Modern Trend IdentifierThis is an update by Lightangel112 to Trendilo (Open-Source).
Thanks @ Lightangel112
The Modern Trend Identifier (MTI) is a sophisticated technical analysis tool designed for traders and analysts seeking to accurately determine market trends. This indicator leverages the Arnaud Legoux Moving Average (ALMA) to smooth price data and calculate percentage changes, providing a clearer and more responsive trend analysis. MTI is engineered to highlight trend direction with visual cues, fill areas between the indicator and its bands, and color bars based on trend direction, making it a powerful tool for identifying market momentum and potential reversals.
Capabilities
Smoothing and Trend Calculation:
Utilizes ALMA to smooth price data, reducing noise and providing a clearer view of the trend.
Calculates percentage changes in price over a user-defined lookback period.
Dynamic Range Adjustment:
Normalizes the ALMA percentage change values to ensure they stay within a -100 to 100 range.
Uses a combination of linear and smoothstep compression to handle extreme values without losing sensitivity.
Trend Direction and Highlighting:
Determines the trend direction based on the relationship between the smoothed ALMA percentage change and dynamically adjusted RMS (Root Mean Square) bands.
Colors the trend line to visually indicate whether the market is in an uptrend, downtrend, or neutral state.
Dynamic Threshold Calculation:
Calculates dynamic thresholds using percentile ranks to adapt to changing market conditions.
Visualization Enhancements:
Fills areas between the ALMA percentage change line and its RMS bands to provide a clear visual indication of the trend strength.
Offers the option to color price bars based on the identified trend direction.
Customizable Settings:
Provides extensive customization options for lookback periods, smoothing parameters, ALMA settings, band multipliers, and more.
Allows users to enable or disable various visual enhancements and customize their appearance.
Use Cases
Trend Identification:
MTI helps traders identify the current market trend, whether it's bullish, bearish, or neutral. This can be particularly useful for trend-following strategies.
Momentum Analysis:
By highlighting areas of strong momentum, MTI enables traders to spot potential breakouts or breakdowns. This can be useful for both entry and exit decisions.
Support and Resistance Levels:
The dynamic threshold bands can act as support and resistance levels. Traders can use these levels to set stop-loss and take-profit orders.
Divergence Detection:
MTI can help in identifying divergences between price and the indicator, which can signal potential trend reversals. This is useful for traders looking to capitalize on trend changes.
Risk Management:
The fill areas and colored bars provide clear visual cues about trend strength and direction, aiding in better risk management. Traders can adjust their positions based on the strength of the trend.
Backtesting:
The extensive customization options allow traders to backtest different settings and parameters to optimize their trading strategies for various market conditions.
Multiple Timeframes:
MTI can be applied to multiple timeframes, from intraday charts to daily, weekly, or monthly charts, making it a versatile tool for traders with different trading styles.
Example Scenarios
Day Trading:
A day trader can use MTI on a 5-minute chart to identify intraday trends. By adjusting the lookback period and smoothing parameters, the trader can quickly spot potential entry and exit points based on short-term momentum changes.
Swing Trading:
A swing trader might apply MTI to a 4-hour chart to identify medium-term trends. The dynamic thresholds can help in setting appropriate stop-loss levels, while the trend direction highlighting aids in making informed decisions about holding or exiting positions.
Position Trading:
For a position trader using a daily chart, MTI can help identify the overarching trend. The trader can use the fill areas and bar coloring to assess the strength of the trend and make decisions about entering or exiting long-term positions.
Market Analysis:
An analyst could use MTI to study historical price movements and identify patterns. By examining how the indicator reacted to past market conditions, the analyst can gain insights into potential future price movements.
In summary, the Modern Trend Identifier (MTI) is a versatile and powerful tool that enhances trend analysis with advanced smoothing techniques, dynamic adjustments, and comprehensive visual cues. It is designed to meet the needs of traders and analysts across various trading styles and timeframes, providing clear and actionable insights into market trends and momentum.
Updated with the following:
Additions and Enhancements in MTI
Grouped Inputs with Descriptive Tooltips:
Inputs are organized into groups for better clarity.
Each input parameter includes a descriptive tooltip.
Dynamic Threshold Calculation:
Added dynamic threshold calculation using percentile ranks to adapt to changing market conditions.
Normalization and Compression:
Added normalization factor to ensure plots are within -100 to 100 range.
Introduced smoothstep function for smooth transition and selectively applied linear and smoothstep compression to values outside -80 to 100 range.
Enhanced Visualization:
Highlighted trend direction with RGB colors.
Enhanced fill areas between the ALMA percentage change line and its RMS bands.
Colored price bars based on the identified trend direction.
RMS Lines Adjustment:
Dynamically adjusted RMS calculation without strict capping.
Ensured RMS lines stay below fill areas to maintain clarity.
Descriptive and Organized Code:
Enhanced code clarity with detailed comments.
Organized code into logical sections for better readability and maintenance.
Key Differences and Improvements.
Input Customization:
Trendilo: Inputs are simple and ungrouped.
MTI: Inputs are grouped and include tooltips for better user guidance.
Trend Calculation:
Trendilo: Uses ALMA and calculates percentage change.
MTI: Enhanced with normalization, compression, and dynamic threshold calculation.
Normalization and Compression:
Trendilo: No normalization or compression applied.
MTI: Normalizes values to -100 to 100 range and applies smoothstep compression to handle extreme values.
Dynamic RMS Adjustment:
Trendilo: Simple RMS calculation.
MTI: Dynamically adjusted RMS calculation to ensure clarity in visualization.
Visual Enhancements:
Trendilo: Basic trend highlighting and filling.
MTI: Enhanced visual cues with RGB colors, dynamic threshold bands, and improved fill areas.
Code Clarity:
Trendilo: Functional but lacks detailed comments and organization.
MTI: Well-organized, extensively commented code for better readability and maintainability.
Oscillators
Chande Momentum Oscillator (CMO) Buy Sell Strategy [TradeDots]The "Chande Momentum Oscillator (CMO) Buy Sell Strategy" leverages the CMO indicator to identify short-term buy and sell opportunities.
HOW DOES IT WORK
The standard CMO indicator measures the difference between recent gains and losses, divided by the total price movement over the same period. However, this version of the CMO has some limitations.
The primary disadvantage of the original CMO is its responsiveness to short-term volatility, making the signals less smooth and more erratic, especially in fluctuating markets. This instability can lead to misleading buy or sell signals.
To address this, we integrated the concept from the Moving Average Convergence Divergence (MACD) indicator. By applying a 9-period exponential moving average (EMA) to the CMO line, we obtained a smoothed signal line. This line acts as a filter, identifying confirmed overbought or oversold states, thereby reducing the number of false signals.
Similar to the MACD histogram, we generate columns representing the difference between the CMO and its signal line, reflecting market momentum. We use this momentum indicator as a criterion for entry and exit points. Trades are executed when there's a convergence of CMO and signal lines during an oversold state, and they are closed when the CMO line diverges from the signal line, indicating increased selling pressure.
APPLICATION
Since the 9-period EMA smooths the CMO line, it's less susceptible to extreme price fluctuations. However, this smoothing also makes it more challenging to breach the original +50 and -50 benchmarks.
To increase trading opportunities, we've tightened the boundary ranges. Users can customize the target benchmark lines in the settings to adjust for the volatility of the underlying asset.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
Signal Cool Down Period: 5
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Trend Momentum Strength Indicator, Built for Pairs TradingOverview:
This script combines multiple indicators to provide a comprehensive analysis of both trend strength and trend momentum. It is tailored specifically for pairs trading strategies but can also be used for other trading strategies.
Benefit of Comprehensive Analysis:
Having an indicator that evaluates both trend strength and trend momentum is crucial for traders looking to make informed decisions. It allows traders to not only identify the direction and intensity of a trend but also gauge the momentum behind it. This dual capability helps in confirming potential trade opportunities, whether for entering trades with strong trends or considering reversals during overbought or oversold conditions. By integrating both aspects into one tool, traders can gain a holistic view of market dynamics, enhancing their ability to time entries and manage risk effectively.
Features:
* Trend Strength:
Enhanced ADX Formula: The script includes modifications to the standard ADX formula along with DI+ and DI- to provide more responsive trend strength readings.
Directional Indicators: DI+ (green line) indicates positive directional movement, while DI- (red line) indicates negative directional movement.
Trend Momentum:
Modified Stochastic Indicators: The script uses %K and %D indicators, modified and combined with ADX to give a clear indication of trend momentum.
Momentum Strength: This helps determine the strength and direction of the momentum.
Trading Signals:
Combining Indicators: The script combines ADX, DI+, DI-, %K, and %D to generate comprehensive trading signals.
Optimal Entry Points: Designed to identify optimal entry points for trades, particularly in pairs trading.
Colored Area at Bottom:
This area provides two easy-to-read functions:
Color:
Green: Upward momentum (ratio above 1)
Red: Downward momentum (ratio below 1)
Height:
Higher in green: Stronger upward momentum
Lower in red: Stronger downward momentum
Legend:
Green Line: DI+ (Positive)
Red Line: DI- (Negative)
Black Line: ADX
How to Read This Indicator:
1) Trend Direction:
DI+ above DI-: Indicates an upward trend.
DI- above DI+: Indicates a downward trend.
2) Trend Strength:
ADX below 20: Indicates a neutral trend.
ADX between 20 and 25: Indicates a weak trend.
ADX above 25: Indicates a strong trend.
Trading Signals in Pairs Trading:
Neutral Trend: Ideal for pairs trading when no strong trend is detected.
