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
Cerca negli script per "momentum"
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.
Multi indicators tableThis is a comprehensive trading tool that presents an overview of the market in a tabular format. It consists of five distinct categories of trading indicators : Volatility, Trend, Momentum, Reversal, and Volume. Each category includes a series of indicators that are widely used in the trading communauty.
The Volatility category includes the Average True Range (ATR) and Bollinger Bands indicators. The Trend category comprises the Average Directional Index (ADX), four Exponential Moving Averages (EMAs), Aroon, Parabolic SAR, and the Supertrend. The Momentum category includes the Stochastic Relative Strength Index (StochRSI), Money Flow Index (MFI), Williams %R, Relative Strength Index (RSI), and Commodity Channel Index (CCI). The Reversal category includes Parabolic SAR, Moving Average Convergence Divergence (MACD), and PP Supertrend. Finally, the Volume category includes the Volume Exponential Moving Average (EMA) indicator.
The indicators states are easily readable, the indicator case is colored based on his actual state. A bullish color (green by default), a bearish color (red by default),
a very bullish color (dark green by default), a very bearish color (dark red by default) and a neutral color (gray by default) displayed when the indicator doesn't give us a clear signal. Some indicators do not have a very bullish or very bearish state. Concerning volatility indicators, the bullish color indicates high volatility, the bearish color indicates low volatility, and the neutral color indicates normal volatility.
Most of the indicators displayed in the table are customizable, and traders can choose to hide the categories they don't want to use. The Indicator provides a quick and easily readable view on the market and allows traders to reduce the number of indicators on their chart making it lighter and more readable.
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
Natural Market River [CC]The Natural Market River was created by Jim Sloman (Ocean Theory pgs 59-62) and this is another momentum indicator that is extremely similar to the previous indicator I published, the Natural Market Mirror . This has almost identical buy and sell signals but different way to handle calculations so I'm going to leave it up to you which one you will prefer. Since this is almost identical, the buy and sell signals work in the same way with both strong signals and normal ones. Buy when the line turns green and sell when it turns red.
Let me know what other indicators you would like to see me publish!
Natural Market Mirror [CC]The Natural Market Mirror was created by Jim Sloman (Ocean Theory pgs 49-57) and this is a continuation of my series from Jim Sloman's indicators. This indicator is also a momentum indicator and is very similar to the previous indicator I published, the Ocean Indicator and of course this indicator is built using ideas from the Ocean indicator. It may just be my opinion but I feel like this indicator provides better buy and sell signals in comparison. I built this using strong buy and sell indicators in addition to normal ones so darker colors are the strong signals and lighter colors are the normal signals. Buy when the line turns green and sell when it turns red.
Let me know what other indicators you would like me to publish!
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.
Relative Strength Line by @iArpanKHello Traders!
I'm a Momentum Trader, following the Indian & US markets. Most of us are familiar with the Relative Strength (RS) indicator, popularized by Investor's Business Daily (IBD) and available on their MarketSmith platform. So, here I'm sharing a script that does the same and additionally pops an alert label when the RS line hits a new high (similar to Blue Dot appearance on MarketSmith charts).
User Settings
Inputs tab
Base Symbol : Symbol of the security/index with which you want to compare your current active symbol.
Period : Number of days since which you want to scan for a new high (default is 250 days, which approximately pops alerts for new 52 week high in RS). For example, if you want to look for new 10 days high in RS, set the Period to 10.
Style tab
RS Line : Change color using the palette provided (default is blue).
Alert Label : Show/hide alert labels by checking/unchecking the box. Change color using the palette provided. Change alert label symbol.
Precision : Default is two decimal places. Can be changed as per requirement.
Usage
The indicator consists of two components- the Relative Strength (RS) line & alert labels on new RS highs. Relative strength gives a measure of how the underlying security is performing with respect to a base index or security. For example, how is NSE:DIXON performing w.r.t NSE:NIFTY or how is NASDAQ:AAPL performing w.r.t. the TVC:SPX .
A rising RS line tells us that the underlying entity is outperforming the base entity. Similarly, a declining RS line shows under-performance of the underlying entity. A new high in RS (especially before a new high in price) often gives valuable information about the underlying security's strength w.r.t. the general market, and can tip us off to a possible breakout in the price in near future.
Making RS lists (list of stocks making new high in RS on heavy down days in index) can be very helpful to sort out leaders that are best resisting the decline and are likely to move up aggressively when the market turns favorable.
