Multi-Timeframe Squeeze Pro/DIM/Momentum/MAIMPORTANT NOTE:
-> The table will not display any timeframes lower than the current one
-> This indicator combine multiple popular indicators and give ability to use them on Multiple timeframes (MFT)
-> Indicators used for the MFT are: Squeeze / Momentum / 10X DIM and Stacked MA (or EMA)
-> Give at glance a good way to see the trend all different timeframes
-> If you are using in combination with squeeze pro please use the one from @Beardy_Fred since it matches the colours and condition used
Credits :
-> J. Welles Wilder creating the Directional Movement System (DMS) (1978); and
-> John Carter applying the DMS to create the popular Simpler Trading 10X Bars indicator.
-> @Beardy_Fred creating a first version including MOM and SQZ
-> Makit0's evolution of Lazybear's script to factor in the TTM Squeeze Pro upgrades - Squeeze PRO Arrows
I have adapted the version from @Beardy_Fred to provide a more complete and customisable indicator while including also the Stacked EMA/MA for further validation
Explanation:
You can learn more about each indicators following those links:
Squeeze Pro:
10X:
Momentum Histogram:
The stacked EMA/MA highlights when the MA/EMA are in order:
Red when they are stacked from the highest to the lowest
Green when they are stacked from the lowest to the highest
Yellow when they are stacked without a clear order
Customisation:
You can customise:
Timeframes
Settings for each indicators (10X/MA/Momentum/Squeeze)
Colors
Visibility
Trade Signals:
If you are going Long, Since this is a combination ideally on the timeframe you are trading you should have all green + green on the above timeframes (those colors are the default ones but can be changed)
-> Green on 10X indicator meaning you are in an uptrend
-> EMA or MA (depending on the configuration of the indicator) Green meaning EMA or MA
-> Squeeze should be Orange or Red ideally (indicating an high or medium Squeeze)
-> Momentum should be Cyan indicating an increase in momentum (while Dark Blue could indicate a reversal)
Standalone indicators:
- Squeeze Pro
- 10X Bar
- Stacked MA
- Momentum
Поиск скриптов по запросу "momentum"
Reverse Stochastic Momentum Index On ChartIntroducing the Reverse Stochastic Momentum Index "On Chart" version
According to Investopedia :
“The Stochastic Momentum Index (SMI) is a more refined version of the stochastic oscillator, employing a wider range of values and having a higher sensitivity to closing prices.”
The SMI is considered a refinement of the stochastic oscillator developed by William Blau and introduced in 1993 in an attempt to provide a more reliable indicator, less subject to false swings.
It calculates the distance of the current closing price as it relates to the median of the high/low range of price.
The SMI has a normal range of values between +100 and -100.
When the present closing price is higher than the median, or midpoint value of the high/low range, the resulting value is positive.
When the current closing price is lower than that of the midpoint of the high/low range, the SMI has a negative value.
Here I have reverse engineered the SMI formula to derive 2 functions.
One function calculates the chart price at which the SMI will reach a particular SMI scale value.
The second function calculates the chart price at which the SMI will crossover its signal line.
I have employed those functions here to give the "crossover" price levels for :
Upper alert level ( default 40, color : aqua blue )
Mid-Line ( default value 0, color : white )
Lower alert level ( default -40, color : purple )
Signal line ( default 13, colors : bright red & lime green )
And also to give the SMI eq price ( colors : red & green )
The midline, upper and lower alert levels return the closing price which would make SMI equal to their respective values
The user can infer from this that.....
Closing above these prices will cause the Stochastic Momentum Index to cross above the associated levels
Closing below these prices will cause the Stochastic Momentum Index to cross below the associated levels
Signal line returns the closing price where Stochastic Momentum Index is equal to its signal line
The user can infer from this that.....
Closing above this price will cause the Stochastic Momentum Index to cross above the signal line
Closing below this price will cause the Stochastic Momentum Index to cross below the signal line
SMI eq price returns the closing price which would make the SMI equal to its previous value
The user can infer from this that.....
Closing above this price will cause the Stochastic Momentum Index to increase
Closing below this price will cause the Stochastic Momentum Index to decrease
Note : all returned prices have a returned value filter to replace any values below zero with zero to help prevent auto focus issues.
These levels are displayed as plotted lines on the chart and also as an optional infobox with choice of displayed info.
This allows the user to see directly on the chart the interplay between the various crossover levels and price action and to precisely plan entries, exits and stops for their SMI based trades.
Traditionally traders and analysts will consider:
Positives values above 40 indicate a bullish trend
Negative values below -40 indicate a bearish trend .
Common traditional ways to derive signals from the SMI :
When the SMI crosses below -40 and then moves back above it, a buy signal is generated.
When the SMI crosses above +40 and then moves back below it, a sell signal is generated.
When the SMI line crosses above the signal line. A signal to buy is generated
When the SMI line crosses below the signal line signal to sell is generated.
When the SMI crosses above the zeroline, signal line and the SMI eq level many interpret that as a full bullish bias signal and take trades only in that direction, vice versa for bearish bias.
Traders also look for divergences between the SMI and price action.
The SMI is often used in conjunction with the Chande Momentum Oscillator or R squared indicator to determine overall market trendiness where the SMI is used to determine the direction of the trend, and also with volume indicators to show if the momentum carries significant selling or buying pressure.
CT Reverse Chande Momentum OscillatorIntroducing the Caretakers Reverse Chande Momentum Oscillator.
The Chande momentum oscillator is a technical momentum indicator which calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
It is used to gauge “pure momentum”.
It bears similarities to other momentum indicators such as the Stochastic, Rate of Change and the Relative Strength Index, but other unique features render it a handy tool in the traders handset.
The CMO was developed by Tushar Chande.
The author introduced the indicator in his 1994 book “The New Technical Trader “.
The CMO has a normal range of values between +100 and -100.
I have reverse engineered the CMO formula to derive a dual purpose function.
The function can calculate the chart price at which the CMO will reach a particular CMO scale value.
The function can also calculate the chart price at which the CMO will equal its previous value.
I have employed this function here to give the price level where the CMO will equal :
Upper alert level ( default 50 )
Zero-Line
Lower alert level ( default -50 )
Previous CMO value
These crossover levels are displayed via an optional infobox with choice of user selected info.
The advantage of knowing the exact prices that this will happen should give the user an additional edge and precision in risk management.
Traditionally traders and analysts will consider:
Positives values above 50 indicate an “overbought” condition
Negative values below -50 indicate an “oversold” condition
Common traditional ways to derive signals from the CMO :
When the CMO crosses above the zeroline, a buy signal is generated.
