Supertrend StrategyThe Supertrend Strategy was created based on the Supertrend and Relative Strength Index (RSI) indicators, widely respected tools in technical analysis. This strategy combines these two indicators to capture market trends with precision and reliability, looking for optimizing exit levels at oversold or overbought price levels.
The Supertrend indicator identifies trend direction based on price and volatility by using the Average True Range (ATR). The ATR measures market volatility by calculating the average range between an asset’s high and low prices over a set period. It provides insight into price fluctuations, with higher ATR values indicating increased volatility and lower values suggesting stability. The Supertrend Indicator plots a line above or below the price, signaling potential buy or sell opportunities: when the price closes above the Supertrend line, an uptrend is indicated, while a close below the line suggests a downtrend. This line shifts as price movements and volatility levels change, acting as both a trailing stop loss and trend confirmation.
To enhance the Supertrend strategy, the Relative Strength Index (RSI) has been added as an exit criterion. As a momentum oscillator, the RSI indicates overbought (usually above 70) or oversold (usually below 30) conditions. This integration allows trades to close when the asset is overbought or oversold, capturing gains before a possible reversal, even if the percentage take profit level has not been reached. This mechanism aims to prevent losses due to market reversals before the Supertrend signal changes.
### Key Features
1. **Entry criteria**:
- The strategy uses the Supertrend indicator calculated by adding or subtracting a multiple of the ATR from the closing price, depending on the trend direction.
- When the price crosses above the Supertrend line, the strategy signals a long (buy) entry. Conversely, when the price crosses below, it signals a short (sell) entry.
- The strategy performs a reversal if there is an open position and a change in the direction of the supertrend occurs
2. **Exit criteria**:
- Take profit of 30% (default) on the average position price.
- Oversold (≤ 5) or overbought (≥ 95) RSI
- Reversal when there is a change in direction of the Supertrend
3. **No Repainting**:
- This strategy is not subject to repainting, as long as the timeframe configured on your chart is the same as the supertrend timeframe .
4. **Position Sizing by Equity and risk management**:
- This strategy has a default configuration to operate with 35% of the equity. At the time of opening the position, the supertrend line is typically positioned at about 12 to 16% of the entry price. This way, the strategy is putting at risk about 16% of 35% of equity, that is, around 5.6% of equity for each trade. The percentage of equity can be adjusted by the user according to their risk management.
5. **Backtest results**:
- This strategy was subjected to deep backtesting and operations in replay mode, including transaction fees of 0.12%, and slippage of 5 ticks.
- The past results in deep backtest and replay mode were compatible and profitable (Variable results depending on the take profit used, supertrend and RSI parameters). However, it should be noted that few operations were evaluated, since the currency in question has been created for a short time and the frequency of operations is relatively small.
- Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
Default Settings
Chart timeframe: 2h
Supertrend Factor: 3.42
ATR period: 14
Supertrend timeframe: 2 h
RSI timeframe: 15 min
RSI Lenght: 5 min
RSI Upper limit: 95
RSI Lower Limit: 5
Take Profit: 30%
BYBIT:1000000MOGUSDT.P
Oscylatory
Atr Target TP & Protecion Zone [Pinescriptlabs]This indicator provides an adaptive trailing stop system with dynamic price targets and protection zones, ideal for position management.
Main Features:
🚦 ADAPTIVE TRAILING STOP:
Automatically adjusts based on volatility (ATR) and volume
Two modes: "Modified" and "UnModified" for true range calculation
Displayed as a line with colored background (green for longs, red for shorts)
🎯 TARGET ZONES (T1 & T2):
Calculates two target zones (T1 and T2) based on:
Market strength (combination of RSI, volume, MFI, ADX, MACD)
Current volatility (ATR)
Distance from current price
Visualized with blue boxes (T1) and purple boxes (T2)
🛡️ PROTECTION ZONE:
Automatically activates in sideways markets
Provides an additional buffer to the trailing stop
Helps avoid premature exits in volatile markets
📊 INFORMATION PANELS:
Top Right Panel displays:
Current trend direction
Target status (T1 & T2)
Market strength
Current ATR
RSI level
Bottom Right Panel displays:
Trailing status (WIDE/NORMAL)
Volume impact
Directional strength
Protection zone status
Español:
Este indicador proporciona un sistema de trailing stop adaptativo con objetivos de precio dinámicos y zonas de protección, ideal para la gestión de posiciones.
**Características Principales**:
🚦 **TRAILING STOP ADAPTATIVO**:
- Se ajusta automáticamente según la volatilidad (ATR) y el volumen
- Dos modos: "Modified" y "UnModified" para el cálculo del rango verdadero
- Se visualiza como una línea con fondo coloreado (verde para largos, rojo para cortos)
🎯 **ZONAS OBJETIVO (T1 y T2)**:
- Calcula dos zonas objetivo (T1 y T2) basadas en:
- Fuerza del mercado (combinación de RSI, volumen, MFI, ADX, MACD)
- Volatilidad actual (ATR)
- Distancia al precio actual
- Visualización mediante cajas azules (T1) y moradas (T2)
🛡️ **ZONA DE PROTECCIÓN**:
- Se activa automáticamente en mercados laterales
- Proporciona un buffer adicional al trailing stop
- Ayuda a evitar salidas prematuras en mercados volátiles
📊 **PANELES INFORMATIVOS**:
*Panel Superior Derecho* muestra:
- Dirección de la tendencia actual
- Estado de los objetivos (T1 y T2)
- Fuerza del mercado
- ATR actual
- Nivel de RSI
*Panel Inferior Derecho* muestra:
- Estado del trailing (WIDE/NORMAL)
- Impacto del volumen
- Fuerza direccional
- Estado de la zona de protección
RSI from Rolling VWAP [CHE]Introducing the RSI from Rolling VWAP Indicator
Elevate your trading strategy with the RSI from Rolling VWAP —a cutting-edge indicator designed to provide unparalleled insights and enhance your decision-making on TradingView. This advanced tool seamlessly integrates the Relative Strength Index (RSI) with a Rolling Volume-Weighted Average Price (VWAP) to deliver precise and actionable trading signals.
Why Choose RSI from Rolling VWAP ?
- Clear Trend Detection: Our enhanced algorithms ensure accurate identification of bullish and bearish trends, allowing you to capitalize on market movements with confidence.
- Customizable Time Settings: Tailor the time window in days, hours, and minutes to align perfectly with your unique trading strategy and market conditions.
- Flexible Moving Averages: Select from a variety of moving average types—including SMA, EMA, WMA, and more—to smooth the RSI, providing clearer trend analysis and reducing market noise.
- Threshold Alerts: Define upper and lower RSI thresholds to effortlessly spot overbought or oversold conditions, enabling timely and informed trading decisions.
- Visual Enhancements: Enjoy a visually intuitive interface with color-coded RSI lines, moving averages, and background fills that make interpreting market data straightforward and efficient.
- Automatic Signal Labels: Receive immediate bullish and bearish labels directly on your chart, signaling potential trading opportunities without the need for constant monitoring.
Key Features
- Inspired by Proven Tools: Building upon the robust foundation of TradingView's Rolling VWAP, our indicator offers enhanced functionality and greater precision.
- Volume-Weighted Insights: By incorporating volume into the VWAP calculation, gain a deeper understanding of price movements and market strength.
- User-Friendly Configuration: Easily adjust settings to match your trading preferences, whether you're a novice trader or an experienced professional.
- Hypothesis-Driven Analysis: Utilize hypothetical results to backtest strategies, understanding that past performance does not guarantee future outcomes.
How It Works
1. Data Integration: Utilizes the `hlc3` (average of high, low, and close) as the default data source, with customization options available to suit your trading needs.
