RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
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What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
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Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
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Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
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TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
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Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
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Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
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Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
在腳本中搜尋"Relative"
SwiftEdge NW EnvelopeSwiftEdge NW Envelope
Overview
The SwiftEdge NW Envelope is a visually striking technical indicator designed for traders seeking to identify high-probability buy and sell opportunities in volatile markets. By combining the Relative Strength Index (RSI), Average True Range (ATR), and Nadaraya-Watson Envelope, this indicator provides a unique blend of momentum, volatility, and non-linear trend analysis. Its futuristic, AI-inspired aesthetic—featuring neon gradients and dynamic colors—enhances chart readability while delivering actionable trading signals.
What It Does
The SwiftEdge NW Envelope generates buy and sell signals based on price interactions with dynamically calculated support and resistance bands, confirmed by RSI conditions. The indicator:
Plots a Nadaraya-Watson Envelope to identify smooth, non-linear price trends and dynamic support/resistance zones.
Uses ATR to scale the envelope’s bands, adapting to market volatility.
Employs RSI to confirm overbought/oversold conditions, ensuring signals align with momentum.
Visualizes signals with neon-colored markers, background zones, and labels for intuitive decision-making.
How It Works
The indicator integrates three key components:
Nadaraya-Watson Envelope:
A kernel-based regression technique that smooths price data to create a central trend line (mean) and dynamic upper/lower bands.
Unlike traditional moving averages, it provides a non-linear, adaptive view of price trends, making it ideal for capturing complex market movements.
The band width is determined by ATR, ensuring responsiveness to volatility.
Average True Range (ATR):
Measures market volatility to scale the envelope’s bands.
A multiplier (default: 0.5) adjusts the sensitivity of the bands, allowing traders to fine-tune the indicator for different assets or market conditions.
Relative Strength Index (RSI):
A momentum oscillator with a shortened period (default: 5) for increased sensitivity.
Confirms buy signals when RSI is oversold (default: <30) and sell signals when RSI is overbought (default: >70).
Signal Logic
Buy Signal: Triggered when the price crosses above the lower band of the Nadaraya-Watson Envelope and RSI is below the oversold threshold. Marked by a green circle and a "BUY" label below the candle.
Sell Signal: Triggered when the price crosses below the upper band and RSI is above the overbought threshold. Marked by a magenta circle and a "SELL" label above the candle.
Background Zones: Green (buy) or red (sell) translucent zones highlight signal areas for quick recognition.
Visual Features
Dynamic Colors: The central trend line shifts between cyan (uptrend), purple (downtrend), or gray (neutral) based on price position relative to the mean.
Neon Gradient Fill: A translucent blue fill between the upper (green) and lower (red) bands creates a glowing, futuristic effect.
Modern Signal Markers: Small, vibrant circles (green for buy, magenta for sell) and clear labels enhance visual clarity.
Why This Combination?
The SwiftEdge NW Envelope combines RSI, ATR, and Nadaraya-Watson Envelope to create a robust trading tool:
RSI provides momentum confirmation, filtering out false signals in choppy markets.
ATR ensures the envelope adapts to changing volatility, making it suitable for both trending and ranging markets.
Nadaraya-Watson Envelope offers a sophisticated, non-linear alternative to traditional bands (e.g., Bollinger Bands), capturing subtle price dynamics. Together, these components deliver a balanced approach to trend-following and mean-reversion strategies, with RSI acting as a gatekeeper to improve signal reliability.
Customize Settings:
RSI Period (5): Adjust for more/less sensitivity to momentum.
RSI Overbought/Oversold (70/30): Modify thresholds to tighten or loosen signal conditions.
ATR Period (14) and Multiplier (0.5): Tune volatility sensitivity.
NW Length (25), Bandwidth (8.0), Multiplier (3.0): Adjust the smoothness and width of the envelope.
Interpret Signals:
Buy: Look for green circles and "BUY" labels when price crosses above the lower band, confirmed by low RSI.
Sell: Look for magenta circles and "SELL" labels when price crosses below the upper band, confirmed by high RSI.
Use background zones to quickly spot active signal areas.
Combine with Other Tools:
Pair with support/resistance levels or volume analysis for additional confirmation.
Test signals on a demo account before live trading.
Originality
The SwiftEdge NW Envelope stands out due to:
Its innovative use of Nadaraya-Watson regression, a less common but powerful tool for non-linear trend analysis.
A unique visual design with neon gradients and dynamic colors, inspired by AI and futuristic interfaces, making it both functional and visually engaging.
A streamlined signal system that balances momentum (RSI), volatility (ATR), and trend (Nadaraya-Watson), reducing noise and enhancing trade precision.
Notes
Best suited for volatile markets (e.g., forex, crypto, stocks) where price swings create clear envelope breakouts.
Adjust input parameters to match your trading style (e.g., shorter RSI period for scalping, wider bands for swing trading).
Always backtest and validate signals in your specific market and timeframe before trading.
Max The Minner: RSI Bands with Min/Max [by Oberlunar]This Pine Script, titled "Max The Minner: RSI Bands with Min/Max " is a technical indicator designed to visualize RSI-based dynamic bands with local minimum and maximum levels on a chosen timeframe. The script incorporates user-configurable parameters for RSI thresholds, resolution, and color settings, providing traders with a highly customizable tool for analyzing price behavior in relation to overbought and oversold conditions.
Core Functionality
The script begins by calculating the RSI (Relative Strength Index) using user-defined inputs for overbought and oversold levels, the RSI length, and the resolution (default set to daily). The RSI is computed through an exponential moving average (EMA) approach that smooths the upward and downward price movements, creating adaptive upper (ub) and lower (lb) bands based on the overbought and oversold thresholds.
