when evaluating potential trade entries and exits.
Key Features:
Volume Analysis: Calculates a Z-score to detect unusual trading activity.
Momentum Measurement: Evaluates the rate of price change to gauge market velocity.
Trend Confirmation: Utilizes an Exponential Moving Average (EMA) to assess overall market direction.
Signal Filtering: Incorporates minimum movement thresholds and a confirmation period to reduce false signals.
Visual Enhancements: Background shading indicates trend direction, and buy/sell markers highlight key signals.
How It Works:
The VTCO applies a volume multiplier to momentum readings when volume activity significantly deviates from its historical norm. Additionally, it prioritizes momentum moves that align with the prevailing market trend. A smoothing mechanism refines the oscillator’s signal line, ensuring a more stable and actionable output. The indicator generates alerts when key conditions are met, assisting traders in identifying potential trend shifts.
Signal Generation:
Buy Signal: Triggered when the oscillator crosses above zero after an oversold condition, ideally within an uptrend.
Sell Signal: Triggered when the oscillator crosses below zero after an overbought condition, ideally within a downtrend.
Alerts: Configurable alerts notify traders when key market conditions are met.
Usage Considerations:
Works effectively across various timeframes but may provide more reliable signals on higher timeframes.
Best utilized in conjunction with additional technical indicators and risk management strategies.
No indicator guarantees future performance; proper analysis and trade management remain essential.
Disclaimer:
This indicator is provided for educational purposes only and should not be considered financial advice. Trading involves risk, and past performance is not indicative of future results. Always conduct independent analysis before making trading decisions.
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Bollinger Bands color candlesThis Pine Script indicator applies Bollinger Bands to the price chart and visually highlights candles based on their proximity to the upper and lower bands. The script plots colored candles as follows:
Bullish Close Above Upper Band: Candles are colored green when the closing price is above the upper Bollinger Band, indicating strong bullish momentum.
Bearish Close Below Lower Band: Candles are colored red when the closing price is below the lower Bollinger Band, signaling strong bearish momentum.
Neutral Candles: Candles that close within the bands remain their default color.
This visual aid helps traders quickly identify potential breakout or breakdown points based on Bollinger Band dynamics.
Kalman Synergy Oscillator (KSO)The Kalman Synergy Oscillator (KSO) is an innovative technical indicator that combines the Kalman filter with two well-established momentum oscillators: the Relative Strength Index (RSI) and Williams %R. This combination aims to provide traders with a more refined tool for market analysis.
The use of the Kalman filter is a key feature of the KSO. This sophisticated algorithm is known for its ability to extract meaningful signals from noisy data. In financial markets, this translates to smoothing out price action while maintaining responsiveness to genuine market movements. By applying the Kalman filter to price data before calculating the RSI and Williams %R, the KSO potentially offers more stable and reliable signals.
The synergy between the Kalman-filtered price data and the two momentum indicators creates an oscillator that attempts to capture market dynamics more effectively. The RSI contributes its strength in measuring the magnitude and speed of price movements, while Williams %R adds sensitivity to overbought and oversold conditions. Basing these calculations on Kalman-filtered data may help reduce false signals and provide a clearer picture of underlying market trends.
A notable aspect of the KSO is its dynamic weighting system. This approach adjusts the relative importance of the RSI and Williams %R based on their current strengths, allowing the indicator to emphasize the most relevant information as market conditions change. This flexibility, combined with the noise-reduction properties of the Kalman filter, positions the KSO as a potentially useful tool for different market conditions.
In practice, traders might find that the KSO offers several potential benefits:
Smoother oscillator movements, which could aid in trend identification and reversal detection.
Possibly reduced whipsaws, particularly in choppy or volatile markets.
Potential for improved divergence detection, which might lead to more timely reversal signals.
Consistent performance across different timeframes, due to the adaptive nature of the Kalman filter.
While the KSO builds upon existing concepts in technical analysis, its integration of the Kalman filter with traditional momentum indicators offers traders an interesting tool for market analysis. It represents an attempt to address common challenges in technical analysis, such as noise reduction and false signal minimization.
As with any technical indicator, the KSO should be used as part of a broader trading strategy rather than in isolation. Its effectiveness will depend on how well it aligns with a trader's individual approach and market conditions. For traders looking to explore a more refined momentum oscillator, the Kalman Synergy Oscillator could be a worthwhile addition to their analytical toolkit.
Bullrun Profit Maximizer [QuantraSystems]Bullrun Profit Maximizer
Quantra Systems guarantees that the information created and published within this document and on the Tradingview platform is fully compliant with applicable regulations, does not constitute investment advice, and is not exclusively intended for qualified investors.
Important Note!
The system equity curve presented here has been generated as part of the process of testing and verifying the methodology behind this script.
Crucially, it was developed after the system was conceptualized, designed, and created, which helps to mitigate the risk of overfitting to historical data. In other words, the system was built for robustness, not for simply optimizing past performance.
This ensures that the system is less likely to degrade in performance over time, compared to hyper optimized systems that are tailored to past data. No tweaks or optimizations were made to this system post backtest.
Even More Important Note!!
The nature of markets is that they change quickly and unpredictably. Past performance does not guarantee future results - this is a fundamental rule in trading and investing.
While this system is designed with broad, flexible conditions to adapt quickly to a range of market environments, it is essential to understand that no assumptions should be made about future returns based on historical data. Markets are inherently uncertain, and this system - like all trading systems - cannot predict future outcomes.
Introduction
The "Adaptive Pairwise Momentum System" is not a prototype to the Bullrun Profit Maximizer (BPM) . The Bullrun Profit Maximizer is a fully re-engineered, higher frequency momentum system.
The Bullrun Profit Maximizer (BPM) uses a completely different filter logic and refines momentum calculations, specifically to support higher frequency trading on Crypto's Blue Chip assets. It correctly calculates fees and slippage by compounding them against System Profit before plotting the equity curve.
Unlike prior systems, this script utilizes a completely new filter logic and refined momentum calculation, specifically built to support higher frequency trading on blue-chip assets, while minimizing the impact of fees and slippage.
While the APMS focuses on Macro Trend Alignment, the BPM instead applies an equity curve based filter, allowing for targeted precision on the current asset’s trend without relying on broader market conditions. This approach delivers more responsive and asset specific signals, enhancing agility in today’s fast paced crypto markets.
The BPM dynamically optimizes capital allocation across up to four high performing assets, ensuring that the portfolio adapts swiftly to changing market conditions. The system logic consists of sophisticated quantitative methods, rapid momentum analysis and alpha cyclicality/seasonality optimizations. The overarching goal is to ensure that the portfolio is always invested in the highest performing asset based on dynamic market conditions, while at the same time managing risk through rapid asset filters and internal mechanisms like alpha cyclicality, volatility and beta analysis.
In addition to these core functionalities, the BPM comes with the typical Quantra Systems UI design, structured to reduce data clutter and provide users with only the most essential, impactful information. The BPM UI format delivers clear and easy to read signals. It enables rapid decision making in a high frequency environment without compromising on depth or accuracy.
Bespoke Logic Filtering with Equity Curve Precision
The BPM script utilizes a completely new methodology and focuses on intraday rotations of blue-chip crypto assets, while previously built systems were designed with a longer term focus in mind.
In response to the need for more precise signal generation, the BPM replaces the previous macro trend filter with a new, highly specific equity curve activation filter. This unique logic filter is driven solely by the performance trends of the asset currently held by the system. By analyzing the equity curve directly, this system can make more targeted, timely allocations based on asset specific momentum, allowing for quick adjustments that are more relevant to the held asset rather than general market conditions.
The benefits of this new, unique approach are twofold: first, it avoids premature allocation shifts based on broader macro movements, and second, it enables the system to adapt dynamically to the performance of each asset individually. This asset specific filtering allows traders to capitalize on localized strength within individual blue-chip cryptoassets without being affected by lags in the overall market trend.