The concept of RS is extensively used by momentum traders and growth stock traders. When used in conjunction with price & volume action, this can be a very powerful tool in your trading arsenal. You can now easily spot RS trends and new highs visually by simply adding this indicator to your chart!
Conclusion
If you like this script, click on Add to favorite indicators , so that you can easily add this indicator from your favorites tab right away.
Thanks!
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
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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.
Strong Holders MomentumThis indicator is called "Strong Holders Momentum" (SH Momentum) and is a modified oscillator that analyzes the difference between two moving averages (fast and slow) across different timeframes. Its primary purpose is to identify trend strength and direction, as well as potential reversal points.
This indicator detects early momentum shifts in assets approaching key reversal zones by tracking:
- Convergence of the smoothed moving average (SMMA)
- Trend confirmation across multiple timeframes
- Visual assessment of momentum intensity
### Key Features:
1. Dual Smoothed Moving Averages (SMMA)
- Uses two modified moving averages (SMMA — Smoothed Moving Average) with different periods:
- `fast_length` (default: 4) — fast MA.
- `slow_length` (default: 12) — slow MA.
- The difference between them (`ma_diff = fast_ma - slow_ma`) generates the primary signal.
2. Higher Timeframe Analysis
- The indicator automatically calculates the moving average difference (`ma_diff`) on a higher timeframe (`res_multi` times larger than the current one) to determine the global trend.
- Example: If the current timeframe is 1H and `res_multi = 3`, the higher timeframe will be 3H.
3. Visualization:
- Histogram (bars) — displays the current `ma_diff` value. Color depends on the direction and position relative to zero.
- Lines — duplicates the histogram as a line.
- Background — shaded red/green based on the higher timeframe trend direction.
4. Color Scheme:
- Above zero and rising: Light green (`#81C784`).
- Below zero and rising: Deep green (`#26A69A`).
- Above zero and falling: Bright red (`#EF5350`).
- Below zero and falling: Light pink (`#FFCDD2`).
Signal Interpretation:
- Green bars: Increasing bullish momentum.
- Red bars: Growing bearish pressure.
- Background color: Trend bias on the higher timeframe (red = bearish, green = bullish).
### Logic:
- A rising `ma_diff` indicates strengthening momentum.
- Zero-line crossovers may signal a trend reversal.
- Divergence between current and higher timeframes (e.g., uptrend on lower TF vs. downtrend on higher TF) can warn of trend weakness.
### Applications:
- Trend strategies: Buy when the histogram rises above zero; sell when it falls below.
- Trend filter: Alignment of directions across timeframes strengthens signals.
- Divergences: Discrepancies between price and indicator may hint at reversals.
This indicator combines features of MACD (MA difference) and Momentum.
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.
Stochastic Order Flow Momentum [ScorsoneEnterprises]This indicator implements a stochastic model of order flow using the Ornstein-Uhlenbeck (OU) process, combined with a Kalman filter to smooth momentum signals. It is designed to capture the dynamic momentum of volume delta, representing the net buying or selling pressure per bar, and highlight potential shifts in market direction. The volume delta data is sourced from TradingView’s built-in functionality:
www.tradingview.com
For a deeper dive into stochastic processes like the Ornstein-Uhlenbeck model in financial contexts, see these research articles: arxiv.org and arxiv.org
The SOFM tool aims to reveal the momentum and acceleration of order flow, modeled as a mean-reverting stochastic process. In markets, order flow often oscillates around a baseline, with bursts of buying or selling pressure that eventually fade—similar to how physical systems return to equilibrium. The OU process captures this behavior, while the Kalman filter refines the signal by filtering noise. Parameters theta (mean reversion rate), mu (mean level), and sigma (volatility) are estimated by minimizing a squared-error objective function using gradient descent, ensuring adaptability to real-time market conditions.
How It Works
The script combines a stochastic model with signal processing. Here’s a breakdown of the key components, including the OU equation and supporting functions.