These bands are then dynamically adjusted based on the current price (src) and the EMA calculations. The upper band (ub) represents a potential resistance zone aligned with the RSI overbought level, while the lower band (lb) represents a support zone aligned with the RSI oversold level. The script employs additional calculations to ensure the adaptive nature of these bands, depending on whether the RSI is pushing higher or lower relative to its thresholds.
Local Minima and Maxima
A key feature of the indicator is its ability to track and update local minima and maxima based on the chosen timeframe. The script uses a buffer system that refreshes these levels every three bars to smooth out noise and avoid excessive sensitivity to short-term fluctuations. These local extrema (localMin and localMax) are retrieved from the lower and upper prices of the selected timeframe and act as dynamic benchmarks for evaluating the RSI bands.
Conditional Logic
The script includes conditional logic to determine when the RSI bands intersect with or approach the local maxima or minima. For example:
The upper band (ub) is plotted only if it is below the local maximum, suggesting that price may encounter resistance.
Similarly, the lower band (lb) is plotted only if it is above the local minimum, indicating potential support.
This logic ensures that the bands are contextually relevant to the prevailing market structure, rather than being static overlays.
Visualization
The RSI bands and local extrema are plotted on the chart using color-coded lines, with transparency adjustable through user inputs. The upper band and local maximum are linked with a fill area, visually representing the resistance zone. Similarly, the lower band and local minimum are filled to highlight the support zone. These fills provide a clear depiction of price boundaries, making it easier for traders to spot key levels.
Additionally, the script marks breakout conditions. If the price exceeds the local maximum, a label is plotted at the breakout point with a distinctive style and color. Similarly, a breakout below the local minimum is labeled, providing a visual cue for significant price movements.
Customization
The script offers extensive customization options for both functionality and appearance:
Users can define the overbought and oversold levels for RSI, along with the RSI length and the resolution (timeframe).
Colors for the upper and lower bands, along with transparency (alpha) levels, can be adjusted, allowing for seamless integration with different chart styles.
The periodicity of the local minima and maxima updates is hardcoded to three bars but could be further parameterized for greater flexibility.
This indicator is particularly useful for traders who rely on RSI-based strategies and need a dynamic representation of overbought and oversold conditions in conjunction with local price extremes. By combining RSI bands with the context provided by local minima and maxima, it allows traders to:
Identify potential support and resistance levels.
Visualize price behavior relative to RSI thresholds.
Spot breakout opportunities when price exceeds predefined levels.
Daksh RSI POINT to ShootHere are the key points and features of the Pine Script provided:
### 1. **Indicator Settings**:
- The indicator is named **"POINT and Shoot"** and is set for non-overlay (`overlay=false`) on the chart.
- `max_bars_back=4000` is defined, indicating the maximum number of bars that the script can reference.
### 2. **Input Parameters**:
- `Src` (Source): The price source, default is `close`.
- `rsilen` (RSI Length): The length for calculating RSI, default is 20.
- `linestylei`: Style for the trend lines (`Solid` or `Dashed`).
- `linewidth`: Width of the plotted lines, between 1 and 4.
- `showbroken`: Option to show broken trend lines.
- `extendlines`: Option to extend trend lines.
- `showpivot`: Show pivot points (highs and lows).
- `showema`: Show a weighted moving average (WMA) line.
- `len`: Length for calculating WMA, default is 9.
### 3. **RSI Calculation**:
- Calculates a custom RSI value using relative moving averages (`ta.rma`), and optionally uses On-Balance Volume (`ta.obv`) if `indi` is set differently.
- Plots RSI values as a green or red line depending on its position relative to the WMA.
### 4. **Pivot Points**:
- Utilizes the `ta.pivothigh` and `ta.pivotlow` functions to detect pivot highs and lows over the defined period.
- Stores up to 10 recent pivot points for highs and lows.
### 5. **Trend Line Drawing**:
- Lines are drawn based on pivot highs and lows.
- Calculates potential trend lines using linear interpolation and validates them by checking if subsequent bars break or respect the trend.
- If the trend is broken, and `showbroken` is enabled, it draws dotted lines to represent these broken trends.
### 6. **Line Management**:
- Initializes multiple lines (`l1` to `l20` and `t1` to `t20`) and uses these lines for drawing uptrend and downtrend lines.
- The maximum number of lines is set to 20 for uptrends and 20 for downtrends, due to a limit on the total number of lines that can be displayed on the chart.
### 7. **Line Style and Color**:
- Defines different colors for uptrend lines (`ulcolor = color.red`) and downtrend lines (`dlcolor = color.blue`).
- Line styles are determined by user input (`linestyle`) and use either solid or dashed patterns.
- Broken lines use a dotted style to indicate invalidated trends.
### 8. **Pivot Point Plotting**:
- Plots labels "H" and "L" for pivot highs and lows, respectively, to visually indicate turning points on the chart.
### 9. **Utility Functions**:
- Uses helper functions to get the values and positions of the last 10 pivot points, such as `getloval`, `getlopos`, `gethival`, and `gethipos`.
- The script uses custom logic for line placement based on whether the pivots are lower lows or higher highs, with lines adjusted dynamically based on price movement.
### 10. **Plotting and Visuals**:
- The main RSI line is plotted using a color gradient based on its position relative to the WMA.
- Horizontal lines (`hline1` and `hline2`) are used for visual reference at RSI levels of 60 and 40.
- Filled regions between these horizontal lines provide visual cues for potential overbought or oversold zones.
These are the main highlights of the script, which focuses on trend detection, visualization of pivot points, and dynamic line plotting based on price action.
