MACD & RSI Overlay (Expo)█ Overview
The MACD & RSI Overlay (Expo) trading indicator is a technical analysis tool that combines two popular indicators, the Relative Strength Index (RSI ) and the Moving Average Convergence Divergence (MACD ), and overlays them onto the price chart. The indicator oscillates relative to price, so it plots the RSI and MACD around price while still displaying the same insights as the regular MACD and RSI indicators. This feature gives traders a unique perspective, allowing them to see the relationship between price, momentum, and trend in a single chart.
This indicator is a valuable addition to any trader's technical analysis toolkit, whether they are a beginner or an experienced trader.
█ MACD
█ RSI
The RSI comes with overbought and oversold areas, which can be set by the trader.
█ MACD & RSI
█ Trend Feature
What sets the MACD & RSI Overlay indicator apart is its ability to factor in the underlying trend. This feature makes the indicator more useful than ever before, as traders can use it to filter trades in the direction of the trend. By considering the underlying trend, traders can gain valuable insights into market trends.
█ Benefits
One of the primary benefits of having the MACD and RSI plotted directly on the price chart is that it provides a more intuitive understanding of the relationship between price, momentum, and trend. Traders can quickly identify the direction of the trend by observing the price movement relative to the MACD and RSI lines. In addition, by having these indicators plotted on the chart, traders can quickly identify potential buy and sell signals and develop new trading strategies.
█ How to use
One of the most popular strategies is to use the MACD & RSI Overlay indicator to look for crossings. A crossing occurs when the MACD and RSI lines cross over each other or when they cross over the signal line. These crossings can signal potential trend reversals and momentum shifts. For example, if the MACD line crosses over the signal line from below, it could indicate a bullish signal, while a cross from above could indicate a bearish signal.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Komut dosyalarını "Relative Strength Index (RSI) " için ara
Bollinger Band Alert with RSI Filter IndicatorThis code is for a technical analysis indicator called Bollinger Band Alert with RSI Filter. It uses two tools: Bollinger Bands and Relative Strength Index (RSI) to identify potential trading signals in the market.
Bollinger Bands are lines plotted two standard deviations away from a simple moving average of the price of a stock or asset. They help traders determine whether prices are high or low on a relative basis.
The RSI is a momentum indicator that measures the strength of recent price changes to evaluate whether an asset is overbought or oversold.
The code has some input parameters that a user can change, such as length and multiplier, which are used to calculate the Bollinger Bands, and upper and lower RSI levels to define the overbought and oversold zones.
The code then uses if statements to generate alerts if certain conditions are met. The alert condition is triggered if the close price of an asset crosses above or below the upper or lower Bollinger Bands, and if the RSI is either above or below the overbought or oversold threshold levels.
Finally, the code generates plots to visualize the Bollinger Bands and displays triangles above or below the bars indicating when to enter a long or short position based on the strategy's criteria.
Stan Weinstein Trend IndicatorThis indicator is a trend indicator for trading charts based on the method of Stan Weinstein. It uses various technical methods to identify four trend phases on an asset: consolidation, advancement, plateauing, and decline. Users can customize the indicator by modifying parameters such as the periods for various calculations, such as the exponential moving average (EMA), the relative strength index (RSI), and support and resistance levels. The results of these calculations are then used to determine if an asset is in a phase of consolidation, advancement, plateauing, or decline.
The results are displayed as markers on the chart, with the following colors:
White: Consolidation
Green: Advancement
Blue: Plateauing
Red: Decline
According to the method of Stan Weinstein, it is recommended to buy an asset during an advancement phase and sell it during a plateauing phase. Similarly, it is recommended to sell an asset during a decline phase and cut this sale when the consolidation phase starts. It is important to note that this indicator is for informational purposes only and should not be used as investment advice. It is important to conduct fundamental and technical analysis before making an investment decision. It is also recommended to combine this analysis with other methods for optimal results and to consider the risks associated with any investment.
All default parameters of this indicator have been carefully chosen to provide the best possible results, however, it is possible to modify them according to personal preferences. It is important to note that modifying certain parameters may make the indicator less relevant and it is therefore recommended not to deviate too much from default values, unless you have a good understanding of the Stan Weinstein method and the technical indicators used.
It is important to note that this indicator is optimized for 1-week charts. It can be used to look at charts at other timeframes but calculations will always be based on weekly data.
Also, it is noteworthy that this indicator is optimized for cryptocurrencies, except Bitcoin, as it is used to calculate the relative strength of a token. However, you can choose the asset or index you want in the menu to calculate the relative strength. Furthermore, all the default settings are carefully chosen, but users are free to modify them, but doing so may result in less relevant results.
STD Aadaptive, floating RSX Dynamic Momentum Index [Loxx]STD Aadaptive, floating RSX Dynamic Momentum Index is an attempt to improve Chande's original work on Dynamic Momentum Index. The full name of this indicator is "Standard-Deviation-Adaptive, floating-level, Dynamic Momentum Index on Jurik's RSX".
What Is Dynamic Momentum Index?
The dynamic momentum index is used in technical analysis to determine if a security is overbought or oversold. This indicator, developed by Tushar Chande and Stanley Kroll, is very 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), while the dynamic momentum index uses different time periods as volatility changes, typically between five and 30.
What is RSX?
RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI, but with one important exception: the noise is gone with no added lag.
Differences
RSX is used instead of RSI for the calculation, producing a much smoother result
Standard deviation is used to adapt the RSX calculation
Floating levels are used instead of fixed levels for OB/OS
Included
-Change bar colors
Best Currency Strength Indicator By Mahfuz AzimBest Currency Strength Indicator is a visual guide that demonstrates which currencies are currently strong, and which ones are weak.
FX Currency strength indicators include multiple calculation to choose from
1. Relative Strength Index ( RSI )
2. True Strength Index (TSI)
3. Absolute Strength Index (ASI)
4. Linear Regression Slope ( LRS )
5. Rate of Change ( ROC ) and
6. Z-Score
FX Currency Strength IndicatorFX Currency strength indicator is a visual guide that demonstrates which currencies are currently strong, and which ones are weak.
FX Currency strength indicators include multiple calculation to choose from
1. Relative Strength Index (RSI)
2. True Strength Index (TSI)
3. Absolute Strength Index (ASI)
4. Linear Regression Slope (LRS)
5. Rate of Change (ROC)
6. Z-Score
Three display modes
1. Lines
2. Columns
3. Areas
AP IFTCCIv2/IFTStoch/IFTRSI Multi-TimeframeMulti-Timeframe IFT-CCI/Stoch/RSI Composite
This enhanced indicator combines three powerful oscillators—Inverse Fisher Transform (IFT) versions of the Commodity Channel Index (CCI), Stochastic, and Relative Strength Index (RSI)—into a unified multi-timeframe analysis tool. Originally developed by John Ehlers (pioneer of cyclical analysis and signal processing in trading systems) and adapted by KIVANC (@fr3762), this version adds dual-timeframe capability to compare indicator values across different chart resolutions.
Key Features:
Triple Oscillator Composite
IFT-CCI: Smoothed CCI values transformed via Ehlers' Inverse Fisher Transform (blue-gold)
IFT-Stochastic: Classic stochastic oscillator processed through IFT (blue)
IFT-RSI: RSI oscillator converted to IFT format (magenta)
Composite Average Line: Combined average of all three indicators (green)
Multi-Timeframe Analysis
Compare primary and secondary timeframes (e.g., 1H vs. 4H, daily vs. weekly)
Primary timeframe plots use solid lines with 80% opacity
Secondary timeframe (optional) uses dashed/circle markers with 40% opacity
Key Levels
Overbought (+0.75) and oversold (-0.75) reference lines
Zero-centerline for momentum direction bias
Applications:
Trend Confirmation: Align higher timeframe signals with lower timeframe entries
Divergence Detection: Spot inter-timeframe discrepancies in momentum
Regime Filter: Use higher timeframe composite values to filter trades
Technical Basis:
Inverse Fisher Transform: Compresses oscillator values into bounded (-1 to +1) range while emphasizing extreme moves
Dual WMA Smoothing: Combines initial calculation smoothing (WMA1) with final output smoothing (WMA2)
Exponential Scaling: (e^2x - 1)/(e^2x + 1) formula converts Gaussian-like distributions to bounded outputs
Credits:
Original Concept: John Ehlers (IFT methodology, cyclical analysis foundations)
Initial Implementation: KIVANC (@fr3762 on Twitter) for the base IFT-CCI/Stoch/RSI script
Multi-Timeframe Adaptation: for cross-resolution analysis capabilities
This tool is particularly effective for traders seeking to align multiple timeframes while using Ehlers' noise-reduction techniques. The composite average line provides a consensus view, while the individual oscillators help identify component strength/weakness.
RSI HeartHere's an introduction you can use for your RSI Heart indicator:
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### RSI Heart Indicator
The **RSI Heart Indicator** provides a visually engaging way to monitor and track the **Relative Strength Index (RSI)** across multiple timeframes (10m, 15m, 30m, and 1H). It not only shows the RSI value but also uses heart-shaped symbols to reflect the current market condition based on RSI levels, making it easier to understand the strength and momentum of a given asset at a glance.
### Key Features:
- **Multi-Timeframe Support**: The indicator pulls the RSI values from multiple timeframes (10 minutes, 15 minutes, 30 minutes, and 1 hour) so you can analyze market strength at different intervals in one view.
- **Heart Symbols**: RSI values are displayed alongside heart emojis (❤️, 💛, 💚) that provide a visual cue for the market condition:
- **❤️ (Overbought or Oversold)**: When RSI is below 27 or above 73.