Overbought/Oversold: Uses %K and %D to identify overbought/oversold conditions that support trade decisions.
Entry Signals: Green signals for long positions, red signals for short positions, based on combined criteria of neutral trend strength and supportive momentum.
Application in Pairs Trading:
Neutral trend: In pairs trading strategies, where neutral movement is often sought, this indicator provides signals that are especially relevant during periods of neutral trend strength and supportive momentum, aiding traders in identifying optimal entry
Risk Management: Combining signals from ADX, DI+, DI-, %K, and %D helps traders make more informed decisions regarding entry points, enhancing risk management.
Example Chart (The indicator is on the upper right corner):
Clean Presentation: The chart only includes the necessary elements to demonstrate the indicator’s functionality.
Demonstrates: Overbought/oversold conditions, upward/downward/no momentum, and trading signals with/without specific scenarios.
Custom Signal Oscillator StrategyThe CSO is made to help traders easily test their theories by subtracting the difference between two customizable plots(indicators) without having to search for strategies. The general purpose is to provide a tool to users without coding knowledge.
How to use :
Apply the indicator(s) to test
Go to the CSO strategy input settings and select the desired plots from the added indicators. (The back test will enter long or short depending on the fast signal crosses on the slow signal)
Pull up the strategy tester
Adjust the input settings on the selected indicator(s) to back test
For example, the published strategy is using the basis lines from two Donchian channels with varying length. This can be utilized with multiple overlays on the chart and oscillators that are operating on the same scale with each other. Since chart glows aren't extremely common, a glow option is included to stand out on the chart as the chain operator. A long only option for is also included for versatility.
Fusion MFI RSIHello fellas,
This superb indicator summons two monsters called Relative Strength Index (RSI) and Money Flow Index (MFI) and plays the Yu-Gi-Oh! card "Polymerization" to combine them.
Overview
The Fusion MFI RSI Indicator is an advanced analytical tool designed to provide a nuanced understanding of market dynamics by combining the Relative Strength Index (RSI) and the Money Flow Index (MFI). Enhanced with sophisticated smoothing techniques and the Inverse Fisher Transform (IFT), this indicator excels in identifying key market conditions such as overbought and oversold states, trends, and potential reversal points.
Key Features (Brief Overview)
Fusion of RSI and MFI: Integrates momentum and volume for a comprehensive market analysis.
Advanced Smoothing Techniques: Employs Hann Window, Jurik Moving Average (JMA), T3 Smoothing, and Super Smoother to refine signals.
Inverse Fisher Transform (IFT) Enhances the clarity and distinctiveness of indicator outputs.
Detailed Feature Analysis
Fusion of RSI and MFI
RSI (Relative Strength Index): Developed by J. Welles Wilder Jr., the RSI measures the speed and magnitude of directional price movements. Wilder recommended using a 14-day period and identified overbought conditions above 70 and oversold conditions below 30.
MFI (Money Flow Index): Created by Gene Quong and Avrum Soudack, the MFI combines price and volume to measure trading pressure. It is typically calculated using a 14-day period, with over 80 considered overbought and under 20 as oversold.
Application in Fusion: By combining RSI and MFI, the indicator leverages RSI's sensitivity to price changes with MFI's volume-weighted confirmation, providing a robust analysis tool. This combination is particularly effective in confirming the strength behind price movements, making the signals more reliable.
Advanced Smoothing Techniques
Hann Window: Traditionally used to reduce the abrupt data discontinuities at the edges of a sample, it is applied here to smooth the price data.
Jurik Moving Average (JMA): Known for preserving the timing and smoothness of the data, JMA reduces market noise effectively without significant lag.
T3 Smoothing: Developed to respond quickly to market changes, T3 provides a smoother response to price fluctuations.
Super Smoother: Filters out high-frequency noise while retaining important trends.
Application in Fusion: These techniques are chosen to refine the output of the combined RSI and MFI values, ensuring the indicator remains responsive yet stable, providing clearer and more actionable signals.
Inverse Fisher Transform (IFT):
Developed by John Ehlers, the IFT transforms oscillator outputs to enhance the clarity of extreme values. This is particularly useful in this fusion indicator to make critical turning points more distinct and actionable.
Mathematical Calculations for the Fusion MFI RSI Indicator
RSI (Relative Strength Index)
The RSI is calculated using the following steps:
Average Gain and Average Loss: First, determine the average gain and average loss over the specified period (typically 14 days). This is done by summing all the gains and losses over the period and then dividing each by the period.
Average Gain = (Sum of Gains over the past 14 periods) / 14
Average Loss = (Sum of Losses over the past 14 periods) / 14
Relative Strength (RS): This is the ratio of average gain to average loss.
RS = Average Gain / Average Loss
RSI: Finally, the RSI is calculated using the RS value:
RSI = 100 - (100 / (1 + RS))
MFI (Money Flow Index)
The MFI is calculated using several steps that incorporate both price and volume:
Typical Price: Calculate the typical price for each period.
Typical Price = (High + Low + Close) / 3
Raw Money Flow: Multiply the typical price by the volume for the period.
Raw Money Flow = Typical Price * Volume
Positive and Negative Money Flow: Compare the typical price of the current period to the previous period to determine if the money flow is positive or negative.
If today's Typical Price > Yesterday's Typical Price, then Positive Money Flow = Raw Money Flow; Negative Money Flow = 0
If today's Typical Price < Yesterday's Typical Price, then Negative Money Flow = Raw Money Flow; Positive Money Flow = 0
Money Flow Ratio: Calculate the ratio of the sum of Positive Money Flows to the sum of Negative Money Flows over the past 14 periods.
Money Flow Ratio = (Sum of Positive Money Flows over 14 periods) / (Sum of Negative Money Flows over 14 periods)
MFI: Finally, calculate the MFI using the Money Flow Ratio.
MFI = 100 - (100 / (1 + Money Flow Ratio))
Fusion of RSI and MFI
The final Fusion MFI RSI value could be calculated by averaging the IFT-transformed values of RSI and MFI, providing a single oscillator value that reflects both momentum and volume-weighted price action:
Fusion MFI RSI = (MFI weight * MFI) + (RSI weight * RSI)
Suggested Settings and Trading Rules
Original Usage
RSI: Wilder suggested buying when the RSI moves above 30 from below (enter long) and selling when the RSI moves below 70 from above (enter short). He recommended exiting long positions when the RSI reaches 70 or higher and exiting short positions when the RSI falls below 30.
MFI: Quong and Soudack recommended buying when the MFI is below 20 and starts rising (enter long), and selling when it is above 80 and starts declining (enter short). They suggested exiting long positions when the MFI reaches 80 or higher and exiting short positions when the MFI falls below 20.
Fusion Application
Settings: Use a 14-day period for this indicator's calculations to maintain consistency with the original settings suggested by the inventors.
Trading Rules:
Enter Long Signal: Consider entering a long position when both RSI and MFI are below their respective oversold levels and begin to rise. This indicates strong buying pressure supported by both price momentum and volume.
Exit Long Signal: Exit the long position when either RSI or MFI reaches its respective overbought threshold, suggesting a potential reversal or decrease in buying pressure.
Enter Short Signal: Consider entering a short position when both indicators are above their respective overbought levels and begin to decline, suggesting that selling pressure is mounting.
Exit Short Signal: Exit the short position when either RSI or MFI falls below its respective oversold threshold, indicating diminishing selling pressure and a potential upward reversal.
How to Use the Indicator
Select Source and Timeframe: Choose the data source and the timeframe for analysis.
Configure Fusion Settings: Adjust the weights for RSI and MFI.
Choose Smoothing Technique: Select and configure the desired smoothing method to suit the market conditions and personal preference.
Enable Fisherization: Optionally apply the Inverse Fisher Transform to enhance signal clarity.
Customize Visualization: Set up gradient coloring, background plots, and bands according to your preferences.
Interpret the Indicator: Use the Fusion value and visual cues to identify market conditions and potential trading opportunities.
Conclusion
The Fusion MFI RSI Indicator integrates classical and modern technical analysis concepts to provide a comprehensive tool for market analysis. By combining RSI and MFI with advanced smoothing techniques and the Inverse Fisher Transform, this indicator offers enhanced insights, aiding traders in making more informed and timely trading decisions. Customize the settings to align with your trading strategy and leverage this powerful tool to navigate financial markets effectively.
Best regards,
simwai
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Credits to:
@loxx – T3
@everget – JMA
@cheatcountry – Hann Window
Persistent Homology Based Trend Strength OscillatorPersistent Homology Based Trend Strength Oscillator
The Persistent Homology Based Trend Strength Oscillator is a unique and powerful tool designed to measure the persistence of market trends over a specified rolling window. By applying the principles of persistent homology, this indicator provides traders with valuable insights into the strength and stability of uptrends and downtrends, helping to inform better trading decisions.
What Makes This Indicator Original?
This indicator's originality lies in its application of persistent homology , a method from topological data analysis, to financial markets. Persistent homology examines the shape and features of data across multiple scales, identifying patterns that persist as the scale changes. By adapting this concept, the oscillator tracks the persistence of uptrends and downtrends in price data, offering a novel approach to trend analysis.
Concepts Underlying the Calculations:
Persistent Homology: This method identifies features such as clusters, holes, and voids that persist as the scale changes. In the context of this indicator, it tracks the duration and stability of price trends.
Rolling Window Analysis: The oscillator uses a specified window size to calculate the average length of uptrends and downtrends, providing a dynamic view of trend persistence over time.