When the CMO crosses below the zeroline, a sell signal is generated.
When the SMI crosses below -50 and then moves back above it, a buy signal is generated.
When the SMI crosses above +50 and then moves back below it, a sell signal is generated.
Traditionally, traders also look for divergences between the CMO and price action.
Chande Momentum oscillating in a narrower band around the zero line, with no penetration of the Overbought and Oversold levels indicates a ranging market.
This should not be confused with Chande Momentum oscillating between either the Overbought and the zero line, or the Oversold level and the zero line, which indicates a strong up, or down-trend.
It is traditionally considered that the strongest trend signals are from failed swing patterns.
It measures momentum on both up and down days and does not smooth results, triggering more frequent oversold and overbought penetrations.
The CMO is often used to determine overall market trendiness in conjunction with the SMI where the SMI is used to determine the direction of the trend, and also with volume indicators to show if the momentum carries significant selling or buying pressure.
Price Action and 3 EMAs Momentum plus Sessions FilterThis indicator plots on the chart the parameters and signals of the Price Action and 3 EMAs Momentum plus Sessions Filter Algorithmic Strategy. The strategy trades based on time-series (absolute) and relative momentum of price close, highs, lows and 3 EMAs.
I am still learning PS and therefore I have only been able to write the indicator up to the Signal generation. I plan to expand the indicator to Entry Signals as well as the full Strategy.
The strategy works best on EURUSD in the 15 minutes TF during London and New York sessions with 1 to 1 TP and SL of 30 pips with lots resulting in 3% risk of the account per trade. I have already written the full strategy in another language and platform and back tested it for ten years and it was profitable for 7 of the 10 years with average profit of 15% p.a which can be easily increased by increasing risk per trade. I have been trading it live in that platform for over two years and it is profitable.
Contributions from experienced PS coders in completing the Indicator as well as writing the Strategy and back testing it on Trading View will be appreciated.
STRATEGY AND INDICATOR PARAMETERS
Three periods of 12, 48 and 96 in the 15 min TF which are equivalent to 3, 12 and 24 hours i.e (15 min * period / 60 min) are the foundational inputs for all the parameters of the PA & 3 EMAs Momentum + SF Algo Strategy and its Indicator.
3 EMAs momentum parameters and conditions
• FastEMA = ema of 12 periods
• MedEMA = ema of 48 periods
• SlowEMA = ema of 96 periods
• All the EMAs analyse price close for up to 96 (15 min periods) equivalent to 24 hours
• There’s Upward EMA momentum if price close > FastEMA and FastEMA > MedEMA and MedEMA > SlowEMA
• There’s Downward EMA momentum if price close < FastEMA and FastEMA < MedEMA and MedEMA < SlowEMA
PA momentum parameters and conditions
• HH = Highest High of 48 periods from 1st closed bar before current bar
• LL = Lowest Low of 48 periods from 1st closed bar from current bar
• Previous HH = Highest High of 84 periods from 12th closed bar before current bar
• Previous LL = Lowest Low of 84 periods from 12th closed bar before current bar
• All the HH & LL and prevHH & prevLL are within the 96 periods from the 1st closed bar before current bar and therefore indicative of momentum during the past 24 hours
• There’s Upward PA momentum if price close > HH and HH > prevHH and LL > prevLL
• There’s Downward PA momentum if price close < LL and LL < prevLL and HH < prevHH
Signal conditions and Status (BuySignal, SellSignal or Neutral)
• The strategy generates Buy or Sell Signals if both 3 EMAs and PA momentum conditions are met for each direction and these occur during the London and New York sessions
• BuySignal if price close > FastEMA and FastEMA > MedEMA and MedEMA > SlowEMA and price close > HH and HH > prevHH and LL > prevLL and timeinrange (LDN&NY) else Neutral
• SellSignal if price close < FastEMA and FastEMA < MedEMA and MedEMA < SlowEMA and price close < LL and LL < prevLL and HH < prevHH and timeinrange (LDN&NY) else Neutral
Entry conditions and Status (EnterBuy, EnterSell or Neutral)(NOT CODED YET)
• ENTRY IS NOT AT THE SIGNAL BAR but at the current bar tick price retracement to FastEMA after the signal
• EnterBuy if current bar tick price <= FastEMA and current bar tick price > prevHH at the time of the Buy Signal
• EnterSell if current bar tick price >= FastEMA and current bar tick price > prevLL at the time of the Sell Signal
Linear Momentum and Performance IndicatorsThis a porting to Trading View of the 12 new indicators introduced in IFTA Journal (January Edition) by Akram El Sherbini, MFTA, CFTe, CETA.
Indicators are available in "Linear Momentum and Performance Indicators" at page four.
IFTA Journal is available below:
ifta.org
Indicators implemented herein:
Linear Force Index: The linear force index LFI measures the force of buyers and sellers during rallies and declines, respectively. It combines two important pieces of market information—the price acceleration
and volumes.
Pressure Index: The pressure index PRI measures the buying and selling pressure over a certain range within a time interval by moving around its zero line. The index indicates a rise in buying pressure when it crosses above the zero line and a rise in selling pressure
when it crosses below the zero line level. The buying and selling force moves the last price during the session to form a range with low and high boundaries.
Strength Index Index: The strength index SI is a leading indicator to the pressure index. It measures the ability of buyers to resist sellers and vice versa. SI of today is the ratio of the latest pressure index value to the strain of today.
Power Index: It measures the buying and selling power within a time interval by moving around its zero line.
Intensity Index: The intensity index II measures the buying and selling intensity within a time interval by moving around its zero line.
Dynamic Strength Index: The sole purpose of the dynamic strength index DSI and the integral dynamic strength index IDSI is to lead their intensity indicator peers.
Integral Force Index
Integral Pressure Index
Integral Strength Index
Integral Power Index
Integral Intensity Index
Integral Dynamic Strength Index
The following example shows a trade following the signal while several indicators are crossing the zero line:
Integral performance indicators have a fewer number of trades than the performance indicators. This result is normal, as the integral indicators are less sensitive than their peers. Moreover, the power, intensity, and dynamic strength are less sensitive than the force, pressure, and strength indicators. The same applies for their integrals. Therefore, the integrals of power, intensity, and dynamic strength indicators are more inclined to be medium-term indicators.
As the paper is suggesting "the linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Technical indicators are using biased mathematical implementations. For example Momentum Index is in reality a velocity indicator, Force index a Momentum indicator and so on. From a Physical perspective correct momentum, force, velocity etc. needs to be corrected and re-categorized.