2. Dynamic Time Window: Automatically calculates the optimal time window based on an auto timeframe or allows for fixed time periods, ensuring flexibility and adaptability.
3. Rolling VWAP Calculation: Accurately computes the Rolling VWAP by balancing price and volume over the specified time window, providing a reliable benchmark for price action.
4. RSI Analysis: Measures momentum through RSI based on Rolling VWAP changes, smoothed with your chosen moving average for enhanced trend clarity.
5. Actionable Signals: Detects and labels bullish and bearish conditions when RSI crosses predefined thresholds, offering clear indicators for potential market entries and exits.
Seamless Integration with Your TradingView Experience
Adding the RSI from Rolling VWAP to your TradingView charts is straightforward:
1. Add to Chart: Simply copy the Pine Script code into TradingView's Pine Editor and apply it to your desired chart.
2. Customize Settings: Adjust the Source Settings, Time Settings, RSI Settings, MA Settings, and Color Settings to align with your trading strategy.
3. Monitor Signals: Watch for RSI crossings above or below your set thresholds, accompanied by clear labels indicating bullish or bearish trends.
4. Optimize Your Trades: Leverage the visual and analytical strengths of the indicator to make informed buy or sell decisions, maximizing your trading potential.
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.
Get Started Today
Transform your trading approach with the RSI from Rolling VWAP indicator. Experience the synergy of momentum and volume-based analysis, and unlock the potential for more accurate and profitable trades.
Download now and take the first step towards a more informed and strategic trading journey!
For further inquiries or support, feel free to contact
Best regards
Chervolino
Inspired by the acclaimed Rolling VWAP by TradingView
Z-Scored Moving Average Suite [KFB Quant]Z-Scored Moving Average Suite
This indicator combines several types of moving averages—Simple, Exponential, and Weighted—with a Z-Score calculation to give a clearer understanding of price trends in relation to their historical averages. It is used to detect overbought (OB) and oversold (OS) conditions, allowing you to see when an asset is deviating significantly from its mean.
Key Components:
Moving Averages: The suite includes Simple (SMA), Exponential (EMA), and Weighted (WMA) Moving Averages. For each, a single, double, and triple version is calculated to smooth out noise.
Z-Score: The Z-Score measures how far the current price is from its moving average in terms of standard deviations, helping to highlight unusual price behavior.
Overbought and Oversold Levels:
- When the Z-Score crosses above a predefined threshold (1.5 by default), the asset is considered Overbought (OB).
- When the Z-Score drops below a certain level (-1.5 by default), the asset is seen as Oversold (OS).
Visualization:
- The histogram represents the average Z-Score of all the moving averages combined, colored based on bullish (blue) or bearish (brown) trends.
- Individual Z-Scores for each moving average type (SMA, EMA, WMA) are also plotted, providing further insight into the momentum and direction.
Signals:
- The table in the chart shows a summary of Z-Scores for each type of moving average. It also provides a quick glance at whether the asset is in a bullish or bearish phase, if the Z-Scores are rising or falling, and whether the asset is overbought or oversold.
This tool is highly customizable, with adjustable lengths for the moving averages and Z-Scores, making it a flexible addition to any trading strategy that relies on mean-reversion or trend analysis.
Disclaimer: This tool is provided for informational and educational purposes only and should not be considered as financial advice. Always conduct your own research and consult with a licensed financial advisor before making any investment decisions.
Savitzky Golay Median Filtered RSI [BackQuant]Savitzky Golay Median Filtered RSI
Introducing BackQuant's Savitzky Golay Median Filtered RSI, a cutting-edge indicator that enhances the classic Relative Strength Index (RSI) by applying both a Savitzky-Golay filter and a median filter to provide smoother and more reliable signals. This advanced approach helps reduce noise and captures true momentum trends with greater precision. Let’s break down how the indicator works, the features it offers, and how it can improve your trading strategy.
Core Concept: Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a widely used momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100, with levels above 70 typically indicating overbought conditions and levels below 30 indicating oversold conditions. However, the standard RSI can sometimes generate noisy signals, especially in volatile markets, making it challenging to identify reliable entry and exit points.
To improve upon the traditional RSI, this indicator introduces two powerful filters: the Savitzky-Golay filter and a median filter.
Savitzky-Golay Filter: Smoothing with Precision
The Savitzky-Golay filter is a digital filtering technique used to smooth data while preserving important features, such as peaks and trends. Unlike simple moving averages that can distort important price data, the Savitzky-Golay filter uses polynomial regression to fit the data, providing a more accurate and less lagging result.
In this script, the Savitzky-Golay filter is applied to the RSI values to smooth out short-term fluctuations and provide a more reliable signal. By using a window size of 5 and a polynomial degree of 2, the filter effectively reduces noise without compromising the integrity of the underlying price movements.
Median Filter: Reducing Outliers
After applying the Savitzky-Golay filter, the median filter is applied to the smoothed RSI values. The median filter is particularly effective at removing short-lived outliers, further enhancing the accuracy of the RSI by reducing the impact of sudden and temporary price spikes or drops. This combination of filters creates an ultra-smooth RSI that is better suited for detecting true market trends.
Long and Short Signals
The Savitzky Golay Median Filtered RSI generates long and short signals based on user-defined threshold levels:
Long Signals: A long signal is triggered when the filtered RSI exceeds the Long Threshold (default set at 176). This indicates that momentum is shifting upward, and it may present a good buying opportunity.
Short Signals: A short signal is generated when the filtered RSI falls below the Short Threshold (default set at 162). This suggests that momentum is weakening, potentially signaling a selling opportunity or exit from a long position.
These threshold levels can be adjusted to suit different market conditions and timeframes, allowing traders to fine-tune the sensitivity of the indicator.
Customization and Visualization Options
The Savitzky Golay Median Filtered RSI comes with several customization options, enabling traders to tailor the indicator to their specific needs:
Calculation Source: Select the price source for the RSI calculation (default is OHLC4, but it can be changed to close, open, high, or low prices).
RSI Period: Adjust the lookback period for the RSI calculation (default is 14).
Median Filter Length: Control the length of the median filter applied to the smoothed RSI, affecting how much noise is removed from the signal.
Threshold Levels: Customize the long and short thresholds to define the sensitivity for generating buy and sell signals.
UI Settings: Choose whether to display the RSI and thresholds on the chart, color the bars according to trend direction, and adjust the line width and colors used for long and short signals.
Visual Feedback: Color-Coded Signals and Thresholds
To make the signals easier to interpret, the indicator offers visual feedback by coloring the price bars and the RSI plot according to the current market trend:
Green Bars indicate long signals when momentum is bullish.
Red Bars indicate short signals when momentum is bearish.
Gray Bars indicate neutral or undecided conditions when no clear signal is present.
In addition, the Long and Short Thresholds can be plotted directly on the chart to provide a clear reference for when signals are triggered, allowing traders to visually gauge the strength of the RSI relative to its thresholds.
Alerts for Automation
For traders who prefer automated notifications, the Savitzky Golay Median Filtered RSI includes built-in alert conditions for long and short signals. You can configure these alerts to notify you when a buy or sell condition is met, ensuring you never miss a trading opportunity.
Trading Applications
This indicator is versatile and can be used in a variety of trading strategies:
Trend Following: The combination of Savitzky-Golay and median filtering makes this RSI particularly useful for identifying strong trends without being misled by short-term noise. Traders can use the long and short signals to enter trades in the direction of the prevailing trend.
Reversal Trading: By adjusting the threshold levels, traders can use this indicator to spot potential reversals. When the RSI moves from overbought to oversold levels (or vice versa), it may signal a shift in market direction.
Swing Trading: The smoothed RSI provides a clear signal for short to medium-term price movements, making it an excellent tool for swing traders looking to capitalize on momentum shifts.