High Frequency Momentum Calculation for Enhanced Flexibility
The BPM incorporates a newly designed momentum calculation that increases its suitability across lower timeframes. This new momentum indicator captures and processes more data points within a shorter window than ever before, rather than extending bar intervals and potentially losing high frequency detail. This creates a smooth, data rich featureset that is especially suited for blue-chip assets, where liquidity reduces slippage and fees, making higher frequency trading viable.
By retaining more data, this system captures subtle shifts in momentum more effectively than traditional approaches, offering higher resolution insights. These modifications result in a system capable of generating highly responsive signals on faster timeframes, empowering traders to act quickly in volatile markets.
User Interface and Enhanced Readability
The BPM also features a reimagined, streamlined user interface, making it easier than ever to monitor essential signals at a glance. The new layout minimizes extraneous data points in the tables, leaving only the most actionable information for traders. This cleaner presentation is purpose built to help traders identify the strongest asset in real time, with clear, color coded signals to facilitate swift decision making in fast moving markets.
Equity Stats Table : Designed for clarity, the stats table focuses on the current allocation’s performance metrics, emphasizing the most critical metrics without unnecessary clutter.
Color Coded Highlights : The interface includes the option to highlight both the current top performing asset, and historical allocations - with indicators of momentum shifts and performance metrics readily accessible.
Clear Signals : Visual cues are presented in an enhanced way to improve readability, including simplified line coloring, and improve visualization of the outperforming assets in the allocation table.
Dynamic Asset Reallocation
The BPM dynamically allocates capital to the strongest performing asset in a selected pool. This system incorporates a re-engineered, pairwise momentum measurement designed to operate at higher frequencies. The system evaluates each asset against others in real time, ensuring only the highest momentum asset receives allocation. This approach keeps the portfolio positioned for maximum efficiency, with an updated weighting logic that favors assets showing both strength and sustainability.
Position Changes and Slippage Calculation
Position changes are optimized for faster reallocation, with realistic slippage and fee calculations factored into each trade. The system’s structure minimizes the impact of these costs on blue-chip assets, allowing for more active management on short timeframes without incurring significant drag on performance.
A Special Note on Fees + Slippage
In the image above, the system has been applied to four different timeframes - 12h, 8h, 4h and 1h - using identical settings and a selected slippage and fees amount of 0.2%. In this stress test, we isolate the choppy downwards period from the previous Bitcoin all time high - set in March 2024, to the current date where Bitcoin is currently sitting at around the same level.
This illustrates an important concept: starting at the 12h, the system performed better as the timeframes decreased. In fact, only on the 4hr chart did the system equity curve make a new all time high alongside Bitcoin. It is worth noting that market phases that are “non-trending” are generally the least profitable periods to use a momentum/trend system - as most systems will get caught by false momentum and will “buy the top,” and then proceed to “sell the bottom.”
Lower timeframes typically offer more data points for the algorithm to compute over, and enable quicker entries and exits within a robust system, often reducing downside risk and compounding gains more effectively - in all market environments.
However, slippage, fees, and execution constraints are still limiting factors. Although blue-chip cryptocurrencies are more liquid and can be traded with lower fees compared to low cap assets, frequent trading on lower timeframes incurs cumulative slippage costs. With the BPM system set to a realistic slippage rate of 0.2% per trade, this example emphasizes how even lower fees impact performance as trade frequency increases.
Finding the optimal balance between timeframe and slippage impact requires careful consideration of factors such as portfolio size, liquidity of selected tokens, execution speed, and the fee rate of the exchange you execute trades on.
Number of Position Changes
Understanding the number of position changes in a strategy is critical to assessing its feasibility in real world trading. Frequent position changes can lead to increased costs due to slippage and fees. Monitoring the number of position changes provides insight into the system’s behavior - helping to evaluate how active the strategy is and whether it aligns with the trader's desired time input for position management.
Equity Curve and Performance Calculations
To provide a benchmark, the script also generates a Buy-and-Hold (or "HODL") equity curve that represents a 100% allocation to Bitcoin, the highest market cap cryptoasset. This allows users to easily compare the performance of the dynamic rotation system with that of a more traditional investment strategy.
The script tracks key performance metrics for both the dynamic portfolio and the HODL strategy, including:
Sharpe Ratio
The Sharpe Ratio is a key metric that evaluates a portfolio’s risk adjusted return by comparing its ‘excess’ return to its volatility. Traditionally, the Sharpe Ratio measures returns relative to a risk-free rate. However, in our system’s calculation, we omit the risk-free rate and instead measure returns above a benchmark of 0%. This adjustment provides a more universal comparison, especially in the context of highly volatile assets like cryptocurrencies, where a traditional risk-free benchmark, such as the usual 3-month T-bills, is often irrelevant or too distant from the realities of the crypto market.
By using 0% as the baseline, we focus purely on the strategy's ability to generate raw returns in the face of market risk, which makes it easier to compare performance across different strategies or asset classes. In an environment like cryptocurrency, where volatility can be extreme, the importance of relative return against a highly volatile backdrop outweighs comparisons to a risk-free rate that bears little resemblance to the risk profile of digital assets.
Sortino Ratio
The Sortino Ratio improves upon the Sharpe Ratio by specifically targeting downside risk and leaves the upside potential untouched. In contrast to the Sharpe Ratio (which penalizes both upside and downside volatility), the Sortino Ratio focuses only on negative return deviations. This makes it a more suitable metric for evaluating strategies like the Bullrun Profit Maximizer - that aim to minimize drawdowns without restricting upside capture. By measuring returns relative to a 0% baseline, the Sortino ratio provides a clearer assessment of how well the system generates gains while avoiding substantial losses in highly volatile markets like crypto.
Omega Ratio
The Omega Ratio is calculated as the ratio of gains to losses across all return thresholds, providing a more complete view of how the system balances upside and downside risk even compared to the Sortino Ratio. While it achieves a similar outcome to the Sortino Ratio by emphasizing the system's ability to capture gains while limiting losses, it is technically a mathematically superior method. However, we include both the Omega and Sortino ratios in our metric table, as the Sortino Ratio remains more widely recognized and commonly understood by traders and investors of all levels.
Usage Summary:
While the backtests in this description are generated as if a trader held a portfolio of just the strongest tokens, this was mainly designed as a method of logical verification and not a recommended investment strategy. In practice, this system can be used in multiple ways.
It can be used as above, or as a factor in forming part of a broader asset selection tool, or even a method of filtering tokens by strength in order to inform a day trader which tokens might be optimal to look at, for long-only trading setups on an intrabar timeframe.
Summary
The Bullrun Profit Maximizer is an advanced tool tailored for traders, offering the precision and agility required in today’s markets. With its asset specific equity curve filter, reworked momentum analysis, and streamlined user interface, this system is engineered to maximize gains and minimize risk during bullmarkets, with a strong focus on risk adjusted performance.
Its refined approach, focused on high resolution data processing and adaptive reallocation, makes it a powerful choice for traders looking to capture high quality trends on clue-chip assets, no matter the market’s pace.
Fusion MFI RSIHello fellas,
This superb indicator summons two monsters called Relative Strength Index (RSI) and Money Flow Index (MFI) and plays the Yu-Gi-Oh! card "Polymerization" to combine them.
Overview
The Fusion MFI RSI Indicator is an advanced analytical tool designed to provide a nuanced understanding of market dynamics by combining the Relative Strength Index (RSI) and the Money Flow Index (MFI). Enhanced with sophisticated smoothing techniques and the Inverse Fisher Transform (IFT), this indicator excels in identifying key market conditions such as overbought and oversold states, trends, and potential reversal points.
Key Features (Brief Overview)
Fusion of RSI and MFI: Integrates momentum and volume for a comprehensive market analysis.
Advanced Smoothing Techniques: Employs Hann Window, Jurik Moving Average (JMA), T3 Smoothing, and Super Smoother to refine signals.
Inverse Fisher Transform (IFT) Enhances the clarity and distinctiveness of indicator outputs.
Detailed Feature Analysis
Fusion of RSI and MFI
RSI (Relative Strength Index): Developed by J. Welles Wilder Jr., the RSI measures the speed and magnitude of directional price movements. Wilder recommended using a 14-day period and identified overbought conditions above 70 and oversold conditions below 30.