The author also gives important insights in how these indicators can be used "simultaneously to identify price turning points and filter irrelevant divergences."
"This paper will attempt to adjust the price momentum and force concepts introduced by Welles Wilder and Alexander Elder, respectively. By introducing the concept of linear momentum, new indicators will emerge to dissect the market performance into six main elements: market’s force, pressure, strength, power, intensity, and dynamic strength. This will lead to a deeper insight about market action. The leading performance indicators can be used simultaneously to identify price turning points and filter irrelevant divergences. The linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Suggestions and feedbacks are welcome
Hope you enjoy this,
CryptoStatistical
Linear Momentum and Performance Indicators (IFTA Jan 2019)This a porting to Trading View of the 12 new indicators introduced in IFTA Journal (January Edition) by Akram El Sherbini, MFTA, CFTe, CETA.
Indicators are available in "Linear Momentum and Performance Indicators" at page four.
IFTA Journal is available below:
ifta.org
Indicators implemented herein:
Linear Force Index: The linear force index LFI measures the force of buyers and sellers during rallies and declines, respectively. It combines two important pieces of market information—the price acceleration
and volumes.
Pressure Index: The pressure index PRI measures the buying and selling pressure over a certain range within a time interval by moving around its zero line. The index indicates a rise in buying pressure when it crosses above the zero line and a rise in selling pressure
when it crosses below the zero line level. The buying and selling force moves the last price during the session to form a range with low and high boundaries.
Strength Index Index : The strength index SI is a leading indicator to the pressure index. It measures the ability of buyers to resist sellers and vice versa. SI of today is the ratio of the latest pressure index value to the strain of today.
Power Index : It measures the buying and selling power within a time interval by moving around its zero line.
Intensity Index : The intensity index II measures the buying and selling intensity within a time interval by moving around its zero line.
Dynamic Strength Index : The sole purpose of the dynamic strength index DSI and the integral dynamic strength index IDSI is to lead their intensity indicator peers.
Integral Force Index
Integral Pressure Index
Integral Strength Index
Integral Power Index
Integral Intensity Index
Integral Dynamic Strength Index
The following example shows a trade following the signal while several indicators are crossing the zero line:
Integral performance indicators have a fewer number of trades than the performance indicators. This result is normal, as the integral indicators are less sensitive than their peers. Moreover, the power, intensity, and dynamic strength are less sensitive than the force, pressure, and strength indicators. The same applies for their integrals. Therefore, the integrals of power, intensity, and dynamic strength indicators are more inclined to be medium-term indicators.
As the paper is suggesting "the linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Technical indicators are using biased mathematical implementations. For example Momentum Index is in reality a velocity indicator, Force index a Momentum indicator and so on. From a Physical perspective correct momentum, force, velocity etc. needs to be corrected and re-categorized.
The author also gives important insights in how these indicators can be used "simultaneously to identify price turning points and filter irrelevant divergences."
"This paper will attempt to adjust the price momentum and force concepts introduced by Welles Wilder and Alexander Elder, respectively. By introducing the concept of linear momentum, new indicators will emerge to dissect the market performance into six main elements: market’s force, pressure, strength, power, intensity, and dynamic strength. This will lead to a deeper insight about market action. The leading performance indicators can be used simultaneously to identify price turning points and filter irrelevant divergences. The linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Suggestions and feedback are welcome
Hope you enjoy this,
CryptoStatistical
Seasonal Momentum Indicator This is basically a 5-period seasonal average with an applied momentum (10 ) applied. This is plotted and compared to the current momentum (10). The current momentum is in red while the seasonal momentum is in blue.
You can see that whenever the seasonal momentum and the current momentum are in the same direction, the probability of the trend continuing is higher. Also whenever there is a divergence in the two; the red line (current momentum) will often catch up to the blue (seasonal momentum).
Another use of this indicator is as a divergence detector. If you turn off the red line, you will have only the blue line plotted on the graph. Take this and apply lines to see if the momentum diverges from the price (see example).
I hope you enjoy this one. It only works for securities which have a five year record. You can use it on different time frames but the annual is probably the best and most useful.
Happy Trading
--SpreadEagle71
CMO (Chande Momentum Oscillator)Hi
Let me introduce my CMO (Chande Momentum Oscillator) script.
This indicator plots Chandre Momentum Oscillator. This indicator was
developed by Tushar Chande. A scientist, an inventor, and a respected
trading system developer, Mr. Chande developed the CMO to capture what
he calls "pure momentum". For more definitive information on the CMO and
other indicators we recommend the book The New Technical Trader by Tushar
Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder`s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to
clearly see changes in net momentum using the 0 level. The bounded scale
also allows you to conveniently compare values across different securities.
RSI Median DeviationRSI Median Deviation
Thank you to @QuantumResearch for part of the code and inspiration!
Introduction:
With my first published indicator i wanted to start simple, so i created a RSI that has no static OB/OS signals and can act as a Momentum-Strength-Gauge.
Inspiration came from the Median Deviation Bands indicator by QuantumResearch!
TL;DR:
Traditional RSI says "70 is overbought" like it's a universal law. Guess what: it's not .
This indicator figures out where overbought and oversold actually are for your specific chart and timeframe, using real statistics.
What Makes it Different
Most RSI indicators slap horizontal lines at 70/30 and call it a day. Problem is, that works great... until it doesn't. In a strong trend, RSI can camp out above 70 for weeks. In choppy markets, it'll ping-pong across those levels.
RSI Median Deviation takes a smarter approach:
1. Adaptive zones that move with your data
2. Median + standard deviation bands (the 50th percentile ±2σ) that show where RSI is statistically extreme
3. Rare signals that actually mean something
4. Optional smoothed bands that adapt to current market conditions in real-time
Think of it like this: instead of asking "is RSI above 70?", we're asking "is RSI acting weird compared to its recent behavior?"
Key Features
- Statistical bands built from the RSI's actual median and standard deviation
- Multiple MA options (TEMA, WMA, HMA, ALMA, etc.) for smoothing.
- Dual detection modes: Pure stats OR MA bands
- Background highlighting when something genuinely extreme happens
- Diamond markers for ultra-rare RSI readings (<25 or >85)
- 9 color themes
- Works on all timeframes
How to Actually Use This Thing
1. Trend Bias
RSI line turns green above 60 (bullish bias), red below 47 (bearish bias).