- **💛 (Near Oversold/Overbought)**: When RSI is between 27-30 or 70-73.
- **💚 (Neutral)**: When RSI is between 30 and 70.
- **Customizable Visibility**: Toggle visibility for each timeframe's RSI using simple on/off settings, giving you control over which timeframes are displayed in your chart.
### How it Can Help:
- **Quick Market Sentiment Analysis**: The heart symbols and RSI values allow you to quickly assess whether an asset is in an overbought or oversold condition.
- **Multi-Timeframe RSI**: By viewing RSI across multiple timeframes, you can gain a more comprehensive understanding of market momentum and strength.
- **Personalized to Your Preferences**: Adjust the settings to only show the timeframes that matter most to you, creating a customized and clean chart view.
This indicator helps traders make more informed decisions by providing a clear, easy-to-read representation of market conditions across various timeframes, all within one indicator.
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This introduction explains what the indicator does, its features, and how it can benefit traders in a concise and easy-to-understand way.
Fuzzy SMA Trend Analyzer (experimental)[FibonacciFlux]Fuzzy SMA Trend Analyzer (Normalized): Advanced Market Trend Detection Using Fuzzy Logic Theory
Elevate your technical analysis with institutional-grade fuzzy logic implementation
Research Genesis & Conceptual Framework
This indicator represents the culmination of extensive research into applying fuzzy logic theory to financial markets. While traditional technical indicators often produce binary outcomes, market conditions exist on a continuous spectrum. The Fuzzy SMA Trend Analyzer addresses this limitation by implementing a sophisticated fuzzy logic system that captures the nuanced, multi-dimensional nature of market trends.
Core Fuzzy Logic Principles
At the heart of this indicator lies fuzzy logic theory - a mathematical framework designed to handle imprecision and uncertainty:
// Improved fuzzy_triangle function with guard clauses for NA and invalid parameters.
fuzzy_triangle(val, left, center, right) =>
if na(val) or na(left) or na(center) or na(right) or left > center or center > right // Guard checks
0.0
else if left == center and center == right // Crisp set (single point)
val == center ? 1.0 : 0.0
else if left == center // Left-shoulder shape (ramp down from 1 at center to 0 at right)
val >= right ? 0.0 : val <= center ? 1.0 : (right - val) / (right - center)
else if center == right // Right-shoulder shape (ramp up from 0 at left to 1 at center)
val <= left ? 0.0 : val >= center ? 1.0 : (val - left) / (center - left)
else // Standard triangle
math.max(0.0, math.min((val - left) / (center - left), (right - val) / (right - center)))
This implementation of triangular membership functions enables the indicator to transform crisp numerical values into degrees of membership in linguistic variables like "Large Positive" or "Small Negative," creating a more nuanced representation of market conditions.
Dynamic Percentile Normalization
A critical innovation in this indicator is the implementation of percentile-based normalization for SMA deviation:
// ----- Deviation Scale Estimation using Percentile -----
// Calculate the percentile rank of the *absolute* deviation over the lookback period.
// This gives an estimate of the 'typical maximum' deviation magnitude recently.
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
// ----- Normalize the Raw Deviation -----
// Divide the raw deviation by the estimated 'typical max' magnitude.
normalized_diff = raw_diff / diff_abs_percentile
// ----- Clamp the Normalized Deviation -----
normalized_diff_clamped = math.max(-3.0, math.min(3.0, normalized_diff))
This percentile normalization approach creates a self-adapting system that automatically calibrates to different assets and market regimes. Rather than using fixed thresholds, the indicator dynamically adjusts based on recent volatility patterns, significantly enhancing signal quality across diverse market environments.
Multi-Factor Fuzzy Rule System
The indicator implements a comprehensive fuzzy rule system that evaluates multiple technical factors:
SMA Deviation (Normalized): Measures price displacement from the Simple Moving Average
Rate of Change (ROC): Captures price momentum over a specified period
Relative Strength Index (RSI): Assesses overbought/oversold conditions
These factors are processed through a sophisticated fuzzy inference system with linguistic variables:
// ----- 3.1 Fuzzy Sets for Normalized Deviation -----
diffN_LP := fuzzy_triangle(normalized_diff_clamped, 0.7, 1.5, 3.0) // Large Positive (around/above percentile)
diffN_SP := fuzzy_triangle(normalized_diff_clamped, 0.1, 0.5, 0.9) // Small Positive
diffN_NZ := fuzzy_triangle(normalized_diff_clamped, -0.2, 0.0, 0.2) // Near Zero
diffN_SN := fuzzy_triangle(normalized_diff_clamped, -0.9, -0.5, -0.1) // Small Negative
diffN_LN := fuzzy_triangle(normalized_diff_clamped, -3.0, -1.5, -0.7) // Large Negative (around/below percentile)
// ----- 3.2 Fuzzy Sets for ROC -----
roc_HN := fuzzy_triangle(roc_val, -8.0, -5.0, -2.0)
roc_WN := fuzzy_triangle(roc_val, -3.0, -1.0, -0.1)
roc_NZ := fuzzy_triangle(roc_val, -0.3, 0.0, 0.3)
roc_WP := fuzzy_triangle(roc_val, 0.1, 1.0, 3.0)
roc_HP := fuzzy_triangle(roc_val, 2.0, 5.0, 8.0)
// ----- 3.3 Fuzzy Sets for RSI -----
rsi_L := fuzzy_triangle(rsi_val, 0.0, 25.0, 40.0)
rsi_M := fuzzy_triangle(rsi_val, 35.0, 50.0, 65.0)
rsi_H := fuzzy_triangle(rsi_val, 60.0, 75.0, 100.0)
Advanced Fuzzy Inference Rules
The indicator employs a comprehensive set of fuzzy rules that encode expert knowledge about market behavior:
// --- Fuzzy Rules using Normalized Deviation (diffN_*) ---
cond1 = math.min(diffN_LP, roc_HP, math.max(rsi_M, rsi_H)) // Strong Bullish: Large pos dev, strong pos roc, rsi ok
strength_SB := math.max(strength_SB, cond1)
cond2 = math.min(diffN_SP, roc_WP, rsi_M) // Weak Bullish: Small pos dev, weak pos roc, rsi mid
strength_WB := math.max(strength_WB, cond2)
cond3 = math.min(diffN_SP, roc_NZ, rsi_H) // Weakening Bullish: Small pos dev, flat roc, rsi high
strength_N := math.max(strength_N, cond3 * 0.6) // More neutral
strength_WB := math.max(strength_WB, cond3 * 0.2) // Less weak bullish
This rule system evaluates multiple conditions simultaneously, weighting them by their degree of membership to produce a comprehensive trend assessment. The rules are designed to identify various market conditions including strong trends, weakening trends, potential reversals, and neutral consolidations.
Defuzzification Process
The final step transforms the fuzzy result back into a crisp numerical value representing the overall trend strength:
// --- Step 6: Defuzzification ---
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10 // Use small epsilon instead of != 0.0 for float comparison
fuzzyTrendScore := (strength_SB * STRONG_BULL +
strength_WB * WEAK_BULL +
strength_N * NEUTRAL +
strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1 (strong bearish) to +1 (strong bullish), providing a smooth, continuous evaluation of market conditions that avoids the abrupt signal changes common in traditional indicators.
Advanced Visualization with Rainbow Gradient
The indicator incorporates sophisticated visualization using a rainbow gradient coloring system:
// Normalize score to for gradient function
normalizedScore = na(fuzzyTrendScore) ? 0.5 : math.max(0.0, math.min(1.0, (fuzzyTrendScore + 1) / 2))
// Get the color based on gradient setting and normalized score
final_color = get_gradient(normalizedScore, gradient_type)
This color-coding system provides intuitive visual feedback, with color intensity reflecting trend strength and direction. The gradient can be customized between Red-to-Green or Red-to-Blue configurations based on user preference.
Practical Applications
The Fuzzy SMA Trend Analyzer excels in several key applications:
Trend Identification: Precisely identifies market trend direction and strength with nuanced gradation
Market Regime Detection: Distinguishes between trending markets and consolidation phases
Divergence Analysis: Highlights potential reversals when price action and fuzzy trend score diverge
Filter for Trading Systems: Provides high-quality trend filtering for other trading strategies
Risk Management: Offers early warning of potential trend weakening or reversal
Parameter Customization
The indicator offers extensive customization options:
SMA Length: Adjusts the baseline moving average period
ROC Length: Controls momentum sensitivity
RSI Length: Configures overbought/oversold sensitivity
Normalization Lookback: Determines the adaptive calculation window for percentile normalization
Percentile Rank: Sets the statistical threshold for deviation normalization
Gradient Type: Selects the preferred color scheme for visualization
These parameters enable fine-tuning to specific market conditions, trading styles, and timeframes.
Acknowledgments
The rainbow gradient visualization component draws inspiration from LuxAlgo's "Rainbow Adaptive RSI" (used under CC BY-NC-SA 4.0 license). This implementation of fuzzy logic in technical analysis builds upon Fermi estimation principles to overcome the inherent limitations of crisp binary indicators.
This indicator is shared under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Remember that past performance does not guarantee future results. Always conduct thorough testing before implementing any technical indicator in live trading.
RSI & EMA IndicatorMulti-Timeframe EMA & RSI Analysis with Trend Merging Detection
Overview
This script provides traders with a multi-timeframe analysis tool that simplifies trend detection, momentum confirmation, and potential trend shifts. It integrates Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI) across Daily, Weekly, and Monthly timeframes, helping traders assess both long-term and short-term market conditions at a glance.