MFI (Money Flow Index): Created by Gene Quong and Avrum Soudack, the MFI combines price and volume to measure trading pressure. It is typically calculated using a 14-day period, with over 80 considered overbought and under 20 as oversold.
Application in Fusion: By combining RSI and MFI, the indicator leverages RSI's sensitivity to price changes with MFI's volume-weighted confirmation, providing a robust analysis tool. This combination is particularly effective in confirming the strength behind price movements, making the signals more reliable.
Advanced Smoothing Techniques
Hann Window: Traditionally used to reduce the abrupt data discontinuities at the edges of a sample, it is applied here to smooth the price data.
Jurik Moving Average (JMA): Known for preserving the timing and smoothness of the data, JMA reduces market noise effectively without significant lag.
T3 Smoothing: Developed to respond quickly to market changes, T3 provides a smoother response to price fluctuations.
Super Smoother: Filters out high-frequency noise while retaining important trends.
Application in Fusion: These techniques are chosen to refine the output of the combined RSI and MFI values, ensuring the indicator remains responsive yet stable, providing clearer and more actionable signals.
Inverse Fisher Transform (IFT):
Developed by John Ehlers, the IFT transforms oscillator outputs to enhance the clarity of extreme values. This is particularly useful in this fusion indicator to make critical turning points more distinct and actionable.
Mathematical Calculations for the Fusion MFI RSI Indicator
RSI (Relative Strength Index)
The RSI is calculated using the following steps:
Average Gain and Average Loss: First, determine the average gain and average loss over the specified period (typically 14 days). This is done by summing all the gains and losses over the period and then dividing each by the period.
Average Gain = (Sum of Gains over the past 14 periods) / 14
Average Loss = (Sum of Losses over the past 14 periods) / 14
Relative Strength (RS): This is the ratio of average gain to average loss.
RS = Average Gain / Average Loss
RSI: Finally, the RSI is calculated using the RS value:
RSI = 100 - (100 / (1 + RS))
MFI (Money Flow Index)
The MFI is calculated using several steps that incorporate both price and volume:
Typical Price: Calculate the typical price for each period.
Typical Price = (High + Low + Close) / 3
Raw Money Flow: Multiply the typical price by the volume for the period.
Raw Money Flow = Typical Price * Volume
Positive and Negative Money Flow: Compare the typical price of the current period to the previous period to determine if the money flow is positive or negative.
If today's Typical Price > Yesterday's Typical Price, then Positive Money Flow = Raw Money Flow; Negative Money Flow = 0
If today's Typical Price < Yesterday's Typical Price, then Negative Money Flow = Raw Money Flow; Positive Money Flow = 0
Money Flow Ratio: Calculate the ratio of the sum of Positive Money Flows to the sum of Negative Money Flows over the past 14 periods.
Money Flow Ratio = (Sum of Positive Money Flows over 14 periods) / (Sum of Negative Money Flows over 14 periods)
MFI: Finally, calculate the MFI using the Money Flow Ratio.
MFI = 100 - (100 / (1 + Money Flow Ratio))
Fusion of RSI and MFI
The final Fusion MFI RSI value could be calculated by averaging the IFT-transformed values of RSI and MFI, providing a single oscillator value that reflects both momentum and volume-weighted price action:
Fusion MFI RSI = (MFI weight * MFI) + (RSI weight * RSI)
Suggested Settings and Trading Rules
Original Usage
RSI: Wilder suggested buying when the RSI moves above 30 from below (enter long) and selling when the RSI moves below 70 from above (enter short). He recommended exiting long positions when the RSI reaches 70 or higher and exiting short positions when the RSI falls below 30.
MFI: Quong and Soudack recommended buying when the MFI is below 20 and starts rising (enter long), and selling when it is above 80 and starts declining (enter short). They suggested exiting long positions when the MFI reaches 80 or higher and exiting short positions when the MFI falls below 20.
Fusion Application
Settings: Use a 14-day period for this indicator's calculations to maintain consistency with the original settings suggested by the inventors.
Trading Rules:
Enter Long Signal: Consider entering a long position when both RSI and MFI are below their respective oversold levels and begin to rise. This indicates strong buying pressure supported by both price momentum and volume.
Exit Long Signal: Exit the long position when either RSI or MFI reaches its respective overbought threshold, suggesting a potential reversal or decrease in buying pressure.
Enter Short Signal: Consider entering a short position when both indicators are above their respective overbought levels and begin to decline, suggesting that selling pressure is mounting.
Exit Short Signal: Exit the short position when either RSI or MFI falls below its respective oversold threshold, indicating diminishing selling pressure and a potential upward reversal.
How to Use the Indicator
Select Source and Timeframe: Choose the data source and the timeframe for analysis.
Configure Fusion Settings: Adjust the weights for RSI and MFI.
Choose Smoothing Technique: Select and configure the desired smoothing method to suit the market conditions and personal preference.
Enable Fisherization: Optionally apply the Inverse Fisher Transform to enhance signal clarity.
Customize Visualization: Set up gradient coloring, background plots, and bands according to your preferences.
Interpret the Indicator: Use the Fusion value and visual cues to identify market conditions and potential trading opportunities.
Conclusion
The Fusion MFI RSI Indicator integrates classical and modern technical analysis concepts to provide a comprehensive tool for market analysis. By combining RSI and MFI with advanced smoothing techniques and the Inverse Fisher Transform, this indicator offers enhanced insights, aiding traders in making more informed and timely trading decisions. Customize the settings to align with your trading strategy and leverage this powerful tool to navigate financial markets effectively.
Best regards,
simwai
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Credits to:
@loxx – T3
@everget – JMA
@cheatcountry – Hann Window
Machine Learning: STDEV Oscillator [YinYangAlgorithms]This Indicator aims to fill a gap within traditional Standard Deviation Analysis. Rather than its usual applications, this Indicator focuses on applying Standard Deviation within an Oscillator and likewise applying a Machine Learning approach to it. By doing so, we may hope to achieve an Adaptive Oscillator which can help display when the price is deviating from its standard movement. This Indicator may help display both when the price is Overbought or Underbought, and likewise, where the price may face Support and Resistance. The reason for this is that rather than simply plotting a Machine Learning Standard Deviation (STDEV), we instead create a High and a Low variant of STDEV, and then use its Highest and Lowest values calculated within another Deviation to create Deviation Zones. These zones may help to display these Support and Resistance locations; and likewise may help to show if the price is Overbought or Oversold based on its placement within these zones. This Oscillator may also help display Momentum when the High and/or Low STDEV crosses the midline (0). Lastly, this Oscillator may also be useful for seeing the spacing between the High and Low of the STDEV; large spacing may represent volatility within the STDEV which may be helpful for seeing when there is Momentum in the form of volatility.
Tutorial:
Above is an example of how this Indicator looks on BTC/USDT 1 Day. As you may see, when the price has parabolic movement, so does the STDEV. This is due to this price movement deviating from the mean of the data. Therefore when these parabolic movements occur, we create the Deviation Zones accordingly, in hopes that it may help to project future Support and Resistance locations as well as helping to display when the price is Overbought and Oversold.
If we zoom in a little bit, you may notice that the Support Zone (Blue) is smaller than the Resistance Zone (Orange). This is simply because during the last Bull Market there was more parabolic price deviation than there was during the Bear Market. You may see this if you refer to their values; the Resistance Zone goes to ~18k whereas the Support Zone is ~10.5k. This is completely normal and the way it is supposed to work. Due to the nature of how STDEV works, this Oscillator doesn’t use a 1:1 ratio and instead can develop and expand as exponential price action occurs.
The Neutral (0) line may also act as a Support and Resistance location. In the example above we can see how when the STDEV is below it, it acts as Resistance; and when it’s above it, it acts as Support.
This Neutral line may also provide us with insight as towards the momentum within the market and when it has shifted. When the STDEV is below the Neutral line, the market may be considered Bearish. When the STDEV is above the Neutral line, the market may be considered Bullish.