Risk Management: The filtered RSI can be used as part of a broader risk management strategy, helping traders avoid false signals and stay in trades only when the momentum is strong.
Final Thoughts
The Savitzky Golay Median Filtered RSI takes the classic RSI to the next level by applying advanced smoothing techniques that reduce noise and improve signal reliability. Whether you’re a trend follower, swing trader, or reversal trader, this indicator provides a more refined approach to momentum analysis, helping you make better-informed trading decisions.
As with all indicators, it is important to backtest thoroughly and incorporate sound risk management strategies when using the Savitzky Golay Median Filtered RSI in your trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Kalman For Loop [BackQuant]Kalman For Loop
Introducing BackQuant's Kalman For Loop (Kalman FL) — a highly adaptive trading indicator that uses a Kalman filter to smooth price data and generate actionable long and short signals. This advanced indicator is designed to help traders identify trends, filter out market noise, and optimize their entry and exit points with precision. Let’s explore how this indicator works, its key features, and how it can enhance your trading strategies.
Core Concept: Kalman Filter
The Kalman Filter is a mathematical algorithm used to estimate the state of a system by filtering noisy data. It is widely used in areas such as control systems, signal processing, and time-series analysis. In the context of trading, a Kalman filter can be applied to price data to smooth out short-term fluctuations, providing a clearer view of the underlying trend.
Unlike moving averages, which use fixed weights to smooth data, the Kalman Filter adjusts its estimate dynamically based on the relationship between the process noise and the measurement noise. This makes the filter more adaptive to changing market conditions, providing more accurate trend detection without the lag associated with traditional smoothing techniques.
Please see the original Kalman Price Filter
In this script, the Kalman For Loop applies the Kalman filter to the price source (default set to the closing price) to generate a smoothed price series, which is then used to calculate signals.
Adaptive Smoothing with Process and Measurement Noise
Two key parameters govern the behavior of the Kalman filter:
Process Noise: This controls the extent to which the model allows for uncertainty in price changes. A lower process noise value will make the filter smoother but slower to react to price changes, while a higher value makes it more sensitive to recent price fluctuations.
Measurement Noise: This represents the uncertainty or "noise" in the observed price data. A higher measurement noise value gives the filter more leeway to ignore short-term fluctuations, focusing on the broader trend. Lowering the measurement noise makes the filter more responsive to minor changes in price.
These settings allow traders to fine-tune the Kalman filter’s sensitivity, adjusting it to match their preferred trading style or market conditions.
For-Loop Scoring Mechanism
The Kalman FL further enhances the effectiveness of the Kalman filter by using a for-loop scoring system. This mechanism evaluates the smoothed price over a range of periods (defined by the Calculation Start and Calculation End inputs), assigning a score based on whether the current filtered price is higher or lower than previous values.
Long Signals: A long signal is generated when the for-loop score surpasses the Long Threshold (default set at 20), indicating a strong upward trend. This helps traders identify potential buying opportunities.
Short Signals: A short signal is triggered when the score crosses below the Short Threshold (default set at -10), signaling a potential downtrend or selling opportunity.
These signals are plotted on the chart, giving traders a clear visual indication of when to enter long or short positions.
Customization and Visualization Options
The Kalman For Loop comes with a range of customization options to give traders full control over how the indicator operates and is displayed on the chart:
Kalman Price Source: Choose the price data used for the Kalman filter (default is the closing price), allowing you to apply the filter to other price points like open, high, or low.
Filter Order: Set the order of the Kalman filter (default is 5), controlling how far back the filter looks in its calculations.
Process and Measurement Noise: Fine-tune the sensitivity of the Kalman filter by adjusting these noise parameters.
Signal Line Width and Colors: Customize the appearance of the signal line and the colors used to indicate long and short conditions.
Threshold Lines: Toggle the display of the long and short threshold lines on the chart for better visual clarity.
The indicator also includes the option to color the candlesticks based on the current trend direction, allowing traders to quickly identify changes in market sentiment. In addition, a background color feature further highlights the overall trend by shading the background in green for long signals and red for short signals.
Trading Applications
The Kalman For Loop is a versatile tool that can be adapted to a variety of trading strategies and markets. Some of the primary use cases include:
Trend Following: The adaptive nature of the Kalman filter helps traders identify the start of new trends with greater precision. The for-loop scoring system quantifies the strength of the trend, making it easier to stay in trades for longer when the trend remains strong.
Mean Reversion: For traders looking to capitalize on short-term reversals, the Kalman filter's ability to smooth price data makes it easier to spot when price has deviated too far from its expected path, potentially signaling a reversal.
Noise Reduction: The Kalman filter excels at filtering out short-term price noise, allowing traders to focus on the broader market movements without being distracted by minor fluctuations.
Risk Management: By providing clear long and short signals based on filtered price data, the Kalman FL helps traders manage risk by entering positions only when the trend is well-defined, reducing the chances of false signals.
Alerts and Automation
To further assist traders, the Kalman For Loop includes built-in alert conditions that notify you when a long or short signal is generated. These alerts can be configured to trigger notifications, helping you stay on top of market movements without constantly monitoring the chart.
Final Thoughts
The Kalman For Loop is a powerful and adaptive trading indicator that combines the precision of the Kalman filter with a for-loop scoring mechanism to generate reliable long and short signals. Whether you’re a trend follower or a reversal trader, this indicator offers the flexibility and accuracy needed to navigate complex markets with confidence.
As always, it’s important to backtest the indicator and adjust the settings to fit your trading style and market conditions. No indicator is perfect, and the Kalman FL should be used alongside other tools and sound risk management practices for the best results.
SMI Ergodic Indicator/Oscillator▮ Introduction
The Stochastic Momentum Index Ergodic Indicator (SMII) is a technical analysis tool designed to predict trend reversals in the price of an asset.
It functions as a momentum oscillator, measuring the ratio of the smoothed price change to the smoothed absolute price change over a given number of previous periods.
The Ergodic SMI is based on the True Strength Index (TSI) and integrates a signal line, which is an exponential moving average (EMA) of the SMI indicator itself.
It provides a clearer picture of market trends than the traditional stochastic oscillator by incorporating the concept of "ergodicity", which helps remove market noise.
On ther other hand, the Stochastic Momentum Index Ergodic Oscillator (SMIO) is a histogram that measures the difference between TSI and it's signal line.
By default, in TradingView both SMII and SMIO are provided independently.
Here in this script these two indicators are combined, providing a more comprehensive view of price direction and market strength.
▮ Motivation: why another indicator?
The intrinsic value of this indicator lies in the fact that it allows fine adjustments in both calculation parameters, data source and visualization, features that are not present in the standard indicators or similar.
Also, trend lines breakouts and divergences detector were added.
▮ What to look for
When using the indicator, there are a few things to look out for.
First, look at the SMI signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMI and the price.
If price is rising but the SMI is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMI is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
Divergences can be considered in both indicator and/or histogram.
Examples:
▮ Notes
The indicator presented here offers both the "SMII" and the "SMIO", that is, the "Stochastic Momentum Index Ergodic Indicator" together with the "Stochastic Momentum Index Ergodic Oscillator" (histogram), as per the documentation described in reference links.
So it is important to highlight the differences in relation to my other indicator, Stochastic Momentum Index (SMI) Refurbished .
This last one is purely based on the **SMI**, which is implemented using smoothed ratio between the relative range and the high/low range.
Although they may seem the same in some situations, the calculation is actually different. The TSI tends to be more responsive at the expense of being noisier, while the SMI tends to be smoother. Which of these two indicators is best depends on the situation, the context, and the analyst's personal preference.
Please refer to reference links to more info.