This script is a simplification and modification of the EMA Cheatsheet by MarketMoves, reducing chart clutter while adding EMA merging detection to highlight potential trend reversals or breakouts.
Originality and Usefulness
Unlike traditional indicators, which focus on a single timeframe, this script combines multiple timeframes in a single view to offer a comprehensive market outlook.
What Makes This Indicator Unique?
This Indicator to Combine RSI and EMA Clouds for Multiple Timeframes
Multi-Timeframe Trend Analysis in One Visual Tool
EMA Merging Detection to Spot Trend Shifts Early
Momentum Validation Using RSI Across Daily, Weekly, and Monthly Timeframes
Reduces Chart Clutter While Providing Actionable Trade Signals
I couldn't find a TradingView indicator that displayed RSI and EMA clouds together across Daily, Weekly, and Monthly timeframes. This tool bridges that gap, allowing traders to see trend strength and momentum shifts across key timeframes without switching charts.
How the Script Works
1. Trend Direction via EMAs
The script tracks Short-term (5 & 12-period), Medium-term (34 & 50-period), and Long-term (72 & 89-period) EMAs across Daily, Weekly, and Monthly timeframes.
Bullish trend: When faster EMAs are above slower EMAs.
Bearish trend: When faster EMAs are below slower EMAs.
A visual table simplifies trend recognition with:
Green cells for bullish alignment.
Red cells for bearish alignment.
This color-coded system allows traders to quickly assess market momentum across different timeframes without excessive manual analysis.
2. Momentum Confirmation with RSI
The RSI(14) values for Daily, Weekly, and Monthly timeframes are displayed alongside the EMAs.
RSI above 70 suggests overbought conditions.
RSI below 30 suggests oversold conditions.
By combining RSI with EMA trends, traders can confirm whether momentum supports the trend direction or if the market is losing strength.
3. Trend Shift Detection (EMA Merging Mechanism)
A unique feature of this script is EMA merging detection, which occurs when:
The short, medium, and long-term EMAs come within 0.5% of the price.
This often signals trend reversals, breakouts, or consolidations.
When this condition is met, a warning signal appears, alerting traders to potential market shifts.
Who This Indicator Is For?
This script is designed for traders who want to track trends across multiple timeframes while keeping a clean and simplified chart.
Swing & Position Traders – Identify strong trends and potential momentum shifts for longer-term trades.
Trend Followers – Stay aligned with major market trends and avoid trading against momentum.
Day Traders – Use the Daily timeframe for entries while referencing higher timeframes for confirmation.
How to Use the Indicator
Add the indicator to any chart.
Check the trend table in the top-right corner:
Green cells indicate a bullish trend.
Red cells indicate a bearish trend.
Look at RSI values to confirm momentum:
RSI above 70 = Overbought.
RSI below 30 = Oversold.
Watch for the "Merge" alert to spot potential reversals or consolidations.
Combine signals from multiple timeframes for stronger trade decisions.
Why This Indicator is Unique on TradingView?
Before this script, no TradingView indicator displayed RSI and EMA clouds together across multiple timeframes (Daily, Weekly, Monthly).
This tool eliminates the need to:
Manually check multiple timeframes for trend alignment.
Add multiple EMA and RSI indicators to the same chart, creating clutter.
Constantly switch between different timeframes to confirm momentum and trend direction.
With this indicator, traders can see trend strength and momentum shifts instantly, improving their decision-making process.
Chart Guidelines
The script is designed for use on a clean chart to maximize clarity.
The trend alignment table is displayed in a non-intrusive manner so traders can focus on price action.
No additional indicators are required, but users may combine this script with volume-based indicators for further confirmation.
The script name and timeframe should always be visible on published charts to help traders understand the analysis.
Final Notes
This script is a simplification and modification of the EMA Cheatsheet by MarketMoves, improving trend detection, momentum confirmation, and EMA merging detection.
It is designed to help traders quickly identify trend direction, confirm momentum, and detect potential trend shifts, reducing the need for excessive manual analysis.
Disclaimer: This indicator is for educational purposes only and does not constitute financial advice. Trading involves risk; always use proper risk management when applying this tool in live markets.
Uptrick: Zero Lag HMA Trend Suite1. Name and Purpose
Uptrick: Zero Lag HMA Trend Suite is a Pine Version 6 script that builds upon the Hull Moving Average (HMA) to offer an advanced trend analysis tool. Its purpose is to help traders identify trend direction, potential reversals, and overall market momentum with reduced lag compared to traditional moving averages. By combining the HMA with Average True Range (ATR) thresholds, slope-dependent coloring, Volume Weighted Average Price (VWAP) ribbons, and optional reversal signals, the script aims to give a detailed view of price activity in various market environments.
2. Overview
This script begins with the calculation of a Hull Moving Average, a method that blends Weighted Moving Averages in a way designed to cut down on lag while still smoothing out price fluctuations. Next, several enhancements are applied. The script compares current HMA values to previous ones for slope-based coloring, which highlights uptrends and downtrends at a glance. It also plots buy and sell signals when price moves beyond or below thresholds determined by the ATR and the user’s chosen signal multiplier. An optional VWAP ribbon can be shown to confirm bullish or bearish conditions relative to a volume-weighted benchmark. Additionally, the script can plot reversal signals (labeled with B) at points where price crosses back toward the HMA from above or below. Taken together, these elements allow traders to visualize both the short-term momentum and the broader context of how price interacts with volatility and overall market direction.
3. Why These Indicators Have Been Linked Together
The reason the Hull Moving Average, the Average True Range, and the VWAP have been integrated into one script is to tackle multiple facets of market analysis in a single tool. The Zero Lag Hull Moving Average provides a responsive trend line, the ATR offers a measure of volatility that helps distinguish significant price shifts from typical fluctuations, and the VWAP acts as a reference for fair value based on traded volume. By layering all three, the script helps traders avoid the need to juggle multiple separate indicators and offers a holistic perspective. The slope-based coloring focuses on trend direction, the ATR-based thresholds refine possible buy and sell zones, and the VWAP ribbons provide insight into how price stands relative to an important volume-weighted level. The inclusion of up and down signals and reversal B labels further refines entries and exits.
4. Why Use Uptrick: Zero Lag HMA Trend Suite
The Hull Moving Average is already known for reacting more quickly to price changes compared to other moving averages while retaining a degree of smoothness. This suite enhances the basic HMA by showing colored gradients that make it easy to spot trend direction changes, highlighting potential entry or exit points based on volatility-driven thresholds, and optionally layering a volume-based measure of bullish or bearish market sentiment. By relying on a zero lag approach and additional data points, the script caters to those wanting a more responsive method of identifying shifts in market dynamics. The added reversal signals and up or down alerts give traders extra confirmation for potential turning points.
5. How This Extension Improves on the Basic HMA
This extension not only plots the Hull Moving Average but also includes data-driven alerts and visual cues that traditional HMA lines do not provide. First, it offers multi-layered slope coloring, making up or down trends quickly apparent. Second, it uses ATR-based thresholds to pinpoint moments when price may be extending beyond normal volatility, thus generating buy or sell signals. Third, the script introduces an optional VWAP ribbon to indicate whether the market is trading above or below this pivotal volume-weighted benchmark, adding a further confirmation step for bullish or bearish conditions. Finally, it incorporates optional reversal signals labeled with B, indicating points where price might swing back toward the main HMA line.
6. Core Components
The script can be broken down into several primary functions and features.
a. Zero Lag HMA Calculation
Uses two Weighted Moving Averages (half-length and full-length) combined through a smoothing step based on the square root of the chosen length. This approach is designed to reduce lag significantly compared to other moving averages.
b. Slope Detection
Compares current and prior HMA values to determine if the trend is up or down. The slope-based coloring changes between turquoise shades for upward movement and magenta shades for downward movement, making trend direction immediately visible.
c. ATR-Based Thresholding for Up and Down Signals
The script calculates an Average True Range over a user-defined period, then multiplies it by a signal factor to form two bands around the HMA. When price crosses below the lower band, an up (buy) signal appears; when it crosses above the upper band, a down (sell) signal is shown.
d. Reversal Signals (B Labels)
Tracks when price transitions back toward the main HMA from an extreme zone. When enabled, these reversal points are labeled with a B and can help traders see potential turning points or mean-reversion setups.
e. VWAP Bands
An optional Volume Weighted Average Price ribbon that plots above or below the HMA, indicating bullish or bearish conditions relative to a volume-weighted price benchmark. This can also act as a kind of support/ resistance.
7. User Inputs
a. HMA Length
Controls how quickly the moving average responds to price changes. Shorter lengths react faster but can lead to more frequent signals, whereas longer lengths produce smoother lines.
b. Source
Specifies the price input, such as close or an alternative source, for the calculation. This can help align the HMA with specific trading strategies.
c. ATR Length and Signal Multiplier
Defines how the script calculates average volatility and sets thresholds for buy or sell alerts. Adjusting these values can help filter out noise or highlight more aggressive signals.
d. Slope Index
Determines how many bars to look back for detecting slope direction, influencing how sensitive the slope coloring is to small fluctuations.
e. Show Buy and Sell Signals, Reversal Signals, and VWAP
Lets users toggle the display of these features. Turning off certain elements can reduce chart clutter if traders prefer a simpler layout.
