Wyckoff Accumulation Distribution Wyckoff Accumulation & Distribution Indicator (RSI-Based)
This Pine Script is a technical analysis indicator built around the Wyckoff Method, designed to detect accumulation and distribution phases using RSI (Relative Strength Index) and pivot points. It automatically marks key structural turning points on the chart and highlights relevant zones with colored boxes.
What Does It Do?
Draws accumulation and distribution boxes based on RSI behavior.
Automatically detects Wyckoff structural signals:
SC (Selling Climax)
AR (Automatic Rally)
ST (Secondary Test)
BC (Buying Climax)
DAR (Automatic Reaction)
DST (Secondary Test - Distribution)
Identifies trend transitions by detecting sideways RSI movement.
Attempts to detect spring and UTAD-like deviations based on RSI reversals.
Uses RSI extremes in conjunction with pivot points to generate Wyckoff signals.
How Does It Work?
RSI Zone: It identifies sideways markets when RSI stays within ±20 of the 50 level (this range is configurable).
Pivot Points: It detects pivot highs/lows that sync with RSI values (pivotLen is adjustable).
Trend Box Drawing:
When RSI exits the sideways zone, the script draws a gray box between the highest high and lowest low within that range.
If RSI breaks upward, the box becomes green (Accumulation); if downward, it becomes red (Distribution).
Wyckoff Structural Points:
SC/BC: Detected when a pivot occurs with RSI below/above a threshold.
AR/DAR: The next opposite pivot after SC or BC.
ST/DST: The next same-direction pivot after AR or DAR.
How to Use It
Works best on 4H or daily charts for more reliable signals. Shorter timeframes may generate noise.
Primarily used for interpreting RSI structures through the lens of Wyckoff methodology.
Box colors help quickly identify market phase:
Green box: Likely Accumulation
Red box: Likely Distribution
Triangular markers show key signals:
SC, AR, ST: Accumulation points
BC, DAR, DST: Distribution points
Use these signals alongside price action to manually interpret Wyckoff phases.
image.binance.vision
image.binance.vision
What Is the Wyckoff Method?
The Wyckoff Method, developed in the 1930s by Richard Wyckoff, is a market analysis approach that focuses on supply and demand dynamics behind price movements.
Wyckoff’s 5 Phases:
Accumulation: Smart money gradually buying at low prices.
Markup: Price begins trending upwards.
Distribution: Smart money selling to retail traders.
Markdown: Downtrend begins as supply outweighs demand.
Re-accumulation / Re-distribution: Trend-continuation phases with consolidations.
This indicator is specifically designed to detect phase 1 (Accumulation) and phase 3 (Distribution).
Extra Notes
Repainting is minimal, as pivots are confirmed using historical candles.
Labels use plotshape for a clean, minimalist visual style.
Other Wyckoff events (like SOS, LPS, UT, UTAD) could be added in future updates.
This script does not generate buy/sell signals; it is meant for structural interpretation.
Educational
Godfather of Support & Resistance Godfather of Support & Resistance
Overview
The Godfather of Support & Resistance script is a powerful tool designed to help traders identify critical support and resistance levels on their charts. These price levels are vital for understanding market behavior, as they often act as turning points where prices reverse, consolidate, or break through. By automating the detection of these levels, this script simplifies your trading decisions and enhances your technical analysis.
How It Works
Pivot Points for Level Detection:
The script uses pivot points to identify potential support (lows) and resistance (highs) levels:
A pivot high is a local peak (a high surrounded by lower highs).
A pivot low is a local trough (a low surrounded by higher lows).
You can adjust the Pivot Length (pivotLen) input to control the sensitivity of detection. Smaller values detect more levels, while larger values focus on major levels.
Dynamic Grouping with Tolerance:
The script dynamically groups nearby price levels using a tolerance percentage. This tolerance is based on the level's price, making it adaptive to all types of assets (low- and high-priced).
For example, if the tolerance is set to 1% and a level is at $100, levels within $1 are grouped together.
Touch Count for Significance:
The script tracks how many times the price interacts with each level (touch count). Only levels that meet or exceed the Minimum Touches (minTouches) input are displayed on the chart. This ensures only meaningful levels are highlighted.
Clear Visual Representation:
Resistance Levels (Red Lines): Represent areas where the price tends to reverse downward.
Support Levels (Green Lines): Represent areas where the price tends to reverse upward.
Labels are added to each level (optional) to display the price and the number of touches for better decision-making.
