Reverse Cutlers Relative Strength IndexIntroduction
The Reverse Cutlers Relative Strength Index (RCRSI) is an indicator which tells the user what price is required to give a particular Cutlers Relative Strength Index (RSI) value, or cross its Moving Average (MA) signal line.
Overview
Background & Credits:
The relative strength index (RSI) is a momentum indicator used in technical analysis that was originally developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, “New Concepts in Technical Trading Systems.”.
Cutler created a variation of the RSI known as “Cutlers RSI” using a different formulation to avoid an inherent accuracy problem which arises when using Wilders method of smoothing.
Further developments in the use, and more nuanced interpretations of the RSI have been developed by Cardwell, and also by well-known chartered market technician, Constance Brown C.M.T., in her acclaimed book "Technical Analysis for the Trading Professional” 1999 where she described the idea of bull and bear market ranges for RSI, and while she did not actually reveal the formulas, she introduced the concept of “reverse engineering” the RSI to give price level outputs.
Renowned financial software developer, co-author of academic books on finance, and scientific fellow to the Department of Finance and Insurance at the Technological Educational Institute of Crete, Giorgos Siligardos PHD. brought a new perspective to Wilder’s RSI when he published his excellent and well-received articles "Reverse Engineering RSI " and "Reverse Engineering RSI II " in the June 2003, and August 2003 issues of Stocks & Commodities magazine, where he described his methods of reverse engineering Wilders RSI.
Several excellent Implementations of the Reverse Wilders Relative Strength Index have been published here on Tradingview and elsewhere.
My utmost respect, and all due credits to authors of related prior works.
Introduction
It is worth noting that while the general RSI formula, and the logic dictating the UpMove and DownMove data series as described above has remained the same as the Wilders original formulation, it has been interpreted in a different way by using a different method of averaging the upward, and downward moves.
Cutler recognized the issue of data length dependency when using wilders smoothing method of calculating RSI which means that wilders standard RSI will have a potential initialization error which reduces with every new data point calculated meaning early results should be regarded as unreliable until enough calculation iterations have occurred for convergence.
Hence Cutler proposed using Simple Moving Averaging for gain and loss data which this Indicator is based on.
Having "Reverse engineered" prices for any oscillator makes the planning, and execution of strategies around that oscillator far simpler, more timely and effective.
Introducing the Reverse Cutlers RSI which consists of plotted lines on a scale of 0 to 100, and an optional infobox.
The RSI scale is divided into zones:
• Scale high (100)
• Bull critical zone (80 - 100)
• Bull control zone (62 - 80)
• Scale midline (50)
• Bear critical zone (20 - 38)
• Bear control zone (0 - 20)
• Scale low (0)
The RSI plots are:
• Cutlers RSI
• RSI MA signal line
• Test price RSI
• Alert level high
• Alert level low
The info box displays output closing price levels where Cutlers RSI value will crossover:
• Its previous value. (RSI )
• Bull critical zone.
• Bull control zone.
• Mid-Line.
• Bear control zone.
• Bear critical zone.
• RSI MA signal line
• Alert level High
• Alert level low
And also displays the resultant RSI for a user defined closing price:
• Test price RSI
The infobox outputs can be shown for the current bar close, or the next bar close.
The user can easily select which information they want in the infobox from the setttings
Importantly:
All info box price levels for the current bar are calculated immediately upon the current bar closing and a new bar opening, they will not change until the current bar closes.
All info box price levels for the next bar are projections which are continually recalculated as the current price changes, and therefore fluctuate as the current price changes.
Understanding the Relative Strength Index
At its simplest the RSI is a measure of how quickly traders are bidding the price of an asset up or down.
It does this by calculating the difference in magnitude of price gains and losses over a specific lookback period to evaluate market conditions.
The RSI is displayed as an oscillator (a line graph that can move between two extremes) and outputs a value limited between 0 and 100.
It is typically accompanied by a moving average signal line.
Traditional interpretations
Overbought and oversold:
An RSI value of 70 or above indicates that an asset is becoming overbought (overvalued condition), and may be may be ready for a trend reversal or corrective pullback in price.
An RSI value of 30 or below indicates that an asset is becoming oversold (undervalued condition), and may be may be primed for a trend reversal or corrective pullback in price.
Midline Crossovers:
When the RSI crosses above its midline (RSI > 50%) a bullish bias signal is generated. (only take long trades)
When the RSI crosses below its midline (RSI < 50%) a bearish bias signal is generated. (only take short trades)
Bullish and bearish moving average signal Line crossovers:
When the RSI line crosses above its signal line, a bullish buy signal is generated
When the RSI line crosses below its signal line, a bearish sell signal is generated.
Swing Failures and classic rejection patterns:
If the RSI makes a lower high, and then follows with a downside move below the previous low, a Top Swing Failure has occurred.
If the RSI makes a higher low, and then follows with an upside move above the previous high, a Bottom Swing Failure has occurred.
Examples of classic swing rejection patterns
Bullish swing rejection pattern:
The RSI moves into oversold zone (below 30%).
The RSI rejects back out of the oversold zone (above 30%)
The RSI forms another dip without crossing back into oversold zone.
The RSI then continues the bounce to break up above the previous high.
Bearish swing rejection pattern:
The RSI moves into overbought zone (above 70%).
The RSI rejects back out of the overbought zone (below 70%)
The RSI forms another peak without crossing back into overbought zone.
The RSI then continues to break down below the previous low.
Divergences:
A regular bullish RSI divergence is when the price makes lower lows in a downtrend and the RSI indicator makes higher lows.
A regular bearish RSI divergence is when the price makes higher highs in an uptrend and the RSI indicator makes lower highs.
A hidden bullish RSI divergence is when the price makes higher lows in an uptrend and the RSI indicator makes lower lows.
A hidden bearish RSI divergence is when the price makes lower highs in a downtrend and the RSI indicator makes higher highs.
Regular divergences can signal a reversal of the trending direction.
Hidden divergences can signal a continuation in the direction of the trend.
Chart Patterns:
RSI regularly forms classic chart patterns that may not show on the underlying price chart, such as ascending and descending triangles & wedges, double tops, bottoms and trend lines etc.
Support and Resistance:
It is very often easier to define support or resistance levels on the RSI itself rather than the price chart.
Modern interpretations in trending markets:
Modern interpretations of the RSI stress the context of the greater trend when using RSI signals such as crossovers, overbought/oversold conditions, divergences and patterns.
Constance Brown, CMT, was one of the first who promoted the idea that an oversold reading on the RSI in an uptrend is likely much higher than 30%, and that an overbought reading on the RSI during a downtrend is much lower than the 70% level.
In an uptrend or bull market, the RSI tends to remain in the 40 to 90 range, with the 40-50 zone acting as support.
During a downtrend or bear market, the RSI tends to stay between the 10 to 60 range, with the 50-60 zone acting as resistance.
For ease of executing more modern and nuanced interpretations of RSI it is very useful to break the RSI scale into bull and bear control and critical zones.
These ranges will vary depending on the RSI settings and the strength of the specific market’s underlying trend.
Limitations of the RSI
Like most technical indicators, its signals are most reliable when they conform to the long-term trend.
True trend reversal signals are rare, and can be difficult to separate from false signals.
False signals or “fake-outs”, e.g. a bullish crossover, followed by a sudden decline in price, are common.
Since the indicator displays momentum, it can stay overbought or oversold for a long time when an asset has significant sustained momentum in either direction.
Data Length Dependency when using wilders smoothing method of calculating RSI means that wilders standard RSI will have a potential initialization error which reduces with every new data point calculated meaning early results should be regarded as unreliable until calculation iterations have occurred for convergence.
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MACD Forecast [Titans_Invest]MACD Forecast — The Future of MACD in Trading
The MACD has always been one of the most powerful tools in technical analysis.
But what if you could see where it’s going, instead of just reacting to what has already happened?
Introducing MACD Forecast — the natural evolution of the MACD Full , now taken to the next level. It’s the world’s first MACD designed not only to analyze the present but also to predict the future behavior of momentum.
By combining the classic MACD structure with projections powered by Linear Regression, this indicator gives traders an anticipatory, predictive view, redefining what’s possible in technical analysis.
Forget lagging indicators.
This is the smartest, most advanced, and most accurate MACD ever created.
🍟 WHY MACD FORECAST IS REVOLUTIONARY
Unlike the traditional MACD, which only reflects current and past price dynamics, the MACD Forecast uses regression-based projection models to anticipate where the MACD line, signal line, and histogram are heading.
This means traders can:
• See MACD crossovers before they happen.
• Spot trend reversals earlier than most.
• Gain an unprecedented timing advantage in both discretionary and automated trading.
In other words: this indicator lets you trade ahead of time.
🔮 FORECAST ENGINE — POWERED BY LINEAR REGRESSION
At its core, the MACD Forecast integrates Linear Regression (ta.linreg) to project the MACD’s future behavior with exceptional accuracy.
Projection Modes:
• Flat Projection: Assumes trend continuity at the current level.
• LinReg Projection: Applies linear regression across N periods to mathematically forecast momentum shifts.
This dual system offers both a conservative and adaptive view of market direction.
📐 ACCURACY WITH FULL CUSTOMIZATION
Just like the MACD Full, this new version comes with 20 customizable buy-entry conditions and 20 sell-entry conditions — now enhanced with forecast-based rules that anticipate crossovers and trend reversals.
You’re not just reacting — you’re strategizing ahead of time.
⯁ HOW TO USE MACD FORECAST❓
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
🤖 BUILT FOR AUTOMATION AND BOTS 🤖
Whether for manual trading, quantitative strategies, or advanced algorithms, the MACD Forecast was designed to integrate seamlessly with automated systems.
With predictive logic at its core, your strategies can finally react to what’s coming, not just what already happened.
🥇 WHY THIS INDICATOR IS UNIQUE 🥇
• World’s first MACD with Linear Regression Forecasting
• Predictive Crossovers (before they appear on the chart)
• Maximum flexibility with Long & Short combinations — 20+ fully configurable conditions for tailor-made strategies
• Fully automatable for quantitative systems and advanced bots
This isn’t just an update.
It’s the final evolution of the MACD.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔮 Linear Regression Function 🔮
______________________________________________________
• Our indicator includes MACD forecasts powered by linear regression.
Forecast Types:
• Flat: Assumes prices will stay the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset : Offset.
• return: Linear regression curve.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : MACD Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
🎗️ In memory of João Guilherme — your light will live on forever.
CT Reverse True Strength Indicator On ChartIntroducing the Caretakers “On Chart” Reverse True Strength Index.
According to Wikipedia….
“The True Strength Index (TSI) is a technical indicator used in the analysis of financial markets that attempts to show both trend direction and overbought/oversold conditions. It was first published William Blau in 1991.
The indicator uses moving averages of the underlying momentum of a financial instrument.
Momentum is considered a leading indicator of price movements, and a moving average characteristically lags behind price.
The TSI combines these characteristics to create an indication of price and direction more in sync with market turns than either momentum or moving average.”
The TSI has a normal range of values between +100 and -100.
Traditionally traders and analysts will consider:
Positives values above 25 to indicate an “overbought” condition
Negative values below -25 to indicate an “oversold” condition
I have reverse engineered the True Strength Index formula to derive 2 new functions.
1) The reverse TSI function is dual purpose which can be used to calculate….
The chart price at which the TSI will reach a particular TSI scale value.
The chart price at which the TSI will equal its previous value.
2) The reverse TSI signal cross function can be used to calculate the chart price at which the TSI will cross its signal line.