8. Calculation Process
The script’s calculation follows a step-by-step approach. It first computes two Weighted Moving Averages of the selected price source, one over half the specified length and one over the full length. It then combines these using 2*wma1 minus wma2 to reduce lag, followed by applying another weighted average using the square root of the length. Simultaneously, it computes the ATR for a user-defined period. By multiplying ATR by the signal multiplier, it establishes upper and lower bands around the HMA, where crossovers generate buy (up) or sell (down) signals. The script can also plot reversal signals (B labels) when price crosses back from these bands in the opposite direction. For the optional VWAP feature, Pine Script’s ta.vwap function is used, and differences between the HMA and VWAP levels determine the color and opacity of the ribbon.
9. Signal Generation and Filtering
The ATR-based thresholds reduce the influence of small, inconsequential price swings. When price falls below the lower band, the script issues an up (buy) signal. If price breaks above the upper band, a down (sell) signal appears. These signals are visible through labels placed near the bars. Reversal signals, labeled with B, can be turned on to help detect when price retraces from an extended area back toward the main HMA line. Traders can disable or enable these signals to match their preferred level of chart detail or risk tolerance.
10. Visualization on the Chart
The Zero HMA Lag Trend Suite aims for visual clarity. The HMA line is plotted multiple times with increasing transparency to create a gradient effect. Turquoise gradients indicate upward slopes, and magenta gradients signify downward slopes. Bar coloring can be configured to align with the slope direction, providing quick insight into current momentum. When enabled, buy or sell labels are placed under or above the bars as price crosses the ATR-defined boundaries. If the reversal option is active, B labels appear around areas where price changes direction. The optional VWAP ribbons form background bands, using distinct coloration to signal whether price is above or below the volume-weighted metric.
11. Market Adaptability
Because the script’s parameters (HMA length, ATR length, signal multiplier, and slope index) are user-configurable, it can adapt to a wide range of markets and timeframes. Intraday traders may prefer a shorter HMA length for quick signals, while swing or position traders might use a longer HMA length to filter out short-lived price changes. The source setting can also be adjusted, allowing for specialized data inputs beyond just close or open values.
12. Risk Management Considerations
The script’s signals and labels are based on past price data and volatility readings, and they do not guarantee profitable outcomes. Sharp market reversals or unforeseen fundamental events can produce false signals. Traders should combine this tool with broader risk management strategies, including stop-loss placement, position sizing, and independent market analyses. The Zero HMA Lag Trend Suite can help highlight potential opportunities, but it should not be relied upon as the sole basis for trade decisions.
13. Combining with Other Tools
Many traders choose to verify signals from the Zero HMA Lag Trend Suite using popular indicators like the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), or even simple volume-based metrics to confirm whether a price movement has sufficient momentum. Conventional techniques such as support and resistance levels, chart patterns, or candlestick analysis can also supplement signals generated by the script’s up, down, or reversal B labels.
14. Parameter Customization and Examples
a. Short-Term Day Trading
Using a shorter HMA length (for instance, 9 or 14) and a slightly higher ATR multiplier might provide timely buy and sell signals, though it may also produce more whipsaws in choppy markets.
b. Swing or Position Trading
Selecting a longer HMA length (such as 50 or 100) with a moderate ATR multiplier can help users track more significant and sustained market moves, potentially reducing the effect of minor fluctuations.
c. Multiple Timeframe Blends
Some traders load two versions of the indicator on the same chart, one for short-term signals (with frequent B label reversals) and another for the broader trend direction, aligning entry and exit decisions with the bigger picture.
15. Realistic Expectations
Even though the Hull Moving Average helps minimize lag and the script incorporates volatility-based filters and optional VWAP overlays, it cannot predict future market behavior with complete accuracy. Periods of low liquidity or sudden market shocks can still lead to signals that do not reflect longer-term trends. Frequent parameter review and manual confirmation are advised before executing trades based solely on the script’s outputs.
16. Theoretical Background
The Hull Moving Average formula aims to balance smoothness with reactivity, accomplished by combining Weighted Moving Averages at varying lengths. By subtracting a slower average from a faster one and then applying another smoothing step with the square root of the original length, the HMA is designed to respond more promptly to price changes than typical exponential or simple moving averages. The ATR component, introduced by J. Welles Wilder, calculates the average range of price movement over a user-defined period, allowing the script to assess volatility and adapt signals accordingly. VWAP provides a volume-weighted benchmark that many institutional traders track to gauge fair intraday value.
17. Originality and Uniqueness
Although multiple HMA-based indicators can be found, Uptrick: Zero Lag HMA Trend Suite sets itself apart by merging slope-based coloring, ATR thresholds, VWAP ribbons, up or down labels, and optional reversal signals all in one cohesive platform. This synergy aims to reduce chart clutter while still giving traders a comprehensive look at trend direction, volatility, and volume-based sentiment.
18. Summary
Uptrick: Zero Lag HMA Trend Suite is a specialized trading script designed to highlight potential market trends and reversals with minimal delay. It leverages the Hull Moving Average for an adaptive yet smooth price line, pairs ATR-based thresholds for detecting possible breakouts or dips, and provides VWAP-based ribbons for added volume-weighted context. Traders can further refine their entries and exits by enabling up or down signals and reversal labels (B) where price may revert toward the HMA. Suitable for a wide range of timeframes and instrument types, the script encourages a disciplined approach to trade management and risk control.
19. Disclaimer
This script is provided for informational and educational purposes only. Trading and investing involve significant financial risk, and no indicator can guarantee success under all conditions. Users should practice robust risk management, including the placement of stop losses and position sizing, and should confirm signals with additional analysis tools. The developer of this script assumes no liability for any trading decisions or outcomes resulting from its use.
NVOL Normalized Volume & VolatilityOVERVIEW
Plots a normalized volume (or volatility) relative to a given bar's typical value across all charted sessions. The concept is similar to Relative Volume (RVOL) and Average True Range (ATR), but rather than using a moving average, this script uses bar data from previous sessions to more accurately separate what's normal from what's anomalous. Compatible on all timeframes and symbols.
Having volume and volatility processed within a single indicator not only allows you to toggle between the two for a consistent data display, it also allows you to measure how correlated they are. These measurements are available in the data table.
DATA & MATH
The core formula used to normalize each bar is:
( Value / Basis ) × Scale
Value
The current bar's volume or volatility (see INPUTS section). When set to volume, it's exactly what you would expect (the volume of the bar). When set to volatility, it's the bar's range (high - low).
Basis
A statistical threshold (Mean, Median, or Q3) plus a Sigma multiple (standard deviations). The default is set to the Mean + Sigma × 3 , which represents 99.7% of data in a normal distribution. The values are derived from the current bar's equivalent in other sessions. For example, if the current bar time is 9:30 AM, all previous 9:30 AM bars would be used to get the Mean and Sigma. Thus Mean + Sigma × 3 would represent the Normal Bar Vol at 9:30 AM.
Scale
Depends on the Normalize setting, where it is 1 when set to Ratio, and 100 when set to Percent. This simply determines the plot's scale (ie. 0 to 1 vs. 0 to 100).
INPUTS
While the default configuration is recommended for a majority of use cases (see BEST PRACTICES), settings should be adjusted so most of the Normalized Plot and Linear Regression are below the Signal Zone. Only the most extreme values should exceed this area.
Normalize
Allows you to specify what should be normalized (Volume or Volatility) and how it should be measured (as a Ratio or Percentage). This sets the value and scale in the core formula.
Basis
Specifies the statistical threshold (Mean, Median, or Q3) and how many standard deviations should be added to it (Sigma). This is the basis in the core formula.
Mean is the sum of values divided by the quantity of values. It's what most people think of when they say "average."
Median is the middle value, where 50% of the data will be lower and 50% will be higher.
Q3 is short for Third Quartile, where 75% of the data will be lower and 25% will be higher (think three quarters).
Sample
Determines the maximum sample size.
All Charted Bars is the default and recommended option, and ignores the adjacent lookback number.
Lookback is not recommended, but it is available for comparisons. It uses the adjacent lookback number and is likely to produce unreliable results outside a very specific context that is not suitable for most traders. Normalization is not a moving average. Unless you have a good reason to limit the sample size, do not use this option and instead use All Charted Bars .
Show Vol. name on plot
Overlays "VOLUME" or "VOLATILITY" on the plot (whichever you've selected).
Lin. Reg.
Polynomial regressions are great for capturing non-linear patterns in data. TradingView offers a "linear regression curve", which this script uses as a substitute. If you're unfamiliar with either term, think of this like a better moving average.
You're able to specify the color, length, and multiple (how much to amplify the value). The linear regression derives its value from the normalized values.
Norm. Val.
This is the color of the normalized value of the current bar (see DATA & MATH section). You're able to specify the default, within signal, and beyond signal colors. As well as the plot style.
Fade in colors between zero and the signal
Programmatically adjust the opacity of the primary plot color based on it's normalized value. When enabled, values equal to 0 will be fully transparent, become more opaque as they move away from 0, and be fully opaque at the signal. Adjusting opacity in this way helps make difference more obvious.
Plot relative to bar direction
If enabled, the normalized value will be multiplied by -1 when a bar's open is greater than the bar's close, mirroring price direction.
Technically volume and volatility are directionless. Meaning there's really no such thing as buy volume, sell volume, positive volatility, or negative volatility. There is just volume (1 buy = 1 sell = 1 volume) and volatility (high - low). Even so, visually reflecting the net effect of pricing pressure can still be useful. That's all this setting does.
Sig. Zone
Signal zones make identifying extremes easier. They do not signal if you should buy or sell, only that the current measurement is beyond what's normal. You are able to adjust the color and bounds of the zone.