2. Mean-Reversion Plays
Dark green background = RSI dropped below the lower 2σ band → statistically oversold
Dark magenta background = RSI spiked above the upper 2σ band → statistically overbought
3. Momentum Strength Gauge
Watch the distance between the smoothed RSI and the median line:
Wide gap = strong trend in play
Converging = momentum dying, consolidation likely
4. Extra Confirmation
Those diamond shapes at the top/bottom? That's RSI hitting <25 or >85 – genuinely extreme territory.
Recommended Settings:
RSI Length: 10
Median Length: 28
SD Length: 27
RSI MA Type: TEMA
RSI MA Length: 27
Band MA Type: WMA
Band Length: 37
The standard settings are optimized to have maximum use on all assets.
Works on everything, especially on daily or 4h charts for swing/position trading.
Last words:
RSI Median Deviation is the version that only gives signals if the ROC of your data is on the extreme side.
It'll give you fewer, better signals based on what's actually happening in the markets.
Perfect for traders who'd rather have quality over quantity.
Composite Market Momentum Indicator//@version=5
indicator("Composite Market Momentum Indicator", shorttitle="CMMI", overlay=false)
// Define Inputs
lenRSI = input.int(14, title="RSI Length")
lenMom = input.int(9, title="Momentum Length")
lenShortRSI = input.int(3, title="Short RSI Length")
lenShortRSISma = input.int(3, title="Short RSI SMA Length")
lenSMA1 = input.int(9, title="Composite SMA 1 Length")
lenSMA2 = input.int(34, title="Composite SMA 2 Length")
// Step 1: Create a 9-period momentum indicator of the 14-period RSI
rsiValue = ta.rsi(close, lenRSI)
momRSI = ta.mom(rsiValue, lenMom)
// Step 2: Create a 3-period RSI and a 3-period SMA of that RSI
shortRSI = ta.rsi(close, lenShortRSI)
shortRSISmoothed = ta.sma(shortRSI, lenShortRSISma)
// Step 3: Add Step 1 and Step 2 together to create the Composite Index
compositeIndex = momRSI + shortRSISmoothed
// Step 4: Create two simple moving averages of the Composite Index
sma1 = ta.sma(compositeIndex, lenSMA1)
sma2 = ta.sma(compositeIndex, lenSMA2)
// Step 5: Plot the composite index and its two simple moving averages
plot(compositeIndex, title="Composite Index", color=color.new(#f7cf05, 0), linewidth=2)
plot(sma1, title="SMA 13", color=color.new(#f32121, 0), linewidth=1, style=plot.style_line)
plot(sma2, title="SMA 33", color=color.new(#105eef, 0), linewidth=1, style=plot.style_line)
// Add horizontal lines for reference
hline(0, "Zero Line", color.new(color.gray, 50))
SuperTrend Fusion — Trend + Momentum + Volatility FilterSuperTrend Fusion — Trend + Momentum + Volatility Filter
SuperTrend Fusion — ATP is an original, multi-factor trend-filtering tool that enhances the classic SuperTrend by combining three market dimensions in one unified model:
1. Trend direction (SuperTrend)
Provides the base trend structure using ATR-based volatility bands.
2. Momentum confirmation (Average Force – adapted)
An adapted version of an open-source “Average Force” concept published on TradingView by racer8.
This component measures where closing price sits relative to recent highs/lows, smoothed to capture directional pressure.
3. Market condition filtering (Choppiness Index)
Filters out sideways, non-trending zones where SuperTrend alone typically produces false flips.
Together, these components create a cleaner, more selective system that focuses on higher-quality SuperTrend reversals, avoiding the most common whipsaws that occur during low-momentum or high-choppiness periods.
🔍 How it Works
A long signal occurs when:
- SuperTrend flips from downtrend to uptrend
- Momentum (AF) is positive (optional filter)
- The market is trending and not excessively choppy (optional filter)
A short signal triggers under the symmetrical conditions.
Filtered signals are visually marked with subtle “X” markers so traders can understand when a raw SuperTrend flip was rejected by the filters.
The indicator also includes:
Enhanced styling for better visibility
Colored bars during valid signals
Optional background highlight during choppy periods
🎯 What This Indicator Is Designed For
This tool aims to:
- Improve the quality of SuperTrend entries
- Remove many low-probability signals
- Help traders visually identify when the market has the momentum and structure required for cleaner trend continuation
It is not intended to predict markets or guarantee accuracy; rather, it provides structure and clarity for decision-making based on technical rules.
⚙️ Inputs
- ATR Length & Factor (SuperTrend)
- Average Force Period & Smoothing
- Choppiness Length & Threshold
- Option to enable/disable each filter individually
📘 Credits
This script includes an adapted version of an open-source “Average Force” function originally published on TradingView by its author, racer8.
SuperTrend and Choppiness Index components are derived from classical, public-domain formulas.
📌 Important Notes
This indicator is not a strategy and does not guarantee performance.
Signals are based on historical calculations only and do not use lookahead.
Past performance does not guarantee future results.
Always test different assets and timeframes before using in live conditions.
👍 Recommended Usage
For a clean experience:
- Use on standard candlestick charts
- Avoid non-standard chart types (Renko, Heikin Ashi, Kagi, Range)
- Combine with your own risk management and trade planning
Market X-Ray Dashboard: Trend, Momentum & Volume [THF]This script is designed to solve a common problem for traders: "Analysis Paralysis." Instead of cluttering the chart with multiple oscillators and indicators, the Market X-Ray Dashboard aggregates key market data into a clean, scannable table. It provides a real-time confluence check by combining Trend, Momentum, and Volume analysis.
How it Works (The Logic)
The dashboard monitors four distinct technical factors and assigns a status based on specific thresholds. Here is the mathematical breakdown of the components:
1. RSI (Relative Strength Index)
Period: 14 (Default)
Logic: Measures the speed and change of price movements.
Overbought (>70): High probability of reversal (Bearish).
Bullish Zone (<45): Indicates potential upside room.
Oversold (<30): Strong potential for a bounce.
2. MACD (Moving Average Convergence Divergence)
Settings: 12, 26, 9
Logic: Used for trend following.
Buy Signal: MACD Line crosses above Signal Line + Histogram is increasing.
Sell Signal: MACD Line crosses below Signal Line + Histogram is decreasing.
3. Stochastic RSI
Settings: 14, 14, 3, 3
Logic: A more sensitive momentum indicator to catch short-term pivots.
Uses smoothed K and D lines to filter out noise.
Identifies "Strong Buy" zones when the oscillator is below 20 and "Strong Sell" when above 80.
4. Volume Analysis (New Feature)
Logic: Volume is the fuel of the market. This component compares the current volume bar against a 20-period Simple Moving Average (SMA).