RSI K-Means Clustering [UAlgo]The "RSI K-Means Clustering " indicator is a technical analysis tool that combines the Relative Strength Index (RSI) with K-means clustering techniques. This approach aims to provide more nuanced insights into market conditions by categorizing RSI values into overbought, neutral, and oversold clusters.
The indicator adjusts these clusters dynamically based on historical RSI data, allowing for more adaptive and responsive thresholds compared to traditional fixed levels. By leveraging K-means clustering, the indicator identifies patterns in RSI behavior, which can help traders make more informed decisions regarding market trends and potential reversals.
🔶 Key Features
K-means Clustering: The indicator employs K-means clustering, an unsupervised machine learning technique, to dynamically determine overbought, neutral, and oversold levels based on historical RSI data.
User-Defined Inputs: You can customize various aspects of the indicator's behavior, including:
RSI Source: Select the data source used for RSI calculation (e.g., closing price).
RSI Length: Define the period length for RSI calculation.
Training Data Size: Specify the number of historical RSI values used for K-means clustering.
Number of K-means Iterations: Set the number of iterations performed by the K-means algorithm to refine cluster centers.
Overbought/Neutral/Oversold Levels: You can define initial values for these levels, which will be further optimized through K-means clustering.
Alerts: The indicator can generate alerts for various events, including:
Trend Crossovers: Alerts for when the RSI crosses above/below the neutral zone, signaling potential trend changes.
Overbought/Oversold: Alerts when the RSI reaches the dynamically determined overbought or oversold thresholds.
Reversals: Alerts for potential trend reversals based on RSI crossing above/below the calculated overbought/oversold levels.
RSI Classification: Alerts based on the current RSI classification (ranging, uptrend, downtrend).
🔶 Interpreting Indicator
Adjusted RSI Value: The primary plot represents the adjusted RSI value, calculated based on the relative position of the current RSI compared to dynamically adjusted overbought and oversold levels. This value provides an intuitive measure of the market's momentum. The final overbought, neutral, and oversold levels are determined by K-means clustering and are displayed as horizontal lines. These levels serve as dynamic support and resistance points, indicating potential reversal zones.
Classification Symbols : The "RSI K-Means Clustering " indicator uses specific symbols to classify the current market condition based on the position of the RSI value relative to dynamically determined clusters. These symbols provide a quick visual reference to help traders understand the prevailing market sentiment. Here's a detailed explanation of each classification symbol:
Ranging Classification ("R")
This symbol appears when the RSI value is closest to the neutral threshold compared to the overbought or oversold thresholds. It indicates a ranging market, where the price is moving sideways without a clear trend direction. In this state, neither buyers nor sellers are in control, suggesting a period of consolidation or indecision. This is often seen as a time to wait for a breakout or reversal signal before taking a position.
Up-Trend Classification ("↑")
The up-trend symbol, represented by an upward arrow, is displayed when the RSI value is closer to the overbought threshold than to the neutral or oversold thresholds. This classification suggests that the market is in a bullish phase, with buying pressure outweighing selling pressure. Traders may consider this as a signal to enter or hold long positions, as the price is likely to continue rising until the market reaches an overbought condition.
Down-Trend Classification ("↓")
The down-trend symbol, depicted by a downward arrow, appears when the RSI value is nearest to the oversold threshold. This indicates a bearish market condition, where selling pressure dominates. The market is likely experiencing a downward movement, and traders might view this as an opportunity to enter or hold short positions. This symbol serves as a warning of potential further declines, especially if the RSI continues to move toward the oversold level.
Bullish Reversal ("▲")
This signal occurs when the RSI value crosses above the oversold threshold. It indicates a potential shift from a downtrend to an uptrend, suggesting that the market may start to move higher. Traders might use this signal as an opportunity to enter long positions.
Bearish Reversal ("▼")
This signal appears when the RSI value crosses below the overbought threshold. It suggests a possible transition from an uptrend to a downtrend, indicating that the market may begin to decline. This signal can alert traders to consider entering short positions or taking profits on long positions.
These classification symbols are plotted near the adjusted RSI line, with their positions adjusted based on the standard deviation and a distance multiplier. This placement helps in visualizing the classification's strength and ensuring clarity in the indicator's presentation. By monitoring these symbols, traders can quickly assess the market's state and make more informed trading decisions.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
RSI, STOCHASTIC RSI AND MFI COMBOCombining the Relative Strength Index (RSI), Stochastic RSI (StochRSI), and Money Flow Index (MFI) can provide traders with a comprehensive approach to analyze market momentum, overbought/oversold conditions, and money flow. Each indicator offers unique insights, and their combination can help confirm trading signals and filter out false signals. Let's delve into each indicator and then discuss how they can be used together:
Relative Strength Index (RSI) 14: DA BLUE LINE
The RSI is a momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100 and is typically used to identify overbought (>70) and oversold (<30) conditions. A reading above 70 may indicate that an asset is overbought and could be due for a pullback, while a reading below 30 may suggest that an asset is oversold and could be due for a bounce.
Stochastic RSI (StochRSI) 14: DA RED LINE
The StochRSI is an oscillator that combines the features of both the Stochastic Oscillator and RSI. It measures the relative position of the RSI within its range over a specific period (e.g., 14 periods). Like the RSI, the StochRSI oscillates between 0 and 100 and is used to identify overbought and oversold conditions. Typically:
A StochRSI above 0.8 may suggest overbought conditions.
A StochRSI below 0.2 may indicate oversold conditions.
Money Flow Index (MFI) 14: DA PURPLE LINE
The MFI is a momentum oscillator that measures the inflow and outflow of money into an asset over a specific period (e.g., 14 periods). It oscillates between 0 and 100 and is used to identify overbought and oversold conditions based on both price and volume. Generally:
An MFI above 80 may indicate overbought conditions.