The Red Line represents the STDEV’s High and the Green Line represents the STDEV’s Low. When the STDEV’s High and Low get tight and close together, this may represent there is currently Low Volatility in the market. Low Volatility may cause consolidation to occur, however it also leaves room for expansion.
However, when the STDEV’s High and Low are quite spaced apart, this may represent High levels of Volatility in the market. This may mean the market is more prone to parabolic movements and expansion.
We will conclude our Tutorial here. Hopefully this has given you some insight into how applying Machine Learning to a High and Low STDEV then creating Deviation Zones based on it may help project when the Momentum of the Market is Bullish or Bearish; likewise when the price is Overbought or Oversold; and lastly where the price may face Support and Resistance in the form of STDEV.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Stochastic Zone Strength Trend [wbburgin]The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including possible entry/exit conditions), 3) works on every instrument, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength .
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust version of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I will go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength:
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength:
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Finally, the colors are changeable on the bottom.
Final Notes
As with previous and future invite-only scripts, I only restrict access to 1) maintain effectiveness of scripts, 2) because I use these scripts myself heavily, and/or 3) to support myself. Additionally, I will never make an restricted indicator that is not completely original in idea, scope, and execution.
Yours,
wbburgin
Vaidotas Momentum ScoreHello Traders!
Discover Myfractalrange latest addition on TradingView, Vaidotas Segenis Momentum Score.
How people calculate Momentum is subjective and many people (even professionals) use different Momentum formulas depending on how they view it. This is sometimes confusing for traders.
The purpose of this indicator is to identify periods of strong price momentum relative to historical volatility. Higher momentum scores indicate stronger price trends, while lower scores suggest weaker trends. Traders and investors may use this indicator to identify potential buy or sell signals based on the strength of price movements. The formula Vaidotas uses calculate Momentum Score for different periods based on the price data.
There are 3 different look back periods in the script, you will find them in "Input":
Period 1 : 10 Days
Period 2 : 30 Days
Period 3 : 90 Days
Now let's go over the different steps of the formula:
Step 1 - Calculate the daily normal returns : this gives the daily percentage change in price
Step 2 - Calculate the standard deviation of the daily normal returns over a specific look back period (Default: 100 days) : the standard deviation measures the volatility or dispersion of the returns
Step 4 - Calculate the squared standard deviation multiplied by the square root of the respective period: This is done for three different periods (Period 1, Period 2, Period 3), it amplifies the standard deviation by the square root of the period, which gives more weight to recent price changes.
Step 5 - Calculate the normal returns for each period: This calculates the percentage change in price over the specified period
Step 5 - Calculate the momentum score for each period: This score represents the relative strength or momentum of the price change compared to the expected volatility.
Using the momentum indicator involves interpreting the values and considering certain thresholds to make trading decisions. While there is no definitive rule for all markets and assets, we can provide you with a general guideline on how traders may want to use the indicator and explain the significance of certain values:
1) Strong Trend: When the momentum score is significantly positive (above a certain threshold, such as +2), it suggests a strong upward price trend.
2) Weak Trend: Conversely, when the momentum score is significantly negative (below a certain threshold, such as -2), it indicates a strong downward price trend. Traders may interpret this as a potential signal to enter or maintain a short position, expecting the trend to continue.
3) Lack of Trend: When the momentum score is close to zero, it suggests a lack of significant trend or sideways movement in the price. Values around 0 indicate a potential range-bound market or consolidation.
However, it's important to note that the specific threshold values for defining significant trends or reversals may vary depending on the asset, timeframe, and market conditions. Traders often adjust these thresholds based on their own experience and backtesting results.
Here are a few more examples to illustrate the use of the momentum indicator:
- Example 1 - Strong Uptrend Confirmation :
The momentum score is consistently above +2, indicating a strong upward trend. Traders may consider this as a potential signal to enter or maintain a long position, expecting the trend to continue.
- Example 2 - Reversal Signal :
The momentum score has been positive for an extended period but starts to decline and eventually crosses below -2. This could be seen as a potential reversal signal, suggesting that the uptrend is losing strength and a bearish trend might develop. Traders may consider exiting long positions or even taking short positions based on this reversal signal.
- Example 3 - Sideways Market :
The momentum score fluctuates around 0, without displaying any significant positive or negative values. This indicates a lack of clear trend and suggests that the asset is trading in a range or consolidating. Traders may choose to avoid taking new positions until a stronger trend emerges.
Why is it interesting to use different look back periods?
The use of different look back periods in the momentum indicator formula allows traders to assess momentum across multiple timeframes. By comparing the momentum results for each period, traders can gain a broader perspective on the strength of the trend and potential opportunities. Here's how a trader might use the different look back periods and their corresponding momentum results:
1) Identifying Consistency: Traders can compare the momentum results for different periods to assess the consistency of the trend. If the momentum scores for all periods are consistently positive or negative, it suggests a strong and consistent trend across multiple timeframes. This can provide traders with higher confidence in the trend's strength and potential trading opportunities.
2) Convergence or Divergence: Traders can analyze the relationship between the momentum results for different periods. If the momentum scores for all periods are converging (moving closer together), it indicates a higher degree of agreement across different timeframes and strengthens the signal. Conversely, if the momentum scores for different periods diverge (move apart), it may suggest a weakening or conflicting trend. Traders should exercise caution when the momentum scores diverge as it may signal a potential reversal or market uncertainty.
3) Confirmation of Momentum: Traders can use the momentum results for different periods to confirm the strength of a trend. For example, if the momentum scores for shorter periods (e.g., Period 1) are significantly higher than those for longer periods (e.g., Period 2 and Period 3), it suggests a recent increase in momentum and a potentially stronger trend. This confirmation can assist traders in making more informed trading decisions and timing their entries or exits.
4) Multiple Timeframe Analysis: Traders often employ a multiple timeframe analysis approach to validate their trading decisions. By comparing the momentum results for different periods, traders can assess the alignment of momentum across various timeframes. For instance, if the momentum scores for shorter, medium, and longer periods all indicate a strong trend in the same direction, it reinforces the conviction in the trade.
As a conclusion, the momentum indicator can be useful to traders for several reasons:
1) Identifying Trend Strength: The momentum indicator helps traders assess the strength of a price trend. When the momentum score is high, it suggests that the trend is strong and likely to continue. This information can be valuable for trend-following strategies, as it helps traders identify potentially profitable opportunities and stay on the right side of the market.
2) Spotting Reversals: Momentum indicators can also help traders identify potential trend reversals. When the momentum score diverges from the price movement, it may indicate a weakening trend or an upcoming reversal. Traders can use this signal to adjust their positions or look for opportunities to enter or exit trades.
3) Confirming Breakouts: Breakout traders often use momentum indicators to confirm the validity of a breakout. If a price breaks above a resistance level, and the momentum score also increases significantly, it provides additional confirmation that the breakout is strong and may continue. This helps traders have more confidence in their breakout trades.
4) Setting Stop Loss and Take Profit Levels: By understanding the strength of a price trend through the momentum indicator, traders can set appropriate stop-loss and take-profit levels. A strong momentum score may indicate that a trend is likely to continue, allowing traders to set wider profit targets. Conversely, a weak momentum score may suggest that the trend is losing steam, prompting traders to set tighter stop-loss levels to protect their capital.
4) Divergence Analysis: Momentum indicators can be used in conjunction with other technical indicators to identify divergences. Divergence occurs when the price and momentum indicator move in opposite directions. It can signal potential trend reversals or shifts in market sentiment, providing traders with opportunities to adjust their positions.
It's important to note that while momentum indicators can be useful tools, they should not be relied upon solely for making trading decisions. It's recommended to use them in conjunction with other technical analysis tools and consider other factors such as market conditions, risk management, and fundamental analysis. Remember that the momentum indicator is just one tool among many, and it's important to consider other factors such as volume, trend, volatility, and overall market conditions when making trading decisions. Additionally, using stop-loss orders and proper risk management techniques is crucial to mitigate potential losses.
We hope that you will find these explanations useful, please contact us by private message for access.
Enjoy!
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorised. This script is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. Myfractalrange is not responsible for any losses you may incur. Please invest wisely.