Int. Levels
Interim levels can be useful when you want to visually bracket values into high / medium / low. These levels can have a value anywhere between 0 and 1. They will automatically be multiplied by 100 when the scale is set to Percent.
Zero Line
This setting allows you to specify the visibility of the zero line to best suit your trading style.
Volume & Volatility Stats
Displays a table of core values for both volume and volatility. Specifically the actual value, threshold (mean, median, or Q3), sigma (standard deviation), basis, normalized value, and linear regression.
Correlation Stats
Displays a table of correlation statistics for the current bar, as well as the data set average. Specifically the coefficient, R2, and P-Value.
Indices & Sample Size
Displays a table of mixed data. Specifically the current bar's index within the session, the current bar's index within the sample, and the sample size used to normalize the current bar's value.
BEST PRACTICES
NVOL can tell you what's normal for 9:30 AM. RVOL and ATR can only tell you if the current value is higher or lower than a moving average.
In a normal distribution (bell curve) 99.7% of data occurs within 3 standard deviations of the mean. This is why the default basis is set to "Mean, 3"; it includes the typical day-to-day fluctuations, better contextualizing what's actually normal, minimizing false positives.
This means a ratio value greater than 1 only occurs 0.3% of the time. A series of these values warrants your attention. Which is why the default signal zone is between 1 and 2. Ratios beyond 2 would be considered extreme with the default settings.
Inversely, ratio values less than 1 (the normal daily fluctuations) also tell a story. We should expect most values to occur around the middle 3rd, which is why interim levels default to 0.33 and 0.66, visually simplifying a given move's participation. These can be set to whatever you like and only serve as visual aids for your specific trading style.
It's worth noting that the linear regression oscillates when plotted directionally, which can help clarify short term move exhaustion and continuation. Akin to a relative strength index (RSI), it may be used to inform a trading decision, but it should not be the only factor.
Bewakoof stock indicator**Title**: "Bewakoof Stock Indicator: Multi-Timeframe RSI and SuperTrend Entry-Exit System"
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### Description
The **Bewakoof Stock Indicator** is an original trading tool that combines multi-timeframe RSI analysis with the SuperTrend indicator to create reliable entry and exit signals for trending markets. This indicator is designed for traders looking to follow strong trends with built-in risk management. By filtering entries through short- and long-term momentum and utilizing dynamic trailing exits, this indicator provides a structured approach to trading.
#### Indicator Components
1. **Multi-Timeframe RSI Analysis**:
- The Relative Strength Index (RSI) is calculated across three timeframes: Daily, Weekly, and Monthly.
- By examining multiple timeframes, the indicator confirms that trends align over short, medium, and long-term intervals, making buy signals more reliable.
- **Buy Condition**: All three RSI values must meet these thresholds:
- **Daily RSI > 50** – indicates short-term upward momentum,
- **Weekly RSI > 60** – signals medium-term strength,
- **Monthly RSI > 60** – confirms long-term trend alignment.
- This filtering process ensures that buy signals are generated only in stable, upward-trending markets.
2. **SuperTrend Confirmation**:
- The SuperTrend (20-period ATR with a multiplier of 2) acts as a trend filter and trailing stop mechanism.
- For a buy condition to be valid, the closing price must be above the SuperTrend level, verifying that the market is trending up.
- The combination of RSI and SuperTrend helps to avoid false signals, focusing only on well-established trends.
#### Trade Signals
- **Buy Signal**: When both the multi-timeframe RSI and SuperTrend conditions are met, a buy signal is triggered, indicated by a “BUY” label on the chart with details:
- **Entry Price**,
- **Initial Stop-Loss** (set at the SuperTrend level for risk control),
- **Target 1** – calculated with a 1:1 risk-reward ratio based on the initial stop-loss,
- **Target 2** – calculated with a 1:2 risk-reward ratio based on the initial stop-loss.
- **Exit Signals**: This indicator provides two exit strategies to protect profits:
1. **Fixed Stop-Loss**: Automatically set at the SuperTrend level at the time of entry to limit risk.
2. **Trailing Exit**: Exits are triggered if the price crosses below the SuperTrend level, adapting to potential trend reversals.
#### Labeling & Alerts
The **Bewakoof Stock Indicator** offers intuitive labeling and alert options:
- **Labels**: Buy and exit points are clearly marked, showing entry, stop-loss, and targets directly on the chart.
- **Alerts**: Custom alerts can be set for:
- **Buy signals** when both conditions are met, and
- **Exit signals** triggered by the stop-loss or trailing exit.
#### Use Case and Benefits
This indicator is ideal for trend-following traders who value risk control and trend confirmation:
- **Stronger Trend Signals**: By requiring RSI alignment across multiple timeframes, this indicator focuses only on trades with strong trend momentum.
- **Dynamic Risk Management**: Using both fixed and trailing exits enables flexible trade management, balancing risk and potential reward.
- **Simple Trade Execution**: The chart labels and alerts simplify trade decisions, making it easy to enter, manage, and exit trades.
#### How to Use
1. **Add** the Bewakoof Stock Indicator to your chart.
2. **Watch** for the "BUY" label as your entry point.
3. **Manage the trade** using the labeled stop-loss and target levels.
4. **Exit** on either a stop-loss hit or when the price crosses below the SuperTrend for a trailing exit.
The **Bewakoof Stock Indicator** is a complete solution for trend-following traders, combining the strength of multi-timeframe RSI with the SuperTrend’s trend-following capabilities. This systematic approach aims to provide high-confidence entries and effective risk management, empowering traders to follow trends with precision and control.
FMS Suite [KFB Quant]FMS Suite
Overview
The FMS Suite is a powerful and adaptive trend and momentum analysis tool that leverages multiple technical indicators to deliver a comprehensive signal for market direction. This suite combines the strengths of the Aroon, DMI, RSI, Supertrend, and Trix indicators, offering traders a well-rounded perspective on market trends.
How It Works
The FMS Suite integrates five essential components to assess market behavior:
Aroon Indicator : Detects trend strength and direction by analyzing the frequency of recent highs and lows over multiple timeframes. Directional Movement Index (DMI) : Measures the direction and strength of trends, with an ADX component for better trend assessment. Relative Strength Index (RSI) : Evaluates market momentum by indicating overbought or oversold conditions, with signals derived from the 50-line. Supertrend : Utilizes ATR-based volatility measures to establish dynamic support and resistance levels, signaling potential trend changes. Trix : A triple-smoothed EMA oscillator that highlights trend reversals using rate-of-change dynamics.
Each component is calculated across three separate timeframes (fast, medium, and slow), which are then averaged to produce a final FMS Signal . Users can also apply signal smoothing to reduce noise and enhance clarity.
Key Features
Customizable Parameters : Adjust the lengths for each component (fast, medium, slow) to optimize the indicator's responsiveness to different markets. Signal Smoothing Options : Select from various smoothing methods, including SMA, EMA, DEMA, and WMA, to fine-tune the FMS signal. Visual Representation : The FMS Suite plots a histogram representing the raw signal and a smoother line for clearer trend visualization. The background color shifts dynamically to indicate long, short, or neutral conditions. Threshold-Based Alerts : Set your own long and short thresholds, tailoring the indicator to your trading strategy and market outlook. Informative Table Display : An integrated table provides an at-a-glance summary of the current FMS and smoothed FMS signals, along with their respective scores and market state.
How to Use
Trend Confirmation : Utilize the FMS histogram and smoothed signal to validate or challenge existing trend assumptions. Trade Entries and Exits : Identify potential buy (long) or sell (short) signals based on the relationship between the FMS signal and predefined thresholds. Strategy Customization : Fine-tune the indicator settings to align with your trading style, whether it’s short-term scalping or long-term trend following.
Important Considerations
Not Predictive : The FMS Suite does not predict future price movements and should be used in conjunction with other analysis methods. It is based on historical price data, and past performance is not indicative of future results. Settings and Backtesting : Experiment with different lengths and smoothing techniques to optimize performance for specific instruments and market conditions. Always backtest thoroughly.
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.
RSI Weighted Trend System I [InvestorUnknown]The RSI Weighted Trend System I is an experimental indicator designed to combine both slow-moving trend indicators for stable trend identification and fast-moving indicators to capture potential major turning points in the market. The novelty of this system lies in the dynamic weighting mechanism, where fast indicators receive weight based on the current Relative Strength Index (RSI) value, thus providing a flexible tool for traders seeking to adapt their strategies to varying market conditions.
Dynamic RSI-Based Weighting System
The core of the indicator is the dynamic weighting of fast indicators based on the value of the RSI. In essence, the higher the absolute value of the RSI (whether positive or negative), the higher the weight assigned to the fast indicators. This enables the system to capture rapid price movements around potential turning points.
Users can choose between a threshold-based or continuous weight system:
Threshold-Based Weighting: Fast indicators are activated only when the absolute RSI value exceeds a user-defined threshold. Below this threshold, fast indicators receive no weight.
Continuous Weighting: By setting the weight threshold to zero, the fast indicators always receive some weight, although this can result in more false signals in ranging markets.