▮ References
SMI documentation
SMII documentation
SMIO documentation
Stochastic RSI OHLC StrategyThe script titled "Stochastic RSI High Low Close Bars" is a versatile trading strategy implemented in Pine Script, designed for TradingView. Here's an overview of its features:
Description
This strategy leverages the Stochastic RSI to determine entry and exit signals in the market, focusing on high, low, and close values of the indicator. It incorporates various trading styles, stop-loss mechanisms, and multi-timeframe analysis to adapt to different market conditions.
Key Features
Stochastic RSI Analysis:
Uses the Stochastic RSI to identify potential entry points for long and short positions.
Tracks high, low, and close values for more granular analysis.
Multiple Trading Styles:
Supports diverse trading styles like Volume Color Swing, RSI Divergence, RSI Pullback, and more.
Allows switching between these styles to suit market dynamics.
Session-Based Trading:
Offers session control, limiting trades to specific hours (e.g., NY sessions).
Can close all positions at the end of the trading day.
Stop-Loss and Take-Profit Mechanisms:
Includes both static and dynamic stop-losses, with options for time-based stops, trailing stops, and momentum-based exits.
Customizable take-profit levels ensure efficient trade management.
Volume Analysis:
Integrates volume indicators to add a bias for trade entries and exits, enhancing signal reliability.
Multi-Timeframe Integration:
Employs multi-timeframe RSI analysis, allowing the strategy to capture broader trends and optimize entries.
This script is designed to provide flexibility and adaptability, making it useful for different trading strategies and market conditions. It is suitable for traders looking to refine their entries and exits with a focus on the Stochastic RSI.
Fetch Z-scoreThis script is enspired by the creator of the Z-score probability indicator made by www.tradingview.com
I took his calculation for the z-score and created my own strategy based on that z-score.
What is z-score? The Z-score represents how far the current price deviates from the moving average, measured in terms of standard deviations
What does this script do with the Z-score?
The script offers several customizable options, including displaying buy and sell signals based on Z-score thresholds and overlaying these signals directly on the chart or below/above the bars.
The idea is that when the Z-score exceeds a certain treshold, a count will start. The count will lead to a signal. For example: Say the Z-score dipped below -1. From there, the script will by default count whether the current Z-score is higher than the Z-score of the past 10 datapoints. If so, a buy signal will be printed on the chart. The idea is that the Z-score will creep up after a low, making sure you buy earyly in the new uptrend, making this a trend followiung system, with early trend detection.
You can choose whether you want the buy and sell signals on the seperate pane, or on the chart by toggeling a simple setting.
What are my favorite settings?
- Timeframe: weekly
- SMA Length: 75
- Z score buy treshold: -1.5
- Z score sell treshold: 3
- Lookback buy period: 20
- Lookback sell period: 20
Market Phases [OmegaTools]The Market Phases indicator utilizes the Detrended Price Oscillator (DPO) to assess various asset classes, bonds, or stock sectors across different market phases. It offers users the ability to monitor and compare trends in multiple markets through a normalized DPO approach, providing insights into relative overbought or oversold conditions. The indicator supports three distinct modes: "Asset Classes," "Bonds," and "Stock Sectors," allowing flexibility in market analysis based on user preference.
Key Features:
Detrended Price Oscillator (DPO) Calculation: The DPO is computed to remove longer-term trends and focus on shorter-term cyclical behavior. The indicator applies normalization using linear interpolation to smooth out the values for better comparison across different markets.
Three Analysis Modes:
Asset Classes: Compares the DPO for major asset classes, including stocks (S&P 500), bonds (US 10-Year), commodities (Gold), and the US Dollar Index (DXY).
Bonds: Analyzes the DPO across various bond categories such as investment-grade bonds (LQD), high-yield bonds (HYG), emerging market bonds (EMB), and corporate bonds.
Stock Sectors: Provides insight into key stock sectors, including Technology (XLK), Utilities (XLU), Financials (XLF), and Healthcare (XLV).
Real-Time Plotting:
The indicator plots the DPO values of the selected assets, bonds, or sectors on the chart. It provides a visual representation of the market phases, helping to identify potential market reversals or trends. Each plot is color-coded for clarity:
Blue: Asset/Sector 1
Red: Asset/Sector 2
Green: Asset/Sector 3
Orange: Asset/Sector 4
Table Display:
A dynamic table is displayed on the chart, showing the DPO values for the selected mode's assets or sectors. This allows quick comparison and evaluation of market trends.
Inputs:
DPO Length: Defines the lookback period for DPO calculation, adjustable between 10 and 500.
Normalization Length: Sets the length for normalizing the DPO values, with options ranging from 100 to 2000.
Mode: Choose between "Asset Classes," "Bonds," or "Stock Sectors" for tailored market analysis.
This tool is perfect for traders seeking to identify cyclical market phases, compare different asset classes, or monitor sector rotation dynamics. Use it to align your trading strategies with broader market trends and uncover potential trading opportunities across multiple markets.
DYNAMIC USD MOMENTUM INDICATOR
Hello traders,
Welcome to my script, an indicator helping you to quickly see the performance of USD in constant daily comparison to other currencies.
This script requests price data from other charts but displays overbought and oversold labels on any selected chart currency pair.
See attached images to spot high probability reversal days when USD is in extremes against multiple other currencies. The output labels represent the currency traded against USD and reaching overbought and oversold zoned on a dynamic RSI scale.
Suggested pairs with higher co relation to stronger or weaker dollar:
AUD/USD, CAD/USD, EUR/USD, GBP/USD, NZD/USD
CHF/USD and JPY/USD require more in depth analysis of individual performance of JPY AND CHF
Distance between EMA 50-100/100-150This script calculates and plots the percentage difference between the 50-period, 100-period, and 150-period Exponential Moving Averages (EMA) on a TradingView chart. The aim is to provide a clear visual representation of the market's momentum by analyzing the distance between key EMAs over time.
Key features of this script:
1. EMA Calculation : The script computes the EMA values for 50, 100, and 150 periods and calculates the percentage difference between EMA 50 and 100, and between EMA 100 and 150.
2. Custom Threshold : Users can adjust a threshold percentage to highlight significant divergences between the EMAs. A default threshold is set to 0.1%.
3. Visual Alerts : When the percentage difference exceeds the threshold, a visual marker appears on the chart:
Green Circles for bullish momentum (positive divergence),
Red Circles for bearish momentum (negative divergence),
Diamonds to indicate the first occurrence of new bullish or bearish signals, allowing users to catch fresh market trends.
4. Dynamic Plotting : The script plots two lines representing the percentage difference for each EMA pair, offering a quick and intuitive way to monitor trends.
Ideal for traders looking to gauge market direction using the relationship between multiple EMAs, this script simplifies analysis by focusing on key moving average interactions.
Normalized Linear Regression (LSMA) OscillatorNormalized Linear Regression (LSMA) Oscillator
By Nathan Farmer
The Normalized LSMA Oscillator is a trend-following indicator that enhances the classic Linear Regression (LSMA) by applying a range of normalization techniques. This indicator allows traders to smooth out and normalize LSMA signals for better trend detection and dynamic market adaptation.
Key Features:
Configurable Normalization Methods:
This indicator offers several normalization techniques, such as Z-Score, Min-Max, Mean Normalization, Robust Scaler, Logistic Function, and Quantile Transformation. Each method helps in refining LSMA outputs to improve clarity in both trending and ranging market conditions.
Smoothing Options:
Smoothing can be applied after normalization, helping to reduce noise in the signals, thus making trend-following strategies that use this indicator more effective.
Recommended Settings:
Logistic Function Normalization: Recommended length of around 12, based on my preferred signal frequency.
Z-Score Normalization: Medium period (close to the default of 50), based on my preferred signal frequency.
Min-Max Normalization: Medium period, based on my preferred signal frequency.
Mean Normalization: Medium period, based on my preferred signal frequency.