Threshold-Based Trend Identification: It differentiates between uptrends and downtrends based on specified thresholds for price changes, ensuring precision in trend detection.
How It Works:
The oscillator monitors consecutive changes in closing prices to identify uptrends and downtrends.
An uptrend is detected when the closing price increase exceeds a specified positive threshold.
A downtrend is detected when the closing price decrease exceeds a specified negative threshold.
The lengths of these trends are recorded and averaged over the chosen window size.
The Trend Persistence Index is calculated as the difference between the average uptrend length and the average downtrend length, providing a measure of trend persistence.
How Traders Can Use It:
Identify Trend Strength: The Trend Persistence Index offers a clear measure of the strength and stability of uptrends and downtrends. A higher value indicates stronger and more persistent uptrends, while a lower value suggests stronger and more persistent downtrends.
Spot Trend Reversals: Significant shifts in the Trend Persistence Index can signal potential trend reversals. For instance, a transition from positive to negative values might indicate a shift from an uptrend to a downtrend.
Confirm Trends: Use the Trend Persistence Index alongside other technical indicators to confirm the strength and duration of trends, enhancing the accuracy of your trading signals.
Manage Risk: Understanding trend persistence can help traders manage risk by identifying periods of high trend stability versus periods of potential volatility. This can be crucial for timing entries and exits.
Example Usage:
Default Settings: Start with the default settings to get a feel for the oscillator’s behavior. Observe how the Trend Persistence Index reacts to different market conditions.
Adjust Thresholds: Fine-tune the positive and negative thresholds based on the asset's volatility to improve trend detection accuracy.
Combine with Other Indicators: Use the Persistent Homology Based Trend Strength Oscillator in conjunction with other technical indicators such as moving averages, RSI, or MACD for a comprehensive analysis.
Backtesting: Conduct backtesting to see how the oscillator would have performed in past market conditions, helping you to refine your trading strategy.
Statistical RSI Pivot Reversal Indicator [UAlgo]🔶 Idea
The "Statistical RSI Pivot Reversal Indicator " is designed to enhance traditional RSI analysis by incorporating statistical methods to identify potential reversal points more accurately. The core concept is to detect frequently occurring pivot points in the RSI data, which can indicate strong support or resistance levels. By analyzing the most frequent RSI values at these pivots, the script provides traders with clearer signals for potential market reversals, helping to improve the timing of entry and exit points in their trading strategies.
🔶 Key Features
Enhanced RSI Analysis:
This script calculates the Relative Strength Index (RSI) based on user-defined parameters and identifies pivot points in the RSI data. By analyzing these pivots, it detects the most frequently occurring RSI values at support and resistance levels.
Signal Filtering Options:
Filter buy and sell signals based on whether the RSI is in overbought (above 70) or oversold (below 30) conditions, enhancing the reliability of signals.
Visual and Alert Features:
Visual Signals: The script plots the RSI, the most frequent high and low RSI values, and buy/sell signals on the chart.
Alerts: Set up custom alerts for buy and sell conditions, ensuring you never miss a trading opportunity.
🔶 Disclaimer
The "Statistical RSI Pivot Reversal Indicator " script is intended for educational and informational purposes only.
It does not constitute financial advice or investment recommendations.
Trading financial instruments involves risk, and it is possible to lose more than your initial investment. Past performance is not indicative of future results.
intellect_city - World Cycle - Ath & Atl - Logarithmic - Signal.Indicator Overview
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - The Pi Cycle Top and Bottom Oscillator is an adaptation of the original Pi Cycle Top chart. It compares the 111-Day Moving Average circle and the 2 * 350-Day Moving Average circle of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the important mathematical number Pi.
When the 111-Day Moving Average circle reaches the 2 * 350-Day Moving Average circle, it indicates that the market is becoming overheated. That is because the mid time frame momentum reference of the 111-Day Moving Average has caught up with the long timeframe momentum reference of the 2 * 350-Day Moving Average.
Historically this has occurred within 3 days of the very top of each market cycle.
When the 111 Day Moving Average circle falls back beneath the 2 * 350 Day Moving Average circle, it indicates that the market momentum of that cycle is significantly cooling down. The oscillator drops down into the lower green band shown where the 111 Day Moving Average is moving at a 75% discount relative to the 2 * 350 Day Moving Average.
Historically, this has highlighted broad areas of bear market lows.
IMPORTANT: You need to set a LOGARITHMIC graph. (The function is located at the bottom right of the screen)
IMPORTANT: The INTELLECT_city indicator is made for signal purchases of sales, there is also a strategic one from INTELLECT_city
IMPORTANT: The Chart shows all cycles, both buying and selling.
IMPORTANT: Suitable timeframes are 1 daily (recommended) and 1 weekly
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Описание на русском:
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Обзор индикатора
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - Логарифмический - Сигнал - Осциллятор вершины и основания цикла Пи представляет собой адаптацию оригинального графика вершины цикла Пи. Он сравнивает круг 111-дневной скользящей средней и круг 2 * 350-дневной скользящей средней цены Биткойна. Эти две скользящие средние были выбраны как 350/111 = 3,153; Приближение важного математического числа Пи.
Когда круг 111-дневной скользящей средней достигает круга 2 * 350-дневной скользящей средней, это указывает на то, что рынок перегревается. Это происходит потому, что опорный моментум среднего временного интервала 111-дневной скользящей средней догнал опорный момент импульса длинного таймфрейма 2 * 350-дневной скользящей средней.
Исторически это происходило в течение трех дней после вершины каждого рыночного цикла.
Когда круг 111-дневной скользящей средней опускается ниже круга 2 * 350-дневной скользящей средней, это указывает на то, что рыночный импульс этого цикла значительно снижается. Осциллятор опускается в нижнюю зеленую полосу, показанную там, где 111-дневная скользящая средняя движется со скидкой 75% относительно 2 * 350-дневной скользящей средней.
Исторически это высветило широкие области минимумов медвежьего рынка.
ВАЖНО: Выставлять нужно ЛОГАРИФМИЧЕСКИЙ график. (Находиться функция с правой нижней части экрана)
ВАЖНО: Индикатор INTELLECT_city сделан для сигнальных покупок продаж, есть также и стратегический от INTELLECT_сity
ВАЖНО: На Графике видны все циклы, как на покупку так и на продажу.
ВАЖНО: Подходящие таймфреймы 1 дневной (рекомендовано) и 1 недельный
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Beschreibung - Deutsch
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Indikatorübersicht
INTELLECT_city – Weltzyklus – ATH & ATL – Zeitrahmen 1T und 1W – Logarithmisch – Signal – Der Pi-Zyklus-Top- und Bottom-Oszillator ist eine Anpassung des ursprünglichen Pi-Zyklus-Top-Diagramms. Er vergleicht den 111-Tage-Gleitenden-Durchschnittskreis und den 2 * 350-Tage-Gleitenden-Durchschnittskreis des Bitcoin-Preises. Diese beiden gleitenden Durchschnitte wurden als 350 / 111 = 3,153 ausgewählt; eine Annäherung an die wichtige mathematische Zahl Pi.
Wenn der 111-Tage-Gleitenden-Durchschnittskreis den 2 * 350-Tage-Gleitenden-Durchschnittskreis erreicht, deutet dies darauf hin, dass der Markt überhitzt. Das liegt daran, dass der Momentum-Referenzwert des 111-Tage-Gleitenden-Durchschnitts im mittleren Zeitrahmen den Momentum-Referenzwert des 2 * 350-Tage-Gleitenden-Durchschnitts im langen Zeitrahmen eingeholt hat.
Historisch gesehen geschah dies innerhalb von 3 Tagen nach dem Höhepunkt jedes Marktzyklus.
Wenn der Kreis des 111-Tage-Durchschnitts wieder unter den Kreis des 2 x 350-Tage-Durchschnitts fällt, deutet dies darauf hin, dass die Marktdynamik dieses Zyklus deutlich nachlässt. Der Oszillator fällt in das untere grüne Band, in dem der 111-Tage-Durchschnitt mit einem Abschlag von 75 % gegenüber dem 2 x 350-Tage-Durchschnitt verläuft.
Historisch hat dies breite Bereiche mit Tiefstständen in der Baisse hervorgehoben.
WICHTIG: Sie müssen ein logarithmisches Diagramm festlegen. (Die Funktion befindet sich unten rechts auf dem Bildschirm)
WICHTIG: Der INTELLECT_city-Indikator dient zur Signalisierung von Käufen oder Verkäufen, es gibt auch einen strategischen Indikator von INTELLECT_city
WICHTIG: Das Diagramm zeigt alle Zyklen, sowohl Kauf- als auch Verkaufszyklen.
WICHTIG: Geeignete Zeitrahmen sind 1 täglich (empfohlen) und 1 wöchentlich
Multiple Oscillator Conditions Final [siulian] v2This tool is created to gather multiple oscilators condition under the same umbrela and back-test your idea.
Basically the only intention of this tool is to used in combination with a back-tester indicator ( or manually ) where you get the entry based on the cumulative signals provided by this tool.
For example you can to combine RSI , MACD, CCI, Keltner Channels or whatever indicator you think it might give you an edge for an entry signal.
You can combine up to 7 indicators either by comparing them with a static value or with another indicator (for example you can compare RSI with RSI MA, Volume with Volume MA, etc)
There are two lines which will be printed.
1) Result(blue line) - it will print 1 when all the condition are met ( the same can be used for back-testing tools)
2) Condition Met count(yellow line) - which will count how many conditions from the ones selected are triggered ( for example you have 6 indicators that are matching the conditions and you still want to take a trade even if the condition number 7 is not met)
Alarms can be setup to check if more than defined conditions are present.