// Ornstein-Uhlenbeck model for volume delta
ou_model(params, v_t, lkb) =>
theta = clamp(array.get(params, 0), 0.01, 1.0)
mu = clamp(array.get(params, 1), -100.0, 100.0)
sigma = clamp(array.get(params, 2), 0.01, 100.0)
error = 0.0
v_pred = array.new(lkb, 0.0)
array.set(v_pred, 0, array.get(v_t, 0))
for i = 1 to lkb - 1
v_prev = array.get(v_pred, i - 1)
v_curr = array.get(v_t, i)
// Discretized OU: v_t = v_{t-1} + theta * (mu - v_{t-1}) + sigma * noise
v_next = v_prev + theta * (mu - v_prev)
array.set(v_pred, i, v_next)
v_curr_clean = na(v_curr) ? 0 : v_curr
v_pred_clean = na(v_next) ? 0 : v_next
error := error + math.pow(v_curr_clean - v_pred_clean, 2)
error
The ou_model function implements a discretized Ornstein-Uhlenbeck process:
v_t = v_{t-1} + theta (mu - v_{t-1})
The model predicts volume delta (v_t) based on its previous value, adjusted by the mean-reverting term theta (mu - v_{t-1}), with sigma representing the volatility of random shocks (approximated in the Kalman filter).
Parameters Explained
The parameters theta, mu, and sigma represent distinct aspects of order flow dynamics:
Theta:
Definition: The mean reversion rate, controlling how quickly volume delta returns to its mean (mu). Constrained between 0.01 and 1.0 (e.g., clamp(array.get(params, 0), 0.01, 1.0)).
Interpretation: A higher theta indicates faster reversion (short-lived momentum), while a lower theta suggests persistent trends. Initial value is 0.1 in init_params.
In the Code: In ou_model, theta scales the pull toward \mu, influencing the predicted v_t.
Mu:
Definition: The long-term mean of volume delta, representing the equilibrium level of net buying/selling pressure. Constrained between -100.0 and 100.0 (e.g., clamp(array.get(params, 1), -100.0, 100.0)).
Interpretation: A positive mu suggests a bullish bias, while a negative mu indicates bearish pressure. Initial value is 0.0 in init_params.
In the Code: In ou_model, mu is the target level that v_t reverts to over time.
Sigma:
Definition: The volatility of volume delta, capturing the magnitude of random fluctuations. Constrained between 0.01 and 100.0 (e.g., clamp(array.get(params, 2), 0.01, 100.0)).
Interpretation: A higher sigma reflects choppier, noisier order flow, while a lower sigma indicates smoother behavior. Initial value is 0.1 in init_params.
In the Code: In the Kalman filter, sigma contributes to the error term, adjusting the smoothing process.
Summary:
theta: Speed of mean reversion (how fast momentum fades).
mu: Baseline order flow level (bullish or bearish bias).
sigma: Noise level (variability in order flow).
Other Parts of the Script
Clamp
A utility function to constrain parameters, preventing extreme values that could destabilize the model.
ObjectiveFunc
Defines the objective function (sum of squared errors) to minimize during parameter optimization. It compares the OU model’s predicted volume delta to observed data, returning a float to be minimized.
How It Works: Calls ou_model to generate predictions, computes the squared error for each timestep, and sums it. Used in optimization to assess parameter fit.
FiniteDifferenceGradient
Calculates the gradient of the objective function using finite differences. Think of it as finding the "slope" of the error surface for each parameter. It nudges each parameter (theta, mu, sigma) by a small amount (epsilon) and measures the change in error, returning an array of gradients.
Minimize
Performs gradient descent to optimize parameters. It iteratively adjusts theta, mu, and sigma by stepping down the "hill" of the error surface, using the gradients from FiniteDifferenceGradient. Stops when the gradient norm falls below a tolerance (0.001) or after 20 iterations.
Kalman Filter
Smooths the OU-modeled volume delta to extract momentum. It uses the optimized theta, mu, and sigma to predict the next state, then corrects it with observed data via the Kalman gain. The result is a cleaner momentum signal.
Applied
After initializing parameters (theta = 0.1, mu = 0.0, sigma = 0.1), the script optimizes them using volume delta data over the lookback period. The optimized parameters feed into the Kalman filter, producing a smoothed momentum array. The average momentum and its rate of change (acceleration) are calculated, though only momentum is plotted by default.
A rising momentum suggests increasing buying or selling pressure, while a flattening or reversing momentum indicates fading activity. Acceleration (not plotted here) could highlight rapid shifts.
Tool Examples
The SOFM indicator provides a dynamic view of order flow momentum, useful for spotting directional shifts or consolidation.
Low Time Frame Example: On a 5-minute chart of SEED_ALEXDRAYM_SHORTINTEREST2:NQ , a rising momentum above zero with a lookback of 5 might signal building buying pressure, while a drop below zero suggests selling dominance. Crossings of the zero line can mark transitions, though the focus is on trend strength rather than frequent crossovers.