// Calculate weight for Fast Indicators based on RSI (Slow Indicator weight is kept to 1 for simplicity)
f_RSI_Weight_System(series float rsi, simple float weight_thre) =>
float fast_weight = na
float slow_weight = na
if weight_thre > 0
if math.abs(rsi) <= weight_thre
fast_weight := 0
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(rsi))
slow_weight := 1
else
fast_weight := 0 + math.sqrt(math.abs(rsi))
slow_weight := 1
Slow and Fast Indicators
Slow Indicators are designed to identify stable trends, remaining constant in weight. These include:
DMI (Directional Movement Index) For Loop
CCI (Commodity Channel Index) For Loop
Aroon For Loop
Fast Indicators are more responsive and designed to spot rapid trend shifts:
ZLEMA (Zero-Lag Exponential Moving Average) For Loop
IIRF (Infinite Impulse Response Filter) For Loop
Each of these indicators is calculated using a for-loop method to generate a moving average, which captures the trend of a given length range.
RSI Normalization
To facilitate the weighting system, the RSI is normalized from its usual 0-100 range to a -1 to 1 range. This allows for easy scaling when calculating weights and helps the system adjust to rapidly changing market conditions.
// Normalize RSI (1 to -1)
f_RSI(series float rsi_src, simple int rsi_len, simple string rsi_wb, simple string ma_type, simple int ma_len) =>
output = switch rsi_wb
"RAW RSI" => ta.rsi(rsi_src, rsi_len)
"RSI MA" => ma_type == "EMA" ? (ta.ema(ta.rsi(rsi_src, rsi_len), ma_len)) : (ta.sma(ta.rsi(rsi_src, rsi_len), ma_len))
Signal Calculation
The final trading signal is a weighted average of both the slow and fast indicators, depending on the calculated weights from the RSI. This ensures a balanced approach, where slow indicators maintain overall trend guidance, while fast indicators provide timely entries and exits.
// Calculate Signal (as weighted average)
sig = math.round(((DMI*slow_w) + (CCI*slow_w) + (Aroon*slow_w) + (ZLEMA*fast_w) + (IIRF*fast_w)) / (3*slow_w + 2*fast_w), 2)
Backtest Mode and Performance Metrics
This version of the RSI Weighted Trend System includes a comprehensive backtesting mode, allowing users to evaluate the performance of their selected settings against a Buy & Hold strategy. The backtesting includes:
Equity calculation based on the signals generated by the indicator.
Performance metrics table comparing Buy & Hold strategy metrics with the system’s signals, including: Mean, positive, and negative return percentages, Standard deviations (of all, positive and negative returns), Sharpe Ratio, Sortino Ratio, and Omega Ratio
f_PerformanceMetrics(series float base, int Lookback, simple float startDate, bool Annualize = true) =>
// Initialize variables for positive and negative returns
pos_sum = 0.0
neg_sum = 0.0
pos_count = 0
neg_count = 0
returns_sum = 0.0
returns_squared_sum = 0.0
pos_returns_squared_sum = 0.0
neg_returns_squared_sum = 0.0
// Loop through the past 'Lookback' bars to calculate sums and counts
if (time >= startDate)
for i = 0 to Lookback - 1
r = (base - base ) / base
returns_sum += r
returns_squared_sum += r * r
if r > 0
pos_sum += r
pos_count += 1
pos_returns_squared_sum += r * r
if r < 0
neg_sum += r
neg_count += 1
neg_returns_squared_sum += r * r
float export_array = array.new_float(12)
// Calculate means
mean_all = math.round((returns_sum / Lookback) * 100, 2)
mean_pos = math.round((pos_count != 0 ? pos_sum / pos_count : na) * 100, 2)
mean_neg = math.round((neg_count != 0 ? neg_sum / neg_count : na) * 100, 2)
// Calculate standard deviations
stddev_all = math.round((math.sqrt((returns_squared_sum - (returns_sum * returns_sum) / Lookback) / Lookback)) * 100, 2)
stddev_pos = math.round((pos_count != 0 ? math.sqrt((pos_returns_squared_sum - (pos_sum * pos_sum) / pos_count) / pos_count) : na) * 100, 2)
stddev_neg = math.round((neg_count != 0 ? math.sqrt((neg_returns_squared_sum - (neg_sum * neg_sum) / neg_count) / neg_count) : na) * 100, 2)
// Calculate probabilities
prob_pos = math.round((pos_count / Lookback) * 100, 2)
prob_neg = math.round((neg_count / Lookback) * 100, 2)
prob_neu = math.round(((Lookback - pos_count - neg_count) / Lookback) * 100, 2)
// Calculate ratios
sharpe_ratio = math.round(mean_all / stddev_all * (Annualize ? math.sqrt(Lookback) : 1), 2)
sortino_ratio = math.round(mean_all / stddev_neg * (Annualize ? math.sqrt(Lookback) : 1), 2)
omega_ratio = math.round(pos_sum / math.abs(neg_sum), 2)
// Set values in the array
array.set(export_array, 0, mean_all), array.set(export_array, 1, mean_pos), array.set(export_array, 2, mean_neg),
array.set(export_array, 3, stddev_all), array.set(export_array, 4, stddev_pos), array.set(export_array, 5, stddev_neg),
array.set(export_array, 6, prob_pos), array.set(export_array, 7, prob_neu), array.set(export_array, 8, prob_neg),
array.set(export_array, 9, sharpe_ratio), array.set(export_array, 10, sortino_ratio), array.set(export_array, 11, omega_ratio)
// Export the array
export_array
The metrics help traders assess the effectiveness of their strategy over time and can be used to optimize their settings.
Calibration Mode
A calibration mode is included to assist users in tuning the indicator to their specific needs. In this mode, traders can focus on a specific indicator (e.g., DMI, CCI, Aroon, ZLEMA, IIRF, or RSI) and fine-tune it without interference from other signals.
The calibration plot visualizes the chosen indicator's performance against a zero line, making it easy to see how changes in the indicator’s settings affect its trend detection.
Customization and Default Settings
Important Note: The default settings provided are not optimized for any particular market or asset. They serve as a starting point for experimentation. Traders are encouraged to calibrate the system to suit their own trading strategies and preferences.
The indicator allows deep customization, from selecting which indicators to use, adjusting the lengths of each indicator, smoothing parameters, and the RSI weight system.
Alerts
Traders can set alerts for both long and short signals when the indicator flips, allowing for automated monitoring of potential trading opportunities.
Rsi Long-Term Strategy [15min]Hello, I would like to present to you The "RSI Long-Term Strategy" for 15min tf
The "RSI Long-Term Strategy " is designed for traders who prefer a combination of momentum and trend-following techniques. The strategy focuses on entering long positions during significant market corrections within an overall uptrend, confirmed by both RSI and volume. The use of long-term SMAs ensures that trades are made in line with the broader market trend. The stop-loss feature provides risk management by limiting losses on trades that do not perform as expected. This strategy is particularly well-suited for longer-term traders who monitor 15-minute charts but look for substantial trend reversals or continuations.
Indicators and Parameters:
Relative Strength Index (RSI):
- The RSI is calculated using a 10-period length. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions. The script defines oversold conditions when the RSI is at or below 30 and overbought conditions when the RSI is at or above 70.
Volume Condition:
-The strategy incorporates a volume condition where the current volume must be greater than 2.5 times the 20-period moving average of volume. This is used to confirm the strength of the price movement.
Simple Moving Averages (SMA):
- The strategy uses two SMAs: SMA1 with a length of 250 periods and SMA2 with a length of 500 periods. These SMAs help identify long-term trends and generate signals based on their crossover.
Strategy Logic:
Entry Logic:
A long position is initiated when all the following conditions are met:
The RSI indicates an oversold condition (RSI ≤ 30).
SMA1 is above SMA2, indicating an uptrend.
The volume condition is satisfied, confirming the strength of the signal.
Exit Logic:
The strategy closes the long position when SMA1 crosses under SMA2, signaling a potential end of the uptrend (a "Death Cross").
Stop-Loss:
A stop-loss is set at 5% below the entry price to manage risk and limit potential losses.
Buy and sell signals are highlighted with circles below or above bars:
Green Circle : Buy signal when RSI is oversold, SMA1 > SMA2, and the volume condition is met.
Red Circle : Sell signal when RSI is overbought, SMA1 < SMA2, and the volume condition is met.
Black Cross: "Death Cross" when SMA1 crosses under SMA2, indicating a potential bearish signal.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
BabyShark VWAP Strategy What the code does:
This Pine Script implements a trading strategy based on two indicators: Volume Weighted Average Price (VWAP) and On Balance Volume (OBV) Relative Strength Index (RSI). The strategy aims to identify potential buy and sell signals based on deviations from VWAP and OBV RSI crossing certain threshold levels.
How it does it:
**VWAP Calculation**: The script calculates the VWAP using either standard deviation or average deviation over a specified length. It then plots the VWAP and its upper and lower deviation bands.
**OBV RSI Calculation**: It computes the OBV and then calculates the RSI using the cumulative changes in OBV. The RSI is plotted and compared against predefined levels.
**Table Visibility and Occurrence Counting**: It allows the user to display a table showing the number of occurrences where the price is above Upper Dev 2, below Lower Dev 2, crosses above a higher RSI level, or crosses below a lower RSI level.
**Entries**: Long and short entry conditions are defined based on the position of the price relative to the VWAP deviation bands and the color of the OBV RSI. Entries are made when specific conditions are met, and there hasn't been a recent entry.
**Exit Conditions**: The script includes stop-loss and take-profit mechanisms. It exits positions based on price crossing the VWAP or a certain percentage, and it prevents further trading after a certain number of consecutive losses.
What traders can use it for:
**Trend Identification**: Traders can use the VWAP and its deviation bands to identify potential trend reversals or continuations.
**Volume Confirmation**: The inclusion of OBV RSI provides confirmation of price movements based on volume changes.
**Entry and Exit Signals**: The script generates buy and sell signals based on the specified conditions, allowing traders to enter and exit positions with defined stop-loss and take-profit levels.