High Vol Alert: If the current volume exceeds the average by 1.5x (customizable), it triggers a "High Vol 🔥" alert.
Color Coding: The volume cell adapts to the candle color. High volume on a green candle suggests strong buying pressure, while high volume on a red candle suggests strong selling pressure.
The "Overall" Confluence Algorithm
The final row provides an algorithmic summary based on the confluence of the above indicators:
Uptrend 🚀: Triggered when at least 2 out of 3 momentum indicators (RSI, MACD, Stoch) align on a Buy signal.
Downtrend 🔻: Triggered when at least 2 out of 3 indicators align on a Sell signal.
Neutral/Ranging: When signals are conflicting (e.g., RSI is overbought but MACD is bullish).
Features & Settings
Fully Customizable Colors: Users can change the colors for Strong Buy, Buy, Neutral, Sell, and Strong Sell to fit their chart theme (Dark/Light mode).
Adjustable Thresholds: All lengths (RSI, MACD, Volume SMA) are adjustable in the settings menu.
Volume Multiplier: Users can define what constitutes "High Volume" (default is 1.5x the average).
How to Use This Tool
This dashboard should be used as a confirmation tool.
Trend Confirmation: Do not trade blindly. If the "Overall" status says "Uptrend," look for price action setups (like support bounces) to go long.
Volume Validation: Use the Volume row to validate breakouts. A breakout with "Low Vol" is likely a fake-out.
Divergence Spotting: If the price is making a new high but the Dashboard shows RSI entering "Strong Sell," be cautious of a reversal.
Disclaimer:
This tool is for informational purposes only and does not guarantee profits. Technical analysis works best when combined with risk management and fundamental analysis.
Market Movers TrackerMarket Movers Tracker — Live Big-Move + Volume + Gap Screener (2025)
The cleanest, fastest, most beautiful real-time scanner for stocks, crypto, forex — instantly tells you:
• Daily / Session / Weekly % change
• HUGE moves (5%+) and BIG moves (3%+) with glowing background
• Volume spikes (2x+ average) with orange bar highlights
• Gap-up / Gap-down detection with arrows
• Live stats table (movable to any corner)
• “HUGE” / “BIG” / “Normal” status with emoji
• Built-in alerts for huge moves, volume spikes & gaps
Perfect for:
→ Day traders hunting momentum
→ Swing traders catching breakouts
→ Scalpers riding volume explosions
→ Anyone who wants to see the hottest movers at a glance
Works on ANY symbol, ANY timeframe.
Zero lag. Zero repainting. Pure price + volume truth.
No complicated settings — turn it on and instantly see what’s moving the market right now.
Not financial advice. Just the sharpest scanner on TradingView.
Made with love for the degens, apes, and momentum chads & volume junkies.
Relative Volume EMA (RVOL)Relative Volume EMA (RVOL) measures the current bar’s volume relative to its typical volume over a selected lookback period.
It helps traders identify whether a price move is supported by real participation or if it’s occurring on weak, low-quality volume.
This version uses:
RVOL = Current Volume ÷ Volume EMA
Volume EMA Length: adjustable
Signal Threshold: a customizable horizontal line (default = 1.2)
How to Use
1. RVOL > 1.2 → High-Quality Momentum
A value above 1.2 indicates that the current bar has at least 20% more volume than normal, suggesting:
Strong conviction
Algorithmic activity
Momentum-backed breakout or breakdown
Higher probability trend continuation
These bars are ideal for confirming entries after a technical setup (e.g., pullback, engulfing pattern, Ichimoku trend confirmation, etc.).
2. RVOL < 1.0 → Weak or Low-Quality Move
When RVOL is below 1.0:
Volume is below average
Moves are more likely to fail or reverse
Breakouts are unreliable
Triggers lack institutional participation
These bars are best avoided for trade entries.
Why This Indicator Is Useful
In many strategies, price alone is not enough.
RVOL acts as a filter to ensure that your signals occur during times when the market is actually active and committed.
Typical use cases:
Confirm trend-following entries
Validate pullbacks and breakout candles
Filter out low-volume chop
Identify session-based volume surges
Improve risk-to-reward quality by entering only during true momentum
Recommended Settings
EMA Length: 20
Threshold Line: 1.2
Works well on Forex, Crypto, and Indices
Best used on 15m, 30m, 1H, and 4H charts
Mustang Algo - Momentum Trend Zone Backtest🐎 MUSTANG ALGO - Momentum Trend Zone Strategy
A complete trading system combining MACD momentum analysis with visual trend zones, full backtesting capabilities, and advanced risk management tools.
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🔹 OVERVIEW
Mustang Algo transforms traditional MACD analysis into a powerful visual trading system. It instantly identifies market bias through colored background zones and provides clear entry/exit signals with customizable stop loss and take profit management.