Robust Scaler: Medium period, based on my preferred signal frequency.
Quantile Transformation: Medium period, based on my preferred signal frequency.
Usage:
Designed primarily for trend-following strategies, this indicator adapts well to varying market conditions. Traders can experiment with the various normalization and smoothing settings to match the indicator to their specific needs and market preferences.
Recommendation before usage:
Always backtest the indicator for yourself with respect to how you intend to use it. Modify the parameters to suit your needs, over your preferred time frame, on your preferred asset. My preferences are for the assets I happened to be looking at when I made this indicator. Odds are, you're looking at something else, over a different time frame, in a different market environment than what my settings are tailored for.
RSI with Dynamic ColorsThe "RSI with Dynamic Colors" is a custom indicator built on top of the traditional Relative Strength Index (RSI), which helps traders identify overbought or oversold market conditions. This enhanced version includes added functionality like dynamic colors, highlighting specific conditions, and more customization options. Here's a breakdown of how this indicator works:
Indicator Components:
Relative Strength Index (RSI) Calculation:
The RSI is a momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100, helping traders determine if an asset is overbought or oversold.
In this version, the RSI is calculated with a configurable lookback period (default is 14) and applies smoothing to both upward and downward price changes using the Relative Moving Average (RMA).
Dynamic Coloring:
The indicator dynamically changes the color of the RSI line based on its value. Specific thresholds include:
Blue: When the RSI is at or above an extreme overbought level (≥ 85).
Red: When the RSI is in the overbought zone (≥ 70 but < 85).
Yellow: When the RSI is at or below the extreme oversold level (≤ 15).
Green: When the RSI is in the oversold zone (≤ 30 but > 15).
White: When the RSI is between the oversold and overbought zones.
Moving Average Options (MA):
The indicator allows the user to plot an optional moving average of the RSI for additional trend confirmation. Users can select from various types of moving averages, including Simple Moving Average (SMA), Exponential Moving Average (EMA), and others.
Bollinger Bands can be optionally applied around the RSI to visualize volatility.
Overbought and Oversold Highlights:
It provides visual highlights (green for overbought and red for oversold) in the background of the RSI plot, making it easier to identify potential reversal zones.
Divergence Detection (Optional):
The indicator can optionally display regular bullish or bearish divergence, which can signal potential trend reversals. Divergence occurs when price moves in the opposite direction of the RSI.
Bullish divergence is indicated when the price makes lower lows while the RSI makes higher lows.
Bearish divergence is shown when the price makes higher highs while the RSI makes lower highs.
Alerts:
Users can set up alerts for bullish or bearish divergence, making it easier to get notified when key conditions occur in the market.
Use Case:
This custom RSI indicator is designed for traders who want to combine the classic RSI functionality with enhanced visual aids, such as color coding for different RSI zones, customizable moving averages, and Bollinger Bands. It is particularly useful for identifying potential market tops and bottoms by highlighting overbought/oversold conditions and divergence signals.
In summary, this indicator not only retains the traditional RSI's power but also adds new layers of insight through color, moving averages, and divergence detection, helping traders make better-informed decisions.
Signals Pro [traderslog]The "Signals Pro" indicator is an advanced and versatile trading tool designed to help traders accurately identify key buy and sell signals using a combination of technical analysis factors such as candle patterns , RSI (Relative Strength Index) , and candle stability . It is highly customizable and offers a range of options that make it suitable for both short-term and long-term traders. By filtering market noise and providing actionable insights, this indicator enhances decision-making and helps traders capitalize on market movements.
At the core of the "Signals Pro" indicator is the concept of Candle Stability . The Candle Stability Index measures the ratio between a candle's body and its wicks, providing insight into the strength of the price movement during that period. A higher value indicates that the candle is more stable, meaning that the price has moved significantly without much retracement. This stability filter is crucial because it prevents the generation of signals during volatile or choppy market conditions where price direction is uncertain. Traders can adjust the Candle Stability Index from 0 to 1, allowing for precise control over how stable a candle must be for the indicator to generate a signal.
Another key feature is the use of RSI (Relative Strength Index) , a momentum oscillator that measures the speed and change of price movements. The RSI index parameter in the indicator can be customized to detect overbought or oversold conditions. When the RSI falls below the defined threshold, it signals that the market may be oversold , which can indicate a potential buying opportunity . Conversely, when the RSI exceeds a certain value, it suggests that the market is overbought , signaling a potential selling opportunity . This allows traders to time their trades more effectively by entering when market conditions are favorable and exiting before a potential reversal occurs.
The Candle Delta Length is another critical element of the "Signals Pro" indicator. This parameter measures how much the price has increased or decreased over a specific number of candles. By adjusting the Candle Delta Length , traders can define how many periods the indicator should analyze before generating a signal. A longer Candle Delta Length means the price has been trending in one direction for a longer period, providing more reliable signals. For instance, if the price has been steadily decreasing for five candles, this could signal a bullish reversal , triggering a buy signal .
To further enhance its accuracy, the "Signals Pro" indicator includes a unique feature that allows traders to disable repeating signals . This is particularly useful in situations where the market is moving sideways or during low volatility periods, where multiple signals may cluster close together, creating confusion. By enabling the disable repeating signals option, traders can prevent these repeated signals and focus on the most important and confirmed signals, ensuring cleaner charts and reducing the risk of overtrading.
A key technical aspect of the indicator is its ability to detect bullish and bearish engulfing patterns . The indicator looks for bullish engulfing patterns, which occur when a bullish candle fully engulfs the body of the previous bearish candle, signaling a potential bullish reversal . Conversely, bearish engulfing patterns occur when a bearish candle fully engulfs the previous bullish candle, indicating a bearish reversal . By incorporating these candle patterns with the Candle Stability Index and RSI levels , the indicator provides highly reliable signals based on price action and market sentiment.
Visual customization is another major advantage of the "Signals Pro" indicator. Traders can choose from several different label styles , such as text bubbles , triangles , or arrows to mark the buy and sell signals on the chart. This makes the signals stand out and easy to interpret at a glance. Furthermore, the color of these signals can be customized: green for buy signals and red for sell signals , along with options to adjust the text size and label styles for even more personalization. Traders can make the signals more or less prominent based on their preference, enhancing readability and workflow efficiency.
The indicator also includes a comprehensive alert system , ensuring traders never miss an opportunity. Alerts can be set for both buy and sell signals , and the system triggers in real-time when a valid signal is generated. This is especially useful for active traders who want to stay on top of the markets without constantly monitoring their screens. The alert system helps ensure that traders are notified of potential trading opportunities as soon as they arise, allowing them to act quickly in volatile markets.
From a practical standpoint, the "Signals Pro" indicator is designed to work seamlessly across multiple timeframes, making it suitable for scalpers, day traders, swing traders, and even long-term investors. Its flexibility allows it to adapt to different trading styles and time horizons, providing value for a wide range of market participants.
In summary, the Signals Pro indicator offers a robust and customizable solution for identifying buy and sell signals . By combining candle stability , RSI analysis , and engulfing patterns , the indicator provides traders with reliable signals to enter or exit trades. The ability to customize signal appearance, coupled with a real-time alert system , makes the "Signals Pro" indicator an invaluable tool for traders looking to improve their timing and decision-making. Whether you are looking to capture short-term price movements or want to time entries and exits in longer-term trends, this indicator offers the insights needed to navigate the markets with confidence.
Aroon Oscillator [BigBeluga]Aroon Oscillator with Mean Reversion & Trend Signals is a versatile tool that helps traders identify both trend direction and potential mean reversion points. The core Aroon Oscillator tracks the strength of a trend by measuring how long it has been since a high or low price occurred within a specified period. This oscillator provides trend-following signals (LONG/SHORT) along with mean reversion signals, giving traders both the ability to ride trends and anticipate reversals.