As a demo in the above image i have put several condition in order to possible catch bottoms.
Please understand this is just an example on how to integrate multiple condition into a single entity and should not be used as is.
1) price should close below KC
2) CCI < - 100
3) RSI < 30
4) Vol > Vol MA
Past performance do not guarantee future performance.
Advanced Awesome Oscillator [CryptoSea]Advanced AO Analysis Indicator
The Advanced AO Analysis indicator is a sophisticated tool designed to evaluate the Awesome Oscillator (AO) in search of regular and hidden divergences that signal potential price reversals. By tracking the intensity and duration of the AO's movements, this indicator aids traders in pinpointing critical points in price action.
Key Features
Divergence Detection: Identifies both regular and hidden bullish and bearish divergences, providing early signs of potential market reversals.
Customizable Lookback Periods: Allows users to set specific lookback windows to define the strength and relevance of detected divergences.
Adaptive Oscillator Display: Features customizable display options for the AO, enabling users to view data in different modes suited to their analysis needs.
Alert System: Includes configurable alerts to notify users of potential divergence formations, helping traders respond promptly.
How it Works
AO Calculation: Computes the AO as the difference between short-term and long-term moving averages of the midpoints of bars, highlighting momentum shifts.
Pivot Point Analysis: Utilizes advanced algorithms to find low and high pivot points based on the oscillator values, crucial for spotting trend reversals.
Range Validation: Verifies that divergences occur within a predefined range from pivot points, ensuring their validity and strength.
Visualisation: Plots AO values and potential divergences directly on the chart, aiding in quick visual analysis.
Application
Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of AO movements and divergence.
Trend Confirmation: Reinforces trading strategies by confirming potential reversals with pivot point detection and divergence analysis.
Behavioural Insight: Offers insights into market dynamics and sentiment by analyzing the depth and duration of AO cycles above and below zero.
The Advanced AO Analysis indicator equips traders with a powerful analytical tool for studying the Awesome Oscillator in-depth, enhancing their ability to spot and act on divergence-based trading opportunities in the cryptocurrency markets.
Williams %R OB/OS Candle Coloring### Description for TradingView Publication
**Title:** Williams %R OB/OS Candle Coloring
**Description:**
This Pine Script indicator enhances the visibility of market conditions by changing the color of the candlesticks based on the Williams %R values. It helps traders quickly identify overbought and oversold conditions without the need to display the Williams %R line or any additional bands.
**How It Works:**
- The script calculates the Williams %R value using a specified lookback period (default is 14 days).
- It then compares the Williams %R value against predefined overbought and oversold levels.
- **Overbought Condition:** When the Williams %R value is greater than the upper band level (-20 by default), the candlestick color changes to blue.
- **Oversold Condition:** When the Williams %R value is less than the lower band level (-80 by default), the candlestick color changes to yellow.
**How to Use:**
1. **Input Parameters:**
- **Length:** The lookback period for calculating Williams %R (default is 14).
- **Upper Band Level:** The threshold for overbought conditions (default is -20).
- **Lower Band Level:** The threshold for oversold conditions (default is -80).
2. **Candlestick Coloring:**
- Blue candles indicate potential overbought conditions.
- Yellow candles indicate potential oversold conditions.
This indicator is designed to provide a visual cue directly on the price chart, making it easier for traders to spot extreme market conditions at a glance.
**Concepts Underlying the Calculation:**
Williams %R, developed by Larry Williams, is a momentum indicator that measures overbought and oversold levels. It compares the current closing price to the highest high and lowest low over a specified period. By using color-coded candles, traders can quickly assess market conditions and make informed decisions without the need to interpret an additional indicator line.
This script is particularly useful for traders who prefer a clean chart but still want to leverage the insights provided by the Williams %R indicator.
---
### ภาษาไทย:
**คำอธิบาย:**
สคริปต์ Pine Script ตัวนี้ช่วยเพิ่มการมองเห็นสภาวะตลาดโดยการเปลี่ยนสีของแท่งเทียนตามค่าของ Williams %R ช่วยให้เทรดเดอร์สามารถระบุสภาวะการซื้อเกินและขายเกินได้อย่างรวดเร็วโดยไม่ต้องแสดงเส้น Williams %R หรือเส้นระดับเพิ่มเติมใดๆ
**วิธีการทำงาน:**
- สคริปต์คำนวณค่าของ Williams %R โดยใช้ช่วงเวลาที่กำหนด (เริ่มต้นที่ 14 วัน)
- จากนั้นเปรียบเทียบค่าของ Williams %R กับระดับการซื้อเกินและขายเกินที่กำหนดไว้
- **สภาวะการซื้อเกิน:** เมื่อค่าของ Williams %R มากกว่าระดับ Upper Band (-20 เริ่มต้น) สีของแท่งเทียนจะเปลี่ยนเป็นสีน้ำเงิน
- **สภาวะการขายเกิน:** เมื่อค่าของ Williams %R น้อยกว่าระดับ Lower Band (-80 เริ่มต้น) สีของแท่งเทียนจะเปลี่ยนเป็นสีเหลือง
**วิธีการใช้งาน:**
1. **ค่าพารามิเตอร์:**
- **Length:** ช่วงเวลาที่ใช้คำนวณ Williams %R (เริ่มต้นที่ 14)
- **Upper Band Level:** ระดับการซื้อเกิน (เริ่มต้นที่ -20)
- **Lower Band Level:** ระดับการขายเกิน (เริ่มต้นที่ -80)
2. **การเปลี่ยนสีแท่งเทียน:**
- แท่งเทียนสีน้ำเงินระบุถึงสภาวะการซื้อเกิน
- แท่งเทียนสีเหลืองระบุถึงสภาวะการขายเกิน
อินดิเคเตอร์นี้ถูกออกแบบมาเพื่อให้สัญญาณภาพตรงบนกราฟราคาช่วยให้เทรดเดอร์สามารถมองเห็นสภาวะตลาดได้อย่างชัดเจนและทำการตัดสินใจได้ง่ายขึ้น
**แนวคิดที่อยู่เบื้องหลังการคำนวณ:**
Williams %R ที่พัฒนาโดย Larry Williams เป็นอินดิเคเตอร์โมเมนตัมที่วัดระดับการซื้อเกินและขายเกิน มันเปรียบเทียบราคาปิดปัจจุบันกับราคาสูงสุดและต่ำสุดในช่วงเวลาที่กำหนด โดยใช้แท่งเทียนที่มีการเปลี่ยนสี เทรดเดอร์สามารถประเมินสภาวะตลาดและทำการตัดสินใจได้อย่างรวดเร็วโดยไม่ต้องตีความเส้นอินดิเคเตอร์เพิ่มเติม
สคริปต์นี้มีประโยชน์โดยเฉพาะสำหรับเทรดเดอร์ที่ต้องการกราฟที่สะอาดแต่ยังต้องการใช้ข้อมูลเชิงลึกจากอินดิเคเตอร์ Williams %R
Enhanced Reversal DetectionScript Description:
The "Enhanced Reversal Detection" indicator is a powerful tool designed to identify potential market reversals across various financial instruments. It incorporates a sophisticated algorithm that analyzes price action along with key technical indicators such as the Relative Strength Index (RSI), Bollinger Bands, and Moving Average (MA).
How to Use:
Adjustable Parameters: The indicator offers a range of adjustable parameters to cater to different trading preferences and market conditions.
RSI Length: Adjusts the length of the RSI calculation to fine-tune sensitivity.
Overbought Level: Sets the threshold for identifying overbought conditions on the RSI scale.
Oversold Level: Sets the threshold for identifying oversold conditions on the RSI scale.
Bollinger Bands Length: Determines the length of the Bollinger Bands calculation.
Bollinger Bands Multiplier: Adjusts the standard deviation multiplier for the Bollinger Bands, influencing band width.
Moving Average Length: Defines the length of the Moving Average calculation to capture trend direction.
Min Bars Between Signals: Sets the minimum number of bars required between consecutive reversal signals.
ADX Length: Adjusts the length of the Average Directional Index (ADX) calculation.
ADX Threshold: Defines the threshold value for ADX, serving as a filter for reversal signals.
Signal Generation: The indicator generates signals for both bullish and bearish reversals based on predefined criteria. A bullish reversal signal is triggered when the closing price exceeds the lower Bollinger Band and RSI falls below the oversold threshold. Conversely, a bearish reversal signal occurs when the closing price falls below the upper Bollinger Band and RSI surpasses the overbought threshold.
Alerts: Traders can opt to receive alerts for bullish and bearish reversal signals, enabling them to stay informed of potential trading opportunities even when away from the platform.
Publication Readiness:
To ensure readiness for publication in the TradingView public library, the script has been meticulously crafted and documented:
The code is extensively commented to provide clear explanations of parameters, calculations, and signal generation logic.
Best coding practices have been followed to enhance readability and maintainability.
Rigorous testing has been conducted to validate the accuracy and reliability of signal generation across various market conditions.
The script adheres to TradingView's guidelines and policies for script publication, ensuring compliance with platform standards and user expectations.
With its comprehensive features and user-friendly design, the "Enhanced Reversal Detection" indicator is poised to become a valuable asset for traders seeking to identify high-probability reversal opportunities in the financial markets.
Cosine Kernel Regressions [QuantraSystems]Cosine Kernel Regressions
Introduction
The Cosine Kernel Regressions indicator (CKR) uses mathematical concepts to offer a unique approach to market analysis. This indicator employs Kernel Regressions using bespoke tunable Cosine functions in order to smoothly interpret a variety of market data, providing traders with incredibly clean insights into market trends.