I have employed these functions here to return the price levels where the True Strength Index would equal :
Upper alert level ( default 25 )
Zero-Line
Lower alert level ( default -25 )
Previous TSI (eq) value
TSI signal line
In this “On Chart” version of the reverse True Strength Index the crossover levels are displayed both as lines on the chart and via an optional info-box with choice of user selected info.
Chart Line Colors
Upper alert level... ( Fuchsia )
Zero-Line............ ( White )
Lower alert level... ( Aqua )
TSI (eq)...............( TSI (eq) > close..Orange, TSI (eq) < close..Lime )
TSI signal line........( Signal Cross Line > Close..Aqua, Signal Cross Line < Close..Fuchsia )
How to interpret the displayed prices returned from the TSI scale zero line and upper and lower alert levels.
Closing exactly at the given price will cause the True Strength Index value to equal the scale value.
Closing above the given price will cause the True Strength Index to cross above the scale value.
Closing below the given price will cause the True Strength Index to cross below the scale value.
How to interpret the displayed price returned from the TSI (eq)
Closing exactly at the price will cause the True Strength Index value to equal the previous TSI value.
Closing above the price will cause the True Strength Index value to increase.
Closing below the price will cause the True Strength Index value to decrease.
How to interpret the displayed price returned from the TSI signal line crossover.
Closing exactly at the given price will cause the True Strength Index value to equal the signal line.
Closing above the given price will cause the True Strength Index to cross above the signal line.
Closing below the given price will cause the True Strength Index to cross below the signal line.
Common methods to derive signals from the TSI :
Zero-line crossovers
When the CMO crosses above the zero-line, a buy signal is generated.
When the CMO crosses below the zero-line, a sell signal is generated.
“Overbought” and “Oversold” crossovers
When the SMI crosses below -25 and then moves back above it, a buy signal is generated.
When the SMI crosses above +25 and then moves back below it, a sell signal is generated.
What Does the True Strength Index (TSI) Tell You?
The indicator is primarily used to identify overbought and oversold conditions in an asset's price, spot divergence, identify trend direction and changes via the zero-line, and highlight short-term price momentum with signal line crossovers.
Since the TSI is based on price movements, oversold and overbought levels will vary by the asset being traded. Some stocks may reach +30 and -30 before tending to see price reversals, while another stock may reverse near +20 and -20.
Mark extreme TSI levels, on the asset being traded, to see where overbought and oversold is. Being oversold doesn't necessarily mean it is time to buy, and when an asset is overbought it doesn't necessarily mean it is time to sell. Traders will typically watch for other signals to trigger a trade decision. For example, they may wait for the price or TSI to start dropping before selling in overbought territory. Alternatively, they may wait for a signal line crossover.
Signal Line Crossovers
The true strength index has a signal line, which is usually a seven- to 13-period EMA of the TSI line. A signal line crossover occurs when the TSI line crosses the signal line. When the TSI crosses above the signal line from below, that may warrant a long position. When the TSI crosses below the signal line from above, that may warrant selling or short selling.
Signal line crossovers occur frequently, so should be utilized only in conjunction with other signals from the TSI. For example, buy signals may be favoured when the TSI is above the zero-line. Or sell signals may be favoured when the TSI is in overbought territory.
Zero-line Crossovers
The zero-line crossover is another signal the TSI generates. Price momentum is positive when the indicator is above zero and negative when it is below zero. Some traders use the zero-line for a directional bias. For example, a trader may decide only to enter a long position if the indicator is above its zero-line. Conversely, the trader would be bearish and only consider short positions if the indicator's value is below zero.
Breakouts and Divergence
Traders can use support and resistance levels created by the true strength index to identify breakouts and price momentum shifts. For instance, if the indicator breaks below a trendline, the price may see continued selling.
Divergence is another tool the TSI provides. If the price of an asset is moving higher, while the TSI is dropping, that is called bearish divergence and could result in a downside price move. If the TSI is rising while the price is falling, that could signal higher prices to come. This is called bullish divergence.
Divergence is a poor timing signal, so it should only be used in conjunction with other signals generated by the TSI or other technical indicators.
The Difference Between the True Strength Index (TSI) and the Moving Average Convergence Divergence (MACD) Indicator.
The TSI is smoothing price changes to create a technical oscillator. The moving average convergence divergence (MACD) indicator is measuring the separation between two moving averages. Both indicators are used in similar ways for trading purposes, yet they are not calculated the same and will provide different signals at different times.
The Limitations of Using the True Strength Index (TSI)
Many of the signals provided by the TSI will be false signals. That means the price action will be different than expected following a trade signal. For example, during an uptrend, the TSI may cross below the zero-line several times, but then the price proceeds higher even though the TSI indicates momentum has shifted down.
Signal line crossovers also occur so frequently that they may not provide a lot of trading benefit. Such signals need to be heavily filtered based on other elements of the indicator or through other forms of analysis. The TSI will also sometimes change direction without price changing direction, resulting in trade signals that look good on the TSI but continue to lose money based on price.
Divergence also tends to unreliable on the indicator. Divergence can last so long that it provides little insight into when a reversal will actually occur. Also, divergence isn't always present when price reversals actually do occur.
The TSI should only be used in conjunction with other forms of analysis, such as price action analysis and other technical indicators.
This is not financial advice, use at your own risk.
CT Reverse True Strength IndicatorIntroducing the Caretakers Reverse True Strength Index.
According to Wikipedia….
“The True Strength Index (TSI) is a technical indicator used in the analysis of financial markets that attempts to show both trend direction and overbought/oversold conditions. It was first published William Blau in 1991.
The indicator uses moving averages of the underlying momentum of a financial instrument.
Momentum is considered a leading indicator of price movements, and a moving average characteristically lags behind price.
The TSI combines these characteristics to create an indication of price and direction more in sync with market turns than either momentum or moving average.”
The TSI has a normal range of values between +100 and -100.
Traditionally traders and analysts will consider:
Positives values above 25 to indicate an “overbought” condition
Negative values below -25 to indicate an “oversold” condition
I have reverse engineered the True Strength Index formula to derive 2 new functions.
The reverse TSI function is dual purpose which can be used to calculate….
The chart price at which the TSI will reach a particular TSI scale value.
The chart price at which the TSI will equal its previous value.
The reverse TSI signal cross function can be used to calculate the chart price at which the TSI will cross its signal line.
I have employed these functions here to return the price levels where the True Strength Index would equal :
Upper alert level ( default 25 )
Zero-Line
Lower alert level ( default -25 )
Previous TSI (eq) value.
TSI signal line
These crossover levels are displayed via an optional info-box with choice of user selected info.
How to interpret the displayed prices returned from the TSI scale zero line and upper and lower alert levels.
Closing exactly at the given price will cause the True Strength Index value to equal the scale value.
Closing above the given price will cause the True Strength Index to cross above the scale value.
Closing below the given price will cause the True Strength Index to cross below the scale value.
How to interpret the displayed price returned from the TSI (eq)
Closing exactly at the price will cause the True Strength Index value to equal the previous TSI value.
Closing above the price will cause the True Strength Index value to increase.
Closing below the price will cause the True Strength Index value to decrease.
How to interpret the displayed price returned from the TSI signal line crossover.
Closing exactly at the given price will cause the True Strength Index value to equal the signal line.
Closing above the given price will cause the True Strength Index to cross above the signal line.
Closing below the given price will cause the True Strength Index to cross below the signal line.
Common methods to derive signals from the TSI :
Zero-line crossovers
When the CMO crosses above the zero-line, a buy signal is generated.
When the CMO crosses below the zero-line, a sell signal is generated.
“Overbought” and “Oversold” crossover
When the SMI crosses below -25 and then moves back above it, a buy signal is generated.
When the SMI crosses above +25 and then moves back below it, a sell signal is generated.
What Does the True Strength Index (TSI) Tell You?
The indicator is primarily used to identify overbought and oversold conditions in an asset's price, spot divergence, identify trend direction and changes via the zero-line, and highlight short-term price momentum with signal line crossovers.
Since the TSI is based on price movements, oversold and overbought levels will vary by the asset being traded. Some stocks may reach +30 and -30 before tending to see price reversals, while another stock may reverse near +20 and -20.
Mark extreme TSI levels, on the asset being traded, to see where overbought and oversold is. Being oversold doesn't necessarily mean it is time to buy, and when an asset is overbought it doesn't necessarily mean it is time to sell. Traders will typically watch for other signals to trigger a trade decision. For example, they may wait for the price or TSI to start dropping before selling in overbought territory. Alternatively, they may wait for a signal line crossover.
Signal Line Crossovers
The true strength index has a signal line, which is usually a seven- to 13-period EMA of the TSI line. A signal line crossover occurs when the TSI line crosses the signal line. When the TSI crosses above the signal line from below, that may warrant a long position. When the TSI crosses below the signal line from above, that may warrant selling or short selling.
Signal line crossovers occur frequently, so should be utilized only in conjunction with other signals from the TSI. For example, buy signals may be favoured when the TSI is above the zero-line. Or sell signals may be favoured when the TSI is in overbought territory.
Zero-line Crossovers
The zero-line crossover is another signal the TSI generates. Price momentum is positive when the indicator is above zero and negative when it is below zero. Some traders use the zero-line for a directional bias. For example, a trader may decide only to enter a long position if the indicator is above its zero-line. Conversely, the trader would be bearish and only consider short positions if the indicator's value is below zero.
Breakouts and Divergence
Traders can use support and resistance levels created by the true strength index to identify breakouts and price momentum shifts. For instance, if the indicator breaks below a trendline, the price may see continued selling.
Divergence is another tool the TSI provides. If the price of an asset is moving higher, while the TSI is dropping, that is called bearish divergence and could result in a downside price move. If the TSI is rising while the price is falling, that could signal higher prices to come. This is called bullish divergence.
Divergence is a poor timing signal, so it should only be used in conjunction with other signals generated by the TSI or other technical indicators.
The Difference Between the True Strength Index (TSI) and the Moving Average Convergence Divergence (MACD) Indicator.
The TSI is smoothing price changes to create a technical oscillator. The moving average convergence divergence (MACD) indicator is measuring the separation between two moving averages. Both indicators are used in similar ways for trading purposes, yet they are not calculated the same and will provide different signals at different times.
The Limitations of Using the True Strength Index (TSI)
Many of the signals provided by the TSI will be false signals. That means the price action will be different than expected following a trade signal. For example, during an uptrend, the TSI may cross below the zero-line several times, but then the price proceeds higher even though the TSI indicates momentum has shifted down.
Signal line crossovers also occur so frequently that they may not provide a lot of trading benefit. Such signals need to be heavily filtered based on other elements of the indicator or through other forms of analysis. The TSI will also sometimes change direction without price changing direction, resulting in trade signals that look good on the TSI but continue to lose money based on price.
Divergence also tends to unreliable on the indicator. Divergence can last so long that it provides little insight into when a reversal will actually occur. Also, divergence isn't always present when price reversals actually do occur.
The TSI should only be used in conjunction with other forms of analysis, such as price action analysis and other technical indicators.
This is not financial advice, use at your own risk.
FIRST-HOUR TOOL V.1.8.08.23Three horizontal lines are drawn on the chart to represent session prices. These prices are calculated based on the user-specified session:
"FirstHour Session High" represents the highest price reached during the firsthour session.
"FirstHour Session Open" represents the opening price of the firsthour session
"FirstHour Session Low" represents the lowest price reached during the firsthour session.