The unique feature of this indicator is the Mean Reversion Signals, marked with dots on the main chart, indicating potential points where the trend might reverse or retrace. In addition, trend-following signals (LONG and SHORT) are plotted directly on the chart, providing clear entry and exit points when a trend is beginning or ending.
🔵 IDEA
The Aroon Oscillator with Mean Reversion indicator provides a combined approach of trend analysis and mean reversion. The core idea is to track the health and momentum of trends, while also identifying when those trends might reverse or slow down. This dual approach allows traders to both follow the prevailing market direction and also capture mean reversion opportunities.
The oscillator is smoothed with John Ehlers' Zero Lag function , which helps reduce noise and improves signal clarity by removing lag without sacrificing the indicator's responsiveness.
The indicator uses color-coded signals and an easy-to-read oscillator to visually represent different types of signals on the chart. This makes it easy for traders to spot important changes in market trends and take action based on both the trend-following and mean reversion aspects of the indicator.
🔵 KEY FEATURES & USAGE
Trend Following Signals (LONG/SHORT):
In addition to mean reversion signals, the indicator also provides clear trend-following signals. LONG signals (green arrows) are plotted when the oscillator crosses above zero, indicating a potential uptrend. Conversely, SHORT signals (blue arrows) are plotted when the oscillator crosses below zero, signaling a potential downtrend.
Mean Reversion Signals:
This indicator features unique mean reversion signals, represented by dots on the main chart. These signals occur when the oscillator crosses over or under a smoother signal line, indicating that the current trend might be losing strength and a reversal or retracement is possible. Green dots represent a possible upward reversion, while blue dots signal a potential downward reversion.
Color-Coded Signals and Oscillator:
The Aroon Oscillator is color-coded to make it visually easier for traders to differentiate between trends and mean reversion signals. When the oscillator is above zero, the area is filled with green, and when it is below zero, the area is filled with blue. This visual representation helps traders quickly identify the current market condition at a glance.
🔵 CUSTOMIZATION
Aroon Length & Smoothing: Control the sensitivity of the Aroon Oscillator by adjusting the lookback period and smoothing settings, allowing traders to fine-tune the indicator to match different market conditions.
Mean Reversion Signals: Enable or disable mean reversion signals based on your trading preferences. Adjust the signal line length to control when these reversal signals are triggered.
Color Customization: Customize the colors for the oscillator and signals to match your chart’s color scheme for better visual clarity.
Chande Momentum Oscillator StrategyThe Chande Momentum Oscillator (CMO) Trading Strategy is based on the momentum oscillator developed by Tushar Chande in 1994. The CMO measures the momentum of a security by calculating the difference between the sum of recent gains and losses over a defined period. The indicator offers a means to identify overbought and oversold conditions, making it suitable for developing mean-reversion trading strategies (Chande, 1997).
Strategy Overview:
Calculation of the Chande Momentum Oscillator (CMO):
The CMO formula considers both positive and negative price changes over a defined period (commonly set to 9 days) and computes the net momentum as a percentage.
The formula is as follows:
CMO=100×(Sum of Gains−Sum of Losses)(Sum of Gains+Sum of Losses)
CMO=100×(Sum of Gains+Sum of Losses)(Sum of Gains−Sum of Losses)
This approach distinguishes the CMO from other oscillators like the RSI by using both price gains and losses in the numerator, providing a more symmetrical measurement of momentum (Chande, 1997).
Entry Condition:
The strategy opens a long position when the CMO value falls below -50, signaling an oversold condition where the price may revert to the mean. Research in mean-reversion, such as by Poterba and Summers (1988), supports this approach, highlighting that prices often revert after sharp movements due to overreaction in the markets.
Exit Conditions:
The strategy closes the long position when:
The CMO rises above 50, indicating that the price may have become overbought and may not provide further upside potential.
Alternatively, the position is closed 5 days after the buy signal is triggered, regardless of the CMO value, to ensure a timely exit even if the momentum signal does not reach the predefined level.
This exit strategy aligns with the concept of time-based exits, reducing the risk of prolonged exposure to adverse price movements (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages the well-known phenomenon of mean-reversion in financial markets. According to research by Jegadeesh and Titman (1993), prices tend to revert to their mean over short periods following strong movements, creating opportunities for traders to profit from temporary deviations.
The CMO captures this mean-reversion behavior by monitoring extreme price conditions. When the CMO reaches oversold levels (below -50), it signals potential buying opportunities, whereas crossing overbought levels (above 50) indicates conditions for selling.
Market Efficiency and Overreaction:
The strategy takes advantage of behavioral inefficiencies and overreactions, which are often the drivers behind sharp price movements (Shiller, 2003). By identifying these extreme conditions with the CMO, the strategy aims to capitalize on the market’s tendency to correct itself when price deviations become too large.
Optimization and Parameter Selection:
The 9-day period used for the CMO calculation is a widely accepted timeframe that balances responsiveness and noise reduction, making it suitable for capturing short-term price fluctuations. Studies in technical analysis suggest that oscillators optimized over such periods are effective in detecting reversals (Murphy, 1999).
Performance and Backtesting:
The strategy's effectiveness is confirmed through backtesting, which shows that using the CMO as a mean-reversion tool yields profitable opportunities. The use of time-based exits alongside momentum-based signals enhances the reliability of the strategy by ensuring that trades are closed even when the momentum signal alone does not materialize.
Conclusion:
The Chande Momentum Oscillator Trading Strategy combines the principles of momentum measurement and mean-reversion to identify and capitalize on short-term price fluctuations. By using a widely tested oscillator like the CMO and integrating a systematic exit approach, the strategy effectively addresses both entry and exit conditions, providing a robust method for trading in diverse market environments.
References:
Chande, T. S. (1997). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. John Wiley & Sons.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Ultimate Oscillator Trading StrategyThe Ultimate Oscillator Trading Strategy implemented in Pine Script™ is based on the Ultimate Oscillator (UO), a momentum indicator developed by Larry Williams in 1976. The UO is designed to measure price momentum over multiple timeframes, providing a more comprehensive view of market conditions by considering short-term, medium-term, and long-term trends simultaneously. This strategy applies the UO as a mean-reversion tool, seeking to capitalize on temporary deviations from the mean price level in the asset’s movement (Williams, 1976).
Strategy Overview:
Calculation of the Ultimate Oscillator (UO):
The UO combines price action over three different periods (short-term, medium-term, and long-term) to generate a weighted momentum measure. The default settings used in this strategy are:
Short-term: 6 periods (adjustable between 2 and 10).
Medium-term: 14 periods (adjustable between 6 and 14).
Long-term: 20 periods (adjustable between 10 and 20).
The UO is calculated as a weighted average of buying pressure and true range across these periods. The weights are designed to give more emphasis to short-term momentum, reflecting the short-term mean-reversion behavior observed in financial markets (Murphy, 1999).
Entry Conditions:
A long position is opened when the UO value falls below 30, indicating that the asset is potentially oversold. The value of 30 is a common threshold that suggests the price may have deviated significantly from its mean and could be due for a reversal, consistent with mean-reversion theory (Jegadeesh & Titman, 1993).
Exit Conditions:
The long position is closed when the current close price exceeds the previous day’s high. This rule captures the reversal and price recovery, providing a defined point to take profits.
The use of previous highs as exit points aligns with breakout and momentum strategies, as it indicates sufficient strength for a price recovery (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages two well-established phenomena in financial markets: momentum and mean-reversion. Momentum, identified in earlier studies like those by Jegadeesh and Titman (1993), describes the tendency of assets to continue in their direction of movement over short periods. Mean-reversion, as discussed by Poterba and Summers (1988), indicates that asset prices tend to revert to their mean over time after short-term deviations. This dual approach aims to buy assets when they are temporarily oversold and capitalize on their return to the mean.