**Statistical Analysis**: The visibility of occurrence counts in the table allows traders to perform statistical analysis on the frequency of price movements relative to the VWAP and OBV RSI levels.
Unbound RSIUnbound RSI
Description
The Unbound RSI or de-oscillated RSI indicator is a novel technical analysis indicator that combines the concepts of the Relative Strength Index (RSI) and moving averages, applied directly over the price chart. This indicator is unique in its approach by transforming the oscillatory nature of the RSI into a format that aligns with the price action, thereby offering a distinctive view of market momentum and trends.
Key Features
Multi-Length RSI Analysis: Incorporates three different lengths of RSI (short, medium, and long), providing insights into the momentum and trend strength at various timeframes.
Deoscillation of RSI: The RSI for each length is 'deoscillated' by adjusting its scale to align with the actual price movements. This is achieved by shifting and scaling the RSI values, effectively merging them with the price line.
Average True Range (ATR) Scaling: The deoscillation process includes scaling by the Average True Range (ATR), making the indicator responsive to the asset’s volatility.
Optional Smoothing: Provides an option to apply a simple moving average (SMA) smoothing to each deoscillated RSI line, reducing noise and highlighting more significant trends.
Dynamic Moving Average (MA) Baseline: Features a moving average calculated from the medium length (default value) de-oscillated RSI, serving as a dynamic baseline to identify overarching trends.
How It’s Different
Unlike standard RSI indicators that oscillate in a fixed range, this indicator transforms the RSI to move in tandem with the price, offering a unique perspective on momentum and trend changes. The use of multiple timeframes for RSI and the inclusion of a dynamic MA baseline provide a multifaceted view of market conditions.
Potential Usage
Trend Identification: The position of the price in relation to the different deoscillated RSI lines and the MA baseline can indicate the prevailing market trend.
Momentum Shifts: Crossovers of the price with the deoscillated RSI lines or the MA baseline can signal potential shifts in momentum, offering entry or exit points.
Volatility Awareness: The ATR-based scaling of the deoscillated RSI lines means the indicator adjusts to changes in volatility, potentially offering more reliable signals in different market conditions.
Comparative Analysis: By comparing the short, medium, and long deoscillated RSI lines, traders can gauge the strength of trends and the convergence or divergence of momentum across timeframes.
Best Practices
Backtesting: Given its novel nature, it’s crucial to backtest the indicator across different assets and market conditions.
Complementary Tools: Combine with other technical analysis tools (like support/resistance levels, other oscillators, volume analysis) for more robust trading signals.
Risk Management: Always use sound risk management strategies, as no single indicator provides foolproof signals.
Unified Composite Index [UCI] [KuraiBlu] [LazyBear]The purpose of this indicator is to combine the four basic types of indicators (Trend, Volatility, Momentum and Volume) to create a singular, composite index in order to provide a more holistic means of observing potential changes within the market, known as the Unified Composite Index . The indicators used in this index are as follows:
Trend - Trend Composite Index
Volatility - Bollinger Bands %b
Momentum - Relative Strength Index
Volume - Money Flow Index
The average price source can’t be altered as I’ve made it an average between ((open + close) / 2) and ((high + low) / 2).
The best way to use this is by observing several of the indicators at once in conjunction with the average, rather than simply using the average produced to determine the right moment to enter, or exit a trade by itself. I've found when one indicator goes way out of bounds relative to the other three (and subsequently, the average array), then it presents a good buying, or selling opportunity.
Some adjustments were made to several of the indicators in order to standardize them on a scale of 1-100 so that they could better accommodate the average array that was finally produced. Thanks to LazyBear for letting me strip down the WaveTrend Oscillator.
Coppock Curve with Pivot Points and Divergence The Coppock Curve is a long-term price momentum indicator used primarily to recognize major downturns and upturns in a stock market index. It is calculated as a 10-month weighted moving average of the sum of the 14-month rate of change and the 11-month rate of change for the index. It is also known as the "Coppock Guide."
The Coppock formula was introduced in Barron's in 1962 by Edwin Coppock.
The Coppock Curve is a technical indicator that provides long-term buy and sell signals for major stock indexes and related ETFs based on shifts in momentum.
What Does the Coppock Curve Tell You?
The Coppock Curve was originally implemented as a long-term buy and sell indicator for major indices such as the S&P 500 and the Wilshire 5000. Often, it is used with long-term time series such as a candlestick chart, but where each candle contains a month's worth of price information.
The Difference Between the Coppock Curve and Rate of Relative Strength Index (RSI)?
The relative strength index looks at how the current price compares to prior prices, though it is calculated differently than the rate of change (ROC) indicator used in the Coppock Curve calculation. Therefore, these indicators will provide different trade signals and information.
What are those circles?
-These are Divergences. Red for Regular-Bearish. Orange for Hidden-Bearish. Green for Regular-Bullish. Aqua for Hidden-Bullish.
What are those triangles?
- These are Pivots . They show when the VPT oscillator might reverse, this is important to know because many times the price action follows this move.
Please keep in mind that this indicator is a tool and not a strategy, do not blindly trade signals, do your own research first! Use this indicator in conjunction with other indicators to get multiple confirmations.
Bollinger Band Width PercentileIntroducing the Bollinger Band Width Percentile
Definitions :
Bollinger Band Width Percentile is derived from the Bollinger Band Width indicator.
It shows the percentage of bars over a specified lookback period that the Bollinger Band Width was less than the current Bollinger Band Width.
Bollinger Band Width is derived from the Bollinger Bands® indicator.
It quantitatively measures the width between the Upper and Lower Bands of the Bollinger Bands.
Bollinger Bands® is a volatility-based indicator.
It consists of three lines which are plotted in relation to a security's price.
The Middle Line is typically a Simple Moving Average.
The Upper and Lower Bands are typically 2 standard deviations above, and below the SMA (Middle Line).
Volatility is a statistical measure of the dispersion of returns for a given security or market index, measured by the standard deviation of logarithmic returns.
The Broad Concept :
Quoting Tradingview specifically for commonly noted limitations of the BBW indicator which I have based this indicator on....
“ Bollinger Bands Width (BBW) outputs a Percentage Difference between the Upper Band and the Lower Band.
This value is used to define the narrowness of the bands.
What needs to be understood however is that a trader cannot simply look at the BBW value and determine if the Band is truly narrow or not.
The significance of an instruments relative narrowness changes depending on the instrument or security in question.
What is considered narrow for one security may not be for another.
What is considered narrow for one security may even change within the scope of the same security depending on the timeframe.
In order to accurately gauge the significance of a narrowing of the bands, a technical analyst will need to research past BBW fluctuations and price performance to increase trading accuracy. ”
Here I present the Bollinger Band Width Percentile as a refinement of the BBW to somewhat overcome the limitations cited above.
Much of the work researching past BBW fluctuations, and making relative comparisons is done naturally by calculating the Bollinger Band Width Percentile.
This calculation also means that it can be read in a similar fashion across assets, greatly simplifying the interpretation of it.
Plotted Components of the Bollinger Band Width Percentile indicator :
Scale High
Mid Line
Scale Low
BBWP plot
Moving Average 1
Moving Average 2
Extreme High Alert
Extreme Low Alert
Bollinger Band Width Percentile Properties:
BBWP Length
The time period to be used in calculating the Moving average which creates the Basis for the BBW component of the BBWP.
Basis Type
The type of moving average to be used as the Basis for the BBW component of the BBWP.
BBWP Lookback
The lookback period to be used in calculating the BBWP itself.
BBWP Plot settings
The BBWP plot settings give a choice between a user defined solid color, and a choice of "Blue Green Red", or "Blue Red" spectrum palettes.
Moving Averages
Has 2 Optional User definable and adjustable moving averages of the BBWP.
Visual Alerts
Optional User adjustable High and low Signal columns.
How to read the BBWP :
A BBWP read of 95 % ... means that the current BBW level is greater than 95% of the lookback period.
A BBWP read of 5 % .... means that the current BBW level is lower than 95% of the lookback period.
Proposed interpretations :
When the BBWP gets above 90 % and particularly when it hits 100% ... this can be a signal that volatility is reaching a maximum and that a macro High or Low is about to be set.
When the BBWP gets below 10 % and particularly when it hits 0% ...... this can be a signal that volatility is reaching a minimum and that there could be a violent range breakout into a trending move.
When the BBWP hits a low level < 5 % and then gets above its moving average ...... this can be an early signal that a consolidation phase is ending and a trending move is beginning.
When the BBWP hits a high level > 95 % and then falls below its moving average ... this can be an early signal that a trending move is ending and a consolidation phase is beginning.
Essential knowledge :
The BBWP was designed with the daily timeframe in mind, but technical analysists may find use for it on other time frames also.
High and Low BBWP readings do not entail any direction bias.
Deeper Concepts :
In finance, “mean reversion” is the assumption that a financial instrument's price will tend to move towards the average price over time.
If we apply that same logic to volatility as represented here by the Bollinger band width percentile, the assumption is that the Bollinger band width percentile will tend to contract from extreme highs, and expand from extreme lows over time corresponding to repeated phases of contraction and expansion of volatility.
It is clear that for most assets there are periods of directional trending behavior followed by periods of “consolidation” ( trading sideways in a range ).
This often ends with a tightening range under reducing volume and volatility ( popularly known as “the squeeze” ).
The squeeze typically ends with a “breakout” from the range characterized by a rapid increase in volume, and volatility when price action again trends directionally, and the cycle repeats.