An MFI below 20 may suggest oversold conditions.
Combining RSI, StochRSI, and MFI:
When combining RSI, StochRSI, and MFI, traders can use the following approach to analyze the market:
Identify Overbought/Oversold Conditions:
Look for confluence between RSI, StochRSI, and MFI readings to identify overbought and oversold conditions.
For example, if RSI > 70, StochRSI > 0.8, and MFI > 80, it may suggest a strong overbought condition, potentially indicating a reversal or pullback.
Confirm Trend Strength:
Use the RSI, StochRSI, and MFI to confirm the strength of a trend.
A rising trend with RSI, StochRSI, and MFI above 50 may suggest strong bullish momentum, while a falling trend with readings below 50 may indicate strong bearish momentum.
Divergence Analysis:
Look for divergences between price and RSI, StochRSI, or MFI to identify potential trend reversals.
For example, if the price makes a higher high, but RSI, StochRSI, or MFI makes a lower high (bearish divergence), it may suggest weakening bullish momentum and potential downside.
Combining RSI, StochRSI, and MFI can offer traders a more holistic view of market momentum, overbought/oversold conditions, and money flow. Backtest it let me know your success.
Rate of Change RSIIndicator Name: Rate of Change RSI
Description:
The Rate of Change (ROC) of the Relative Strength Index (RSI) is a technical indicator designed to provide insights into the momentum of an asset's price movement. It combines the Relative Strength Index (RSI), a popular momentum oscillator, with the Rate of Change (ROC) concept to assess the speed at which RSI values are changing.
How It Works:
Relative Strength Index (RSI): The RSI measures the magnitude of recent price changes to evaluate overbought or oversold conditions in an asset. It oscillates between 0 and 100, with readings above 70 typically indicating overbought conditions and readings below 30 indicating oversold conditions.
Rate of Change (ROC): The ROC calculates the percentage change in a given indicator over a specified period. In this indicator, we apply the ROC to the RSI values to determine how quickly the RSI is changing over time.
Key Features:
Acceleration and Deceleration: The ROC of RSI helps traders identify whether the momentum of the RSI is accelerating or decelerating. Positive values suggest increasing momentum, while negative values indicate decreasing momentum.
Dynamic Color Change: The color of the ROC RSI line changes dynamically based on the RSI level. When the RSI is between 0 and 40, the line color is blue, indicating potential oversold conditions. When the RSI is between 40 and 60, the line color is yellow, suggesting neutral conditions. When the RSI is above 60, the line color changes to green, indicating potential overbought conditions.
How to Use:
Acceleration: When the ROC RSI is positive and increasing while the RSI is above 60 (green), it may signal strong upward momentum.
Deceleration: Conversely, if the ROC RSI is negative and decreasing while the RSI is below 40 (blue), it may indicate weakening downward momentum.
Originality and Usefulness:
This indicator combines the RSI, a well-known momentum oscillator, with the ROC concept to provide a unique perspective on momentum dynamics. By dynamically adjusting the color of the ROC RSI line based on RSI levels, traders can quickly assess potential overbought or oversold conditions in the market.
Chart:
The chart displayed alongside this script provides a clean and easy-to-understand visualization of the ROC RSI indicator. The ROC RSI line color changes dynamically based on RSI levels, allowing traders to visually identify potential market conditions at a glance.
Enhanced Smoothed RSIThe "Enhanced Smoothed RSI Factor" indicator is a robust technical analysis tool designed to assist traders in identifying potential trends and reversals. This indicator combines elements of the Relative Strength Index (RSI) with a smoothed factor, enhancing its reliability and responsiveness. By visualizing the Enhanced Smoothed RSI Factor alongside the standard RSI and their associated upper and lower bands, traders gain insights into potential overbought and oversold conditions, facilitating more informed trading decisions.
How to Use:
Inputs Configuration : Adjust the indicator's parameters according to your trading preferences. Modify the source data (source) to suit the price data you want to analyze. Set the RSI period (rsiPeriod) for RSI calculations, the moving average period (movingAvgPeriod) for the bands, and the smoothing factor (factor) for enhanced responsiveness.
Enhanced Smoothed RSI Factor : The indicator calculates the Enhanced Smoothed RSI Factor by applying an exponential moving average (EMA) to the RSI values. This factor reflects changes in price momentum.
Comparison with Standard RSI : Observe the Enhanced Smoothed RSI Factor and the standard RSI side by side on your chart. While the standard RSI offers insights into price momentum, the Enhanced Smoothed RSI Factor adds an extra layer of smoothing for potentially clearer trend indications.
Bands and Bar Coloring : The indicator plots upper and lower bands, which are derived from weighted and simple moving averages of the Enhanced Smoothed RSI Factor. The color of the bars changes based on the position of the Enhanced Smoothed RSI Factor relative to the bands. Green bars indicate values above the upper band, red bars indicate values below the lower band, and gray bars indicate values within the bands.
Overbought and Oversold Levels : The indicator provides horizontal lines at levels 140 and 80. When the Enhanced Smoothed RSI Factor crosses above 140, it suggests a potential bullish trend, while crossing below 80 suggests a potential bearish trend. Additionally, levels 200 and 180 indicate overbought conditions, and levels 100 and 80 indicate oversold conditions.
Additional Insights : The indicator's upper and lower bands provide valuable insights into potential trend reversals. When the Enhanced Smoothed RSI Factor crosses above the upper band, it may signal an overextended bullish trend. Conversely, a crossover below the lower band may indicate an overextended bearish trend.