These prices are respectively colored with light blue, light yellow, and light pink.
The chart background can change color based on whether the current time is within the specified session. If the current time is within the session, the background will be colored in semi-transparent aqua green. Otherwise, it will remain transparent.
Upward-pointing triangle markers are used to highlight points where the closing price crosses above (crossover) or below (crossunder) the session levels.
These markers appear below the corresponding bar.
They are colored based on the type of crossover:
Yellow for crossover above the "FirstHour High"
Red for crossover above the "FirstHour Open"
Green for crossover above the "FirstHour Low"
Alerts:
Alert messages are generated when crossovers or crossunders of the closing price relative to the session levels occur.
The alerts appear once per bar. Alerts are generated for the following events:
Crossover of the price above the "Session High" with the message "High First Hour Crossover."
Crossunder of the price below the "Session Open" with the message "Open First Hour Crossunder."
Crossunder of the price below the "Session Low" with the message "Low First Hour Crossunder."
Crossover of the price above the "Session Low" with the message "Low First Hour Crossover."
In summary, this indicator provides a visual representation of session prices and events, helping traders spot significant crossovers and crossunders relative to key price levels.
Author @tumiza999
Coins Trend Tracker HTThe Coins Trend Tracker HT script provides a powerful tool for monitoring and comparing the trend signals of multiple cryptocurrencies based on their Exponential Moving Averages (EMAs). This script is particularly useful for traders who want to keep track of multiple coins across different timeframes and identify potential trading opportunities based on EMA crossovers.
Features:
Customizable Coin Selection: Users can select up to four different cryptocurrencies to monitor.
Flexible Timeframes: Users can choose two different timeframes for EMA calculations to suit their trading strategies.
Visual Trend Indicators: The script displays trend indicators (🚀 for bullish and 💀 for bearish) based on the EMA crossover status for each coin and timeframe.
Conditional Cell Coloring: Table cells are color-coded based on the EMA crossover conditions, helping users quickly identify bullish or bearish trends.
Opacity Control: Users can adjust the opacity of the table cell colors for better visualization on the chart.
How It Works:
Coin Selection: Users can select up to four different cryptocurrencies to monitor by entering their ticker symbols.
Timeframe Selection: Users can select two different timeframes for the EMA calculations. The script calculates the 5-period and 20-period EMAs for each coin and timeframe.
EMA Crossovers: The script checks for EMA crossovers (EMA 5 crossing above or below EMA 20) and updates the trend indicators and cell colors accordingly.
Table Display: The script displays a table with the selected coins, their current prices, and trend indicators for the chosen timeframes. The background color of the table cells changes based on the EMA crossover status.
Script Logic:
The get_price function retrieves the latest price of the selected coin for the specified timeframe.
The get_ema_cross function calculates the 5-period and 20-period EMAs and checks for crossover conditions.
The fill_row function populates the table with the coin data, trend indicators, and conditionally colored cells.
The table header and data rows are updated based on the user-selected coins, timeframes, and EMA crossover conditions.
Usage:
Add the script to your TradingView chart.
Customize the coin selection, timeframes, text color, default cell color, bullish and bearish cross colors, and cell opacity through the input settings.
The script will display a table with the selected coins, their current prices, and trend indicators based on the EMA crossovers for the chosen timeframes.
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
RSI Full Forecast [Titans_Invest]RSI Full Forecast
Get ready to experience the ultimate evolution of RSI-based indicators – the RSI Full Forecast, a boosted and even smarter version of the already powerful: RSI Forecast
Now featuring over 40 additional entry conditions (forecasts), this indicator redefines the way you view the market.
AI-Powered RSI Forecasting:
Using advanced linear regression with the least squares method – a solid foundation for machine learning - the RSI Full Forecast enables you to predict future RSI behavior with impressive accuracy.
But that’s not all: this new version also lets you monitor future crossovers between the RSI and the MA RSI, delivering early and strategic signals that go far beyond traditional analysis.
You’ll be able to monitor future crossovers up to 20 bars ahead, giving you an even broader and more precise view of market movements.
See the Future, Now:
• Track upcoming RSI & RSI MA crossovers in advance.
• Identify potential reversal zones before price reacts.
• Uncover statistical behavior patterns that would normally go unnoticed.
40+ Intelligent Conditions:
The new layer of conditions is designed to detect multiple high-probability scenarios based on historical patterns and predictive modeling. Each additional forecast is a window into the price's future, powered by robust mathematics and advanced algorithmic logic.
Full Customization:
All parameters can be tailored to fit your strategy – from smoothing periods to prediction sensitivity. You have complete control to turn raw data into smart decisions.
Innovative, Accurate, Unique:
This isn’t just an upgrade. It’s a quantum leap in technical analysis.
RSI Full Forecast is the first of its kind: an indicator that blends statistical analysis, machine learning, and visual design to create a true real-time predictive system.
⯁ SCIENTIFIC BASIS LINEAR REGRESSION
Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥.
The general formula for a simple linear regression is given by:
y = β₀ + β₁x + ε
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
y = is the predicted variable (e.g. future value of RSI)
x = is the explanatory variable (e.g. time or bar index)
β0 = is the intercept (value of 𝑦 when 𝑥 = 0)
𝛽1 = is the slope of the line (rate of change)
ε = is the random error term
The goal is to estimate the coefficients 𝛽0 and 𝛽1 so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares.
⯁ LEAST SQUARES ESTIMATION
To minimize the error between predicted and observed values, we use the following formulas:
β₁ = /
β₀ = ȳ - β₁x̄
Where:
∑ = sum
x̄ = mean of x
ȳ = mean of y
x_i, y_i = individual values of the variables.
Where:
x_i and y_i are the means of the independent and dependent variables, respectively.
i ranges from 1 to n, the number of observations.
These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity.
⯁ LINEAR REGRESSION IN MACHINE LEARNING
Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies.
By applying this model to the RSI, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis.
⯁ VISUAL INTERPRETATION
Imagine an RSI time series like this:
Time →
RSI →
The regression line will smooth these values and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted RSI, which can be crossed with the actual RSI to generate more intelligent signals.
⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED
Linear Regression Models the relationship between variables using a straight line.
Least Squares Minimizes the sum of squared errors between prediction and reality.
Time Series Forecasting Estimates future values based on historical data.
Supervised Learning Trains models to predict outputs from known inputs.
Statistical Smoothing Reduces noise and reveals underlying trends.
⯁ WHY THIS INDICATOR IS REVOLUTIONARY
Scientifically-based: Based on statistical theory and mathematical inference.
Unprecedented: First public RSI with least squares predictive modeling.
Intelligent: Built with machine learning logic.
Practical: Generates forward-thinking signals.
Customizable: Flexible for any trading strategy.
⯁ CONCLUSION
By combining RSI with linear regression, this indicator allows a trader to predict market momentum, not just follow it.
RSI Full Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology.
⯁ Example of simple linear regression, which has one independent variable:
⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ).
⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values using Matlab:
⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables.
⯁ The result of fitting a set of data points with a quadratic function:
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🔮 Linear Regression: PineScript Technical Parameters 🔮
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Forecast Types:
• Flat: Assumes prices will remain the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
ta.linreg (built-in function)
Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values calculated using the least squares method on the source series.
Syntax:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset: Offset.
• return: Linear regression curve.
This function has been cleverly applied to the RSI, making it capable of projecting future values based on past statistical trends.
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⯁ WHAT IS THE RSI❓
The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend.
⯁ HOW TO USE THE RSI❓
The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:
• Overbought: When the RSI is above 70, indicating that the asset may be overbought.
• Oversold: When the RSI is below 30, indicating that the asset may be oversold.
• Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions.
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⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📈 RSI Conditions:
🔹 RSI > Upper
🔹 RSI < Upper
🔹 RSI > Lower
🔹 RSI < Lower
🔹 RSI > Middle
🔹 RSI < Middle
🔹 RSI > MA
🔹 RSI < MA
📈 MA Conditions:
🔹 MA > Upper
🔹 MA < Upper
🔹 MA > Lower
🔹 MA < Lower
📈 Crossovers:
🔹 RSI (Crossover) Upper
🔹 RSI (Crossunder) Upper
🔹 RSI (Crossover) Lower
🔹 RSI (Crossunder) Lower
🔹 RSI (Crossover) Middle
🔹 RSI (Crossunder) Middle
🔹 RSI (Crossover) MA
🔹 RSI (Crossunder) MA
🔹 MA (Crossover) Upper
🔹 MA (Crossunder) Upper
🔹 MA (Crossover) Lower
🔹 MA (Crossunder) Lower
📈 RSI Divergences:
🔹 RSI Divergence Bull
🔹 RSI Divergence Bear
📈 RSI Forecast:
🔹 RSI (Crossover) MA Forecast
🔹 RSI (Crossunder) MA Forecast
🔹 RSI Forecast 1 > MA Forecast 1
🔹 RSI Forecast 1 < MA Forecast 1
🔹 RSI Forecast 2 > MA Forecast 2
🔹 RSI Forecast 2 < MA Forecast 2
🔹 RSI Forecast 3 > MA Forecast 3
🔹 RSI Forecast 3 < MA Forecast 3
🔹 RSI Forecast 4 > MA Forecast 4
🔹 RSI Forecast 4 < MA Forecast 4
🔹 RSI Forecast 5 > MA Forecast 5
🔹 RSI Forecast 5 < MA Forecast 5
🔹 RSI Forecast 6 > MA Forecast 6
🔹 RSI Forecast 6 < MA Forecast 6
🔹 RSI Forecast 7 > MA Forecast 7
🔹 RSI Forecast 7 < MA Forecast 7
🔹 RSI Forecast 8 > MA Forecast 8
🔹 RSI Forecast 8 < MA Forecast 8
🔹 RSI Forecast 9 > MA Forecast 9
🔹 RSI Forecast 9 < MA Forecast 9
🔹 RSI Forecast 10 > MA Forecast 10
🔹 RSI Forecast 10 < MA Forecast 10
🔹 RSI Forecast 11 > MA Forecast 11
🔹 RSI Forecast 11 < MA Forecast 11
🔹 RSI Forecast 12 > MA Forecast 12
🔹 RSI Forecast 12 < MA Forecast 12
🔹 RSI Forecast 13 > MA Forecast 13
🔹 RSI Forecast 13 < MA Forecast 13
🔹 RSI Forecast 14 > MA Forecast 14
🔹 RSI Forecast 14 < MA Forecast 14
🔹 RSI Forecast 15 > MA Forecast 15
🔹 RSI Forecast 15 < MA Forecast 15
🔹 RSI Forecast 16 > MA Forecast 16
🔹 RSI Forecast 16 < MA Forecast 16
🔹 RSI Forecast 17 > MA Forecast 17
🔹 RSI Forecast 17 < MA Forecast 17
🔹 RSI Forecast 18 > MA Forecast 18
🔹 RSI Forecast 18 < MA Forecast 18
🔹 RSI Forecast 19 > MA Forecast 19
🔹 RSI Forecast 19 < MA Forecast 19
🔹 RSI Forecast 20 > MA Forecast 20
🔹 RSI Forecast 20 < MA Forecast 20
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🔸 CONDITIONS TO SELL 📉