Typical Use Cases :
The Bollinger Band Width Percentile may be especially useful for Options traders, as it can provide a bias for when Options are relatively expensive, or inexpensive from a Volatility (Vega) perspective.
When the Bollinger Band Width Percentile is relatively high ( 85 percentile or above ) it may be more advantageous to be a net seller of Vega.
When the Bollinger Band Width Percentile is relatively low ( 15 percentile or below ) it may be advantageous to be net long Vega.
Here we examine a number of actionable signals on BTCUSD daily timeframe using the BBWP and a momentum oscillator ( using the TSI here but can equally be used with Bollinger bands, moving averages, or the traders preferred momentum oscillator ).
In this first case we will examine how a spot trader and an options trader could each use a low BBWP read to alert them to a good potential trade setup.
note: using a period of 30 for both the Bollinger bands and the BBWP period ( approximately a month ) and a BBWP lookback of 350 ( approximately a year )
As we see the Bollinger Bands have gradually contracted while price action trended down and the BBWP also fell consistently while below its moving average ( denoting falling volatility ) down to an extremely low level <5% until it broke above its moving average along with a break of range to the upside ( signaling the end of the consolidation at a low level and the beginning of a new trending move to the upside with expanding volatility).
In this next case we will continue to follow the price action presuming that the traders have taken or locked in profit at reasonable take profit levels from the previous trade setup.
Here we see the contraction of the Bollinger bands, and the BBWP alongside price action breaking below the BB Basis giving a warning that the trending move to the upside is likely over.
We then see the BBWP rising and getting above its moving average while price action fails to get above the BB Basis, likewise the TSI fails to get above its signal line and actually crosses below its zeroline.
The trader would normally take this as a signal that the next trending move could be to the downside.
The next trending move turns out to be a dramatic downside move which causes the BBWP to hit 100% signaling that volatility is likely to hit a maximum giving good opportunities for profitable trades to the skilled trader as outlined.
Limitations :
Here we will look at 2 cases where blindly taking BBWP signals could cause the trader to take a failed trade.
In this first example we will look at blindly taking a low volatility options trade
Low Volatility and corresponding low BBWP levels do not automatically mean there has to be expansion immediately, these periods of extreme low volatility can go on for quite some time.
In this second example we will look at blindly taking a high volatility spot short trade
High volatility and corresponding high BBWP levels do not automatically mean there has to be a macro high and contraction of volatility immediately, these periods of extreme high volatility can also go on for quite some time, hence the famous saying "The trend is your friend until the end of the trend" and lesser well known, but equally valid saying "never try to short the top of a parabolic blow off top"
Markets are variable and past performance is no guarantee of future results, this is not financial advice, I am not a financial advisor.
Final thoughts
The BBWP is an improvement over the BBW in my opinion, and is a novel, and useful addition to a Technical Analysts toolkit.
It is not a standalone indicator and is meant to be used in conjunction with other tools for direction bias, and Good Risk Management to base sound trades off.
John Bollinger has suggested using Bolliger bands, and its related indicators with two or three other non-correlated indicators that provide more direct market signals.
He believes it is crucial to use indicators based on different types of data.
Some of his favored technical techniques are moving average divergence/convergence (MACD), on-balance volume and relative strength index (RSI).
Thanks
Massive respect to John Bollinger, long-time technician of the markets, and legendary creator of both the Bollinger Bands® in the 1980´s, and the Bollinger band Width indicator in 2010 which this indicator is based on.
His work continues to inspire, decades after he brought the original Bollinger Bands to the market.
Much respect also to Eric Crown who gave me the fundamental knowledge of Technical Analysis, and Options trading.
Clustering & Divergences (RSI-Stoch-CCI) [Sam SDF-Solutions]The Clustering & Divergences (RSI-Stoch-CCI) indicator is a comprehensive technical analysis tool that consolidates three popular oscillators—Relative Strength Index (RSI), Stochastic, and Commodity Channel Index (CCI)—into one unified metric called the Score. This Score offers traders an aggregated view of market conditions, allowing them to quickly identify whether the market is oversold, balanced, or overbought.
Functionality:
Oscillator Clustering: The indicator calculates the values of RSI, Stochastic, and CCI using user-defined periods. These oscillator values are then normalized using one of three available methods: MinMax, Z-Score, or Z-Bins.
Score Calculation: Each normalized oscillator value is multiplied by its respective weight (which the user can adjust), and the weighted values are summed to generate an overall Score. This Score serves as a single, interpretable metric representing the combined oscillator behavior.
Market Clustering: The indicator performs clustering on the Score over a configurable window. By dividing the Score range into a set number of clusters (also configurable), the tool visually represents the market’s state. Each cluster is assigned a unique color so that traders can quickly see if the market is trending toward oversold, balanced, or overbought conditions.
Divergence Detection: The script automatically identifies both Regular and Hidden divergences between the price action and the Score. By using pivot detection on both price and Score data, the indicator marks potential reversal signals on the chart with labels and connecting lines. This helps in pinpointing moments when the price and the underlying oscillator dynamics diverge.
Customization Options: Users have full control over the indicator’s behavior. They can adjust:
The periods for each oscillator (RSI, Stochastic, CCI).
The weights applied to each oscillator in the Score calculation.
The normalization method and its manual boundaries.
The number of clusters and whether to invert the cluster order.
Parameters for divergence detection (such as pivot sensitivity and the minimum/maximum bar distance between pivots).
Visual Enhancements:
Depending on the user’s preference, either the Score or the Cluster Index (derived from the clustering process) is plotted on the chart. Additionally, the script changes the color of the price bars based on the identified cluster, providing an at-a-glance visual cue of the current market regime.
Logic & Methodology:
Input Parameters: The script starts by accepting user inputs for clustering settings, oscillator periods, weights, divergence detection, and manual boundary definitions for normalization.
Oscillator Calculation & Normalization: It computes RSI, Stochastic, and CCI values from the price data. These values are then normalized using either the MinMax method (scaling between a lower and upper band) or the Z-Score method (standardizing based on mean and standard deviation), or using Z-Bins for an alternative scaling approach.
Score Computation: Each normalized oscillator is multiplied by its corresponding weight. The sum of these products results in the overall Score that represents the combined oscillator behavior.
Clustering Algorithm: The Score is evaluated over a moving window to determine its minimum and maximum values. Using these values, the script calculates a cluster index that divides the Score into a predefined number of clusters. An option to invert the cluster calculation is provided to adjust the interpretation of the clustering.
Divergence Analysis: The indicator employs pivot detection (using left and right bar parameters) on both the price and the Score. It then compares recent pivot values to detect regular and hidden divergences. When a divergence is found, the script plots labels and optional connecting lines to highlight these key moments on the chart.
Plotting: Finally, based on the user’s selection, the indicator plots either the Score or the Cluster Index. It also overlays manual boundary lines (for the chosen normalization method) and adjusts the bar colors according to the cluster to provide clear visual feedback on market conditions.
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By integrating multiple oscillator signals into one cohesive tool, the Clustering & Divergences (RSI-Stoch-CCI) indicator helps traders minimize subjective analysis. Its dynamic clustering and automated divergence detection provide a streamlined method for assessing market conditions and potentially enhancing the accuracy of trading decisions.
For further details on using this indicator, please refer to the guide available at:
On Balance Volume Oscillator of Trading Volume TrendOn Balance Volume Oscillator of Trading Volume Trend
Introduction
This indicator, the "On Balance Volume Oscillator of Trading Volume Trend," is a technical analysis tool designed to provide insights into market momentum and potential trend reversals by combining the On Balance Volume (OBV) and Relative Strength Index (RSI) indicators.
Calculation and Methodology
* OBV Calculation: The indicator first calculates the On Balance Volume, which is a cumulative total of the volume of up days minus the volume of down days. This provides a running tally of buying and selling pressure.
* RSI of OBV: The RSI is then applied to the OBV values to smooth the data and identify overbought or oversold conditions.
* Exponential Moving Averages (EMAs): Two EMAs are calculated on the RSI of OBV. A shorter-term EMA (9-period in this case) and a longer-term EMA (100-period) are used to generate signals.
Interpretation and Usage
* EMA Crossovers: When the shorter-term EMA crosses above the longer-term EMA, it suggests increasing bullish momentum. Conversely, a downward crossover indicates weakening bullish momentum or increasing bearish pressure.
* RSI Divergences: Divergences between the price and the indicator can signal potential trend reversals. For example, if the price is making new highs but the indicator is failing to do so, it could be a bearish divergence.
* Overbought/Oversold Conditions: When the RSI of OBV is above 70, it suggests the market may be overbought and a potential correction could be imminent. Conversely, when it is below 30, it suggests the market may be oversold.
Visual Representation
The indicator is plotted on a chart with multiple lines and filled areas:
* Two EMAs: The shorter-term EMA and longer-term EMA are plotted to show the trend of the OBV.
* Filled Areas: The area between the two EMAs is filled with a color to indicate the strength of the trend. The color changes based on whether the shorter-term EMA is above or below the longer-term EMA.
* RSI Bands: Horizontal lines at 30 and 70 mark the overbought and oversold levels for the RSI of OBV.
Summary
The On Balance Volume Oscillator of Trading Volume Trend provides a comprehensive view of market momentum and can be a valuable tool for traders. By combining the OBV and RSI, this indicator helps identify potential trend reversals, overbought and oversold conditions, and the strength of the current trend.
Note: This indicator should be used in conjunction with other technical analysis tools and fundamental analysis to make informed trading decisions.