Important Considerations :
This indicator is most effective when used in conjunction with other technical analysis tools and strategies.
It's recommended to avoid making trading decisions solely based on the Enhanced Smoothed RSI Factor. Combine it with other indicators, chart patterns, and fundamental analysis.
Adjust the overbought and oversold levels to align with your trading strategy and the specific market conditions.
Please remember that trading involves risks, and the indicator's signals are not guaranteed. Always conduct thorough research and consider using a practice account before implementing any trading strategy.
ScalpTrader RSIThis script is a customized Relative Strength Index (RSI) indicator with added functionality, notably the optional Bollinger Bands overlay.
At its core, the script calculates the RSI, which is a popular momentum indicator used in technical analysis to identify overbought and oversold conditions. It does this by taking the average gain and the average loss over a user-defined period (default is 14) to compute the relative strength, which is then transformed into the RSI.
Furthermore, this script provides the option to overlay Bollinger Bands on the RSI line. Bollinger Bands, consisting of a middle band (a moving average) with two outer bands (standard deviations of the middle band), are used to measure volatility and 'relative' high or low prices. When applied to the RSI, they can offer another perspective on the momentum and volatility of the market.
RSI plot values are colored green if above 50 and red if below 50 to give the trader a sense of bullish or bearish price action.
I hope you find the indicator useful. Enjoy.
Yasir Hameed Advance RSI IndicatorRELATIVE STRENGTH INDEX ( RSI )
This is a tool that is widely used
Especially for Overbought and Oversold systems, but I have made some changes in this indicator,
How to use it...!
I have set it as the default setting
- RSI Length: 7
- Overbought: 70
- Oversold: 30
What is unique about this tool?
we can see 3 conditions:
1) RSI Overbought / Oversold with Bullish Engulfing / Bearish Engulfing
2) RSI Overbought / Oversold with Hammer and Shooting Star
3) RSI Overbought / Oversold with 2 Bullish Bars / 2 Bearish Bars
4) RSI Overbought / Oversold with All Patterns at the same time
When the RSI reaches its Oversold line, the code will wait for Bullish Engulfing pattren, when oversold and Bullish engulfing matched, This indicator will generate a buy signal when the condition is met,
and same as for Bear market, When the RSI reaches its Overbought line, the code will wait for Bearish Engulfing pattren, This indicator will generate a sell/exit signal when the condition is met,
2nd condition is that a Hammer candle will be waited for when RSI touches the Overbought line, for Bullish Move
and Shooting Star candle will be waited for when RSI touches the Overbought line, for Bullish Move, for Bearish Move
3rd Condition is also the same as Condition 1 and Condition 2,
When the RSI reaches its Oversold line, the code will wait for 2 Bullish Bars, when oversold and 2 Bullish Bars matched then this indicator will generate a buy signal, and same as for Bear market,
When the RSI reaches its Overbought line, the code will wait for 2 Bearish Bars, when overbought and 2 Bearish Bars matched then this indicator will generate a Sell signal,
4th Condition is that we can use All Conditions at the same time,
- Bullish Engulfing / Bearish Engulfing
- Hammer and Shooting Star
- 2 Bullish Bars / 2 Bearish Bars
RS Compare IndicatorRelative Strength Breakout is always a great indicator of change in trends. This indicator is a visual attempt to show the region of outperformance of a stock with respect to a sector or primary indicator.
The color indicated should read as below
1) Color Red: Indicates that the selected script is underperforming the indexing with which it is compared
2) Color Yellow: Indicates that the selected script is as per the indexing with which it is compared.
3) Color Green: Indicates that the script is outperforming the indexing with which it is compared.
Rumpy's Dynamic Momentum IndexNote : I haven't been able to determine from the info I've found whether the variable length is used for the average gain/loss part of the calculation and/or for the relative strength portion of the calculation . If anyone knows for certain please let me know.
Type A only uses the variable length for the final relative strength calculation and the fixed RSI length for the average gain/loss.
Type B uses the variable length for both.
I do suspect that Type B is correct though as it is a lot more sensitive to momentum changes while Type A tends to just exaggerate normal RSI
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This indicator, developed by Tushar Chande and Stanley Kroll, is similar to the relative strength index (RSI). The main difference between the two is that the RSI uses a fixed number of time periods (usually 14) in its calculation, while the dynamic momentum index uses different time periods as volatility changes, typically between five and 30.
The dynamic momentum index uses fewer periods in its calculation when volatility is high, and more periods when volatility is low.
The number of time periods used in the dynamic momentum index decreases as volatility in the underlying security increases, making this indicator more responsive to changing prices than the RSI. This is particularly useful when an asset's price moves quickly as it approaches key support or resistance levels. Because the indicator is more sensitive, traders can potentially find earlier entry and exit points than with the RSI.
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If you find it useful please consider a tip/donation :
BTC - 3BMEXEDyWJ58eXUEALYPadbn1wwWKmf6sA
CMYK RMI TRIPLE◊ Introduction
This script makes use of three RMI's, to indicate Overbought/Oversold.
Adjustments can easily be made, through its settings or script.
◊ Origin
The Relative Momentum Index was developed by Roger Altman and was introduced in his article in the February, 1993 issue of Technical Analysis of Stocks & Commodities magazine.
While RSI counts up and down days from close to close, the Relative Momentum Index counts up and down days from the close relative to a close x number of days ago.
This results in an RSI that is smoother.
This is a part of Project XIAM.
◊ Theoretical Approach
Philosophy γ :: consequential
◊ Usage
You can use this as an indicator for manual trading, or apply AUTOTVIEW to automate your trading.
My advice is to combine this with another indicator before you do this.