High Time Frame Example: On a daily chart of NYSE:VST , a sustained positive momentum could confirm a bullish trend, while a sharp decline might warn of exhaustion. The mean-reverting nature of the OU process helps filter out noise on longer scales. It doesn’t make the most sense to use this on a high timeframe with what our data is.
Choppy Markets: When momentum oscillates near zero, it signals indecision or low conviction, helping traders avoid whipsaws. Larger deviations from zero suggest stronger directional moves to act on, this is on $STT.
Inputs
Lookback: Users can set the lookback period (default 5) to adjust the sensitivity of the OU model and Kalman filter. Shorter lookbacks react faster but may be noisier; longer lookbacks smooth more but lag slightly.
The user can also specify the timeframe they want the volume delta from. There is a default way to lower and expand the time frame based on the one we are looking at, but users have the flexibility.
No indicator is 100% accurate, and SOFM is no exception. It’s an estimation tool, blending stochastic modeling with signal processing to provide a leading view of order flow momentum. Use it alongside price action, support/resistance, and your own discretion for best results. I encourage comments and constructive criticism.
TMO (True Momentum Oscillator)TMO ((T)rue (M)omentum (O)scilator)
Created by Mobius V01.05.2018 TOS Convert to TV using Claude 3.7 and ChatGPT 03 Mini :
TMO calculates momentum using the delta of price. Giving a much better picture of trend, tend reversals and divergence than momentum oscillators using price.
True Momentum Oscillator (TMO)
The True Momentum Oscillator (TMO) is a momentum-based technical indicator designed to identify trend direction, trend strength, and potential reversal points in the market. It's particularly useful for spotting overbought and oversold conditions, aiding traders in timing their entries and exits.
How it Works:
The TMO calculates market momentum by analyzing recent price action:
Momentum Calculation:
For a user-defined length (e.g., 14 bars), TMO compares the current closing price to past open prices. It assigns:
+1 if the current close is greater than the open price of the past bar (indicating bullish momentum).
-1 if it's less (indicating bearish momentum).
0 if there's no change.
The sum of these scores gives a raw momentum measure.
EMA Smoothing:
To reduce noise and false signals, this raw momentum is smoothed using Exponential Moving Averages (EMAs):
First, the raw data is smoothed by an EMA over a short calculation period (default: 5).
Then, it undergoes additional smoothing through another EMA (default: 3 bars), creating the primary "Main" line of the indicator.
Lastly, a "Signal" line is derived by applying another EMA (also default: 3 bars) to the main line, adding further refinement.
Trend Identification:
The indicator plots two lines:
Main Line: Indicates current momentum strength and direction.
Signal Line: Acts as a reference line, similar to a moving average crossover system.
When the Main line crosses above the Signal line, it suggests strengthening bullish momentum. Conversely, when the Main line crosses below the Signal line, it indicates increasing bearish momentum.
Overbought/Oversold Levels:
The indicator identifies key levels based on the chosen length parameter:
Overbought zone (positive threshold): Suggests the market might be overheated, and a potential bearish reversal or pullback could occur.
Oversold zone (negative threshold): Suggests the market might be excessively bearish, signaling a potential bullish reversal.
Clouds visually mark these overbought/oversold areas, making it easy to see potential reversal zones.
Trading Applications:
Trend-following: Traders can enter positions based on crossovers of the Main and Signal lines.
Reversals: The overbought and oversold areas highlight high-probability reversal points.
Momentum confirmation: Use TMO to confirm price action or other technical signals, improving trade accuracy and timing.
The True Momentum Oscillator provides clarity in identifying momentum shifts, making it a valuable addition to various trading strategies.
Uptrick: Universal Market ValuationIntroduction
Uptrick: Universal Market Valuation is created for traders who seek an analytical tool that brings together multiple signals in one place. Whether you focus on intraday scalping or long-term portfolio management, the indicator merges various well-known technical indicators to help gauge potential overvaluation, undervaluation, and trend direction. It is engineered to highlight different market dimensions, from immediate price momentum to extended cyclical trends.