The CKR is particularly useful for traders looking to understand underlying trends without the 'noise' typical in raw price movements. It can serve as a standalone trend analysis tool or be combined with other indicators for more robust trading strategies.
Legend
Fast Trend Signal Line - This is the foreground oscillator, it is colored upon the earliest confirmation of a change in trend direction.
Slow Trend Signal Line - This oscillator is calculated in a similar manner. However, it utilizes a lower frequency within the cosine tuning function, allowing it to capture longer and broader trends in one signal. This allows for tactical trading; the user can trade smaller moves without losing sight of the broader trend.
Case Study
In this case study, the CKR was used alongside the Triple Confirmation Kernel Regression Oscillator (KRO)
Initially, the KRO indicated an oversold condition, which could be interpreted as a signal to enter a long position in anticipation of a price rebound. However, the CKR’s fast trend signal line had not yet confirmed a positive trend direction - suggesting that entering a trade too early and without confirmation could be a mistake.
Waiting for a confirmed positive trend from the CKR proved beneficial for this trade. A few candles after the oversold signal, the CKR's fast trend signal line shifted upwards, indicating a strong upward momentum. This was the optimal entry point suggested by the CKR, occurring after the confirmation of the trend change, which significantly reduced the likelihood of entering during a false recovery or continuation of the downtrend.
This is one of the many uses of the CKR - by timing entries using the fast signal line , traders could avoid unnecessary losses by preventing premature entries.
Methodology
The methodology behind CKR is a multi-layered approach and utilizes many ‘base’ indicators.
Relative Strength Index
Stochastic Oscillator
Bollinger Band Percent
Chande Momentum Oscillator
Commodity Channel Index
Fisher Transform
Volume Zone Oscillator
The calculated output from each indicator is standardized and scaled before being averaged. This prevents any single indicator from overpowering the resulting signal.
// ╔════════════════════════════════╗ //
// ║ Scaling/Range Adjustment ║ //
// ╚════════════════════════════════╝ //
RSI_ReScale (_res ) => ( _res - 50 ) * 2.8
STOCH_ReScale (_stoch ) => ( _stoch - 50 ) * 2
BBPCT_ReScale (_bbpct ) => ( _bbpct - 0.5 ) * 120
CMO_ReScale (_chandeMO ) => ( _chandeMO * 1.15 )
CCI_ReScale (_cci ) => ( _cci / 2 )
FISH_ReScale (_fish1 ) => ( _fish1 * 30 )
VZO_ReScale (_VP, _TV ) => (_VP / _TV) * 110
These outputs are then fed into a customized cosine kernel regression function, which smooths the data, and combines all inputs into a single coherent output.
// ╔════════════════════════════════╗ //
// ║ COSINE KERNEL REGRESSIONS ║ //
// ╚════════════════════════════════╝ //
// Define a function to compute the cosine of an input scaled by a frequency tuner
cosine(x, z) =>
// Where x = source input
// y = function output
// z = frequency tuner
var y = 0.
y := math.cos(z * x)
Y
// Define a kernel that utilizes the cosine function
kernel(x, z) =>
var y = 0.
y := cosine(x, z)
math.abs(x) <= math.pi/(2 * z) ? math.abs(y) : 0. // cos(zx) = 0
// The above restricts the wave to positive values // when x = π / 2z
The tuning of the regression is adjustable, allowing users to fine-tune the sensitivity and responsiveness of the indicator to match specific trading strategies or market conditions. This robust methodology ensures that CKR provides a reliable and adaptable tool for market analysis.
Relative Momentum Index with Laguerre FilterThe Relative Momentum Index
The Relative Momentum Index (RMI) is an oscillator that is a variation of the Relative Strength Index (RSI), but incorporates momentum over a variable lookback period rather than just consecutive price changes, which can help identify reversals and filter out noise.
It measures the momentum of price changes over a specified period, rather than just the magnitude of price changes like the RSI does.
It counts up and down days from the current closing price relative to the closing price a certain number of days ago (e.g. 5 days ago), instead of just comparing consecutive daily closes like the RSI
It is calculated by taking the ratio of the average upward price changes to the average downward price changes over a given period, where each change is measured from the close X days ago (X is the “momentum” period)
Like the RSI, the RMI oscillates between 0 and 100, with readings above 70 considered overbought and below 30 oversold.
In trending markets, the RMI tends to remain in overbought or oversold territory for extended periods. In trading ranges, it oscillates more predictably between the overbought and oversold levels.
The RMI is generally considered better than the RSI at identifying potential reversal points, as it incorporates a momentum factor rather than just strength.
It can be used in a similar way to the RSI for trade signals, such as buying when it rises above 30 from below, or selling when it falls below 70 from above
The Laguerre filter
A Laguerre filter is a type of infinite impulse response (IIR) filter used for smoothing signals or data. The Laguerre filter provides a way to apply variable smoothing to a signal by adjusting its pole position, allowing you to control the balance between smoothness and lag based on your preferences. It is an alternative to simple moving averages that can better preserve the shape of the original signal.
Adaptive Trend Lines [MAMA and FAMA]Updated my previous algo on the Adaptive Trend lines, however I have added new functionalities and sorted out the settings.
You can now switch between normalized and non-normalized settings, the colors have also been updated and look much better.
The MAMA and FAMA
These indicators was originally developed by John F. Ehlers (Stocks & Commodities V. 19:10: MESA Adaptive Moving Averages). Everget wrote the initial functions for these in pine script. I have simply normalized the indicators and chosen to use the Laplace transformation instead of the hilbert transformation
How the Indicator Works:
The indicator employs a series of complex calculations, but we'll break it down into key steps to understand its functionality:
LaplaceTransform: Calculates the Laplace distribution for the given src input. The Laplace distribution is a continuous probability distribution, also known as the double exponential distribution. I use this because of the assymetrical return profile
MESA Period: The indicator calculates a MESA period, which represents the dominant cycle length in the price data. This period is continuously adjusted to adapt to market changes.
InPhase and Quadrature Components: The InPhase and Quadrature components are derived from the Hilbert Transform output. These components represent different aspects of the price's cyclical behavior.
Homodyne Discriminator: The Homodyne Discriminator is a phase-sensitive technique used to determine the phase and amplitude of a signal. It helps in detecting trend changes.
Alpha Calculation: Alpha represents the adaptive factor that adjusts the sensitivity of the indicator. It is based on the MESA period and the phase of the InPhase component. Alpha helps in dynamically adjusting the indicator's responsiveness to changes in market conditions.
MAMA and FAMA Calculation: The MAMA and FAMA values are calculated using the adaptive factor (alpha) and the input price data. These values are essentially adaptive moving averages that aim to capture the current trend more effectively than traditional moving averages.
But Omar, why would anyone want to use this?
The MAMA and FAMA lines offer benefits:
The indicator offers a distinct advantage over conventional moving averages due to its adaptive nature, which allows it to adjust to changing market conditions. This adaptability ensures that investors can stay on the right side of the trend, as the indicator becomes more responsive during trending periods and less sensitive in choppy or sideways markets.
One of the key strengths of this indicator lies in its ability to identify trends effectively by combining the MESA and MAMA techniques. By doing so, it efficiently filters out market noise, making it highly valuable for trend-following strategies. Investors can rely on this feature to gain clearer insights into the prevailing trends and make well-informed trading decisions.
This indicator is primarily suppoest to be used on the big timeframes to see which trend is prevailing, however I am not against someone using it on a timeframe below the 1D, just be careful if you are using this for modern portfolio theory, this is not suppoest to be a mid-term component, but rather a long term component that works well with proper use of detrended fluctuation analysis.
Dont hesitate to ask me if you have any questions
Again, I want to give credit to Everget and ChartPrime!
Code explanation as required by House Rules:
fastLimit = input.float(title='Fast Limit', step=0.01, defval=0.01, group = "Indicator Settings")
slowLimit = input.float(title='Slow Limit', step=0.01, defval=0.08, group = "Indicator Settings")
src = input(title='Source', defval=close, group = "Indicator Settings")
input.float: Used to create input fields for the user to set the fastLimit and slowLimit values.
input: General function to get user inputs, like the data source (close price) used for calculations.
norm_period = input.int(3, 'Normalization Period', 1, group = "Normalized Settings")
norm = input.bool(defval = true, title = "Use normalization", group = "Normalized Settings")
input.int: Creates an input field for the normalization period.
input.bool: Allows the user to toggle normalization on or off.
Color settings in the code:
col_up = input.color(#22ab94, group = "Color Settings")
col_dn = input.color(#f7525f, group = "Color Settings")
Constants and functions
var float PI = math.pi
laplace(src) =>
(0.5) * math.exp(-math.abs(src))
_computeComponent(src, mesaPeriodMult) =>
out = laplace(src) * mesaPeriodMult
out
_smoothComponent(src) =>
out = 0.2 * src + 0.8 * nz(src )
out
math.pi: Represents the mathematical constant π (pi).
laplace: A function that applies the Laplace transform to the source data.
_computeComponent: Computes a component of the data using the Laplace transform.
_smoothComponent: Smooths data by averaging the current value with the previous one (nz function is used to handle null values).
Alpha function:
_computeAlpha(src, fastLimit, slowLimit) =>
mesaPeriod = 0.0
mesaPeriodMult = 0.075 * nz(mesaPeriod ) + 0.54
...
alpha = math.max(fastLimit / deltaPhase, slowLimit)
out = alpha
out
_computeAlpha: Calculates the adaptive alpha value based on the fastLimit and slowLimit. This value is crucial for determining the MAMA and FAMA lines.