Probability Oscillator (Expo)█ Overview
The Probability Oscillator uses a Bayesian approach to measure the probability of a price movement and trend continuation. This approach considers the prior probability of a price movement and the current market conditions to identify trends, sentiment, momentum, and retracements.
█ How does the indicator work?
The Probability Oscillator is based on the idea of Bayesian probability , which is a way of using existing data to make predictions about the likelihood of an event occurring. This indicator uses the Bayesian probability model to analyze past trading activity and calculate the probability of a trend continuing. This function also considers the prior probability of a price movement and the current market conditions to analyze the likelihood of a retracement.
█ How to use
Investors can use this indicator to measure the market sentiment and the strength/direction of a trend. It does also give insights into momentum moves and retracements.
█ Indicator Customization
The user can change the trend approaches and input source as well as adjust the overbought and oversold areas to make the calculation more sensitive to retracements.
The user can change the sensitivity of the momentum function to adjust it only to identify the most significant momentum moves.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Squeeze mom MTF filtered by Wavetrend with div (Tilt)📋 Description :
This script is based on two famous indicators from @Lazybear : Squeeze Momentum and WaveTrend. fr.tradingview.com
The idea is to use the Wavetrend crossovers and filter them according to the momentum curve.
There is a multi timeframe module with automatic selection of the higher timeframe. The user can also choose his timeframe manually.
There is also a detection of regular and hidden divergences
🛠 Options :
- filtering the cross wave trend according to the momemtum curve
- active or not higher timeframe with automatic or manually timeframe selection
- display or not WaveTrend ans squeeze momentum
- Show a tape that signals when wavetrend is overbought or oversold
- choose colors and apparences
- display a panel for the higher timeframe value
Market phases 2.0The Market Phase 2.0 indicator is designed to display the following features:
1) The TREND OSCILLATOR : This trend oscillator indicates the trend of the stock/instrument. It is calculated on the basis of number of positive candles or negative candles formed during a specific period.
The oscillator oscillates around the zero horizontal line. The trend is considered bullish if the oscillator value is positive and the trend is considered negative if the oscillator value is negative.
2) The MOMENTUM OSCILLATOR:
The momentum oscillator indicates the short term momentum of the stock/instrument. It is calculated on the rate of change of close price for a specific period in the past.
The Momentum oscillator oscillates around the zero horizontal line. If the momentum oscillator has a positive value, the momentum is considered to be on the bullish side and similarly if the momentum oscillator has a negative value, the momentum is considered to be on the bearish side.
3) The SIGNAL LINE: The signal line is represented by the yellow color line. The Signal line combines the value of the Trend oscillator and the Momentum oscillator. The signal also moves around the zero line. There are two dotted lines above and below the zero line.
When the signal line crosses the upper dotted line, it indicates that the stock/instrument has moved on the upper side too quickly or sharply and the ongoing move may not continue for long. It may also be considered as overbought at that point. A red triangle appears at that point.
Similarly, when the signal line crosses the lower dotted line, it indicates that the stock/instrument has moved on the downside too quickly or sharply and the ongoing down move may not continue for long. It may also be considered as oversold at that point. A green triangle appears at that point.
The values for the look back period of the signal line and the values for the upper range and lower range of the indicator can be changed by going to the settings of the indicator.
***Disclaimer: The market movement depends upon a lot of factors which are beyond the scope of this indicator. Hence the indicator may display results not intended on rare occasions.
Trading in the markets involves involves huge risks and one should always follow his/her own research before taking any trading decisions.
MACD Trend Squeezer V2This is a combination of a slightly sped up MACD overlay on top of a modified Bar Trend Squeeze or highly modified Momentum indicator. Helps to see the trend/momentum matched with the characteristics of the MACD and it's historiography. Very user friendly for adjusting color, transparency, depth, lines, size, etc.
MACD is the dark gray line.
Its signal slower line is orange.
Its historiography is the area fill blues and reds
Trend Squeezer / momentum are the Bars in the background.
// Changes from original version \\
Visual depth mostly. Most of the items are adjustable in the settings.
Increased user friendly inputs to adjust colors, lines, data, etc.
(darken / lighten and change background bar colors, increase/decrease line strengths and colors, adjust field data inputs)
The DiamondThe Diamond is a collection of 3 custom oscillators and the RSI. It tries to visualizing how the momentum is increasing and decreasing and gives some buy and sell signals.
Every Line explained:
Orange line: The SMI(Swing Momentum Indicator) it is alternating oscillator between the value -10 and 40 and has its baseline at 10. It showing accumulation and increase of momentum and is used as a trend confirmation
Purple line: The BTD(Buy the Dip) is a modified Version of the SMI. It should be used in Bull or Bearflags to time entries. Also the Horizontal lines can be used as Support or Resistance
Green/Red Band: This one is a custom made stochastic. In its calculation it smoothing Tops/Lows to reduce noise. Also the look is better.
White line: Just a 14-lenght RSI. I use it together with the SMI and BTD to get confirmation
The Indicator is doing best in the crypto market. High market cap Coins/USDT Pairs do better than low market cap and btc pairs. Also it should be only used on timeframes greater than 4h. 6h and daily preferred. On higher time frames you need to adjust the values of the BTD and SMI.
Bearish divergence on both Indicators in a down trending market do give a good short entry.
Bullish divergence on the daily gives good swing entries in a downtrend
Hophop Multiple Timeframe Momentum GridThis indicator is intended to highlight the over bought and over sold momentums for multiple timeframe
As of now it only supports StochRSI and also a variation of it that is more responsive than StochRsi called HophopRsi, I might consider adding more momentum indicators if it is desired
All the needed variables for StochRsi are included as the original indicator, feel free to change them as you normally do on StochRsi
On top of that you can select up to 4 higher timeframe , just make sure that your current timeframe is the smallest one
The top line of the graph shows the current timeframe momentum
1st line = high timeframe 1
2st line = high timeframe 2
3st line = high timeframe 3
4st line = high timeframe 4
Quick demonstration of the usage:
If you benefit from this indicator and you would like to see more of these, please support me by your tips
BTC Tip: 39bwXN1chms1yHskBaYwz76UhDakc7grJ7
LTC Tip: MGD3U9dBCBVctwnoCa1grU8ompxG6hUhMk
ETH Tip: 0xEE9684a5aceE85036527aB48E596DeE4627bD84b
Compare - Oscillator vs BTC momentumI've made a simple indicator to compare the momentum of a trading pair against the momentum of BTC to the dollar. I use it to see how a pair is affected by BTC's momentum... I wouldnt use it to trade off alone, but it can be a useful tool alongside other indicators.
The time range can be adjusted, but I wouldnt reccomend setting it to anything over 12M, or under 1W.... as I'm not sure if it would work.
Any feedback is welcome!
This is an idea I had after looking at a wonderful visualisation made by BarclayJames, link below:
www.tradingview.com
Directional Trend Index (DTI) This technique was described by William Blau in his book "Momentum,
Direction and Divergence" (1995). His book focuses on three key aspects
of trading: momentum, direction and divergence. Blau, who was an electrical
engineer before becoming a trader, thoroughly examines the relationship between
price and momentum in step-by-step examples. From this grounding, he then looks
at the deficiencies in other oscillators and introduces some innovative techniques,
including a fresh twist on Stochastics. On directional issues, he analyzes the
intricacies of ADX and offers a unique approach to help define trending and
non-trending periods.
Directional Trend Index is an indicator similar to DM+ developed by Welles Wilder.
The DM+ (a part of Directional Movement System which includes both DM+ and
DM- indicators) indicator helps determine if a security is "trending." William
Blau added to it a zeroline, relative to which the indicator is deemed positive or
negative. A stable uptrend is a period when the DTI value is positive and rising, a
downtrend when it is negative and falling.
Precision Stochastic DivergenceThis indicator is designed to identify potential market turning points and continuations by detecting Regular and Hidden divergences between closing price action and the Stochastic momentum oscillator. It utilizes specific default parameters (Stochastic: 40,4,3; Pivot Lookback: 5,5 based on close) and incorporates specialized filtering logic for signal qualification.