Overview
The indicator categorizes market conditions into short-term, long-term, or a classic Z-Score style reading. Additionally, it draws on a unified trend line for directional bias. By fusing elements from traditionally separate indicators, the indicator aims to reduce “false positives” while giving a multidimensional view of price behavior. The indicator works best on cryptocurrency markets while remaining a universal valuation indicator that performs well across all timeframes. However, on lower timeframes, the Long-Term Combo input may be too long-term, so it's recommended to select the Short-Term Combo in the inputs for better adaptability.
Originality and Value
The Uptrick: Universal Market Valuation indicator is not just a simple combination of existing technical indicators—it introduces a multi-layered, adaptive valuation model that enhances signal clarity, reduces false positives, and provides traders with a more refined assessment of market conditions.
Rather than treating each included indicator as an independent signal, this script normalizes and synthesizes multiple indicators into a unified composite score, ensuring that short-term and long-term momentum, mean reversion, and trend strength are all dynamically weighted based on market behavior. It employs a proprietary weighting system that adjusts how each component contributes to the final valuation output. Instead of static threshold-based signals, the indicator integrates adaptive filtering mechanisms that account for volatility fluctuations, drawdowns, and momentum shifts, ensuring more reliable overbought/oversold readings.
Additionally, the script applies Z-Score-based deviation modeling, which refines price valuation by filtering out extreme readings that are statistically insignificant. This enhances the detection of true overvaluation and undervaluation points by comparing price behavior against a dynamically calculated standard deviation threshold rather than relying solely on traditional fixed oscillator bands. The MVRV-inspired ratio provides a unique valuation layer by incorporating historical fair-value estimations, offering deeper insight into market overextension.
The Universal Trend Line within the indicator is designed to smooth trend direction while maintaining responsiveness to market shifts. Unlike conventional trend indicators that may lag significantly or produce excessive false signals, this trend-following mechanism dynamically adjusts to changing price structures, helping traders confirm directional bias with reduced noise. This approach enables clearer trend recognition and assists in distinguishing between short-lived pullbacks and sustained market movements.
By merging momentum oscillators, trend strength indicators, volume-driven metrics, statistical deviation models, and long-term valuation principles into a single framework, this indicator eliminates the need for juggling multiple individual indicators, helping traders achieve a holistic market perspective while maintaining customization flexibility. The combination of real-time alerts, dynamic color-based valuation visualization, and customizable trend-following modes further enhances usability, making it a comprehensive tool for traders across different timeframes and asset classes.
Inputs and Features
• Calculation Window (Short-Term and Long-Term)
Defines how much historical data the indicator uses to evaluate the market. A smaller window makes the indicator more reactive, benefiting high-frequency traders. A larger window provides a steadier perspective for longer-term holders.
• Smoothing Period (Short-Term and Long-Term)
Controls how much the raw indicator outputs are “smoothed out.” Lower values reveal subtle intraday fluctuations, while higher values aim to present more robust, stable signals.
• Valuation Mechanism (Short Term Combo, Long Term Combo, Classic Z-Score)
Allows you to pick how the indicator evaluates overvaluation or undervaluation. Short Term Combo focuses on rapid oscillations, Long Term Combo assesses market health over more extended periods, and the Classic Z-Score approach highlights statistically unusual price levels.
Short-Term
• Determination Mechanism (Strict or Loose)
Governs the tolerance for labeling a market as overvalued or undervalued. Strict requires stronger confirmation; Loose begins labeling sooner, potentially catching moves earlier but risking more false signals.
Strict
Loose
• Select Color Scheme
Lets you choose the aesthetic style for your charts. Visual clarity can significantly improve reaction time, especially when multiple indicators are combined.
• Z-Score Coloring Mode (Heat or Slope)
Determines how the Classic Z-Score line and bars are colored. In Heat mode, the indicator intensifies color as readings move further from a baseline average. Slope mode changes color based on the direction of movement, making turning points more evident.
Classic Z-Score - Heat
Classic Z-Score - Slope
• Trend Following Mode (Short, Long, Extra Long, Filtered Long)
Offers various ways to compute and smooth the universal trend line. Short is more sensitive, Long and Extra Long are meant for extended time horizons, and Filtered Long applies an extra smoothing layer to help you see overarching trends rather than smaller fluctuations.
Short Term
Long Term
Extra Long Term
Filtered Long Term
• Table Display
An optional feature that places a concise summary table on the chart. It shows valuation states, trend direction, volatility condition, and other metrics, letting you observe multi-angle readings at a glance.
• Alerts
Multiple alert triggers can be set up—for crossing into overvaluation zones, for abrupt changes in trend, or for high volatility detection. Traders can stay informed without needing to watch charts continuously.