Multi-timeframe Analysis:
The UO’s incorporation of multiple timeframes (short, medium, and long) provides a holistic view of momentum, unlike single-period oscillators such as the RSI. By combining data across different timeframes, the UO offers a more robust signal and reduces the risk of false entries often associated with single-period momentum indicators (Murphy, 1999).
Trading and Market Efficiency:
Studies in behavioral finance, such as those by Shiller (2003), show that short-term inefficiencies and behavioral biases can lead to overreactions in the market, resulting in price deviations. This strategy seeks to exploit these temporary inefficiencies, using the UO as a signal to identify potential entry points when the market sentiment may have overly pushed the price away from its average.
Strategy Performance:
Backtests of this strategy show promising results, with profit factors exceeding 2.5 when the default settings are optimized. These results are consistent with other studies on short-term trading strategies that capitalize on mean-reversion patterns (Jegadeesh & Titman, 1993). The use of a dynamic, multi-period indicator like the UO enhances the strategy’s adaptability, making it effective across different market conditions and timeframes.
Conclusion:
The Ultimate Oscillator Trading Strategy effectively combines momentum and mean-reversion principles to trade on temporary market inefficiencies. By utilizing multiple periods in its calculation, the UO provides a more reliable and comprehensive measure of momentum, reducing the likelihood of false signals and increasing the profitability of trades. This aligns with modern financial research, showing that strategies based on mean-reversion and multi-timeframe analysis can be effective in capturing short-term price movements.
References:
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1976). Ultimate Oscillator. Market research and technical trading analysis.
MTF RSI+CMO PROThis RSI+CMO script combines the Relative Strength Index (RSI) and Chande Momentum Oscillator (CMO), providing a powerful tool to help traders analyze price momentum and spot potential turning points in the market. Unlike using RSI alone, the CMO (especially with a 14-period length) moves faster and accentuates price pops and dips in the histogram, making price shifts more apparent.
Indicator Features:
➡️RSI and CMO Combined: This indicator allows traders to track both RSI and CMO values simultaneously, highlighting differences in their movement. RSI and CMO values are both plotted on the histogram, while CMO values are also drawn as a line moving through the histogram, giving a visual representation of their relationship. The often faster-moving CMO accentuates short-term price movements, helping traders spot subtle shifts in momentum that the RSI might smooth out.
➡️Multi-Time Frame Table: A real-time, multi-time frame table displays RSI and CMO values across various timeframes. This gives traders an overview of momentum across different intervals, making it easier to spot trends and divergences across short and long-term time frames.
➡️Momentum Chart Label: A chart label compares the current RSI and CMO values with values from 1 and 2 bars back, providing an additional metric to gauge momentum. This feature allows traders to easily see if momentum is increasing or decreasing in real-time.
➡️RSI/CMO Bullish and Bearish Signals: Colored arrow plot shapes (above the histogram) indicate when RSI and CMO values are signaling bullish or bearish conditions. For example, green arrows appear when RSI is above 65, while purple arrows show when RSI is below 30 and CMO is below -40, indicating strong bearish momentum.
➡️Divergences in Histogram: The histogram can make it easier for traders to spot divergences between price and momentum. For instance, if the price is making new highs but the RSI or CMO is not, a bearish divergence may be forming. Similarly, bullish divergences can be spotted when prices are making lower lows while RSI or CMO is rising.
➡️Alert System: Alerts are built into the indicator and will trigger when specific conditions are met, allowing traders to stay informed of potential entry or exit points based on RSI and CMO levels without constantly monitoring the chart. These are set manually. Look for the 3 dots in the indicator name.
How Traders Can Use the Indicator:
💥Identifying Momentum Shifts: The RSI+CMO combination is ideal for spotting momentum shifts in the market. Traders can monitor the histogram and the CMO line to determine if the market is gaining or losing strength.
💥Confirming Trade Entries/Exits: Use the real-time RSI and CMO values across multiple time frames to confirm trades. For instance, if the 1-hour RSI is above 70 but the 1-minute RSI is turning down, it could indicate short-term overbought conditions, signaling a potential exit or reversal.
💥Spotting Divergences: Divergences are critical for predicting potential reversals. The histogram can be used to spot divergences when RSI and CMO values deviate from price action, offering an early signal of market exhaustion.
💥Tracking Multi-Time Frame Trends: The multi-time frame table provides insight into the market’s overall trend across several timeframes, helping traders ensure their decisions align with both short and long-term trends.
RSI vs. CMO: Why Use Both?
While both RSI and CMO measure momentum, the CMO often moves faster with a value of 14 for example, reacting to price changes more quickly. This makes it particularly effective for detecting sharp price movements, while RSI helps smooth out price action. By using both, traders get a clearer picture of the market's momentum, particularly during volatile periods.
Confluence and Price Fluidity:
One of the powerful ways to enhance the effectiveness of this indicator is by using it in conjunction with other technical analysis tools to create confluence. Confluence occurs when multiple indicators or price action signals align, providing stronger confirmation for a trade decision. For example:
🎯Support and Resistance Levels: Traders can use RSI+CMO in combination with key support and resistance zones. If the price is nearing a support level and RSI+CMO values start to signal a bullish reversal, this alignment strengthens the case for entering a long position.
🎯Moving Averages: When the RSI+CMO signals a potential trend reversal and this is confirmed by a crossover in moving averages (such as a 50-day and 200-day moving average), traders gain additional confidence in the trade direction.
🎯Momentum Indicators: Traders can also look for momentum indicators like the MACD to confirm the strength of a trend or potential reversal. For instance, if the RSI+CMO values start to decrease rapidly while both the RSI+CMO also shows overbought conditions, this could provide stronger confirmation to exit a long trade or enter a short position.
🎯Candlestick Patterns: Price fluidity can be monitored using candlestick formations. For example, a bearish engulfing pattern with decreasing RSI+CMo values offers confluence, adding confidence to the signal to close or short the trade.
By combining the MTF RSI+CMO PRO with other tools, traders ensure that they are not relying on a single indicator. This layered approach can reduce the likelihood of false signals and improve overall trading accuracy.
Ping Pong Bot StrategyOverview:
The Ping Pong Bot Strategy is designed for traders who focus on scalping and short-term opportunities using support and resistance levels. This strategy identifies potential buy entries when the price reaches a key support area and shows bullish momentum (a green bar). It aims to capitalize on small price movements with predefined risk management and take profit levels, making it suitable for active traders looking to maximize quick trades in trending or ranging markets.
How It Works:
Support & Resistance Calculation:
The strategy dynamically identifies support and resistance levels using the lowest and highest price points over a user-defined period. These levels help pinpoint potential price reversal areas, guiding traders on where to enter or exit trades.
Buy Entry Criteria:
A buy signal is triggered when the closing price is at or below the support level, and the bar is green (i.e., the closing price is higher than the opening price). This ensures that entries are made when prices show signs of upward momentum after hitting support.
Risk Management:
For each trade, a stop loss is calculated based on a user-defined risk percentage, helping to protect against significant drawdowns. Additionally, a take profit level is set at a ratio relative to the risk, ensuring a disciplined approach to exit points.
0.5% Take Profit Target:
The strategy also includes a 0.5% quick take profit target, indicated by an orange arrow when reached. This feature helps traders lock in small gains rapidly, making it ideal for volatile market conditions.
Customizable Inputs:
Length: Adjusts the period for calculating support and resistance levels.
Risk-Reward Ratio: Allows traders to set the desired risk-to-reward ratio for each trade.
Risk Percentage: Defines the risk tolerance for stop loss calculations.