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📉 RSI Conditions:
🔸 RSI > Upper
🔸 RSI < Upper
🔸 RSI > Lower
🔸 RSI < Lower
🔸 RSI > Middle
🔸 RSI < Middle
🔸 RSI > MA
🔸 RSI < MA
📉 MA Conditions:
🔸 MA > Upper
🔸 MA < Upper
🔸 MA > Lower
🔸 MA < Lower
📉 Crossovers:
🔸 RSI (Crossover) Upper
🔸 RSI (Crossunder) Upper
🔸 RSI (Crossover) Lower
🔸 RSI (Crossunder) Lower
🔸 RSI (Crossover) Middle
🔸 RSI (Crossunder) Middle
🔸 RSI (Crossover) MA
🔸 RSI (Crossunder) MA
🔸 MA (Crossover) Upper
🔸 MA (Crossunder) Upper
🔸 MA (Crossover) Lower
🔸 MA (Crossunder) Lower
📉 RSI Divergences:
🔸 RSI Divergence Bull
🔸 RSI Divergence Bear
📉 RSI Forecast:
🔸 RSI (Crossover) MA Forecast
🔸 RSI (Crossunder) MA Forecast
🔸 RSI Forecast 1 > MA Forecast 1
🔸 RSI Forecast 1 < MA Forecast 1
🔸 RSI Forecast 2 > MA Forecast 2
🔸 RSI Forecast 2 < MA Forecast 2
🔸 RSI Forecast 3 > MA Forecast 3
🔸 RSI Forecast 3 < MA Forecast 3
🔸 RSI Forecast 4 > MA Forecast 4
🔸 RSI Forecast 4 < MA Forecast 4
🔸 RSI Forecast 5 > MA Forecast 5
🔸 RSI Forecast 5 < MA Forecast 5
🔸 RSI Forecast 6 > MA Forecast 6
🔸 RSI Forecast 6 < MA Forecast 6
🔸 RSI Forecast 7 > MA Forecast 7
🔸 RSI Forecast 7 < MA Forecast 7
🔸 RSI Forecast 8 > MA Forecast 8
🔸 RSI Forecast 8 < MA Forecast 8
🔸 RSI Forecast 9 > MA Forecast 9
🔸 RSI Forecast 9 < MA Forecast 9
🔸 RSI Forecast 10 > MA Forecast 10
🔸 RSI Forecast 10 < MA Forecast 10
🔸 RSI Forecast 11 > MA Forecast 11
🔸 RSI Forecast 11 < MA Forecast 11
🔸 RSI Forecast 12 > MA Forecast 12
🔸 RSI Forecast 12 < MA Forecast 12
🔸 RSI Forecast 13 > MA Forecast 13
🔸 RSI Forecast 13 < MA Forecast 13
🔸 RSI Forecast 14 > MA Forecast 14
🔸 RSI Forecast 14 < MA Forecast 14
🔸 RSI Forecast 15 > MA Forecast 15
🔸 RSI Forecast 15 < MA Forecast 15
🔸 RSI Forecast 16 > MA Forecast 16
🔸 RSI Forecast 16 < MA Forecast 16
🔸 RSI Forecast 17 > MA Forecast 17
🔸 RSI Forecast 17 < MA Forecast 17
🔸 RSI Forecast 18 > MA Forecast 18
🔸 RSI Forecast 18 < MA Forecast 18
🔸 RSI Forecast 19 > MA Forecast 19
🔸 RSI Forecast 19 < MA Forecast 19
🔸 RSI Forecast 20 > MA Forecast 20
🔸 RSI Forecast 20 < MA Forecast 20
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
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Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
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📜 SCRIPT : RSI Full Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
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o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
faiz MACDMACD: Moving Average Convergence Divergence
The Moving Average Convergence Divergence (MACD) is a popular momentum indicator used in technical analysis to gauge the strength, direction, and potential reversal points of a trend in a financial asset's price movement. Developed by Gerald Appel in the late 1970s, MACD is particularly favored by traders for its ability to capture both trend-following and momentum aspects of price behavior.
Components of the MACD
The MACD is derived from two exponential moving averages (EMAs) of a security's price:
MACD Line: This is the difference between the 12-day and 26-day EMAs. The shorter 12-day EMA reacts more quickly to price changes, while the 26-day EMA smooths out price fluctuations, offering a longer-term perspective.
Formula: MACD Line = 12-day EMA - 26-day EMA
Signal Line: This is the 1-day EMA of the MACD Line itself. The signal line is used to generate buy and sell signals when it crosses the MACD line.
Formula: Signal Line = 1-day EMA of the MACD Line
MACD Histogram: The histogram represents the difference between the MACD Line and the Signal Line. It is displayed as bars that oscillate above and below a zero line, helping to visualize the convergence or divergence between the two lines.
Formula: Histogram = MACD Line - Signal Line
Interpretation of MACD
The MACD indicator is used to identify potential buy and sell signals based on the following observations:
MACD Line and Signal Line Crossovers:
Bullish Crossover: A buy signal occurs when the MACD Line crosses above the Signal Line. This suggests that the momentum is shifting in favor of the bulls, indicating a potential upward price movement.
Bearish Crossover: A sell signal occurs when the MACD Line crosses below the Signal Line. This suggests a bearish trend may be emerging, signaling a potential downward movement.
Divergence:
Bullish Divergence: Occurs when the price of the asset is making new lows, but the MACD is forming higher lows. This suggests that the downward momentum is weakening and a potential reversal to the upside may be imminent.
Bearish Divergence: Occurs when the price is making new highs, but the MACD is forming lower highs. This suggests that the upward momentum is weakening and a reversal to the downside may occur.
Only use it in timeframe m1, and solely use for XAUUSD pair.
Advisable to use it as a confirmation with other indicator such as
BBMA, SMC, SUPPORT RESISTANCE, SUPPLY AND DEMAND.
how to use :
MA 5 Crossing above MA9, will generate BUY signals
MA 5 Crossing below MA9, will generate SELL signals
Trade at your own SKILLS.
I dont mind people using this script for free.
All I want is just prayer for me and my family success.
Thank You and Have a nice and pleasant day :-)
2 MA Cross Cvg Dvg Slope Overview
This indicator combines the Moving Average Convergence Divergence (MACD) and two Moving Averages (MAs) to assess market momentum and trend direction. It aims to provide insights into the strength and direction of price movements by analyzing the MACD line, MAs slopes, and MA crossovers. Instead of eyeballing the exact MA crossovers and MAs slope steepness on the chart and MACD line changes on separate panes, this indicator pixelate the overloaded information or multiple indicators interpretation into a KISS "boolean" decision making.
Key Components
MACD Line
This line represents the difference between the fast MA and slow MA. It reflects short-term price momentum relative to the long-term trend.
Moving Averages (MAs)
Two types of MAs are utilized in this indicator:
Fast MA (short-term): Often a 9-period MA or similar, which reacts quickly to price changes.
Slow MA (long-term): Typically a 21-period MA or similar, which smooths out price fluctuations and identifies the longer-term trend.
Indicator Logic
MA Crossover: The crossover of the fast MA above the slow MA suggests a bullish trend, while a crossover below indicates a bearish trend.
MA Slope Analysis: The indicator also considers the slopes of both the fast and slow MAs to determine the direction:
Both MA Positive Slope: Indicates upward momentum or bullish trend.
Both MA Negative Slope: Indicates downward momentum or bearish trend.
One MA Positive Slope, the other Negative Slope: Indicates indecision.
MACD Line: MACD Line consecutively increase means increasing positive momentum, vice versa.
Interpretation
Uptrend: When fast MA cross over slow MA. Indicator show "+" symbol at top zone with value 0.5.
Additional Uptrend Confirmation: When both MAs have positive slope. Indicator show only green bar.
Uptrend Upward Momentum: MACD Line increase when fast MA above slow MA. Indicator show "." symbol value 0.75.
Uptrend Downward Momentum: MACD Line decrease when fast MA above slow MA. Indicator show "." symbol value 0.25.
Indecision: When one of the MA has positive slope, but another MA has negative slope. Indicator showing both red and green bar.
Downtrend: When fast MA cross under slow MA. Indicator show "+" symbol at bottom zone with value 0.5.
Additional Downtrend Confirmation: When both MAs have negative slope. Indicator show only red bar.
Downtrend Upward Momentum: MACD Line increase when fast MA below slow MA. Indicator show "." symbol value -0.25.
Uptrend Downward Momentum: MACD Line decrease when fast MA below slow MA. Indicator show "." symbol value -0.75.
Combination of above multiple interpretation can further derive different signal for Trend Starts, Trend Continuous, and Trend Reversals.
Usage
This indicator is valuable for traders seeking to:
Identify entry and exit points based on single or multiple combination of MAs and MACD Line signals.
Confirm trend direction using MAs cross over or cross under spotted easily with the "+" symbol above 0 or below 0.
Double confirm the trend based on two MAs align slope direction.
Understand momentum shifts and potential trend reversals with an easy 4 different dots at -0.75, -0.25, 0.25, and 0.75.
Conclusion
By combining MACD Line analysis with Moving Average slopes and crossovers, this indicator offers a comprehensive approach to assessing market momentum and trend direction. It provides clear signals for traders to make informed decisions on when to enter or exit positions, enhancing overall trading strategy effectiveness without the need of referring to multiple chart or zoom in and out of the price chart to identify the crossover and slope direction.
Swing High/Low & EMA Cross AlertScript Description:
This script on TradingView combines the detection of Swing High/Low points with exponential moving average (EMA) crossovers to provide buy and sell alerts and to mark swing points on the chart.
What the Script Does:
Swing High/Low Detection:
Uses the ta.pivothigh function to detect significant high points and the ta.pivotlow function to detect significant low points.
For each detected point, the script checks if it is a new higher high (HH) or lower high (LH) for the highs, and a new lower low (LL) or higher low (HL) for the lows.
Creates visual labels to identify these points on the chart, helping traders to visualize potential reversal points.
EMA Crossover:
Calculates two EMAs: a fast EMA (fastEMA) with a default period of 50 and a slow EMA (slowEMA) with a default period of 200.
Detects bullish crossovers (when fastEMA crosses above slowEMA) and bearish crossunders (when fastEMA crosses below slowEMA).
Generates buy and sell alerts based on these crossovers.
How the Script Works:
EMA Calculation: EMAs are calculated using the closing prices and user-defined periods.
Swing High/Low Detection: Uses the high and low values from the previous length bars to determine the swing points.
Alert Generation: Alerts are triggered when crossovers between the EMAs occur.
How to Use the Script:
Add to Chart: Insert the script into TradingView and apply it to the desired chart.
Configure Parameters:
Adjust the detection period for swing points (length).
Configure the periods for the EMAs (fastLen and slowLen).
Customize the colors for the swing point labels as per your preference.
Monitor Alerts: Use the EMA crossover alerts to make buy or sell decisions. Observe the swing point labels to identify potential trend reversals.
Justification for the Combination:
EMAs: Widely used to identify trend direction. Combining a fast EMA with a slow EMA helps capture both short-term and long-term trend changes.
Swing High/Low: Identifies reversal points in price, which are crucial for determining potential entry and exit points in trades.
Combination:
Combining EMAs and Swing High/Low provides a comprehensive view of price behavior, helping traders to effectively identify trends and reversal points.
This script is useful for traders who want to combine trend analysis (via EMAs) with the identification of reversal points (Swing High/Low), providing a more complete view of price behavior on the chart.
FibPulse144 [CHE] FibPulse144 — ADX-gated 13/21 crossover with 144-trend regime and closed-bar labels
Summary
FibPulse144 combines a fast moving-average crossover with a 144-period trend regime and an ADX strength gate. Signals are confirmed on closed bars only and drawn as labels on the price chart, while an ADX line in a separate pane provides context. Color gradients are derived from normalized ADX, so visual intensity reflects trend strength without changing the underlying logic. The approach reduces false flips during weak conditions and keeps entries aligned with the dominant trend.