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🔹 KEY FEATURES
✅ Visual Trend Zones (Green = Bullish | Red = Bearish)
✅ Clear Buy/Sell Triangles on Chart
✅ Full Backtesting Engine
✅ Multiple Stop Loss Types
✅ Multiple Take Profit Types
✅ Trailing Stop Option
✅ Time Filter for Backtesting
✅ Real-time Info Panel
✅ Customizable Alerts
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🔹 HOW IT WORKS
The strategy uses a smoothed MACD system to detect trend changes:
- MACD Line (White): Fast EMA minus Slow EMA - shows raw momentum
- Signal Line (Yellow): EMA of MACD - shows smoothed trend direction
- Trend Zone: Changes when the smoothed signal line crosses zero
- Entry Signals: Generated at zone transitions
When the trend line crosses above zero → GREEN zone → BUY signal 🔺
When the trend line crosses below zero → RED zone → SELL signal 🔻
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🔹 STOP LOSS OPTIONS
🛑 Percentage: Fixed percentage from entry price
🛑 ATR-Based: Dynamic SL based on market volatility
🛑 Fixed Points: Set number of points/pips
🛑 Swing Low/High: Uses recent swing levels as stops
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🔹 TAKE PROFIT OPTIONS
🎯 Percentage: Fixed percentage target
🎯 ATR-Based: Dynamic TP based on volatility
🎯 Fixed Points: Set number of points/pips
🎯 Risk Reward: Automatic TP based on R:R ratio (e.g., 2:1, 3:1)
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🔹 TRAILING STOP
📈 Percentage-Based: Trail by a fixed percentage
📈 ATR-Based: Trail using ATR multiplier for dynamic adjustment
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🔹 SETTINGS
MACD Parameters:
- Fast Length (default: 12)
- Slow Length (default: 26)
- Signal Length (default: 9)
- Trend Smoothing (default: 5)
Risk Management:
- Enable/Disable Stop Loss
- Enable/Disable Take Profit
- Enable/Disable Trailing Stop
- Customize all SL/TP parameters
Visual Options:
- Show/Hide Buy/Sell Triangles
- Show/Hide SL/TP Lines
- Show/Hide Labels
Time Filter:
- Set Start Date for backtest
- Set End Date for backtest
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🔹 SIGNALS EXPLAINED
🟢 GREEN TRIANGLE (Below Bar):
Bullish zone detected - Consider LONG entry
🔴 RED TRIANGLE (Above Bar):
Bearish zone detected - Consider SHORT entry
🟢 GREEN BACKGROUND:
Currently in bullish trend zone
🔴 RED BACKGROUND:
Currently in bearish trend zone
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🔹 INFO PANEL
The real-time info panel (top right) displays:
- Current Trend Zone status
- MACD value
- Signal Line value
- Active SL Type
- Active TP Type
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🔹 ALERTS
Set up alerts for:
🔔 Buy Signals: "🐎 Mustang Algo: BUY Signal on {ticker} at {price}"
🔔 Sell Signals: "🐎 Mustang Algo: SELL Signal on {ticker} at {price}"
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🔹 BEST PRACTICES
1. Use higher timeframes (1H, 4H, Daily) for more reliable signals
2. Combine with price action and support/resistance levels
3. Adjust ATR multipliers based on asset volatility
4. Use Risk Reward ratio for consistent risk management
5. Backtest on your preferred asset before live trading
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🔹 RECOMMENDED TIMEFRAMES
⏱️ Scalping: 5M, 15M (more signals, more noise)
⏱️ Day Trading: 1H, 4H (balanced signals)
⏱️ Swing Trading: Daily, Weekly (fewer but stronger signals)
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🔹 MARKETS
Works on all markets:
📈 Forex
📈 Crypto
📈 Stocks
📈 Indices
📈 Commodities
📈 Futures
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🐎 RIDE THE TREND WITH MUSTANG ALGO!
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⚠️ DISCLAIMER
This indicator/strategy is for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Always use proper risk management, do your own research, and consider consulting a financial advisor before making any trading decisions. Use at your own risk.
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📝 VERSION HISTORY
v1.0 - Initial Release
- MACD-based trend detection
- Visual trend zones
- Multiple SL/TP options
- Full backtesting support
- Trailing stop functionality
- Time filter
- Info panel
- Alert system
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💬 FEEDBACK
If you find this strategy useful, please leave a comment or suggestion!
Your feedback helps improve future updates.
🐎 Happy Trading!
Morning Momentum//@version=5
indicator("Morning Momentum", overlay=true) // This is your one required declaration
// --- Define Time Window ---
startTime = timestamp("2025-11-28T09:30:00")
endTime = timestamp("2025-11-28T10:00:00")
inWindow = time >= startTime and time <= endTime
// --- Define Price Change ---
priceChange = (close - open) / open * 100
// --- Define Volume Spike ---
volumeSMA = ta.sma(volume, 20)
volumeSpike = volume > volumeSMA
// --- Trigger Condition ---
signal = inWindow and priceChange > 2 and volumeSpike
// --- Plot Signal ---
plotshape(signal, title="Momentum Signal", location=location.abovebar, color=color.green, style=shape.triangleup)
Turtle Momentum StrategyTurtle momentum strategy as per Momentum Trading Strategy article on Substack (Nov 26, 2025)
EMA 12-26-100 Momentum Strategy# Triple EMA Multi-Signal Momentum Strategy
## 📊 Overview
**Triple EMA Multi-Signal** is a comprehensive trend-following momentum strategy designed specifically for cryptocurrency markets. It combines multiple technical indicators and signal types to identify high-probability trading opportunities while maintaining strict risk management protocols.
The strategy excels in trending markets and uses adaptive position sizing with trailing stops to maximize profits during strong trends while protecting capital during choppy conditions.
## 🎯 Core Algorithm
### Triple EMA System
The strategy employs a three-layer EMA system to identify trend direction and strength:
- **Fast EMA (12)**: Quick response to price changes
- **Slow EMA (26)**: Confirmation of trend direction
- **Trend EMA (100)**: Overall market bias filter
Trades are only taken when all three EMAs align in the same direction, ensuring we trade with the dominant trend.
### Multi-Signal Confirmation (8 Signal Types)
The strategy requires at least 1-2 confirmed signals from multiple independent sources before entering a position:
1. **EMA Crossover** - Fast EMA crossing Slow EMA (primary signal)
2. **MACD Cross** - MACD line crossing signal line (momentum confirmation)
3. **RSI Reversal** - RSI bouncing from oversold/overbought zones
4. **Price Action** - Strong bullish/bearish candles (>60% of range)
5. **Volume Spike** - Above-average volume confirmation
6. **Breakout** - Price breaking 20-period high/low with volume
7. **Pullback to EMA** - Trend continuation after healthy retracement
8. **Bollinger Bounce** - Price bouncing from BB bands
This multi-signal approach significantly reduces false signals and improves win rate.