Core Functionality & Features:
Divergence Detection: Identifies standard Regular (potential reversal) and Hidden (potential continuation) divergence patterns. Logic has been optimized for accurate detection of both types.
Precision Filter Mechanism (Regular Divergences): Employs a unique dual-level validation process:
Requires the initial pivot's Stochastic value (%D) to meet Overbought (>80) or Oversold (<20) criteria.
Requires the subsequent pivot's Stochastic value (%D) to reside within a precisely defined range (Default parameterization: Bullish 19-30, Bearish 70-81). This aims to filter divergences based on specific momentum conditions following an initial extreme reading.
Standard Filter (Hidden Divergences): Filters Hidden Divergence signals by requiring both associated Stochastic pivot values to remain outside the primary Overbought/Oversold zones (i.e., >20 for Bullish, <80 for Bearish).
Signal Plotting: Displays 'R' (Regular) and 'H' (Hidden) markers on the chart upon confirmation of filtered divergence conditions. Relevant Stochastic threshold levels and filter range boundaries are plotted for visual reference.
Configuration & Usage Notes:
Parameterization: The default settings (Stochastic: 40,4,3; Pivots: 5,5; Levels: 80/20; Ranges: 19-30 / 70-81) have been specifically calibrated. For optimal performance according to the intended methodology, modification of these core parameters is strongly discouraged.
EMA Filter: Note that EMA trend filtering functionality has been intentionally removed from this version of the indicator.
Applicable Timeframes: While adaptable, performance consistency has been observed on the Hourly (1H) timeframe. Lower intervals such as 6m and 10m are considered optimal secondary timeframes, with 5m and 15m also demonstrating viability depending on market conditions.
Instrument Applicability & Validation:
!!!WARNING FOR GOLD TRADERS!!!
Low time frame spot gold (xauusd) mysteriously proves to give more incorrect signals than every other asset I have tested although higher timeframes like hourlies still signal as intended. The reason MAY be because of not enough testing.
The underlying principle of Stochastic divergence is applicable to various instruments, including Cryptocurrencies (Bitcoin, Ethereum) and Major Indices (SP500, NASDAQ, etc.).
However, the efficiency of this indicator's specific parameterization is contingent upon the volatility profile and price dynamics of the selected instrument.
Mandatory Validation: Rigorous backtesting and/or simulated trading on the specific instrument and timeframe is imperative prior to live deployment. This validation is crucial to ascertain performance characteristics and confirm alignment with individual trading plans and risk management protocols.
By Matthew James
Disclaimer:
Trading involves substantial risk. This indicator serves as an analytical tool and does not constitute financial advice or a guarantee of future results. Users assume full responsibility for their trading decisions. Always employ robust risk management practices.
MACD 4C 2025 - GeorgeMoshe4-Colored MACD by GeorgeMoshe
A visually enhanced MACD that uses four distinct colors to indicate momentum and direction:
Lime – Positive MACD, rising momentum
Green – Positive MACD, declining momentum
Red – Negative MACD, rising momentum (bullish divergence potential)
Maroon – Negative MACD, declining momentum
Ideal for quickly spotting trend strength and possible reversals.
Money Flow Pulse💸 In markets where volatility is cheap and structure is noisy, what matters most isn’t just the move — it’s the effort behind it. Money Flow Pulse (MFP) offers a compact, color-coded readout of real-time conviction by scoring volume-weighted price action on a five-tier scale. It doesn’t try to predict reversals or validate trends. Instead, it reveals the quality of the move in progress: is it fading , driving , exhausting , or hollow ?
🎨 MFP draws from the traditional Money Flow Index (MFI), a volume-enhanced momentum oscillator, but transforms it into a modular “pressure readout” that fits seamlessly into any structural overlay. Rather than oscillating between extremes with little interpretive guidance, MFP discretizes the flow into clean, color-coded regimes ranging from strong inflow (+2) to strong outflow (–2). The result is a responsive diagnostic layer that complements, rather than competes with, tools like ATR and/or On-Balance Volume.
5️⃣ MFP uses a normalized MFI value smoothed over 13 periods and classified into a 5-tier readout of Volume-Driven Conviction :
🍆 Exhaustion Inflow — usually a top or blowoff; not strength, but overdrive (+2)
🥝 Active Inflow — supportive of trend continuation (+1)
🍋 Neutral — chop, coil, or fakeouts (0)
🍑 Selling Intent — weakening structure, possible fade setups (-1)
🍆 Exhaustion Outflow — often signals forced selling or accumulation traps (-2)
🎭 These tiers are not arbitrary. Each one is tuned to reflect real capital behavior across timeframes. For instance, while +1 may support continuation, +2 often precedes exhaustion — especially on the lower timeframes. Similarly, a –1 reading during a pullback suggests sell-side pressure is building, but a shift to –2 may mean capitulation is already underway. The difference between the two can define whether a move is tradable continuation or strategic exhaustion .
🌊 The MFI ROC (Rate of Change) feature can be toggled to become a volatility-aware pulse monitor beneath the derived MFI tier. Instead of scoring direction or structure, ROC reveals how fast conviction is changing — not just where it’s headed, but how hard it's accelerating or decaying. It measures the raw Δ between the current and previous MFI values, exposing bursts of energy, fading pressure, or transitional churn .
🎢 Visually, ROC appears as a low-opacity area fill, anchored to a shared lemon-yellow zero line. When the green swell rises, buying pressure is accelerating; when the red drops, flow is actively deteriorating. A subtle bump may signal early interest — while a steep wave hints at an emotional overreaction. The ROC value itself provides numeric insight alongside the raw MFI score. A reading of +3.50 implies strong upside momentum in the flow — often supporting trend ignition. A score of –6.00 suggests rapid deceleration or full exhaustion — often preceding reversals or failed breakouts.
・ MFI shows you where the flow is
・ ROC tells you how it’s behaving
😎 This blend reveals not just structure or intent — but also urgency . And in flow-based trading, urgency often precedes outcome.
🧩 Divergence isn’t delay — it’s disagreement . One of the most revealing features of MFP is how it exposes momentum dissonance — situations where price and flow part ways. These divergences often front-run pivots , traps , or velocity stalls . Unlike RSI-style divergence, which whispers of exhaustion, MFI divergence signals a breakdown in conviction. The structure may extend — but the effort isn’t there.
・ Price ▲ MFI ▼ → Effortless Markup : Often signals distribution or a grind into liquidity. Without rising MFI, the rally lacks true flow participation — a warning of fragility.
・ Price ▼ MFI ▲ → Absorption or Early Accumulation : Price breaks down, but money keeps flowing in — a hidden bid. Watch for MFI tier shifts or ROC bursts to confirm a reversal.
🏄♂️ These moments don’t require signal overlays or setup hunting. MFP narrates the imbalance. When price breaks structure but flow does not — or vice versa — you’re not seeing trend, you’re seeing disagreement, and that's where edge begins.
💤 MFP is especially effective on intraday charts where volume dislocations matter most. On the 1H or 15m chart, it helps distinguish between breakouts with conviction versus those lacking flow. On higher timeframes, its resolution softens — it becomes more of a drift indicator than a trigger device. That’s by design: MFP prioritizes pulse, not position. It’s not the fire, it’s the heat.
📎 Use MFP in confluence with structural overlays to validate price behavior. A ribbon expansion with rising MFP is real. A compression breakout without +1 flow is "fishy". Watch how MFP behaves near key zones like anchored VWAP, MAs or accumulation pivots. When MFP rises into a +2 and fails to sustain, the reversal isn’t just technical — it’s flow-based.
🪟 MFP doesn’t speak loudly, but it never whispers without reason. It’s the pulse check before action — the breath of the move before the breakout. While it stays visually minimal on the chart, the true power is in the often overlooked Data Window, where traders can read and interpret the score in real time. Once internalized, these values give structure-aware traders a framework for conviction, continuation, or caution.
🛜 MFP doesn’t chase momentum — it confirms conviction. And in markets defined by noise, that signal isn’t just helpful — it’s foundational.