Motivation: Why this design?
Traditional crossover signals can flip repeatedly during sideways phases and often trigger against the higher-time regime. By requiring alignment with a slower trend proxy and by gating entries through a rising ADX condition, FibPulse144 favors structurally cleaner transitions. Gradient coloring communicates strength visually, helping users temper aggressiveness without additional indicators.
What’s different vs. standard approaches?
Baseline: Classic dual-MA crossover with unconditional signals.
Architecture differences:
Two-bar regime confirmation against a 144-period trend average.
Pending-signal logic that waits for regime and optional ADX approval.
ADX strength gate using the prior reading relative to a user threshold and earlier value.
Gradient colors scaled by an ADX window with gamma controls.
Price-chart labels enforced via overlay on an otherwise pane-based indicator.
Practical effect: Fewer signals during weak or choppy conditions, labels that appear only after a bar closes, and color intensity that mirrors trend quality.
How it works (technical)
The script computes fast and slow moving averages using the selected method and lengths. A separate 144-length average defines the regime using a two-bar confirmation above or below it. Crossovers are observed on the previous bar to avoid intrabar ambiguity; once a prior crossover is detected, it is stored as pending. A pending long requires regime alignment and, if enabled, an ADX condition based on the previous reading being above the threshold and greater than an earlier reading. The state machine holds neutral, long, or short until an exit condition or ADX reset is met. ADX is normalized within a user window, scaled with gamma, and mapped to up and down color palettes to render gradients. Labels on the price panel are forced to overlay, while the ADX line and threshold guide remain in a separate pane.
Parameter Guide
Source — Input data for all calculations. Default: close. Tip: keep consistent with your chart.
MA Type — EMA or SMA. Default: EMA. EMA reacts faster; SMA is smoother.
Fast / Slow — Fast and slow lengths for crossover. Defaults: 13 and 21. Shorter reacts earlier; longer reduces noise.
Trend — Regime average length. Default: 144. Larger values stabilize regime; smaller values increase sensitivity.
Use 144 as trend filter — Enables regime gating. Default: true. Disable to allow raw crossovers.
Use ADX filter — Requires ADX strength. Default: true. Disable to allow signals regardless of strength.
ADX Len — DI and ADX smoothing length. Default: 14. Higher values smooth strength; lower values react faster.
ADX Thresh — Minimum strength for signals. Default: 25. Raise to reduce flips; lower to capture earlier moves.
Entry/Exit labels (price) — Price-panel labels on state changes. Default: true.
Signal labels in ADX pane — Small markers at the ADX value on entries. Default: true.
Label size — tiny, small, normal, large. Default: normal.
Enable barcolor — Optional candle tint by regime and gradient. Default: false.
Enable gradient — Turns on ADX-driven color blending. Default: true.
Window — Bars used to normalize ADX for colors. Default: 100; minimum: 5.
Gamma bars / Gamma plots — Nonlinear scaling for bar and line intensities. Default: 0.80; between 0.30 and 2.00.
Gradient transp (0–90) — Transparency for gradient colors. Default: 0.
MA fill transparency (0–100) — Fill opacity between fast and slow lines. Default: 65.
Palette colors (Up/Down) — Dark and neon endpoints for up and down gradients. Defaults as in the code.
Reading & Interpretation
Fast/Slow lines: When the fast line is above the slow line, the line and fill use the long palette; when below, the short palette is used.
Trend MA (144): Neutral gray line indicating the regime boundary.
Labels on price: “LONG” appears when the state turns long; “SHORT” when it turns short. Labels appear only after the bar closes and conditions are satisfied.
ADX pane: The ADX line shows current strength. The dotted threshold line is the user level for gating. Optional small markers indicate entries at the ADX value.
Bar colors (optional): Candle tint intensity reflects normalized ADX. Higher intensity implies stronger conditions.
Practical Workflows & Combinations
Trend following: Use long entries when fast crosses above slow and price has held above the trend average for two bars, with ADX above threshold. Mirror this for shorts below the trend average.
Exits and stops: Consider reducing exposure when price closes on the opposite side of the trend average for two consecutive bars or when ADX fades below the threshold if the ADX filter is enabled.
Structure confirmation: Combine with higher-timeframe structure such as swing highs and lows or a simple market structure overlay for confirmation.
Multi-asset/Multi-TF: Works across liquid assets. For lower timeframes, consider a slightly lower ADX threshold; for higher timeframes, maintain or raise the threshold to avoid unnecessary flips.
Behavior, Constraints & Performance
Repaint/confirmation: Signals are based on previous-bar crossovers and are confirmed on bar close. No higher-timeframe or security calls are used. Intrabar markers are not relied upon.
Resources: The script declares `max_bars_back` of 2000, uses no loops or arrays, and employs persistent variables for pending signals and state.
Known limits: Crossover systems can lag after sudden reversals. During tight ranges, disabling the ADX filter may increase flips; keeping it enabled may skip early transitions.
Sensible Defaults & Quick Tuning
Starting point: EMA, 13/21/144, ADX length 14, ADX threshold 25, gradients on, barcolor off.
Too many flips: Increase ADX threshold or length; increase trend length; consider SMA instead of EMA.
Too sluggish: Lower ADX threshold slightly; shorten fast and slow lengths; reduce the trend length.
Colors overpowering: Increase gradient transparency or reduce gamma values toward one.
What this indicator is—and isn’t
This is a visualization and signal layer that combines crossover, regime, and strength gating. It does not predict future movements, manage risk, or execute trades. Use it alongside clear structure, risk controls, and a defined position management plan.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
[TehThomas] - MA Cross with DisplacementThis TradingView script, "MA Cross with Displacement," is designed to detect potential long and short trade opportunities based on moving average (MA) crossovers combined with price displacement confirmation. The script utilizes two simple moving averages (SMA) and highlights potential trade signals when a crossover occurs alongside a strong price movement (displacement).
Why This Indicator is Useful
This indicator enhances the standard moving average crossover strategy by incorporating a displacement condition, making trade signals more reliable. Many traders rely on moving average crossovers to determine trend reversals, but false signals often occur due to minor price fluctuations. By requiring a significant price movement (displacement), this indicator helps filter out weak or insignificant crossovers, leading to more high-probability trade opportunities.
How It Works
Calculates Two Moving Averages (MA)
The user can set two different MA periods:
MA 1 (blue line): Default period is 9 (shorter-term trend).
MA 2 (red line): Default period is 21 (longer-term trend).
These moving averages smooth out price fluctuations to identify overall trends.
Detects Crossovers
Bullish crossover: The blue MA crosses above the red MA + displacement candle → Potential long signal.
Example of bullish cross with displacement:
Bearish crossover: The blue MA crosses below the red MA + displacement candle → Potential short signal.
Example of bearish cross with displacement:
Confirms Displacement (Strong Price Move)
A price displacement threshold is used (default: 1.1% of the previous candle size).
For a valid trade signal, a crossover must occur alongside a strong price movement.
Bullish Displacement Condition: Price increased by more than the threshold.
Bearish Displacement Condition: Price decreased by more than the threshold.
Visual Indicators on the Chart
Bars are colored green when there is a bullish displacement.
Bars are colored red when there is a bearish displacement.
These color changes help traders quickly identify potential trade setups.
How to Use the Indicator
Add the Script to Your Chart
Copy and paste the script into TradingView's Pine Script Editor.
Click "Add to Chart" to activate it.
Customize the Settings
Adjust the moving average periods to fit your trading strategy.
Modify the displacement threshold based on market volatility.
Change the bar colors for better visualization.
Look for Trade Signals
Long Trade (Buy Signal)
The blue MA crosses above the red MA (bullish crossover).
A green bar appears, confirming bullish displacement.
Short Trade (Sell Signal)
The blue MA crosses below the red MA (bearish crossover).
A red bar appears, confirming bearish displacement.
Use in Conjunction with Other Indicators
This indicator works best when combined with support & resistance levels, RSI, MACD, or volume analysis to improve trade accuracy.
Final Thoughts
The MA Cross with Displacement Indicator improves the reliability of moving average crossovers by requiring strong price movements to confirm a trade signal. This helps traders avoid false breakouts and weak trends, making it a powerful tool for identifying high-probability trades.
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ATR Adjusted RSIATR Adjusted RSI Indicator
By Nathan Farmer
The ATR Adjusted RSI Indicator is a versatile indicator designed primarily for trend-following strategies, while also offering configurations for overbought/oversold (OB/OS) signals, making it suitable for mean-reversion setups. This tool combines the classic Relative Strength Index (RSI) with a unique Average True Range (ATR)-based smoothing mechanism, allowing traders to adjust their RSI signals according to market volatility for more reliable entries and exits.
Key Features:
ATR Weighted RSI:
At the core of this indicator is the ATR-adjusted RSI line, where the RSI is smoothed based on volatility (measured by the ATR). When volatility increases, the smoothing effect intensifies, resulting in a more stable and reliable RSI reading. This makes the indicator more responsive to market conditions, which is especially useful in trend-following systems.
Multiple Signal Types:
This indicator offers a variety of signal-generation methods, adaptable to different market environments and trading preferences:
RSI MA Crossovers: Generates signals when the RSI crosses above or below its moving average, with the flexibility to choose between different moving average types (SMA, EMA, WMA, etc.).
Midline Crossovers: Provides trend confirmation when either the RSI or its moving average crosses the 50 midline, signaling potential trend reversals.
ATR-Inversely Weighted RSI Variations: Uses the smoothed, ATR-adjusted RSI for a more refined and responsive trend-following signal. There are variations both for the MA crossover and the midline crossover.
Overbought/Oversold Conditions: Ideal for mean reversion setups, where signals are triggered when the RSI or its moving average crosses over overbought or oversold levels.
Flexible Customization:
With a wide range of customizable options, you can tailor the indicator to fit your personal trading style. Choose from various moving average types for the RSI, modify the ATR smoothing length, and adjust overbought/oversold levels to optimize your signals.
Usage:
While this indicator is primarily designed for trend-following, its OB/OS configurations make it highly effective for mean-reverting setups as well. Depending on your selected signal type, the relevant indicator line will change color between green and red to visually signal long or short opportunities. This flexibility allows traders to switch between trending and sideways market strategies seamlessly.
A Versatile Tool:
The ATR Adjusted RSI Indicator is a valuable component of any trading system, offering enhanced signals that adapt to market volatility. However, it is not recommended to rely on this indicator alone, especially without thorough backtesting. Its performance varies across different assets and timeframes, so it’s essential to experiment with the parameters to ensure consistent results before applying it in live trading.
Recommendation:
Before incorporating this indicator into live trading, backtest it extensively. Given its flexibility and wide range of signal-generation methods, backtesting allows you to optimize the settings for your preferred assets and timeframes. Only consider using it on it's own if you are confident in its performance based on your own backtest results, and even then, it is not recommended.
Fractal Resonance ComponentLazyBear's WaveTrend port has been praised for highlighting trend reversals with precision and punctuality (minimal lag). But strong "3rd Wave" trends can "embed" or saturate any oscillator flashing several premature crosses while stuck overbought/oversold. This happens when the trend stretches over a longer timescale than the oscillator's averaging window or filter time constant. Our solution: simultaneously monitor many oscillator timescales. Watch for fresh crossovers in "dominant" timescales alternating most smoothly between the overbought (red shade) and oversold (green shade) range.