The script is written in an organized and flexible manner to do this.
◊ Features
3 RMI's with seperately adjustable HIGH / LOW levels.
Trend adjustment on the SLOW RMI.
Adjustable Interval between entries / Once per dip-top entry.
Take Profit & Stop loss
◊ Community
Wanna share your findings ? or need help resolving a problem ?
CMYK :: discord.gg
AUTOVIEW :: discordapp.com
TRADINGVIEW UNOFFICIAL :: discord.gg
Currency Relative Strengths [GM] - Data IndicatorI created this tool for the purpose of determining strongest and weakest currencies over different periods of time. Each major currency is compared to the field of other majors and its average change is measured over a predetermined period of time. The result is displayed as a percentage. I use it for trend following but it can also be used to fade exhaustion.
Instructions
Add indicator to chart
Select a time frame under settings
Place cursor over period of interest
Click "Data Window" on right hand side bar
View % change avg values for each currency
RSI Distribution [Kodexius]RSI Distribution is a statistics driven visualization companion for the classic RSI oscillator. In addition to plotting RSI itself, it continuously builds a rolling sample of recent RSI values and projects their distribution as a forward drawn histogram, so you can see where RSI has spent most of its time over the selected lookback window.
The indicator is designed to add context to oscillator readings. Instead of only treating RSI as a single point estimate that is either “high” or “low”, you can evaluate the current RSI level relative to its own recent history. This makes it easier to recognize when the market is operating inside a familiar regime, and when RSI is pushing into rarer tail conditions that tend to appear during momentum bursts, exhaustion, or volatility expansion.
To complement the histogram, the script can optionally overlay a Gaussian curve fitted to the sample mean and standard deviation. It also runs a Jarque Bera normality check, based on skewness and excess kurtosis, and surfaces the result both visually and in a compact dashboard. On the oscillator panel itself, RSI is presented with a clean gradient line and standard overbought and oversold references, with fills that become more visible when RSI meaningfully extends beyond key thresholds.
🔹 Features
1. Distribution Histogram of Recent RSI Values
The script stores the last N RSI values in an internal sample and uses that rolling window to compute a frequency distribution across a user selected number of bins. The histogram is drawn into the future by a configurable width in bars, which keeps it readable and prevents it from colliding with the active RSI plot. The result is a compact visual summary of where RSI clusters most often, whether it is spending more time near the center, or shifting toward higher or lower regimes.
2. Gaussian Overlay for Shape Intuition
If enabled, a fitted bell curve is drawn on top of the histogram using the sample mean and standard deviation. This overlay is not intended as a direct trading signal. Its purpose is to provide a fast visual comparator between the empirical RSI distribution and a theoretical normal shape. When the histogram diverges strongly from the curve, you can quickly spot skew, heavy tails, or regime changes that often occur when market structure or volatility conditions shift.
3. Jarque Bera Normality Check With Clear PASS/FAIL Feedback
The script computes skewness and excess kurtosis from the RSI sample, then forms the Jarque Bera statistic and compares it to a fixed 95% critical value. When the distribution is closer to normal under this test, the status is marked as PASS, otherwise it is marked as FAIL. This result is displayed in the dashboard and can also influence the histogram styling, giving immediate feedback about whether the recent RSI behavior resembles a bell shaped distribution or a more distorted, regime driven profile.
Jarque Bera is a goodness of fit test that evaluates whether a dataset looks consistent with a normal distribution by checking two shape properties: skewness (asymmetry) and kurtosis (tail heaviness, expressed here as excess kurtosis where a perfect normal has 0). Under the null hypothesis of normality, skewness should be near 0 and excess kurtosis should be near 0. The test combines deviations in both into a single statistic, which is then compared to a chi square threshold. A PASS in this script means the sample does not show strong evidence against normality at the chosen threshold, while a FAIL means the sample is meaningfully skewed, heavy tailed, or both. In practical trading terms, a FAIL often suggests RSI is behaving in a regime where extremes and asymmetry are more common, which is typical during strong trends, volatility expansions, or one sided market pressure. It is still a statistical diagnostic, not a prediction tool, and results can vary with lookback length and market conditions.
4. Integrated Stats Dashboard
A compact table in the top right summarizes key distribution moments and the normality result: Mean, StdDev, Skewness, Kurtosis, and the JB statistic with PASS/FAIL text. Skewness is color coded by sign to quickly distinguish right skew (more time at higher RSI) versus left skew (more time at lower RSI), which can be helpful when diagnosing trend bias and momentum persistence.
5. RSI Visual Quality and Context Zones
RSI is plotted with a gradient color scheme and standard overbought and oversold reference lines. The overbought and oversold areas are filled with a smart gradient so visual emphasis increases when RSI meaningfully extends beyond the 70 and 30 regions, improving readability without overwhelming the panel.
🔹 Calculations
This section summarizes the main calculations and transformations used internally.
1. RSI Series
RSI is computed from the selected source and length using the standard RSI function:
rsi_val = ta.rsi(rsi_src, rsi_len)
2. Rolling Sample Collection
A float array stores recent RSI values. Each bar appends the newest RSI, and if the array exceeds the configured lookback, the oldest value is removed. Conceptually:
rsi_history.push(rsi_val)
if rsi_history.size() > lookback
rsi_history.shift()
This maintains a fixed size window that represents the most recent RSI behavior.
3. Mean, Variance, and Standard Deviation
The script computes the sample mean across the array. Variance is computed as sample variance using (n - 1) in the denominator, and standard deviation is the square root of that variance. These values serve both the dashboard display and the Gaussian overlay parameters.