JW Momentum IndicatorJW Momentum Indicator
This indicator provides clear and actionable buy/sell signals based on a combination of volume-enhanced momentum, divergence detection, and volatility adjustment. It's designed to identify potential trend reversals and momentum shifts with a focus on high-probability setups.
Key Features:
Volume-Enhanced Momentum: The indicator calculates a custom oscillator that combines momentum with volume, giving more weight to momentum when volume is significant. This helps to identify strong momentum moves.
Divergence Detection: It detects bullish and bearish divergences using pivot highs and lows, highlighting potential trend reversals.
Volatility-Adjusted Signals: The indicator adjusts signal sensitivity based on the Average True Range (ATR), making it more reliable in varying market conditions.
Clear Visuals: Buy and sell signals are clearly indicated with up and down triangles, while divergences are highlighted with distinct labels.
How to Use:
Buy Signals: Look for green up triangles or bullish divergence labels.
Sell Signals: Look for red down triangles or bearish divergence labels.
Oscillator and Thresholds: Use the plotted oscillator and thresholds to confirm signal strength.
Parameters:
Momentum Period: Adjusts the length of the momentum calculation.
Volume Average Period: Adjusts the length of the volume average calculation.
Volatility Period: Adjusts the length of the ATR calculation.
Volatility Multiplier: Adjusts the sensitivity of the volatility-adjusted signals.
Disclaimer:
This indicator is for informational purposes only and should not be considered financial advice. Always conduct 1 thorough research and use appropriate risk management techniques when trading.
Whale Activity Tracker Enhanced"Whale Activity Tracker Enhanced: Multi-Timeframe Adaptive Trading Signals"
Description:
The Whale Activity Tracker Enhanced (WAT+) is an innovative, multi-dimensional indicator designed to detect and visualize significant market moves likely driven by large players ("whales"). It combines volume analysis, price action, volatility, and momentum to provide traders with a comprehensive view of potential high-impact market events.
Key Features:
1. Adaptive Volume Spike Detection: Dynamically adjusts to market conditions, identifying unusual volume surges relative to recent activity.
2. Multi-Factor Confirmation: Combines volume spikes with price movements, RSI levels, and volatility measures for higher-probability signals.
3. Liquidity Grab Detection: Identifies potential stop-loss raids and liquidity sweeps through wick-to-body ratio analysis.
4. Customizable Signal Strength: Provides a visual representation of signal intensity, allowing traders to focus on the most significant events.
5. Flexible Timeframe Usage: Optimized settings for both scalp and swing trading, making it versatile across different trading styles.
How It Works:
- Volume Spike Analysis: Compares current volume to a user-defined multiple of the average volume.
- Price Move Threshold: Flags significant percentage price changes to filter out minor fluctuations.
- RSI Integration: Uses RSI to identify potential overbought/oversold conditions coinciding with other signals.
- Volatility Measurement: Incorporates ATR to detect periods of increased market volatility.
- Wick Analysis: Detects potential liquidity grabs by analyzing the ratio of candle wicks to bodies.
Originality:
Unlike standard volume or price action indicators, WAT+ synthesizes multiple market factors to provide a holistic view of potential whale activity. Its adaptive nature and customizable parameters allow it to work across various market conditions and trading styles.
Usage Guide:
1. Scalp Trading Setup:
- Use shorter lookback periods (12-15 bars) and tighter RSI levels (75/25).
- Focus on quick, high-probability trades triggered by volume spikes and price moves.
- Utilize the signal strength indicator for entry confirmation.
2. Swing Trading Setup:
- Extend lookback periods (20-30 bars) and use standard RSI levels (70/30).
- Look for sustained signals over multiple candles for trend confirmation.
- Combine with broader market trend analysis for higher-probability setups.
3. General Tips:
- Use the info panel to analyze the components of each signal.
- Adjust volume and price thresholds based on the specific asset's volatility.
- Combine with support/resistance levels for optimal entry and exit points.
By providing a multi-faceted approach to market analysis, the Whale Activity Tracker Enhanced empowers traders to identify and capitalize on significant market moves across various timeframes and trading styles.
Swing Trading Settings:
General Settings
Lookback Period: 20 to 30 bars. This provides a smoother signal and better context for swing trading.
Volume Spike Multiplier: 2.5 to 3.0. Higher thresholds ensure only significant volume spikes are considered.
Price Move % Threshold: 2.0 to 3.0%. Larger price move thresholds align with swing trading objectives.
RSI Period: 14 to 21. Longer periods smooth out short-term fluctuations.
RSI Overbought/Oversold Levels: 70/30. These levels work well for identifying potential reversals in swing trading.
Signal Detection
Enable Volume Spike Signal: True
Enable Price Move Signal: True
Enable Volatility Signal: True (important for identifying strong trends)
Enable Liquidity Grab Signal: True
Visualization
Show Volume Threshold Line: True
Show Signal Strength: True
Show Info Panel: True (useful for detailed analysis of swing setups)
Colors
Bullish Color: Green
Bearish Color: Red
Liquidity Color: Purple
Additional Parameters
ATR Period: 14 to 20. This helps identify volatility and set stop-loss levels.
Wick-to-Body Ratio: 2.0 or higher. This ensures only significant liquidity grabs are flagged.
Signal Strength Smoothing: 3 to 5 bars for steadier signals.
Scalp Trading:
General Settings
Lookback Period: 12 to 15 bars. This allows for a balance between responsiveness and noise reduction.
Volume Spike Multiplier: 2.0 to 2.2. This setting helps detect significant volume spikes without overreacting to minor fluctuations.
Price Move % Threshold: 1.0 to 1.2%. This captures substantial price movements suitable for scalp trading.
RSI Period: 7 to 9. Shorter periods provide quicker signals, ideal for scalp trading.
RSI Overbought/Oversold Levels: 75/25. Tighter levels help identify potential reversals sooner.
Signal Detection
Enable Volume Spike Signal: True
Enable Price Move Signal: True
Enable Volatility Signal: False (optional, depends on market conditions)
Enable Liquidity Grab Signal: True
Visualization
Show Volume Threshold Line: True
Show Signal Strength: True
Show Info Panel: False (optional, for cleaner charts)
Colors
Bullish Color: Green
Bearish Color: Red
Liquidity Color: Purple
Additional Tips
ATR Period: Keep it around 14 for volatility assessment.
Wick-to-Body Ratio: Adjust to 1.8 or higher for clearer liquidity grabs.
Signal Strength Smoothing: Use 2 to 3 bars for a responsive yet stable signal.
Bollinger Momentum Deviation | QuantEdgeBIntroducing Bollinger Momentum Deviation (BMD) by QuantEdgeB
🛠️ Overview
Bollinger Momentum Deviation (BMD) is a trend-following momentum indicator designed to identify strong price movements while also detecting overbought and oversold conditions in ranging markets.
By normalizing a simple moving average (SMA) with standard deviation, BMD captures momentum shifts, helping traders make data-driven entries and exits. In trending conditions, it acts as a momentum confirmation tool, while in ranging markets, it highlights mean-reversion opportunities for profit-taking or re-accumulation.
BMD combines the best of both worlds—a robust trend-following framework with an integrated volatility-based overbought/oversold detection system.
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✨ Key Features
🔹 Momentum & Trend-Following Core
Built upon a normalized SMA with standard deviation filtering, BMD efficiently tracks price movements while reducing lag.
🔹 Overbought/Oversold Market Detection
By dynamically adjusting its thresholds based on standard deviation, it identifies high-probability reversion zones in sideways markets.
🔹 Adaptive Normalization Mechanism
Ensures consistent signal reliability across different assets and timeframes by standardizing momentum fluctuations.
🔹 Customizable Visual & Signal Settings
Includes multiple color modes, extra plots, and trend labels, making it easy to align with different trading styles.
____
📊 How It Works
1️⃣ Normalized Momentum Calculation
BMD computes a normalized momentum score using a simple moving average (SMA) combined with a standard deviation (SD) filter to create dynamic upper and lower bands. The final momentum score is derived by normalizing the price within this volatility-adjusted range. This normalization makes momentum readings comparable across different price levels and timeframes.