Fractal Resonance Component facilitates simultaneous viewing of eight timescales that are power of 2 multiples of the chart timescale. Each timescale shows lead line, lag line, lead-lag difference, and crossover marks. Add 4 to 8 copies to your chart for a good multi-fractal read. Format * the "Timescale Multiplier" attribute of each row to be twice that of the row above for a sequence like 1, 2, 4, 8, 16, 32, 64, 128...
Fractal Resonance Component shifts its timescales along with your choice of main chart timescale:
1 minute chart: 1 minute through 128 minute (~2 hour) oscillators.
1 hour chart: 1 hour through 128 hour (~2 week) oscillators.
Daily chart: 1 day through 128 day (~4 month) oscillators.
Crossovers in different oscillator ranges tend to have different meanings:
Minor (< 75%) crossovers: small green/red dot
usually noise
Overbought/Sold crossovers (shaded 75 to 100%): black outlined dot (o)
reliable reversal indicators (when they appear alone)
Extreme Overbought (> 100%) crossovers: black outlined plus (+).
Can be a major reversal in fast markets, but usually portend the end of Elliot 3rd waves with just a small corrective (4th wave) retrace before the larger impulsive (5-wave) sequence resumes in original direction.
The final 5th-wave terminus should appear later as a lone non-extreme (black outlined circle) crossover on a slower timescale coincident with weaker (non-extreme) dot crosses on this timescale.
Careful examination of historical charts leads to many useful observations such as:
Dominant crossovers punctuating true reversals are usually in the green/red shaded ranges with black outlined dots (o) rather than minor or Extreme (+) ranges.
Due to market's fractal nature, two well-separated timescales like 1 minute and 1 hour can show dominant crosses simultaneously in opposite directions, e.g. the 1 minute showing a very short term high and the 1 hour a medium term low nearby.
Staying Nimble
Watch out for embedding on your supposedly dominant timescale -- a second cross while stuck in the overbought/oversold region suggests a stronger, longer trend than expected. Drop your eyes to a slower timescale below for the real dominant whose crossover will validate main trend reversal.
Embedding can often be predicted even at the first cross mark by checking whether the green lead line of the next slower timescale (one row below) has already hit the Overbought or especially the Extreme Overbought range but isn't close to rolling over. Fractal Resonance Bar (to be published) uses this principle to mark embedded timescales with white stripes, warning of a powerful trend wave on longer timescales you shouldn't fight until the white stripes subside.
Overnight gaps surge all timescales in ways that obscure the dominant timescale, so for shorter than daily charts, these methods work best on Futures contracts that only suffer weekend gaps.
Volume Flow with Bollinger Bands and EMA Cross SignalsThe Volume Flow with Bollinger Bands and EMA Cross Signals indicator is a custom technical analysis tool designed to identify potential buy and sell signals based on several key components:
Volume Flow: This component combines price movement and trading volume to create a signal that indicates the strength or weakness of price movements. When the price is rising with increasing volume, it suggests strong buying activity, whereas falling prices with increasing volume indicate strong selling pressure.
Bollinger Bands: Bollinger Bands consist of three lines:
The Basis (middle line), which is a Simple Moving Average (SMA) of the price over a set period.
The Upper Band, which is the Basis plus a multiple of the standard deviation (typically 2).
The Lower Band, which is the Basis minus a multiple of the standard deviation. Bollinger Bands help identify periods of high volatility and potential overbought/oversold conditions. When the price touches the upper band, it might indicate that the market is overbought, while touching the lower band might indicate oversold conditions.
EMA Crossovers: The script includes two Exponential Moving Averages (EMAs):
Fast EMA: A shorter-term EMA, typically more sensitive to price changes.
Slow EMA: A longer-term EMA, responding slower to price changes. The crossover of the Fast EMA crossing above the Slow EMA (bullish crossover) signals a potential buy opportunity, while the Fast EMA crossing below the Slow EMA (bearish crossover) signals a potential sell opportunity.
Background Color and Candle Color: The indicator highlights the chart's background with specific colors based on the signals:
Green background for buy signals.
Yellow background for sell signals. Additionally, the candles are colored green for buy signals and yellow for sell signals to visually reinforce the trade opportunities.
Buy/Sell Labels: Small labels are placed on the chart:
"BUY" label in green is placed below the bar when a buy signal is generated.
"SELL" label in yellow is placed above the bar when a sell signal is generated.
Working of the Indicator:
Volume Flow Calculation: The Volume Flow is calculated by multiplying the price change (current close minus the previous close) with the volume. This product is then smoothed with a Simple Moving Average (SMA) over a user-defined period (length). The result is then multiplied by a multiplier to adjust its sensitivity.
Price Change = close - close
Volume Flow = Price Change * Volume
Smoothed Volume Flow = SMA(Volume Flow, length)
The Volume Flow Signal is then: Smooth Volume Flow * Multiplier
This calculation represents the buying or selling pressure in the market.
Bollinger Bands: Bollinger Bands are calculated using the Simple Moving Average (SMA) of the closing price (basis) and the Standard Deviation (stdev) of the price over a period defined by the user (bb_length).
Basis (Middle Band) = SMA(close, bb_length)
Upper Band = Basis + (bb_std_dev * Stdev)
Lower Band = Basis - (bb_std_dev * Stdev)
The upper and lower bands are plotted alongside the price to identify the price's volatility. When the price is near the upper band, it could be overbought, and near the lower band, it could be oversold.
EMA Crossovers: The Fast EMA and Slow EMA are calculated using the Exponential Moving Average (EMA) function. The crossovers are detected by checking:
Buy Signal (Bullish Crossover): When the Fast EMA crosses above the Slow EMA.
Sell Signal (Bearish Crossover): When the Fast EMA crosses below the Slow EMA.
The long_condition variable checks if the Fast EMA crosses above the Slow EMA, and the short_condition checks if it crosses below.
Visual Signals:
Background Color: The background is colored green for a buy signal and yellow for a sell signal. This gives an immediate visual cue to the trader.
Bar Color: The candles are colored green for buy signals and yellow for sell signals.
Labels:
A "BUY" label in green appears below the bar when the Fast EMA crosses above the Slow EMA.
A "SELL" label in yellow appears above the bar when the Fast EMA crosses below the Slow EMA.
Summary of Buy/Sell Logic:
Buy Signal:
The Fast EMA crosses above the Slow EMA (bullish crossover).
Volume flow is positive, indicating buying pressure.
Background turns green and candles are colored green.
A "BUY" label appears below the bar.
Sell Signal:
The Fast EMA crosses below the Slow EMA (bearish crossover).
Volume flow is negative, indicating selling pressure.
Background turns yellow and candles are colored yellow.
A "SELL" label appears above the bar.
Usage of the Indicator:
This indicator is designed to help traders identify potential entry (buy) and exit (sell) points based on:
The interaction of Exponential Moving Averages (EMAs).
The strength and direction of Volume Flow.
Price volatility using Bollinger Bands.
By combining these components, the indicator provides a comprehensive view of market conditions, helping traders make informed decisions on when to enter and exit trades.
UtilityLibrary "Utility"
A utility library for various trading tools such as signal generation, custom indicators, and multi-condition crossovers.
multiCrossover(source1, source2, threshold1, threshold2)
multiCrossover
@description Detects multi-condition crossovers between two sources with threshold filters.
Parameters:
source1 (float) : The first data series to compare.
source2 (float) : The second data series to compare.
threshold1 (float) : A value that source1 must exceed to trigger the crossover.
threshold2 (float) : A value that source2 must exceed to trigger the crossunder.
Returns: A tuple: (crossUp, crossDown) where crossUp is a boolean for upward crossover, and crossDown is for downward crossover.
macdCustom(source, fastLength, slowLength, signalLength, macdThresh)
macdCustom
@description Calculates custom MACD signals based on thresholds.
Parameters:
source (float) : The price data or input series.
fastLength (simple int) : The length of the fast EMA.
slowLength (simple int) : The length of the slow EMA.
signalLength (simple int) : The signal line length.
macdThresh (float) : A threshold for the MACD line to confirm buy/sell signals.
Returns: A tuple: (macdBuySignal, macdSellSignal) where macdBuySignal is true when MACD crosses above, and macdSellSignal is true when MACD crosses below the signal line.
combinedMacdRsi(source, fastLength, slowLength, signalLength, rsiLength, macdThresh, rsiThresh)
combinedMacdRsi
@description Generates combined signals from MACD and RSI indicators.
Parameters:
source (float) : The price data or input series.
fastLength (simple int) : The length of the fast EMA for MACD.
slowLength (simple int) : The length of the slow EMA for MACD.
signalLength (simple int) : The signal line length for MACD.
rsiLength (simple int) : The length of the RSI calculation.
macdThresh (float) : The threshold for MACD signals.
rsiThresh (float) : The threshold for RSI signals.
Returns: A tuple: (buySignal, sellSignal) where buySignal is generated when MACD is positive and RSI is below the threshold, and sellSignal when MACD is negative and RSI is above the threshold.
movingAverageCrossover(source, shortLength, longLength)
movingAverageCrossover
@description Detects crossovers between short-term and long-term moving averages.
Parameters:
source (float) : The price data or input series.
shortLength (int) : The length of the short-term moving average.
longLength (int) : The length of the long-term moving average.
Returns: A tuple: (crossUp, crossDown) where crossUp is true when the short-term MA crosses above the long-term MA, and crossDown when the reverse occurs.
Stochastic RSI with MTF TableShort Description of the Script
The provided Pine Script indicator, titled "Stochastic RSI with MTF Table," calculates and displays the Stochastic RSI for the current timeframe and multiple other timeframes (5m, 15m, 30m, 60m, 240m, and daily). The Stochastic RSI is a momentum indicator that blends the Relative Strength Index (RSI) and Stochastic Oscillator to identify overbought and oversold conditions, as well as potential trend reversals via K and D line crossovers.
Key features of the script include:
Inputs: Customizable parameters such as K smoothing (default 3), D smoothing (default 3), RSI length (default 14), Stochastic length (default 14), source price (default close), and overbought/oversold levels (default 80/20).
MTF Table: A table displays the Stochastic RSI status for each timeframe:
"OB" (overbought) if K > 80, "OS" (oversold) if K < 20, or "N" (neutral) otherwise.
Crossovers: "K↑D" for bullish (K crosses above D) and "K↓D" for bearish (K crosses below D).
Visualization: Plots the K and D lines for the current timeframe, with horizontal lines at 80 (overbought), 50 (middle), and 20 (oversold), plus a background fill for clarity.
Table Position: Configurable to appear in one of four chart corners (default: top-right).
This indicator helps traders assess momentum across multiple timeframes simultaneously, aiding in the identification of trend strength and potential entry/exit points.
Trading Strategy with 50EMA and 200EMA for Highest Winning Rate
To create a strategy with the best probability of a high winning rate using the Stochastic RSI MTF indicator alongside the 50-period Exponential Moving Average (50EMA) and 200-period Exponential Moving Average (200EMA), we can combine trend identification with momentum-based entry timing. The 50EMA and 200EMA are widely used to determine medium- and long-term trends, while the Stochastic RSI MTF table provides multi-timeframe momentum signals. Here’s the strategy:
1. Determine the Overall Trend
Bullish Trend: The 50EMA is above the 200EMA on the current timeframe (e.g., daily or 60m chart). This suggests an uptrend, often associated with a "Golden Cross."