4. Skewness and Excess Kurtosis
Skewness is calculated from the standardized third central moment with a small sample correction. Kurtosis is computed as excess kurtosis (kurtosis minus 3), so the normal baseline is 0. These two metrics summarize asymmetry and tail heaviness, which are the core ingredients for the Jarque Bera statistic.
5. Jarque Bera Statistic and Decision Rule
Using skewness S and excess kurtosis K, the Jarque Bera statistic is computed as:
JB = (n / 6.0) * (S^2 + 0.25 * K^2)
Normality is flagged using a fixed critical value:
is_normal = JB < 5.991
This produces a simple PASS/FAIL classification suitable for fast chart interpretation.
6. Histogram Binning and Scaling
The RSI domain is treated as 0 to 100 and divided into a configurable number of bins. Bin size is:
bin_size = 100.0 / bins
Each RSI sample maps to a bin index via floor(rsi / bin_size), with clamping to ensure the index stays within valid bounds. The script counts occurrences per bin, tracks the maximum frequency, and normalizes each bar height by freq/max_freq so the histogram remains visually stable and comparable as the window updates.
7. Gaussian Curve Overlay (Optional)
The Gaussian overlay uses the normal probability density function with mu as the sample mean and sigma as the sample standard deviation:
normal_pdf(x) = (1 / (sigma * sqrt(2*pi))) * exp(-0.5 * ((x - mu)/sigma)^2)
For drawing, the script samples x across the histogram width, evaluates the PDF, and normalizes it relative to its peak so the curve fits within the same visual height scale as the histogram.
RSI Forecast Colorful [DiFlip]RSI Forecast Colorful
Introducing one of the most complete RSI indicators available — a highly customizable analytical tool that integrates advanced prediction capabilities. RSI Forecast Colorful is an evolution of the classic RSI, designed to anticipate potential future RSI movements using linear regression. Instead of simply reacting to historical data, this indicator provides a statistical projection of the RSI’s future behavior, offering a forward-looking view of market conditions.
⯁ Real-Time RSI Forecasting
For the first time, a public RSI indicator integrates linear regression (least squares method) to forecast the RSI’s future behavior. This innovative approach allows traders to anticipate market movements based on historical trends. By applying Linear Regression to the RSI, the indicator displays a projected trendline n periods ahead, helping traders make more informed buy or sell decisions.
⯁ Highly Customizable
The indicator is fully adaptable to any trading style. Dozens of parameters can be optimized to match your system. All 28 long and short entry conditions are selectable and configurable, allowing the construction of quantitative, statistical, and automated trading models. Full control over signals ensures precise alignment with your strategy.
⯁ Innovative and Science-Based
This is the first public RSI indicator to apply least-squares predictive modeling to RSI calculations. Technically, it incorporates machine-learning logic into a classic indicator. Using Linear Regression embeds strong statistical foundations into RSI forecasting, making this tool especially valuable for traders seeking quantitative and analytical advantages.
⯁ Scientific Foundation: Linear Regression
Linear regression is a fundamental statistical method that models the relationship between a dependent variable y and one or more independent variables x. The general formula for simple linear regression is:
y = β₀ + β₁x + ε
where:
y = predicted variable (e.g., future RSI value)
x = explanatory variable (e.g., bar index or time)
β₀ = intercept (value of y when x = 0)
β₁ = slope (rate of change of y relative to x)
ε = random error term
The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the RSI projection based on recent trends.
⯁ Least Squares Estimation
To minimize the error between predicted and observed values, we use the formulas:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables.
⯁ Linear Regression in Machine Learning
Linear regression is a foundational component of supervised learning. Its simplicity and precision in numerical prediction make it essential in AI, predictive algorithms, and time-series forecasting. Applying regression to RSI is akin to embedding artificial intelligence inside a classic indicator, adding a new analytical dimension.
⯁ Visual Interpretation
Imagine a time series of RSI values like this:
Time →
RSI →
The regression line smooths these historical values and projects itself n periods forward, creating a predictive trajectory. This projected RSI line can cross the actual RSI, generating sophisticated entry and exit signals. In summary, the RSI Forecast Colorful indicator provides both the current RSI and the forecasted RSI, allowing comparison between past and future trend behavior.
⯁ Summary of Scientific Concepts Used
Linear Regression: Models relationships between variables using a straight line.
Least Squares: Minimizes squared prediction errors for optimal fit.
Time-Series Forecasting: Predicts future values from historical patterns.
Supervised Learning: Predictive modeling based on known output values.
Statistical Smoothing: Reduces noise to highlight underlying trends.
⯁ Why This Indicator Is Revolutionary
Scientifically grounded: Built on statistical and mathematical theory.
First of its kind: The first public RSI with least-squares predictive modeling.
Intelligent: Incorporates machine-learning logic into RSI interpretation.
Forward-looking: Generates predictive, not just reactive, signals.
Customizable: Exceptionally flexible for any strategic framework.
⯁ Conclusion
By combining RSI and linear regression, the RSI Forecast Colorful allows traders to predict market momentum rather than simply follow it. It's not just another indicator: it's a scientific advancement in technical analysis technology. Offering 28 configurable entry conditions and advanced signals, this open-source indicator paves the way for innovative quantitative systems.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What Is RSI?
The RSI (Relative Strength Index) is a technical indicator developed by J. Welles Wilder. It measures the velocity and magnitude of recent price movements to identify overbought and oversold conditions. The RSI ranges from 0 to 100 and is commonly used to identify potential reversals and evaluate trend strength.
⯁ How RSI Works
RSI is calculated from average gains and losses over a set period (commonly 14 bars) and plotted on a 0–100 scale. It consists of three key zones:
Overbought: RSI above 70 may signal an overbought market.