Why These Indicators Were Merged
• RSI (Relative Strength Index)
RSI is a cornerstone momentum oscillator that interprets speed and change of price movements. It has widespread recognition among traders for detecting potential overbought or oversold conditions. Including RSI provides a tried-and-tested layer of momentum insight.
• Stochastic Oscillator
This oscillator evaluates the closing price relative to its recent price range. Its responsiveness makes it valuable for pinpointing near-term price fluctuations. Where RSI offers a broader momentum picture, Stochastic adds fine-tuned detection of short-lived rallies or pullbacks.
• MFI (Money Flow Index)
MFI assesses buying and selling pressure by incorporating volume data. Many technical tools are purely price-based, but MFI’s volume component helps address questions of liquidity and actual money flow, offering a glimpse of how robust or weak a current move might be.
• CCI (Commodity Channel Index)
CCI shows how far price lies from its statistically “typical” trend. It can spot emerging trends or warn of overextension. Using CCI alongside RSI and Stochastic further refines the valuation layer by capturing price deviation from its underlying trajectory.
• ADX (Average Directional Index)
ADX reveals the strength of a trend but does not specify its direction. This is especially useful in combination with other oscillators that focus on bullish or bearish momentum. ADX can clarify whether a market is truly trending or just moving sideways, lending deeper context to the indicator's broader signals.
• MACD (Moving Average Convergence Divergence)
MACD is known for detecting momentum shifts via the interaction of two moving averages. Its inclusion ensures the indicator can capture transitional phases in market momentum. Where RSI and Stochastic concentrate on shorter-term changes, MACD has a slightly longer horizon for identifying robust directional changes.
• Momentum and ROC (Rate of Change)
Momentum and ROC specifically measure the velocity of price moves. By indicating how quickly (or slowly) price is changing compared to previous bars, they help confirm whether a trend is gathering steam, losing it, or is in a transitional stage.
• MVRV-Inspired Ratio
Drawn loosely from the concept of comparing market value to some underlying historical or fair-value metric, an MVRV-style ratio can help identify if an asset is trading above or below a considered norm. This additional viewpoint on valuation goes beyond simple price-based oscillations.
• Z-Score
Z-Score interprets how many standard deviations current prices deviate from a central mean. This statistical measure is often used to identify extreme conditions—either overly high or abnormally low. Z-Score helps highlight potential mean reversion setups by showing when price strays far from typical levels.
By merging these distinct viewpoints—momentum oscillators, trend strength gauges, volume flow, standard deviation extremes, and fundamental-style valuation measures—the indicator aims to create a well-rounded, carefully balanced final readout. Each component serves a specialized function, and together they can mitigate the weaknesses of a single metric acting alone.
Summary
This indicator simplifies multi-indicator analysis by fusing numerous popular technical signals into one tool. You can switch between short-term and long-term valuation perspectives or adopt a classic Z-Score approach for spotting price extremes. The universal trend line clarifies direction, while user-friendly color schemes, optional tabular summaries, and customizable alerts empower traders to maintain awareness without constantly monitoring every market tick.
Disclaimer
The indicator is made for educational and informational use only, with no claims of guaranteed profitability. Past data patterns, regardless of the indicators used, never ensure future results. Always maintain diligent risk management and consider the broader market context when making trading decisions. This indicator is not personal financial advice, and Uptrick disclaims responsibility for any trading outcomes arising from its use.
BBVOL SwiftEdgeBBVOL SwiftEdge – Precision Scalping with Volume and Trend Filtering
Optimized for scalping and short-term trading on fast-moving markets (e.g., 1-minute charts), BBVOL SwiftEdge combines Bollinger Bands, Heikin Ashi smoothing, volume momentum, and EMA trend alignment to deliver actionable buy/sell signals with visual trend cues. Ideal for forex, crypto, and stocks.
What Makes BBVOL SwiftEdge Unique?
Unlike traditional Bollinger Bands scripts that focus solely on price volatility, BBVOL SwiftEdge enhances signal precision by:
Using Heikin Ashi to filter out noise and confirm trend direction, reducing false signals in choppy markets.
Incorporating volume analysis to ensure signals align with significant buying or selling pressure (customizable thresholds).
Adding an EMA overlay to keep trades in sync with the short-term trend.
Coloring candlesticks (green for bullish, red for bearish, purple for consolidation) to visually highlight market conditions at a glance.