Bearish Trend: The 50EMA is below the 200EMA on the current timeframe. This indicates a downtrend, often linked to a "Death Cross."
Implementation: Plot the 50EMA and 200EMA on your chart and visually confirm their relative positions.
2. Identify Entry Signals Using the Stochastic RSI MTF Table
In a Bullish Trend (50EMA > 200EMA):
Look for timeframes in the MTF table showing:
Oversold (OS): K < 20, indicating a potential pullback in the uptrend where price may rebound.
Bullish Crossover (K↑D): K crosses above D, signaling rising momentum and a potential entry point.
Example: If the 60m and 240m timeframes show "OS" or "K↑D," this could be a buy signal.
In a Bearish Trend (50EMA < 200EMA):
Look for timeframes in the MTF table showing:
Overbought (OB): K > 80, suggesting a rally in the downtrend where price may reverse downward.
Bearish Crossover (K↓D): K crosses below D, indicating declining momentum and a potential short entry.
Example: If the 30m and daily timeframes show "OB" or "K↓D," this could be a sell/short signal.
Current Timeframe Check: Use the plotted K and D lines on your trading timeframe for precise entry timing (e.g., confirm a K↑D crossover on a 60m chart for a long trade).
3. Confirm Signals Across Multiple Timeframes
Strengthen the Signal: A higher winning rate is more likely when multiple timeframes align with the trend and signal. For instance:
Bullish trend + "OS" or "K↑D" on 60m, 240m, and daily = strong buy signal.
Bearish trend + "OB" or "K↓D" on 15m, 60m, and 240m = strong sell signal.
Prioritize Higher Timeframes: Signals from the 240m or daily timeframe carry more weight due to their indication of broader trends, increasing reliability.
4. Set Stop-Loss and Take-Profit Levels
Long Trades (Bullish):
Stop-Loss: Place below the most recent swing low or below the 50EMA, whichever is closer, to protect against trend reversals.
Take-Profit: Target a key resistance level or use a risk-reward ratio (e.g., 2:1 or 3:1) based on the stop-loss distance.
Short Trades (Bearish):
Stop-Loss: Place above the most recent swing high or above the 50EMA, whichever is closer.
Take-Profit: Target a key support level or apply a similar risk-reward ratio.
Trailing Stop Option: As the trend progresses, trail the stop below the 50EMA (for longs) or above it (for shorts) to lock in profits.
5. Risk Management
Position Sizing: Risk no more than 1-2% of your trading capital per trade to minimize losses from false signals.
Volatility Consideration: Adjust stop-loss distances and position sizes based on the asset’s volatility (e.g., wider stops for volatile stocks or crypto).
Avoid Overtrading: Wait for clear alignment between the EMA trend and MTF signals to avoid low-probability setups.
Example Scenario
Chart: 60-minute timeframe.
Trend: 50EMA > 200EMA (bullish).
MTF Table: 60m shows "OS," 240m shows "K↑D," and daily is "N."
Action: Enter a long position when the 60m K line crosses above D, confirming the table signal.
Stop-Loss: Below the recent 60m swing low (e.g., 2% below entry).
Take-Profit: At the next resistance level or a 3:1 reward-to-risk ratio.
Outcome: High probability of success due to trend alignment and multi-timeframe confirmation.
Why This Strategy Works
Trend Following: Trading in the direction of the 50EMA/200EMA trend reduces the risk of fighting the market’s momentum.
Momentum Timing: The Stochastic RSI MTF table pinpoints pullbacks or reversals within the trend, improving entry timing.
Multi-Timeframe Confirmation: Alignment across timeframes filters out noise, increasing the win rate.
Risk Control: Defined stop-loss and position sizing protect against inevitable losses.
Caveats
No strategy guarantees a 100% win rate; false signals can occur, especially in choppy markets.
Test this strategy on historical data or a demo account to verify its effectiveness for your asset and timeframe.
This approach leverages the strengths of both trend-following (EMA) and momentum (Stochastic RSI) tools, aiming for a high-probability, disciplined trading system.
RSI Forecast [Titans_Invest]RSI Forecast
Introducing one of the most impressive RSI indicators ever created – arguably the best on TradingView, and potentially the best in the world.
RSI Forecast is a visionary evolution of the classic RSI, merging powerful customization with groundbreaking predictive capabilities. While preserving the core principles of traditional RSI, it takes analysis to the next level by allowing users to anticipate potential future RSI movements.
Real-Time RSI Forecasting:
For the first time ever, an RSI indicator integrates linear regression using the least squares method to accurately forecast the future behavior of the RSI. This innovation empowers traders to stay one step ahead of the market with forward-looking insight.
Highly Customizable:
Easily adapt the indicator to your personal trading style. Fine-tune a variety of parameters to generate signals perfectly aligned with your strategy.
Innovative, Unique, and Powerful:
This is the world’s first RSI Forecast to apply this predictive approach using least squares linear regression. A truly elite-level tool designed for traders who want a real edge in the market.
⯁ SCIENTIFIC BASIS LINEAR REGRESSION
Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥.
The general formula for a simple linear regression is given by:
y = β₀ + β₁x + ε
Where:
y = is the predicted variable (e.g. future value of RSI)
x = is the explanatory variable (e.g. time or bar index)
β0 = is the intercept (value of 𝑦 when 𝑥 = 0)
𝛽1 = is the slope of the line (rate of change)
ε = is the random error term
The goal is to estimate the coefficients 𝛽0 and 𝛽1 so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares.
⯁ LEAST SQUARES ESTIMATION
To minimize the error between predicted and observed values, we use the following formulas:
β₁ = /
β₀ = ȳ - β₁x̄
Where:
∑ = sum
x̄ = mean of x
ȳ = mean of y
x_i, y_i = individual values of the variables.
Where:
x_i and y_i are the means of the independent and dependent variables, respectively.
i ranges from 1 to n, the number of observations.
These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity.
⯁ LINEAR REGRESSION IN MACHINE LEARNING
Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies.
By applying this model to the RSI, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis.
⯁ VISUAL INTERPRETATION
Imagine an RSI time series like this:
Time →
RSI →
The regression line will smooth these values and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted RSI, which can be crossed with the actual RSI to generate more intelligent signals.
⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED
Linear Regression Models the relationship between variables using a straight line.
Least Squares Minimizes the sum of squared errors between prediction and reality.
Time Series Forecasting Estimates future values based on historical data.
Supervised Learning Trains models to predict outputs from known inputs.
Statistical Smoothing Reduces noise and reveals underlying trends.
⯁ WHY THIS INDICATOR IS REVOLUTIONARY
Scientifically-based: Based on statistical theory and mathematical inference.
Unprecedented: First public RSI with least squares predictive modeling.
Intelligent: Built with machine learning logic.
Practical: Generates forward-thinking signals.
Customizable: Flexible for any trading strategy.
⯁ CONCLUSION
By combining RSI with linear regression, this indicator allows a trader to predict market momentum, not just follow it.
RSI Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology.
⯁ Example of simple linear regression, which has one independent variable:
⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ).
⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values using Matlab:
⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables.
⯁ The result of fitting a set of data points with a quadratic function:
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🥇 This is the world’s first RSI indicator with: Linear Regression for Forecasting 🥇_______________________________________________________________________
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🔮 Linear Regression: PineScript Technical Parameters 🔮
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Forecast Types:
• Flat: Assumes prices will remain the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
ta.linreg (built-in function)
Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values calculated using the least squares method on the source series.
Syntax:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset: Offset.
• return: Linear regression curve.
This function has been cleverly applied to the RSI, making it capable of projecting future values based on past statistical trends.
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⯁ WHAT IS THE RSI❓
The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend.
⯁ HOW TO USE THE RSI❓
The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:
• Overbought: When the RSI is above 70, indicating that the asset may be overbought.
• Oversold: When the RSI is below 30, indicating that the asset may be oversold.
• Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions.
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⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📈 RSI Conditions:
🔹 RSI > Upper
🔹 RSI < Upper
🔹 RSI > Lower
🔹 RSI < Lower
🔹 RSI > Middle
🔹 RSI < Middle
🔹 RSI > MA
🔹 RSI < MA
📈 MA Conditions:
🔹 MA > Upper
🔹 MA < Upper
🔹 MA > Lower
🔹 MA < Lower
📈 Crossovers:
🔹 RSI (Crossover) Upper
🔹 RSI (Crossunder) Upper
🔹 RSI (Crossover) Lower
🔹 RSI (Crossunder) Lower
🔹 RSI (Crossover) Middle
🔹 RSI (Crossunder) Middle
🔹 RSI (Crossover) MA
🔹 RSI (Crossunder) MA
🔹 MA (Crossover) Upper
🔹 MA (Crossunder) Upper
🔹 MA (Crossover) Lower
🔹 MA (Crossunder) Lower
📈 RSI Divergences:
🔹 RSI Divergence Bull
🔹 RSI Divergence Bear
📈 RSI Forecast:
🔮 RSI (Crossover) MA Forecast
🔮 RSI (Crossunder) MA Forecast
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🔸 CONDITIONS TO SELL 📉
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
📉 RSI Conditions:
🔸 RSI > Upper
🔸 RSI < Upper
🔸 RSI > Lower
🔸 RSI < Lower
🔸 RSI > Middle
🔸 RSI < Middle
🔸 RSI > MA
🔸 RSI < MA
📉 MA Conditions:
🔸 MA > Upper
🔸 MA < Upper
🔸 MA > Lower
🔸 MA < Lower
📉 Crossovers:
🔸 RSI (Crossover) Upper
🔸 RSI (Crossunder) Upper
🔸 RSI (Crossover) Lower
🔸 RSI (Crossunder) Lower
🔸 RSI (Crossover) Middle
🔸 RSI (Crossunder) Middle
🔸 RSI (Crossover) MA
🔸 RSI (Crossunder) MA
🔸 MA (Crossover) Upper
🔸 MA (Crossunder) Upper
🔸 MA (Crossover) Lower
🔸 MA (Crossunder) Lower
📉 RSI Divergences:
🔸 RSI Divergence Bull
🔸 RSI Divergence Bear
📉 RSI Forecast:
🔮 RSI (Crossover) MA Forecast
🔮 RSI (Crossunder) MA Forecast
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
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Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
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📜 SCRIPT : RSI Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
RSI Full [Titans_Invest]RSI Full
One of the most complete RSI indicators on the market.
While maintaining the classic RSI foundation, our indicator integrates multiple entry conditions to generate more accurate buy and sell signals.
All conditions are fully configurable, allowing complete customization to fit your trading strategy.
⯁ WHAT IS THE RSI❓
The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend.
⯁ HOW TO USE THE RSI❓
The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:
Overbought: When the RSI is above 70, indicating that the asset may be overbought.
Oversold: When the RSI is below 30, indicating that the asset may be oversold.
Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions.
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND/OR .
📈 RSI Conditions:
🔹 RSI > Upper
🔹 RSI < Upper
🔹 RSI > Lower
🔹 RSI < Lower
🔹 RSI > Middle
🔹 RSI < Middle
🔹 RSI > MA
🔹 RSI < MA
📈 MA Conditions:
🔹 MA > Upper
🔹 MA < Upper
🔹 MA > Lower
🔹 MA < Lower
📈 Crossovers:
🔹 RSI (Crossover) Upper
🔹 RSI (Crossunder) Upper
🔹 RSI (Crossover) Lower
🔹 RSI (Crossunder) Lower
🔹 RSI (Crossover) Middle
🔹 RSI (Crossunder) Middle
🔹 RSI (Crossover) MA
🔹 RSI (Crossunder) MA
🔹 MA (Crossover) Upper
🔹 MA (Crossunder) Upper
🔹 MA (Crossover) Lower
🔹 MA (Crossunder) Lower
📈 RSI Divergences:
🔹 RSI Divergence Bull
🔹 RSI Divergence Bear
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🔸 CONDITIONS TO SELL 📉
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• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND/OR .