Calculating MAMA and FAMA:
mama = 0.0
mama := alpha * src + (1 - alpha) * nz(mama )
fama = 0.0
fama := alpha2 * mama + (1 - alpha2) * nz(fama )
Normalization:
lowest = ta.lowest(mama_fama_diff, norm_period)
highest = ta.highest(mama_fama_diff, norm_period)
normalized = (mama_fama_diff - lowest) / (highest - lowest) - 0.5
ta.lowest and ta.highest: Find the lowest and highest values of mama_fama_diff over the normalization period.
The oscillator is normalized to a range, making it easier to compare over different periods.
And finally, the plotting:
plot(norm == true ? normalized : na, style=plot.style_columns, color=col_wn, title = "mama_fama_diff Oscillator Normalized")
plot(norm == false ? mama_fama_diff : na, style=plot.style_columns, color=col_wnS, title = "mama_fama_diff Oscillator")
Example of Normalized settings:
Example for setup:
Try to make sure the lower timeframe follows the higher timeframe if you take a trade based on this indicator!
Multi Timeframe Relative Strength Index {DCAquant}Overview
The Multi Timeframe Relative Strength Index (MTF RSI) is a powerful technical analysis tool designed to provide insights into market momentum and potential trend reversals across multiple timeframes. Leveraging the Relative Strength Index (RSI) formula, this indicator offers traders a comprehensive view of market sentiment and identifies overbought and oversold conditions.
Key Features
RSI Calculation:
Utilizes the standard RSI calculation formula to measure the magnitude of recent price changes and assess the strength of market trends.
Employs a user-defined length parameter to customize the sensitivity of the RSI calculation based on trading preferences.
Multiple Timeframe Analysis:
Allows traders to analyze RSI values across up to six different timeframes, ranging from minutes to days, providing a holistic perspective on market dynamics.
Calculates RSI values independently for each selected timeframe, enabling comparison and trend identification.
Threshold Levels:
Defines overbought and oversold levels to highlight potential reversal points in market trends.
Offers flexibility in adjusting threshold levels based on individual risk tolerance and trading strategies.
Neutral Zone:
Establishes upper and lower neutral thresholds to identify periods of consolidation or sideways movement in price.
Helps traders distinguish between trending and ranging market conditions for more accurate analysis.
Moving Average Smoothing:
Provides the option to apply moving average smoothing to aggregated RSI values for enhanced clarity and reduced noise.
Enables smoother visualization of RSI trends, facilitating easier interpretation for traders.
Visual Representation:
Plots the aggregated MTF RSI values on the price chart, allowing traders to visually assess market momentum and potential reversal points.
Utilizes color-coded backgrounds to indicate Long, Short, or Neutral conditions for quick identification.
Dynamic Table Display:
Displays trading signals alongside graphical indicators (rocket for Long, snowflake for Short, and star for Neutral) in a customizable table format.
Offers flexibility in table placement and size to accommodate user preferences.
How to Use:
Parameter Configuration:
Adjust the length parameter to fine-tune the sensitivity of the RSI calculation based on the desired timeframe and trading strategy.
Define overbought and oversold levels to identify potential reversal points in market trends.
Customize upper and lower neutral thresholds to differentiate between trending and ranging market conditions.
Interpretation:
Monitor the aggregated MTF RSI values plotted on the price chart for signals of overbought or oversold conditions.
Pay attention to color-coded backgrounds and graphical indicators in the table for actionable trading insights.
Trading Strategy:
Consider entering Long positions when the aggregated MTF RSI is above the upper neutral threshold, indicating potential bullish momentum.
Evaluate Short opportunities when the aggregated MTF RSI falls below the lower neutral threshold, signaling possible bearish momentum.
Exercise caution during Neutral conditions, as there may be uncertainty in market direction.
Risk Management:
Combine MTF RSI analysis with robust risk management strategies, including stop-loss and take-profit levels, to manage trading risks effectively.
Practice prudent risk management and trade within your risk tolerance to minimize potential losses.
Disclaimer
Trading in financial markets involves risk, and past performance is not indicative of future results. The use of the MTF RSI indicator does not guarantee profits or prevent losses. Traders should conduct their own analysis, exercise caution, and seek advice from qualified financial professionals before making trading decisions.
Velocity And Acceleration with Strategy: Traders Magazine◙ OVERVIEW
Hi, Ivestors and Traders... This Indicator, the focus is Scott Cong's article in the Stocks & Commodities September issue, “VAcc: A Momentum Indicator Based On Velocity And Acceleration”. I have also added a trading strategy for you to benefit from this indicator. First of all, let's look at what the indicator offers us and what its logic is. First, let's focus on the logic of the strategy.
◙ CONCEPTS
Here is a new indicator based on some simple physics concepts that is easy to use, responsive and precise. Learn how to calculate and use it.
The field of physics gives us some important principles that are highly applicable to analyzing the markets. In this indicator, I will present a momentum indicator. Scott Cong developed based on the concepts of velocity and acceleration this indicator. Of the many characteristics of price that traders and analysts often study, rate and rate of change are useful ones. In other words, it’s helpful to know: How fast is price moving, and is it speeding up or slowing down? How is price changing from one period to the next? The indicator I’m introducing here is calculated using the current bar (C) and every bar of a lookback period from the current bar. He named the indicator the VAcc since it’s based on the average of velocity line (av) and acceleration line (Acc) over the lookback period. For longer periods, the VAcc behaves the same way as the MACD, only it’s simpler, more responsive, and more precise. Interestingly, for shorter periods, VAcc exhibits characteristics of an oscillator, such as the stochastics oscillator.
◙ CALCULATION
The calculation of VAcc involves the following steps:
1. Relatively weighted average where the nearer price has the largest influence.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. The Velocity Average is smoothed with an exponential moving average. Now it get:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Similarly, accelerations for each bar within the lookback period and scale factor are calculated as:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEGY
In fact, Scott probably preferred to use it in periods 9 and 26 because it was similar to Macd and used the ratio of 0.5. However, I preferred to use the 8 and 21 periods to provide signals closer to the stochastic oscillator in the short term and used the 0.382 ratio. The logic of the strategy is this
Long Strategy → acc(Acceleration Line) > 0.1 and av(Velocity Average Line) > 0.1(Long Factor)
Short strategy → acc(Acceleration Line) < -0.1 and av(Velocity Average Line) < -0.1(Long Factor)
Here, you can change the Short Factor and Long Factor as you wish and produce more meaningful results that are closer to your own strategy.
I hope you benefits...
◙ GENEL BAKIŞ
Merhaba Yatırımcılar ve Yatırımcılar... Bu Gösterge, Scott Cong'un Stocks & Emtia Eylül sayısındaki “VAcc: Hız ve İvmeye Dayalı Bir Momentum Göstergesi” başlıklı makalesine odaklanmaktadır. Bu göstergeden faydalanabilmeniz için bir ticaret stratejisi de ekledim. Öncelikle göstergenin bize neler sunduğuna ve mantığının ne olduğuna bakalım. Öncelikle stratejinin mantığına odaklanalım.
◙ KAVRAMLAR
İşte kullanımı kolay, duyarlı ve kesin bazı basit fizik kavramlarına dayanan yeni bir gösterge. Nasıl hesaplanacağını ve kullanılacağını öğrenin.
Fizik alanı bize piyasaları analiz etmede son derece uygulanabilir bazı önemli ilkeler verir. Bu göstergede bir momentum göstergesi sunacağım. Scott Cong bu göstergeyi hız ve ivme kavramlarına dayanarak geliştirdi. Yatırımcıların ve analistlerin sıklıkla incelediği fiyatın pek çok özelliği arasında değişim oranı ve oranı yararlı olanlardır. Başka bir deyişle şunu bilmek faydalı olacaktır: Fiyat ne kadar hızlı hareket ediyor ve hızlanıyor mu, yavaşlıyor mu? Fiyatlar bir dönemden diğerine nasıl değişiyor? Burada tanıtacağım gösterge, mevcut çubuk (C) ve mevcut çubuktan bir yeniden inceleme döneminin her çubuğu kullanılarak hesaplanır. Göstergeye, yeniden inceleme dönemi boyunca hız çizgisinin (av) ve ivme çizgisinin (Acc) ortalamasına dayandığı için VAcc adını verdi. Daha uzun süreler boyunca VACc, MACD ile aynı şekilde davranır, yalnızca daha basit, daha duyarlı ve daha hassastır. İlginç bir şekilde, daha kısa süreler için VAcc, stokastik osilatör gibi bir osilatörün özelliklerini sergiliyor.