How Does It Work?
Buy Signal: Triggers when price crosses above the lower Bollinger Band, Heikin Ashi shows bullish momentum (close > open), buy volume exceeds your set threshold (default 30%), and price is above the EMA. A green triangle appears below the candle.
Sell Signal: Triggers when price crosses below the upper Bollinger Band, Heikin Ashi turns bearish (close < open), sell volume exceeds the threshold (default 30%), and price is below the EMA. A red triangle appears above the candle.
Trend Visualization: Candles turn green when price is significantly above the Bollinger Bands’ basis (indicating a bullish trend), red when below (bearish trend), or purple when near the basis (consolidation), based on a customizable threshold (default 10% of BB width).
Risk Management: Each signal calculates a stop-loss (10% beyond the opposite band) and take-profit (opposite band), plotted for reference.
How to Use It
Timeframe: Best on 1-minute to 5-minute charts for scalping; test higher timeframes for swing trading.
Markets: Works well in volatile markets like forex pairs (e.g., EUR/USD), crypto (e.g., BTC/USD), or liquid stocks.
Customization: Adjust Bollinger Bands length (default 10), multiplier (default 1.2), volume thresholds (default 30%), EMA length (default 3), and consolidation threshold (default 0.1%) to match your strategy.
Interpretation: Look for green/red triangles as entry signals, confirmed by candle colors. Purple candles suggest caution—wait for a breakout. Use stop-loss/take-profit levels for trade management.
Underlying Concepts
Bollinger Bands: Measures volatility and identifies overbought/oversold zones.
Heikin Ashi: Smooths price action to emphasize trend direction.
Volume Momentum: Calculates cumulative buy/sell volume percentages to confirm market strength (e.g., buyVolPercent = buyVolume / totalVolume * 100).
EMA: A fast-moving average (default length 3) ensures signals align with the immediate trend.
Chart Setup
The chart displays Bollinger Bands (orange), Heikin Ashi close (green circles), EMA (purple), and volume-scaled lines (lime/red). Signals are marked with triangles, and candle colors reflect trend state. Keep the chart clean by focusing on these outputs for clarity.
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.
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📊 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.
Cluster Reversal Zones📌 Cluster Reversal Zones – Smart Market Turning Point Detector
📌 Category : Public (Restricted/Closed-Source) Indicator
📌 Designed for : Traders looking for high-accuracy reversal zones based on price clustering & liquidity shifts.
🔍 Overview
The Cluster Reversal Zones Indicator is an advanced market reversal detection tool that helps traders identify key turning points using a combination of price clustering, order flow analysis, and liquidity tracking. Instead of relying on static support and resistance levels, this tool dynamically adjusts to live market conditions, ensuring traders get the most accurate reversal signals possible.
📊 Core Features:
✅ Real-Time Reversal Zone Mapping – Detects high-probability market turning points using price clustering & order flow imbalance.
✅ Liquidity-Based Support/Resistance Detection – Identifies strong rejection zones based on real-time liquidity shifts.
✅ Order Flow Sensitivity for Smart Filtering – Filters out weak reversals by detecting real market participation behind price movements.
✅ Momentum Divergence for Confirmation – Aligns reversal zones with momentum divergences to increase accuracy.
✅ Adaptive Risk Management System – Adjusts risk parameters dynamically based on volatility and trend state.
🔒 Justification for Mashup
The Cluster Reversal Zones Indicator contains custom-built methodologies that extend beyond traditional support/resistance indicators:
✔ Smart Price Clustering Algorithm: Instead of plotting fixed support/resistance lines, this system analyzes historical price clustering to detect active reversal areas.
✔ Order Flow Delta & Liquidity Shift Sensitivity: The tool tracks real-time order flow data, identifying price zones with the highest accumulation or distribution levels.
✔ Momentum-Based Reversal Validation: Unlike traditional indicators, this tool requires a momentum shift confirmation before validating a potential reversal.
✔ Adaptive Reversal Filtering Mechanism: Uses a combination of historical confluence detection + live market validation to improve accuracy.
🛠️ How to Use:
• Works well for reversal traders, scalpers, and swing traders seeking precise turning points.
• Best combined with VWAP, Market Profile, and Delta Volume indicators for confirmation.
• Suitable for Forex, Indices, Commodities, Crypto, and Stock markets.
🚨 Important Note:
For educational & analytical purposes only.