📉 RSI Conditions:
🔸 RSI > Upper
🔸 RSI < Upper
🔸 RSI > Lower
🔸 RSI < Lower
🔸 RSI > Middle
🔸 RSI < Middle
🔸 RSI > MA
🔸 RSI < MA
📉 MA Conditions:
🔸 MA > Upper
🔸 MA < Upper
🔸 MA > Lower
🔸 MA < Lower
📉 Crossovers:
🔸 RSI (Crossover) Upper
🔸 RSI (Crossunder) Upper
🔸 RSI (Crossover) Lower
🔸 RSI (Crossunder) Lower
🔸 RSI (Crossover) Middle
🔸 RSI (Crossunder) Middle
🔸 RSI (Crossover) MA
🔸 RSI (Crossunder) MA
🔸 MA (Crossover) Upper
🔸 MA (Crossunder) Upper
🔸 MA (Crossover) Lower
🔸 MA (Crossunder) Lower
📉 RSI Divergences:
🔸 RSI Divergence Bull
🔸 RSI Divergence Bear
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
______________________________________________________
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : RSI Full
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy the Spell!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Supertrend and Fast and Slow EMA StrategyThis strategy combines Exponential Moving Averages (EMAs) and Average True Range (ATR) to create a simple, yet effective, trend-following approach. The strategy filters out fake or sideways signals by incorporating the ATR as a volatility filter, ensuring that trades are only taken during trending conditions. The key idea is to buy when the short-term trend (Fast EMA) aligns with the long-term trend (Slow EMA), and to avoid trades during low volatility periods.
How It Works:
EMA Crossover:
1). Buy Signal: When the Fast EMA (shorter-term, e.g., 20-period) crosses above the Slow EMA (longer-term, e.g., 50-period), this indicates a potential uptrend.
2). Sell Signal: When the Fast EMA crosses below the Slow EMA, this indicates a potential downtrend.
ATR Filter:
1). The ATR (Average True Range) is used to measure market volatility.
2). Trending Market: If the ATR is above a certain threshold, it indicates high volatility and a trending market. Only when ATR is above the threshold will the strategy generate buy/sell signals.
3). Sideways Market: If ATR is low (sideways or choppy market), the strategy will suppress signals to avoid entering during non-trending conditions.
When to Buy:
1). Condition 1: The Fast EMA crosses above the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, indicating that the market is trending (not sideways or choppy).
When to Sell:
1). Condition 1: The Fast EMA crosses below the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, confirming that the market is in a downtrend.
When Not to Enter the Trade:
1). Sideways Market: If the ATR is below the threshold, signaling low volatility and sideways or choppy market conditions, the strategy will not trigger any buy or sell signals.
2). False Crossovers: In low volatility conditions, price action tends to be noisy, which could lead to false signals. Therefore, avoiding trades during these periods reduces the risk of false breakouts.
Additional Factors to Consider Adding:
=> RSI (Relative Strength Index): Adding an RSI filter can help confirm overbought or oversold conditions to avoid buying into overextended moves or selling too low.
1). RSI Buy Filter: Only take buy signals when RSI is below 70 (avoiding overbought conditions).
2). RSI Sell Filter: Only take sell signals when RSI is above 30 (avoiding oversold conditions).
=> MACD (Moving Average Convergence Divergence): Using MACD can help validate the strength of the trend.
1). Buy when the MACD histogram is above the zero line and the Fast EMA crosses above the Slow EMA.
2). Sell when the MACD histogram is below the zero line and the Fast EMA crosses below the Slow EMA.
=> Support/Resistance Levels: Adding support and resistance levels can help you understand market structure and decide whether to enter or exit a trade.
1). Buy when price breaks above a significant resistance level (after a valid buy signal).
2). Sell when price breaks below a major support level (after a valid sell signal).
=> Volume: Consider adding a volume filter to ensure that buy/sell signals are supported by strong market participation. You could only take signals if the volume is above the moving average of volume over a certain period.
=> Trailing Stop Loss: Instead of a fixed stop loss, use a trailing stop based on a percentage or ATR to lock in profits as the trade moves in your favor.
=> Exit Signals: Besides the EMA crossover, consider adding Take Profit or Stop Loss levels, or even using a secondary indicator like RSI to signal an overbought/oversold condition and exit the trade.
Example Usage:
=> Buy Example:
1). Fast EMA (20-period) crosses above the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is below 70, the buy signal is further confirmed as not being overbought.
=> Sell Example:
1). Fast EMA (20-period) crosses below the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is above 30, the sell signal is further confirmed as not being oversold.
Conclusion:
This strategy helps to identify trending markets and filters out sideways or choppy market conditions. By using Fast and Slow EMAs combined with the ATR volatility filter, it provides a reliable approach to catching trending moves while avoiding false signals during low-volatility, sideways markets.
Enhanced SPX and BTC Overlay with EMASPX-BTC Momentum Gauge and EMA Cross Indicator
Thorough Analysis:
• Combined Overlay (Green/Red Line):
o Function: Plots a wide line over the price chart, representing a composite of SPX and BTC dynamics adjusted by volume data.
o Color Coding:
Green: Indicates bullish conditions when the combined value exceeds its 10-period SMA and Bitcoin volume increases.
Red: Signals bearish conditions when the combined value drops below its 10-period SMA and Bitcoin volume decreases.
o Line Characteristics:
Width: Set at 8 for high visibility.
Transparency: 86% for both colors to overlay without obscuring candlesticks.
Scaling: Uses a factor of 0.02446 to amplify movements, making trend changes more noticeable.
• Continuous Bright Red and Green Lines:
o 20-period EMA of Current Ticker (Red):
Purpose: Acts as a medium-term trend indicator, smoothing price data to reflect the asset's general direction over time.
Color: Bright red for easy identification.
Transparency: 60% to keep it visible but not overpowering.
o 5-period EMA of BTC (Green):
Purpose: Provides insights into short-term Bitcoin momentum, capturing rapid changes in market sentiment.
Color: Bright green to distinguish from the red EMA.
Transparency: 30% for high visibility against price movements.
Detailed Analysis of the EMA Cross:
• Crossing Points:
o Bullish Crossover:
Occurs when the 5-period BTC EMA (green) moves above the 20-period EMA of the current ticker (red).
Suggests that Bitcoin's short-term momentum is gaining strength relative to the asset's medium-term trend, potentially signaling an upcoming uptrend or strengthening of an existing one.
o Bearish Crossover:
When the green line falls below the red, it indicates that Bitcoin's immediate momentum is weakening compared to the asset's medium-term trend, which might precede a downtrend or confirm one.
• Early Trade Signals:
o Entry/Exit Points:
These crossovers can guide traders in making timely decisions to enter or exit trades, especially when corroborated by the combined overlay's color.
o Confirmation:
EMA crossovers can confirm trends indicated by the combined overlay. For example, a bullish crossover with a green combined line could validate a buying opportunity.
o Volatility Insights:
The rapid shifts in Bitcoin's 5-period EMA highlight potential volatility spikes, offering an additional layer of market analysis, particularly useful in volatile markets.
• Strategic Use:
o Multi-Market Insight: The script integrates data from both traditional (SPX) and crypto (BTC) markets, allowing for a more comprehensive analysis of market conditions.
o Decision-Making: Provides traders with visual cues for market sentiment, trend direction, and potential reversals, enhancing strategic trading decisions.
o Trend Confirmation: The combination of EMA crossovers and the overlay's color changes offers a multi-faceted approach to trend confirmation or divergence.
In Summary:
• This script merges elements of traditional stock market analysis with cryptocurrency dynamics, utilizing color changes, line thickness, and EMA crossovers to visually communicate market conditions, offering traders a robust tool for analyzing and acting on market movements.
[blackcat] L1 MartinGale Scalping Strategy**MartinGale Strategy** is a popular money management strategy used in trading. It is commonly applied in situations where the trader aims to recover from a losing streak by increasing the position size after each loss.
In the MartinGale Strategy, after a losing trade, the trader doubles the position size for the next trade. This is done in the hopes that a winning trade will eventually occur, which will not only recover the previous losses but also generate a profit.
The idea behind the MartinGale Strategy is to take advantage of the law of averages. By increasing the position size after each loss, the strategy assumes that eventually, a winning trade will occur, which will not only cover the previous losses but also generate a profit. This can be especially appealing for traders looking for a quick recovery from a losing streak.
However, it is important to note that the MartinGale Strategy carries significant risks. If a trader experiences a prolonged losing streak or lacks sufficient capital, the strategy can lead to substantial losses. The strategy's reliance on the assumption of a winning trade can be dangerous, as there is no guarantee that a winning trade will occur within a certain timeframe.
Traders considering implementing the MartinGale Strategy should carefully assess their risk tolerance and thoroughly understand the potential drawbacks. It is crucial to have a solid risk management plan in place to mitigate potential losses. Additionally, traders should be aware that the strategy may not be suitable for all market conditions and may require adjustments based on market volatility.
In summary, the MartinGale Strategy is a money management strategy that involves increasing the position size after each loss in an attempt to recover from a losing streak. While it can offer the potential for quick recovery, it also comes with significant risks that traders should carefully consider before implementing it in their trading approach.
The MartinGale Scalping Strategy is a trading strategy designed to generate profits through frequent trades. It utilizes a combination of moving average crossovers and crossunders to generate entry and exit signals. The strategy is implemented in TradingView's Pine Script language.
The strategy begins by defining input variables such as take profit and stop loss levels, as well as the trading mode (long, short, or bidirectional). It then sets a rule to allow only long entries if the trading mode is set to "Long".
The strategy logic is defined using SMA (Simple Moving Average) crossover and crossunder signals. It calculates a short-term SMA (SMA3) and a longer-term SMA (SMA8), and plots them on the chart. The crossoverSignal and crossunderSignal variables are used to track the occurrence of the crossover and crossunder events, while the crossoverState and crossunderState variables determine the state of the crossover and crossunder conditions.
The strategy execution is based on the current position size. If the position size is zero (no open positions), the strategy checks for crossover and crossunder events. If a crossover event occurs and the trading mode allows long entries, a long position is entered. The entry price, stop price, take profit price, and stop loss price are calculated based on the current close price and the SMA8 value. Similarly, if a crossunder event occurs and the trading mode allows short entries, a short position is entered with the corresponding price calculations.
If there is an existing long position and the current close price reaches either the take profit price or the stop loss price, and a crossunder event occurs, the long position is closed. The entry price, stop price, take profit price, and stop loss price are reset to zero.
Likewise, if there is an existing short position and the current close price reaches either the take profit price or the stop loss price, and a crossover event occurs, the short position is closed and the price variables are reset.
The strategy also plots entry and exit points on the chart using plotshape function. It displays a triangle pointing up for a buy entry, a triangle pointing down for a buy exit, a triangle pointing down for a sell entry, and a triangle pointing up for a sell exit.
Overall, the MartinGale Scalping Strategy aims to capture small profits by taking advantage of short-term moving average crossovers and crossunders. It incorporates risk management through take profit and stop loss levels, and allows for different trading modes to accommodate different market conditions.