◙ HESAPLAMA
VAcc'nin hesaplanması aşağıdaki adımları içerir:
1. Yakın zamandaki fiyatın en büyük etkiye sahip olduğu göreceli ağırlıklı ortalamayı hesaplatıyoruz.
weighted_avg (float src, int length) =>
float sum = 0.0
for _i = 1 to length
float diff = (src - src ) / _i
sum += diff
sum /= length
2. Hız Ortalamasına üstel hareketli ortalamayla düzleştirme uygulanır. Şimdi bu şekilde aşağıdaki kod ile bunu şöyle elde ediyoruz:
VAcc (float src, int period, int smoothing) =>
float vel = ta.ema(weighted_avg(src, period), smoothing)
float acc = weighted_avg(vel, period)
3. Benzer şekilde, yeniden inceleme süresi ve ölçek faktörü içindeki her bir çubuk için fiyattaki ivmelenler yada momentum şu şekilde hesaplanır:
= VAcc(src, length1, length2)
av /= (length1 * scale_factor)
◙ STRATEJİ
Aslında Scott muhtemelen Macd'e benzediği ve 0,5 oranını kullandığı için 9. ve 26. periyotlarda kullanmayı tercih etmişti. Ancak kısa vadede stokastik osilatöre daha yakın sinyaller sağlamak için 8 ve 21 periyotlarını kullanmayı tercih ettim ve 0,382 oranını kullandım. Stratejinin mantığı şu
Uzun Strateji → acc(İvme Çizgisi) > 0,1 ve av(Hız Ortalama Çizgisi) > 0,1(Uzun Faktör)
Kısa strateji → acc(İvme Çizgisi) < -0,1 ve av(Hız Ortalama Çizgisi) < -0,1(Uzun Faktör)
Burada Kısa Faktör ve Uzun Faktör' ü dilediğiniz gibi değiştirip, kendi stratejinize daha yakın, daha anlamlı sonuçlar üretebilirsiniz.
umarım faydasını görürsün...
Volume Weighted Relative Strength Index (VWRSI) [AlgoAlpha]Volume Weighted Relative Strength Index 📈✨
The Volume Weighted Relative Strength Index (VWRSI) by AlgoAlpha enhances traditional RSI by incorporating volume weighting, providing a more nuanced view of market strength. It uses custom range detection to measure consolidation strength, applying dynamic scoring to highlight trend phases. The indicator includes customizable moving averages (SMA, EMA, WMA, VWMA) and color-coded visual cues for uptrends and downtrends. Additionally, it marks significant bullish and bearish trend points with symbols, making it easier to identify potential trading opportunities. This powerful tool helps traders make informed decisions by combining volume, price action, and trend analysis.
✨ Key Features :
📊 Volume-Weighted RSI : Combines RSI with volume for better accuracy.
🔄 Range Detection : Identifies consolidation phases.
🎨 Customizable MAs : Choose from various moving averages.
🔔 Alert Capabilities : Set notifications for trend points.
🚀 How to Use :
🛠 Add Indicator : Add the indicator to favorites, and customize the settings to suite your trading style.
📊 Analyze Market : Watch RSI and range score for trends.
🔔 Set Alerts : Get notified of bullish/bearish points.
✨ How It Works :
The Volume Weighted Relative Strength Index (VWRSI) combines traditional RSI with volume weighting to offer a more comprehensive view of market momentum. It calculates the RSI using the closing price, then weights it by volume to enhance the accuracy of the trend analysis. The indicator also includes a custom range detection feature that evaluates consolidation strength by dynamically scoring the RSI over a specified period. This scoring helps identify phases of strong trends and consolidations. Visual elements like color-coded trend fills and symbols for bullish and bearish points make it easier to spot key market movements and potential trading opportunities.
Stay ahead with VWRSI by AlgoAlpha! 📈💡
Multi-Chart Widget [LuxAlgo]The Multi-Chart Widget tool is a comprehensive solution crafted for traders and investors looking to analyze multiple financial instruments simultaneously. With the capability to showcase up to three additional charts, users can customize each chart by selecting different financial instruments, and timeframes.
Users can add various widely used technical indicators to the charts such as the relative strength index, Supertrend, moving averages, Bollinger Bands...etc.
🔶 USAGE
The tool offers traders and investors a comprehensive view of multiple charts simultaneously. By displaying up to three additional charts alongside the primary chart, users can analyze assets across different timeframes, compare their performance, and make informed decisions.
Users have the flexibility to choose from various customizable chart types, including the recently added "Volume Candles" option.
This tool allows adding to the chart some of the most widely used technical indicators, such as the Supertrend, Bollinger Bands, and various moving averages.
In addition to the charting capabilities, the tool also features a dynamic statistic panel that provides essential metrics and key insights into the selected assets. Users can track performance indicators such as relative strength, trend, and volatility, enabling them to identify trends, patterns, and trading opportunities efficiently.
🔶 DETAILS
A brief overview of the indicators featured in the statistic panel is given in the sub-section below:
🔹Dual Supertrend
The Dual Supertrend is a modified version of the Supertrend indicator, which is based on the concept of trend following. It generates buy or sell signals by analyzing the asset's price movement. The Dual Supertrend incorporates two Supertrend indicators with different parameters to provide potentially more accurate signals. It helps traders identify trend reversals and establish trend direction in a more responsive manner compared to a single Supertrend.
🔹Relative Strength Index
The Relative Strength Index is a momentum oscillator that measures the speed and change of price movements. RSI oscillates between 0 and 100 and is typically used to identify overbought or oversold conditions in a market. Traditionally, RSI values above 70 are considered overbought, suggesting that the asset may be due for a reversal or correction, while RSI values below 30 are considered oversold, indicating potential buying opportunities.
🔹Volatility
Volatility in trading refers to the degree of variation or fluctuation in the price of a financial instrument, such as a stock, currency pair, or commodity, over a certain period of time. It is a measure of the speed and magnitude of price changes and reflects the level of uncertainty or risk in the market. High volatility implies that prices are experiencing rapid and significant movements, while low volatility suggests that prices are relatively stable and are not changing much. Traders often use volatility as an indicator to assess the potential risk and return of an investment and to make informed decisions about when to enter or exit trades.
🔹R-Squared (R²)
R-squared, also known as the coefficient of determination, is a statistical measure that indicates the proportion of the variance in the dependent variable that is predictable from the independent variable(s). In other words, it quantifies the goodness of fit of a regression model to the observed data. R-squared values range from %0 to %100, with higher values indicating a better fit of the model to the data. An R-squared of 100% means that all movements of a security are completely explained by movements in the index, while an R-squared value of %0 indicates that the model does not explain any of the variability in the dependent variable.
In simpler terms, in investing, a high R-squared, from 85% to 100%, indicates that the stock’s or fund’s performance moves relatively in line with the index. Conversely, a low R-squared (around 70% or less) indicates that the fund's performance tends to deviate significantly from the movements of the index.
🔶 SETTINGS
🔹Mini Chart(s) Generic Settings
Mini Charts Separator: This option toggles the visibility of the separator lines.
Number Of Bars: Specifies the number of bars to be displayed for each mini chart.
Horizontal Offset: Determines the distance at which the mini charts will be displayed from the primary chart.
🔹Mini Chart Settings: Top - Middle - Bottom
Mini Chart Top/Middle/Bottom: Toggle the visibility of the selected mini chart.
Symbol: Choose the financial instrument to be displayed in the mini chart. If left as an empty string, it will default to the current chart instrument.
Timeframe: This option determines the timeframe used for calculating the mini charts. If a timeframe lower than the chart's timeframe is selected, the calculations will be based on the chart's timeframe.
Chart Type: Selection from various chart types for the mini charts, including candles, volume candles, line, area, columns, high-low, and Heikin Ashi.
Chart Size: Determines the size of the mini chart.
Technical Indicator: Selection from various technical indicators to be displayed on top of the mini charts.
Note : Chart sizing is relative to other mini charts. For example, If all the mini charts are sized to x5 relative to each other, the result will be the same as if they were all sized as x1. This is because the relative proportions between the mini charts remain consistent regardless of their absolute sizes. Therefore, their positions and sizes relative to each other remain unchanged, resulting in the same visual representation despite the differences in absolute scale.
🔹Supertrend Settings
ATR Length: is the lookback length for the ATR calculation.
Factor: is what the ATR is multiplied by to offset the bands from price.
Color: color customization option.
🔹Moving Average Settings
Type: is the type of the moving average, available types of moving averages include SMA (Simple Moving Average), EMA (Exponential Moving Average), RMA (Root Mean Square Moving Average), HMA (Hull Moving Average), WMA (Weighted Moving Average), and VWMA (Volume Weighted Moving Average).
Source: Determines what data from each bar will be used in calculations.
Length: The time period to be used in calculating the Moving Average.
Color: Color customization option.
🔹Bollinger Bands Settings
Basis Type: Determines the type of Moving Average that is applied to the basis plot line.
Source: Determines what data from each bar will be used in calculations.
Length: The time period to be used in calculating the Moving Average which creates the base for the Upper and Lower Bands.
StdDev: The number of Standard Deviations away from the Moving Average that the Upper and Lower Bands should be.
Color: Color customization options for basis, upper and lower bands.
🔹Mini Chart(s) Panel Settings
Mini Chart(s) Panel: Controls the visibility of the panel containing the mini charts.
Dual Supertrend: Toggles the display of the evaluated dual super trend, based on the super trend settings provided below the option. The definitions for the options are the same as stated above for the super trend.
Relative Strength Index: Toggles the display of the evaluated RSI, based on the source and length settings provided below the option.
Volatility: Toggles the display of the calculated Volatility, based on the length settings provided below the option.
R-Squared: Toggles the display of the calculated R-Squared (R²), based on the length settings provided below the option.
🔶 LIMITATIONS
The tool allows users to display mini charts featuring various types of instruments alongside the primary chart instrument. However, there's a limitation: the selected primary chart instrument must have an ACTIVE market status. Alternatively, if the primary chart instrument is not active, the mini chart instruments must belong to the same exchange and have the same type as the primary chart instrument.
Stochastics - Made EasyThis indicator is a visually improved version of Stochastics. It makes it much easier to see what's happening by simplifying those confusing, intersecting lines. With this, you can detect the Stochastics direction more clearly. All the features are also explained in the tooltips of the input fields. Some extra features are included, such as average top and bottom calculation, standard deviation and divergences.