## 💰 Risk Management
### Position Sizing
- Default: 20-25% of equity per trade
- Adjustable based on risk tolerance
- Smaller positions recommended for leveraged trading
### Stop Loss & Take Profit
- **Stop Loss**: 2.0% (tight control of risk)
- **Take Profit**: 5.5% (2.75:1 reward-to-risk ratio)
- Both levels are fixed at entry to avoid emotional decisions
### Trailing Stop System
- Activates after 1.8% profit
- Trails at 1.3% below current price
- Locks in profits during extended trends
- Automatically adjusts as price moves in your favor
### Maximum Hold Time
- 36-48 hours maximum (configurable)
- Designed to minimize funding rate costs on futures
- Forces position closure to avoid excessive exposure
- Helps maintain capital velocity
## 📈 Key Features
### Trend Filters
- **ADX Filter**: Ensures sufficient trend strength (threshold: 20)
- **EMA Alignment**: All three EMAs must confirm trend direction
- **RSI Boundaries**: Avoids extreme overbought/oversold entries
### Volume Analysis
- Volume must exceed 20-period moving average
- Configurable multiplier (default: 1.0x)
- Helps identify institutional participation
### Automatic Exit Conditions
1. Take Profit target reached
2. Stop Loss triggered
3. Trailing stop activated
4. Trend reversal (EMA cross in opposite direction)
5. Maximum hold time exceeded
## 🎮 Recommended Settings
### For Spot Trading (Conservative)
```
Position Size: 15-20%
Stop Loss: 2.5%
Take Profit: 6.0%
Max Hold: 72 hours
Leverage: 1x
```
### For Futures 3-5x Leverage (Balanced)
```
Position Size: 12-15%
Stop Loss: 2.0%
Take Profit: 5.5%
Max Hold: 36 hours
Trailing: Active
```
### For Aggressive Trading 5-10x (High Risk)
```
Position Size: 8-12%
Stop Loss: 1.5%
Take Profit: 4.5%
Max Hold: 24 hours
ADX Filter: Disabled
```
## 📊 Performance Metrics
### Backtested Results (BTC/USDT 1H, 2 years)
- **Total Return**: ~19% (spot) / ~75% (5x leverage)*
- **Total Trades**: 240-300
- **Win Rate**: 49-52%
- **Profit Factor**: 1.25-1.50
- **Max Drawdown**: ~18-22%
- **Average Trade**: 0.5-3 days
*Leverage results exclude funding rates and real-world slippage
### Optimal Timeframes
- **1 Hour**: Best for active trading (recommended)
- **4 Hour**: More stable, fewer signals
- **15 Min**: High frequency (requires monitoring)
### Best Performing Assets
- BTC/USDT (most tested)
- ETH/USDT
- Major altcoins with good liquidity
- Not recommended for low-cap or illiquid pairs
## ⚙️ How to Use
1. **Add to Chart**: Apply strategy to 1H BTC/USDT chart
2. **Adjust Settings**: Configure risk parameters based on your preference
3. **Review Signals**: Green = Long, Red = Short, labels show signal count
4. **Monitor Performance**: Check strategy tester for detailed statistics
5. **Optimize**: Use strategy optimization to find best parameters for your market
## 🎨 Visual Indicators
The strategy provides clear visual feedback:
- **EMA Lines**: Blue (Fast), Red (Slow), Orange (Trend)
- **BUY/SELL Labels**: Show entry points with signal count
- **Stop/Target Lines**: Red (SL), Green (TP) displayed during active trades
- **Background Color**: Light green (long), light red (short) when in position
- **Info Panel**: Shows current trend, RSI, ADX, and volume status
## ⚠️ Important Notes
### Risk Disclaimer
- This strategy is for educational purposes only
- Past performance does not guarantee future results
- Cryptocurrency trading involves substantial risk
- Only trade with capital you can afford to lose
- Always use proper position sizing and risk management
### Limitations
- Performs poorly in sideways/choppy markets
- Requires sufficient liquidity for best execution
- Backtests do not include:
- Real-world slippage (especially during volatility)
- Funding rates (for perpetual futures)
- Exchange downtime or connection issues
- Emotional trading decisions
### For Futures Trading
If using this strategy on futures with leverage:
- Reduce position size proportionally to leverage
- Account for funding rates (~0.01% per 8h)
- Set max hold time to minimize funding costs
- Use lower leverage (3-5x max recommended)
- Monitor liquidation price carefully
## 🔧 Customization
All parameters are fully customizable:
- EMA periods (fast/slow/trend)
- MACD settings (12/26/9)
- RSI levels (30/70)
- Stop Loss / Take Profit percentages
- Trailing stop activation and offset
- Volume multiplier
- ADX threshold
- Maximum hold time
## 📚 Strategy Logic
The strategy follows this decision tree:
```
1. Check Trend Direction (EMA alignment)
↓
2. Scan for Entry Signals (8 types)
↓
3. Confirm with Filters (ADX, Volume, RSI)
↓
4. Enter Position with Fixed SL/TP
↓
5. Monitor for Exit Conditions:
- TP Hit → Close with profit
- SL Hit → Close with loss
- Trailing Active → Follow price
- Trend Reversal → Close position
- Max Time → Force close
```
## 🎓 Best Practices
1. **Start Conservative**: Use smaller position sizes initially
2. **Track Performance**: Monitor actual vs backtested results
3. **Optimize Regularly**: Market conditions change, adapt parameters
4. **Combine with Analysis**: Don't rely solely on automated signals
5. **Manage Emotions**: Stick to the system, avoid manual overrides
6. **Paper Trade First**: Test on demo before risking real capital
## 📞 Support & Updates
This strategy is actively maintained and updated based on:
- Market condition changes
- User feedback and suggestions
- Performance optimization
- Bug fixes and improvements
## 🏆 Conclusion
Triple EMA Multi-Signal Strategy offers a robust, systematic approach to cryptocurrency trading by combining trend following, momentum indicators, and strict risk management. Its multi-signal confirmation system helps filter false signals while the trailing stop mechanism captures extended trends.
The strategy is suitable for both manual traders looking for high-probability setups and algorithmic traders seeking a proven systematic approach.
**Remember**: No strategy wins 100% of the time. Success comes from consistent application, proper risk management, and continuous adaptation to changing market conditions.
---
*Version: 1.0*
*Last Updated: November 2025*
*Tested on: BTC/USDT, ETH/USDT (1H, 4H timeframes)*
*Recommended Capital: $5,000+ for optimal position sizing*
Volatility Signal-to-Noise Ratio🙏🏻 this is VSNR: the most effective and simple volatility regime detector & automatic volatility threshold scaler that somehow no1 ever talks about.
This is simply an inverse of the coefficient of variation of absolute returns, but properly constructed taking into account temporal information, and made online via recursive math with algocomplexity O(1) both in expanding and moving windows modes.
How do the available alternatives differ (while some’re just worse)?
Mainstream quant stat tests like Durbin-Watson, Dickey-Fuller etc: default implementations are ALL not time aware. They measure different kinds of regime, which is less (if at all) relevant for actual trading context. Mix of different math, high algocomplexity.
The closest one is MMI by financialhacker, but his approach is also not time aware, and has a higher algocomplexity anyways. Best alternative to mine, but pls modify it to use a time-weighted median.
Fractal dimension & its derivatives by John Ehlers: again not time aware, very low info gain, relies on bar sizes (high and lows), which don’t always exist unlike changes between datapoints. But it’s a geometric tool in essence, so this is fundamental. Let it watch your back if you already use it.
Hurst exponent: much higher algocomplexity, mix of parametric and non-parametric math inside. An invention, not a math entity. Again, not time aware. Also measures different kinds of regime.
How to set it up:
Given my other tools, I choose length so that it will match the amount of data that your trading method or study uses multiplied by ~ 4-5. E.g if you use some kind of bands to trade volatility and you calculate them over moving window 64, put VSNR on 256.
However it depends mathematically on many things, so for your methods you may instead need multipliers of 1 or ~ 16.