Take Profit Target: Enables the customization of the quick take profit target.
Ideal For:
Traders who prefer an active trading style and want to leverage support and resistance levels for precise entries and exits. This strategy is particularly useful in markets that experience frequent price bounces between support and resistance, allowing traders to "ping pong" between these levels for profitable trades.
Note:
This strategy is developed mainly for the 5-minute chart and has not been tested on longer time frames. Users should perform their own testing and adjustments if using it on different time frames.
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.
[3Commas] Signal BuilderSignal Builder is a tool designed to help traders create custom buy and sell signals by combining multiple technical indicators. Its flexibility allows traders to set conditions based on their specific strategy, whether they’re into scalping, swing trading, or long-term investing. Additionally, its integration with 3Commas bots makes it a powerful choice for those looking to automate their trades, though it’s also ideal for traders who prefer receiving alerts and making manual decisions.
🔵 How does Signal Builder work?
Signal Builder allows users to define custom conditions using popular technical indicators, which, when met, generate clear buy or sell signals. These signals can be used to trigger TradingView alerts, ensuring that you never miss a market opportunity. Additionally, all conditions are evaluated using "AND" logic, meaning signals are only activated when all user-defined conditions are met. This increases precision and helps avoid false signals.
🔵 Available indicators and recommended settings:
Signal Builder provides access to a wide range of technical indicators, each customizable to popular settings that maximize effectiveness:
RSI (Relative Strength Index): An oscillator that measures the relative strength of price over a specific period. Traders typically configure it with 14 periods, using levels of 30 (oversold) and 70 (overbought) to identify potential reversals.
MACD (Moving Average Convergence Divergence): A key indicator tracking the crossover between two moving averages. Common settings include 12 and 26 periods for the moving averages, with a 9-period signal line to detect trend changes.
Ultimate Oscillator: Combines three different time frames to offer a comprehensive view of buying and selling pressure. Popular settings are 7, 14, and 28 periods.
Bollinger Bands %B: Provides insight into where the price is relative to its upper and lower bands. Standard settings include a 20-period moving average and a standard deviation of 2.
ADX (Average Directional Index): Measures the strength of a trend. Values above 25 typically indicate a strong trend, while values below suggest weak or sideways movement.
Stochastic Oscillator: A momentum indicator comparing the closing price to its range over a defined period. Popular configurations include 14 periods for %K and 3 for %D smoothing.
Parabolic SAR: Ideal for identifying trend reversals and entry/exit points. Commonly configured with a 0.02 step and a 0.2 maximum.
Money Flow Index (MFI): Similar to RSI but incorporates volume into the calculation. Standard settings use 14 periods, with levels of 20 and 80 as oversold and overbought thresholds.
Commodity Channel Index (CCI): Measures the deviation of price from its average. Traders often use a 20-period setting with levels of +100 and -100 to identify extreme overbought or oversold conditions.
Heikin Ashi Candles: These candles smooth out price fluctuations to show clearer trends. Commonly used in trend-following strategies to filter market noise.
🔵 How to use Signal Builder:
Configure indicators: Select the indicators that best fit your strategy and adjust their settings as needed. You can combine multiple indicators to define precise entry and exit conditions.
Define custom signals: Create buy or sell conditions that trigger when your selected indicators meet the criteria you’ve set. For example, configure a buy signal when RSI crosses above 30 and MACD confirms with a bullish crossover.
TradingView alerts: Set up alerts in TradingView to receive real-time notifications when the conditions you’ve defined are met, allowing you to react quickly to market opportunities without constantly monitoring charts.
Monitor with the panel: Signal Builder includes a visual panel that shows active conditions for each indicator in real time, helping you keep track of signals without manually checking each indicator.
🔵 3Commas integration:
In addition to being a valuable tool for any trader, Signal Builder is optimized to work seamlessly with 3Commas bots through Webhooks. This allows you to automate your trades based on the signals you’ve configured, ensuring that no opportunity is missed when your defined conditions are met. If you prefer automation, Signal Builder can send buy or sell signals to your 3Commas bots, enhancing your trading process and helping you manage multiple trades more efficiently.
🔵 Example of use:
Imagine you trade in volatile markets and want to trigger a sell signal when:
Stochastic Oscillator indicates overbought conditions with the %K value crossing below 80.
Bollinger Bands %B shows the price has surpassed the upper band, suggesting a potential reversal.
ADX is below 20, indicating that the trend is weak and could be about to change.
With Signal Builder , you can configure these conditions to trigger a sell signal only when all are met simultaneously. Then, you can set up a TradingView alert to notify you as soon as the signal is activated, giving you the opportunity to react quickly and adjust your strategy accordingly.
👨🏻💻💭 If this tool helps your trading strategy, don’t forget to give it a boost! Feel free to share in the comments how you're using it or if you have any questions.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Williams %R StrategyThe Williams %R Strategy implemented in Pine Script™ is a trading system based on the Williams %R momentum oscillator. The Williams %R indicator, developed by Larry Williams in 1973, is designed to identify overbought and oversold conditions in a market, helping traders time their entries and exits effectively (Williams, 1979). This particular strategy aims to capitalize on short-term price reversals in the S&P 500 (SPY) by identifying extreme values in the Williams %R indicator and using them as trading signals.
Strategy Rules:
Entry Signal:
A long position is entered when the Williams %R value falls below -90, indicating an oversold condition. This threshold suggests that the market may be near a short-term bottom, and prices are likely to reverse or rebound in the short term (Murphy, 1999).
Exit Signal:
The long position is exited when:
The current close price is higher than the previous day’s high, or
The Williams %R indicator rises above -30, indicating that the market is no longer oversold and may be approaching an overbought condition (Wilder, 1978).
Technical Analysis and Rationale:
The Williams %R is a momentum oscillator that measures the level of the close relative to the high-low range over a specific period, providing insight into whether an asset is trading near its highs or lows. The indicator values range from -100 (most oversold) to 0 (most overbought). When the value falls below -90, it indicates an oversold condition where a reversal is likely (Achelis, 2000). This strategy uses this oversold threshold as a signal to initiate long positions, betting on mean reversion—an established principle in financial markets where prices tend to revert to their historical averages (Jegadeesh & Titman, 1993).
Optimization and Performance:
The strategy allows for an adjustable lookback period (between 2 and 25 days) to determine the range used in the Williams %R calculation. Empirical tests show that shorter lookback periods (e.g., 2 days) yield the most favorable outcomes, with profit factors exceeding 2. This finding aligns with studies suggesting that shorter timeframes can effectively capture short-term momentum reversals (Fama, 1970; Jegadeesh & Titman, 1993).
Scientific Context:
Mean Reversion Theory: The strategy’s core relies on mean reversion, which suggests that prices fluctuate around a mean or average value. Research shows that such strategies, particularly those using oscillators like Williams %R, can exploit these temporary deviations (Poterba & Summers, 1988).
Behavioral Finance: The overbought and oversold conditions identified by Williams %R align with psychological factors influencing trading behavior, such as herding and panic selling, which often create opportunities for price reversals (Shiller, 2003).
Conclusion:
This Williams %R-based strategy utilizes a well-established momentum oscillator to time entries and exits in the S&P 500. By targeting extreme oversold conditions and exiting when these conditions revert or exceed historical ranges, the strategy aims to capture short-term gains. Scientific evidence supports the effectiveness of short-term mean reversion strategies, particularly when using indicators sensitive to momentum shifts.
References:
Achelis, S. B. (2000). Technical Analysis from A to Z. McGraw Hill.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Williams, L. (1979). How I Made One Million Dollars… Last Year… Trading Commodities. Windsor Books.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
This explanation provides a scientific and evidence-based perspective on the Williams %R trading strategy, aligning it with fundamental principles in technical analysis and behavioral finance.