Color legend:
Green: Stoch K Above D and Rising
Light Green: Stoch K Above D and Falling
Red: Stoch K Below D and Falling
Light Red: Stoch K Below D and Rising
Blue: Stoch K Crossover D
Orange: Stoch K Crossunder D
Blue Arrow: Bullish Divergence
Orange Arrow: Bearish Divergence
RSI - Made EasyThis indicator is a visually improved version of RSI. It makes it much easier to see what's happening by simplifying those confusing, intersecting lines. With this, you can detect the RSI direction more clearly. All the features are also explained in the tooltips of the input fields. Some extra features are included, such as average top and bottom calculation, standard deviation and divergences.
Color legend:
Green: RSI Above MA and Rising
Light Green: RSI Above MA and Falling
Red: RSI Below MA and Falling
Light Red: RSI Below MA and Rising
Blue: RSI Crossover MA
Orange: RSI Crossunder MA
Blue Arrow: Bullish Divergence
Orange Arrow: Bearish Divergence
Korneev Reverse RSIRethinking the Legendary Relative Strength Index by John Welles Wilder
The essence of the new approach lies in the reverse use of the so-called "overbought" and "oversold" zones. In his 1978 book, "New Concepts in Technical Trading Systems," where the RSI mechanism was thoroughly described, Wilder writes that one way to use the oscillator is to open a long position when the RSI drops into oversold territory (below 30) and to open a short position when the RSI rises to overbought levels (above 70). However, backtesting this strategy with such inputs yields rather mediocre results.
Based on the calculation formula, the RSI calculates the rate of price change over a certain period. Therefore, overbought and oversold zones will have relative significance (relative to the set calculation period). It is no coincidence that the word "relative" was added to the name of the oscillator. It is worth accepting as an axiom the assertion that the price of an asset is fair at every moment in time.
Essentially, the RSI calculates the strength of a trend. If the oscillator value is above 70, it is highly likely that an upward movement is occurring in the market. Therefore, in the current strategy, a long position is opened precisely at the moment of greatest buyer strength (when RSI > 80), i.e., in the direction of the trend, since counter-trend trading with the RSI has proven to be ineffective. The position is closed after the buyers lose their advantage and the RSI drops to 40.
The strategy is recommended to be used only with long positions, as short positions show negative results. The strategy uses a moving average for the RSI with a period of 14 to smooth the oscillator data.
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Переосмысление легендарного осциллятора Relative strength index Джона Уэллса Уайлдера
Суть нового подхода заключается в реверсивном использовании так называемых зон "перекупленности" и "перепроданности". В своей книге от 1978 года "New concepts in tecnical trading systems", в которой был подробно описан механизм работы RSI, Уайлдер пишет, что один из способов использования осциллятора - открытие длинной позиции при снижении RSI в перепроданность (ниже 30) и открытие короткой позиции при повышении RSI до перекупленности (выше 70). Однако бэктест стратегии с такими вводными дает весьма посредственные результаты.
Исходя из формулы расчета, RSI рассчитывает скорость изменения цены за определенный период. Поэтому зоны перекупленности и перепроданности будут иметь относительное значение (относительно установленного периода расчета). Не зря ведь в названии осциллятора было добавлено слово "относительной". Стоит принять за аксиому утверждение, что цена актива справедлива в каждый момент времени.
По сути, RSI рассчитывает силу тренда. Если значение осциллятора выше 70, то на рынке с высокой долей вероятности происходит восходящее движение. Поэтому в текущей стратегии открытие лонга происходит именно в момент наибольшей силы покупателей (когда RSI > 80), то есть в сторону тренда, поскольку контртрендовая торговля по RSI показала свою несостоятельность. Закрытие позиции происходит после того, как покупатели теряют преимущество и RSI снижается до 40.
Стратегию рекомендуется использовать только с длинными позициями, поскольку короткие позиции показывают отрицательный результат. В стратегии используется скользящая средняя для RSI с периодом 14 для сглаживания данных осциллятора.
RSI Multiple TimeFrame, Version 1.0RSI Multiple TimeFrame, Version 1.0
Overview
The RSI Multiple TimeFrame script is designed to enhance trading decisions by providing a comprehensive view of the Relative Strength Index (RSI) across multiple timeframes. This tool helps traders identify overbought and oversold conditions more accurately by analyzing RSI values on different intervals simultaneously. This is particularly useful for traders who employ multi-timeframe analysis to confirm signals and make more informed trading decisions.
Unique Feature of the new script (described in detail below)
Multi-Timeframe RSI Analysis
Customizable Timeframes
Visual Signal Indicators (dots)
Overbought and Oversold Layers with gradual Background Fill
Enhanced Trend Confirmation
Originality and Usefulness
This script combines the RSI indicator across three distinct timeframes into a single view, providing traders with a multi-dimensional perspective of market momentum. It also provides associated signals to better time dips and peaks. Unlike standard RSI indicators that focus on a single timeframe, this script allows users to observe RSI trends across short, medium, and long-term intervals, thereby improving the accuracy of entry and exit signals. This is particularly valuable for traders looking to align their short-term strategies with longer-term market trends.
Signal Description
The script also includes a unique signal feature that plots green and red dots on the chart to highlight potential buy and sell opportunities:
Green Dots : These appear when all three RSI values are under specific thresholds (RSI of the shortest timeframe < 30, the medium timeframe < 40, and the longest timeframe < 50) and the RSI of the shortest timeframe is showing an upward trend (current value is greater than the previous value, and the value two periods ago is greater than the previous value). This indicates a potential buying opportunity as the market may be shifting from an oversold condition.
Red Dots : These appear when all three RSI values are above specific thresholds (RSI of the shortest timeframe > 70, the medium timeframe > 60, and the longest timeframe > 50) and the RSI of the shortest timeframe is showing a downward trend (current value is less than the previous value, and the value two periods ago is less than the previous value). This indicates a potential selling opportunity as the market may be shifting from an overbought condition.
These signals help traders identify high-probability turning points in the market by ensuring that momentum is aligned across multiple timeframes.
Detailed Description
Input Variables
RSI Period (`len`) : The number of periods to calculate the RSI. Default is 14.
RSI Source (`src`) : The price source for RSI calculation, defaulting to the average of the high and low prices (`hl2`).
Timeframes (`tf1`, `tf2`, `tf3`) : The different timeframes for which the RSI is calculated, defaulting to 5 minutes, 1 hour, and 8 hours respectively.
Functionality
RSI Calculations : The script calculates the RSI for each of the three specified timeframes using the `request.security` function. This allows the RSI to be plotted for multiple intervals, providing a layered view of market momentum.
```pine
rsi_tf1 = request.security(syminfo.tickerid, tf1, ta.rsi(src, len))
rsi_tf2 = request.security(syminfo.tickerid, tf2, ta.rsi(src, len))
rsi_tf3 = request.security(syminfo.tickerid, tf3, ta.rsi(src, len))
```
Plotting : The RSI values for the three timeframes are plotted with different colors and line widths for clear visual distinction. This makes it easy to compare RSI values across different intervals.
```pine
p1 = plot(rsi_tf1, title="RSI 5m", color=color.rgb(200, 200, 255), linewidth=2)
p2 = plot(rsi_tf2, title="RSI 1h", color=color.rgb(125, 125, 255), linewidth=2)
p3 = plot(rsi_tf3, title="RSI 8h", color=color.rgb(0, 0, 255), linewidth=2)
```
Overbought and Oversold Levels : Horizontal lines are plotted at standard RSI levels (20, 30, 40, 50, 60, 70, 80) to visually identify overbought and oversold conditions. The areas between these levels are filled with varying shades of blue for better visualization.
```pine
h80 = hline(80, title="RSI threshold 80", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
h70 = hline(70, title="RSI threshold 70", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
...
fill(h70, h80, color=color.rgb(33, 150, 243, 95), title="Background")
```
Signal Plotting : The script adds green and red dots to indicate potential buy and sell signals, respectively. A green dot is plotted when all RSI values are under specific thresholds and the RSI of the shortest timeframe is rising. Conversely, a red dot is plotted when all RSI values are above specific thresholds and the RSI of the shortest timeframe is falling.
```pine
plotshape(series=(rsi_tf1 < 30 and rsi_tf2 < 40 and rsi_tf3 < 50 and (rsi_tf1 > rsi_tf1 ) and (rsi_tf1 > rsi_tf1 )) ? 1 : na, location=location.bottom, color=color.green, style=shape.circle, size=size.tiny)
plotshape(series=(rsi_tf1 > 70 and rsi_tf2 > 60 and rsi_tf3 > 50 and (rsi_tf1 < rsi_tf1 ) and (rsi_tf1 < rsi_tf1 )) ? 1 : na, location=location.top, color=color.red, style=shape.circle, size=size.tiny)
```
How to Use
Configuring Inputs : Adjust the RSI period and source as needed. Modify the timeframes to suit your trading strategy.
Interpreting the Indicator : Use the plotted RSI values to gauge momentum across different timeframes. Look for overbought conditions (RSI above 70, 60 and 50) and oversold conditions (RSI below 30, 40 and 50) across multiple intervals to confirm trade signals.
Signal Confirmation : Pay attention to the green and red dots that provide signals to better time dips and peaks. dots are printed when the lower timeframe (5mn by default) shows sign of reversal.
These signals are more reliable when confirmed across all three timeframes.
This script provides a nuanced view of RSI, helping traders make more informed decisions by considering multiple timeframes simultaneously. By combining short, medium, and long-term RSI values, traders can better align their strategies with overarching market trends, thus improving the precision of their trading actions.