2️⃣ Standard Deviation Filtering
Unlike traditional approaches where standard deviation is derived from price as is the first SD, BMDs second SD is driven from the normalized momentum oscillator itself. This allows for a volatility-adjusted smoothing mechanism that adapts to momentum shifts rather than raw price fluctuations. This ensures that the trend signals remain dynamic and responsive, filtering out short-term noise while keeping the core momentum structure intact. By applying standard deviation directly to the oscillator, BMD achieves a self-regulating feedback loop, improving accuracy in both trending and range-bound conditions.
3️⃣ Signal Generation
✅ Long Signal → Upper BMD SD > Long Threshold (83)
❌ Short Signal → Lower BMD SD < Short Threshold (60)
📌 Additional Features:
- Overbought Zone → Values above 130 indicate price extension.
- Oversold Zone → Values below -10 suggest potential accumulation.
- Momentum Labels → Optional "Long" and "Short" markers for clear trade identification.
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👥 Who Should Use It?
✅ Trend Traders & Momentum Followers → Use BMD as a confirmation tool for strong directional trends.
✅ Range & Mean Reversion Traders → Identify reversal opportunities at extreme BMD levels.
✅ Swing & Position Traders → Utilize normalized momentum shifts for data-driven entries & exits.
✅ Systematic & Quant Traders → Implement BMD within algorithmic frameworks for adaptive market detection.
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⚙️ Customization & Default Settings
🔧 Key Custom Inputs:
- Base Length (Default: 40) → Defines the SMA calculation period.
- Standard Deviation Length (Default: 50) → Controls the volatility filter strength.
- SD Multiplier (Default: 0-7) → Adjusts the sensitivity of the momentum filter.
- Long Threshold (Default: 83) → Above this level, momentum is bullish.
- Short Threshold (Default: 60) → Below this level, momentum weakens.
- Visual Customizations → Multiple color themes, extra plots, and trend labels available.
🚀 By default, BMD is optimized for trend-following and momentum filtering while remaining adaptable to various trading strategies.
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📌 How to Use Bollinger Momentum Deviation (BMD) in Trading
1️⃣ Trend-Following Strategy (Momentum Confirmation)
✔ Enter long positions when BMD crosses above the long threshold (83), confirming upward momentum.
✔ Enter short positions when BMD crosses below the short threshold (60), confirming downward momentum.
✔ Stay in trades as long as BMD remains in trend direction, filtering out noise.
2️⃣ Mean Reversion Strategy (Overbought/Oversold Conditions)
✔ Take profits or hedge when BMD crosses above 130 (overbought).
✔ Re-accumulate positions when BMD drops below -10 (oversold).
📌 Why?
- In trending markets, follow BMD’s momentum confirmation.
- In ranging markets, use BMD’s normalized bands to buy at deep discounts and sell into strength.
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📌 Conclusion
Bollinger Momentum Deviation (BMD) is a versatile momentum indicator that combines trend-following mechanics with volatility-adjusted mean reversion zones. By normalizing SMA-based momentum shifts, BMD ensures robust signal reliability across different assets and timeframes.
🔹 Key Takeaways:
1️⃣ Momentum Confirmation & Trend Detection – Captures directional strength with dynamic filtering.
2️⃣ Overbought/Oversold Conditions – Identifies reversal opportunities in sideways markets.
3️⃣ Adaptive & Customizable – Works across different timeframes and trading styles.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Balance Price Range (BPR) IndicatorOverview
The BPR with Directional Momentum-Filtered Breakouts indicator is designed to identify Balanced Price Ranges (BPR) and d etect high-probability breakouts and breakdowns with directional momentum confirmation . By leveraging historical BPR structures, EMA-based momentum filtering , and a trade cooldown mechanism , this script provides a structured approach to identifying potential trading opportunities while reducing false signals.
This invite-only indicator is ideal for traders who seek precise breakout confirmation, reduced noise, and trend-following logic while maintaining flexibility through adjustable parameters.
How It Works
The script follows a multi-step breakout detection process by integrating multiple key technical components:
1. Balanced Price Range (BPR) Detection:
• A Balanced Candle is identified when the price remains within a specific percentage of its range midpoint.
• These BPR zones represent areas of equilibrium , where a breakout or breakdown is likely to occur.
• The script historically tracks BPR levels across the entire chart to monitor price action around key areas.
2. Momentum-Filtered Breakout & Breakdown Logic:
• Bullish Breakout: Occurs when the price breaks above the historical BPR high with bullish momentum.
• Bearish Breakdown: Occurs when the price breaks below the historical BPR low with bearish momentum.
• Momentum Confirmation: Each breakout requires a strong directional move, measured against the Exponential Moving Average (EMA) .
• Only confirmed breakouts are marked, reducing the likelihood of false signals in choppy markets.
3. Candle-Based Background Visualization:
• Grey Background: Represents a Balanced Price Range (BPR), indicating potential breakout zones.
• Green Background: Indicates a Bullish Breakout when the price successfully breaks and holds above the BPR high.
• Red Background: Indicates a Bearish Breakdown when the price drops below the BPR low.
4. Trade Cooldown Mechanism:
• Prevents consecutive signals from triggering too frequently.
• Default cooldown period: 5 bars (adjustable).
• Ensures that trades are not clustered, improving signal quality.
5. EMA for Trend Direction & Confirmation:
• A 20-period EMA (default, adjustable) is used to confirm trade direction.
• Breakouts above the EMA align with uptrend continuation.
• Breakdowns below the EMA align with downtrend momentum.
Key Features
✔️ Historical BPR Detection – Tracks past BPR levels across the entire chart for structured breakout zones.
✔️ Momentum-Based Breakouts – Ensures breakouts are confirmed by directional price movement before generating signals.
✔️ Candle-Based Background Logic – Subtle candle highlights rather than full background fills, for better chart clarity.
✔️ Trade Cooldown Period – Prevents consecutive buy/sell signals within a defined period, improving signal efficiency.
✔️ Dynamic EMA Confirmation – Ensures trades align with the overall trend, reducing counter-trend trades.
✔️ Customizable Inputs – Adjust breakout thresholds, EMA length, and cooldown periods as per trading style.
✔️ Works Across Multiple Timeframes – Can be applied to intraday, swing, and positional trading strategies.
How to Use
1. Look for Balanced Price Ranges ( BPR )
• These zones highlight equilibrium areas where price is likely to break out.
• Grey-shaded candles indicate potential breakout zones.
2. Monitor for Bullish or Bearish Breakouts
• A green candle background signals a bullish breakout above BPR.
• A red candle background signals a bearish breakdown below BPR.
• The EMA filter helps confirm whether the breakout aligns with the prevailing trend.
3. Follow the Cooldown Logic
• After a breakout signal, wait for the cooldown period before another trade is allowed.
• This helps filter out noisy price action and prevents excessive trading.
4. Use Alongside Other Indicators
• Works well with volume analysis, support/resistance levels, and price action strategies.
• Can be combined with other momentum indicators for further trade confirmation.
Why This Combination?
Unlike generic breakout indicators, this script uniquely combines:
• BPR historical structures for defining potential breakout zones.
• Momentum-based breakout filtering using EMA confirmation.
• Trade cooldown logic to avoid excessive trading signals.
• Subtle candle-based highlights instead of cluttered full-background fills.
This structured approach makes the indicator more robust, adaptive, and reliable in different market conditions.
Why It’s Worth Using?
🔹 Avoid False Breakouts: Built-in momentum confirmation prevents weak or fake breakouts.
🔹 Clean Visualization: No excessive overlays—just precise, meaningful background coloring for breakouts.
🔹 Works in Any Market: Use on stocks, crypto, forex, indices, and commodities across different timeframes.
🔹 User-Friendly & Customizable: Fine-tune parameters to match individual trading styles.
⚠️ Note: This is an Invite-Only script. Access is granted to selected users.
✅ If you find it useful, consider incorporating it into your trend-following & breakout trading strategies.
🚀 Optimize your trading with structured breakout detection! 🚀