Additionally if you wanna use all data to estimate SNR, put 0 into length input.
How to use for regime detection:
First we define:
MR bias: mean reversion bias meaning volatility shorts would work better, fading levels would work better
Momo bias: momentum bias meaning volatility longs would work better, trading breakouts of levels would work better.
The study plots 3 horizontal thresholds for VSNR, just check its location:
Above upper level: significant Momo bias
Above 1 : Momo bias
Below 1 : MR bias
Below lower level: significant MR bias
Take a look at the screenshots, 2 completely different volatility regimes are spotted by VSNR, while an ADF does not show different regime:
^^ CBOT:ZN1!
^^ INDEX:BTCUSD
How to use as automatic volatility threshold scaler
Copy the code from the script, and use VSNR as a multiplier for your volatility threshold.
E.g you use a regression channel and fade/push upper and lower thresholds which are RMSEs multiples. Inside the code, multiply RMSE by VSNR, now you’re adaptive.
^^ The same logic as when MM bots widen spreads with vola goes wild.
How it works:
Returns follow Laplace distro -> logically abs returns follow exponential distro , cuz laplace = double exponential.
Exponential distro has a natural coefficient of variation = 1 -> signal to noise ratio defined as mean/stdev = 1 as well. The same can be said for Student t distro with parameter v = 4. So 1 is our main threshold.
We can add additional thresholds by discovering SNRs of Student t with v = 3 and v = 5 (+- 1 from baseline v = 4). These have lighter & heavier tails each favoring mean reversion or momentum more. I computed the SNR values you see in the code with mpmath python module, with precision 256 decimals, so you can trust it I put it on my momma.
Then I use exponential smoothing with properly defined alphas (one matches cumulative WMA and another minimizes error with WMA in moving window mode) to estimate SNR of abs returns.
…
Lightweight huh?
∞
Stochastic Pro+ Suite📚 What Is the Stochastic Oscillator?
The stochastic oscillator is a momentum indicator comparing a security's closing price to its price range over a set number of periods. The %K line represents the raw stochastic value, while the %D line is a smoothed moving average of %K.
Stochastic helps identify:
Overbought and oversold conditions
Bullish and bearish crossovers
Momentum shifts before price reversals
It is widely used in both trending and ranging markets.
💡 What Makes This Suite Different?
This script supercharges the traditional stochastic with a multi-timeframe engine , divergence detection , and a highly customizable visual suite , including:
✅ Core Features:
- Multi-Timeframe (%K, %D, Spread): Pulls stochastic data from any higher timeframe for improved signal quality.
- Custom Overbought/Oversold Levels: Fully adjustable OB/OS thresholds (default: 80/20).
- %K-%D Spread Histogram: View the difference between %K and %D visually as a histogram.
- Color-coded Cross Highlights: Optional background shading for key crossover events in OB/OS zones (high probability reversal areas).
🔍 Divergence Detection (Optional):
- Bullish Divergence: Price makes lower lows while %K makes higher lows.
- Bearish Divergence: Price makes higher highs while %K makes lower highs.
- Customizable pivot lookbacks and range filters to control divergence strictness.
- Visual divergence labels plotted directly on the oscillator.
🎛️ Fully Toggleable Visuals:
Show/hide %K, %D, OB/OS lines, spread histogram, background highlight, and divergence — all via simple checkboxes.
🔔 Alerts:
Set alerts for both bullish and bearish divergences — ideal for swing, day, or trend reversal strategies.
⚙️ Use Cases
- Spot exhaustion in overbought/oversold zones
- Confirm or filter entries with divergence signals
- Monitor multiple timeframes without switching charts
- Use as a signal tool in confluence with price action or volume indicators
⚠️ Disclaimer
This tool is for educational and informational purposes only. It does not constitute financial advice, trading advice, or investment guidance. Always do your own research and consult a qualified financial advisor before making trading decisions.
MACD Trend & Momentum Dashboard (Weighted, 3 TFs)This indicator provides a multi-timeframe MACD trend and momentum dashboard that works independently of your current chart timeframe. It displays MACD zero-line bias and MACD-vs-Signal trend state across three user-selectable timeframes, using clear color-coded cells for instant visual interpretation. A weighted scoring system combines all six signals into a single market bias classification (Strong Bullish → Strong Bearish). This helps traders quickly understand higher- and lower-timeframe alignment, market regime, and overall trend quality. Ideal for trend- and momentum-followers who want a clean, actionable market overview at a glance.
Sani Momentum Target System [wjdtks255]Sani Momentum Target System Explanation & Trading Method
The Sani Momentum Target System is a momentum-based trading indicator that helps traders identify trend changes and determine precise entry points, stop-loss levels, and multiple profit targets.
Key Features:
Smoothed Price Calculation: Utilizes a glide-like smoothing function to reduce noise in price data.
Moving Averages: Calculates fast and slow EMAs on the smoothed price; the difference creates an oscillator.
Signal Line: A simple moving average smooths the oscillator to generate a signal line.
Trend Signals:
Buy signal when oscillator crosses above the signal line.
Sell signal when oscillator crosses below the signal line.
Entry, Stop Loss, Target Levels:
Entry price is set at current close on signal.
Stop loss is set by multiplying ATR by 2 against trend direction.
Three take profit targets (T1, T2, T3) are set by user-defined multiples of ATR.
Visual Display: Includes colored horizontal lines and labels for entry, stop loss, and targets.
Bars are colored by trend direction, and triangular markers show buy/sell signals.
How To Use This Indicator:
Entry: Place trades in the direction of the signal (long on buy, short on sell).
Stop Loss: Use the ATR-based stop loss line to minimize downside risk.
Profit Taking: Scale out profits or exit trades at target levels T1, T2, and T3.
Trend Confirmation: Confirm with oscillator trend direction before entry to avoid false signals.
Parameter Adjustment: Modify smoothing lengths, ATR period, and target multipliers to fit your trading style and timeframe.
Final Notes:
This indicator streamlines momentum trading by providing clear price targets and risk levels visually.
Always backtest strategies and apply proper risk management.
Suitable across asset classes: stocks, forex, cryptocurrencies.
If you want detailed guidance or customization, feel free to ask!
XAUUSD Fisher Transform Dashboard — Trend & Momentum InsightsThe script offers an educational visualization of trend and momentum on XAUUSD by combining the Fisher Transform with EMA direction. It plots momentum shifts, trend alignment, and includes a concise dashboard showing trend bias, the latest crossover event, and customizable percentage-based reference markers.
This tool is for market analysis and study purposes only and does not provide trading advice.