Oversold: RSI below 30 may signal an oversold market.
Neutral Zone: RSI between 30 and 70, indicating no extreme condition.
These zones help identify potential price reversals and confirm trend strength.
⯁ Entry Conditions
All conditions below are fully customizable and allow detailed control over entry signal creation.
📈 BUY
🧲 Signal Validity: Signal remains valid for X bars.
🧲 Signal Logic: Configurable using AND or OR.
🧲 RSI > Upper
🧲 RSI < Upper
🧲 RSI > Lower
🧲 RSI < Lower
🧲 RSI > Middle
🧲 RSI < Middle
🧲 RSI > MA
🧲 RSI < MA
🧲 MA > Upper
🧲 MA < Upper
🧲 MA > Lower
🧲 MA < Lower
🧲 RSI (Crossover) Upper
🧲 RSI (Crossunder) Upper
🧲 RSI (Crossover) Lower
🧲 RSI (Crossunder) Lower
🧲 RSI (Crossover) Middle
🧲 RSI (Crossunder) Middle
🧲 RSI (Crossover) MA
🧲 RSI (Crossunder) MA
🧲 MA (Crossover)Upper
🧲 MA (Crossunder)Upper
🧲 MA (Crossover) Lower
🧲 MA (Crossunder) Lower
🧲 RSI Bullish Divergence
🧲 RSI Bearish Divergence
🔮 RSI (Crossover) Forecast MA
🔮 RSI (Crossunder) Forecast MA
📉 SELL
🧲 Signal Validity: Signal remains valid for X bars.
🧲 Signal Logic: Configurable using AND or OR.
🧲 RSI > Upper
🧲 RSI < Upper
🧲 RSI > Lower
🧲 RSI < Lower
🧲 RSI > Middle
🧲 RSI < Middle
🧲 RSI > MA
🧲 RSI < MA
🧲 MA > Upper
🧲 MA < Upper
🧲 MA > Lower
🧲 MA < Lower
🧲 RSI (Crossover) Upper
🧲 RSI (Crossunder) Upper
🧲 RSI (Crossover) Lower
🧲 RSI (Crossunder) Lower
🧲 RSI (Crossover) Middle
🧲 RSI (Crossunder) Middle
🧲 RSI (Crossover) MA
🧲 RSI (Crossunder) MA
🧲 MA (Crossover)Upper
🧲 MA (Crossunder)Upper
🧲 MA (Crossover) Lower
🧲 MA (Crossunder) Lower
🧲 RSI Bullish Divergence
🧲 RSI Bearish Divergence
🔮 RSI (Crossover) Forecast MA
🔮 RSI (Crossunder) Forecast MA
🤖 Automation
All BUY and SELL conditions can be automated using TradingView alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies.
⯁ Unique Features
Linear Regression Forecast
Signal Validity: Keep signals active for X bars
Signal Logic: AND/OR configuration
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Chart Labels: BUY/SELL markers above price
Automation & Alerts: BUY/SELL
Background Colors: bgcolor
Fill Colors: fill
Linear Regression Forecast
Signal Validity: Keep signals active for X bars
Signal Logic: AND/OR configuration
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Chart Labels: BUY/SELL markers above price
Automation & Alerts: BUY/SELL
Background Colors: bgcolor
Fill Colors: fill
RSI + MACD Multi-Timeframe StrategyThis strategy combines the Relative Strength Index (RSI) from the daily timeframe with the Moving Average Convergence Divergence (MACD) from the 4-hour timeframe to generate precise long entry and exit signals.
The system uses a multi-timeframe approach to align longer-term trend conditions with shorter-term momentum shifts — allowing traders to catch dips with confirmation and exit before reversals.
🧠 Strategy Logic
✅ Long Entry Condition:
- RSI on the daily (1D) timeframe is oversold (below your defined threshold)
- MACD on the 4H timeframe crosses above the signal line
→ A long trade is opened when these two align
✅ Long Exit Condition:
- RSI on the daily timeframe is overbought
- MACD on the 4H timeframe crosses below the signal line
→ The long trade is closed when these two conditions are met
💡 This strategy currently supports long entries only. Short logic can be added if needed.
📊 Indicator Components
🔹 RSI (Relative Strength Index):
- A momentum oscillator that measures the speed and magnitude of price changes.
- Helps identify overbought (potential sell) and oversold (potential buy) conditions.
- Applied on the 1D timeframe (by default) to reflect broader market trend or exhaustion levels.
🔹 MACD (Moving Average Convergence Divergence):
- A trend-following momentum indicator based on moving averages.
- The MACD Line (fast EMA - slow EMA) crossing above the Signal Line indicates bullish momentum.
- Used here on the 4-hour timeframe (by default) for shorter-term momentum confirmation.
🔹 Multi-Timeframe (MTF) Logic:
- Uses request.security() to pull higher timeframe data (1D for RSI, 4H for MACD).
- Ensures no repainting, as it only uses closed candles from the higher timeframe.
- Aligns longer-term signals with shorter-term entries, reducing false signals.
📈 Plotting Options
The script includes a plot selector input allowing you to toggle between:
- RSI Plot (with overbought/oversold lines)
- MACD Plot (MACD line and signal line)
- This helps visualize signal conditions clearly on your chart.
🛠 Customization
- RSI & MACD settings are fully configurable
- RSI and MACD timeframes can be adjusted independently
⚠️ Disclaimer
This strategy is provided for educational and informational purposes only.
It is not financial advice or a recommendation to buy or sell any asset.
Past performance does not guarantee future results. Always test strategies in a simulated environment before live use, and consult with a licensed financial advisor for investment decisions.