Inputs You Can Customize
Minimum Touches to Show Level:
Set the minimum number of price interactions required for a level to be displayed.
Maximum Lines to Keep:
Limit the number of support and resistance lines displayed to keep your chart clean and focused.
Pivot Length:
Customize the sensitivity of pivot point detection. Smaller values detect more levels, while larger values focus on key levels.
Tolerance for Touch Detection (%):
Adjust the grouping tolerance as a percentage of the price. For example, 1% groups levels that are within 1% of each other.
How to Use
Apply the Script:
Add the script to your TradingView chart, and it will automatically detect and plot support and resistance levels.
Analyze the Levels:
Use Resistance Levels (red lines) as potential sell zones or areas to place stop-loss orders above.
Use Support Levels (green lines) as potential buy zones or areas to place stop-loss orders below.
Customize for Your Trading Style:
Adjust the inputs to match your preferred strategy and the timeframe or asset you're analyzing.
Example Use Case
Imagine you're analyzing a stock:
Resistance Level: The script identifies resistance at $150 with 3 touches. This might be a potential sell zone if the price struggles to break through.
Support Level: The script identifies support at $130 with 4 touches. This might be a potential buy zone if the price shows signs of bouncing upward.
Key Features
Automatically detects and plots support and resistance levels.
Tracks the number of price touches to filter out weak levels.
Adapts dynamically to price ranges using a percentage-based tolerance.
Fully customizable to suit different trading styles and assets.
Clean and professional chart display with a limit on the number of lines.
Notes
This script is for educational purposes only and should not be considered financial advice.
Always perform your own analysis and manage risk before making trading decisions.
Why Use This Script?
The Godfather of Support & Resistance script simplifies your trading decisions by automating the detection of critical price levels. Whether you're a beginner or an experienced trader, this script is designed to save you time and help you focus on making informed trades.
Start using it today to master the art of support and resistance trading!
Let me know if you need further refinements for this description!
AI-EngulfingCandle+Alert+thanks-2-ahmedirshad419!WE MUST APPRECIATE ahmedirshad419 and his great work.
I added some tips and sources instead of the shout for MIT XD.
plotshape(tradeSignal and bullishCandle, title = 'bullish', location = location.belowbar, color = color.new(color.green, 0), style = shape.triangleup, text = 'BUY @ next higher bottom @ upper trend')
plotshape(tradeSignal and bearishCandle, title = 'bearish', location = location.abovebar, color = color.new(color.red, 0), style = shape.triangledown, text = 'SELL @ next lower top @ downer trend')
alertcondition(bullishCandle, title = 'Double Bottom Upcoming', message = 'BUY @ next higher bottom @ upper trend !')
alertcondition(bearishCandle, title = 'Doublle Top Upcoming', message = 'SELL @ next lower top @ downer trend !')
You should see the MIRACLE of your LIFE.
Setup Score Check Final AlertTotal Score
Significance
0–6 points
No trade – "Instinct instead of system"
7–12 points
C-Setup – only small test size
13–17 points
B-Setup – entry with caution
18–21 points
A-Setup – fully feasible
Relative Volume CandlesVisualizes candlesticks with transparency based on volume relative to a moving average. Higher-than-average volume makes candles more opaque, while lower volume increases transparency—helping you spot significant price movements at a glance!
Features:
Customizable up/down candle colors (default: green/red)
Adjustable lookback period for volume averaging (default: 21)
Fine-tune transparency with base transparency (default: 80) and scale (default: 2.0)
Overlay directly on your chart for seamless analysis
Sharpe & Sortino Ratio PROSharpe & Sortino Ratio PRO offers an advanced and more precise way to calculate and visualize the Sharpe and Sortino Ratios for financial assets on TradingView. Its main goal is to provide a scientifically accurate method for assessing the risk-adjusted performance of assets, both in the short and long term. Unlike TradingView’s built-in metrics, this script correctly handles periodic returns, uses optional logarithmic returns, properly annualizes both returns and volatility, and adjusts for the risk-free rate — all critical factors for truly meaningful Sharpe and Sortino calculations.
Users can customize the rolling analysis window (e.g., 252 periods for one year on daily data) and the long-term smoothing period (e.g., 1260 periods for five years). There’s also an option to select between linear and logarithmic returns and to manually input a risk-free rate if real-time data from FRED (the 3-Month T-Bill Rate via FRED:DGS3MO) is unavailable. Based on the chart’s timeframe (daily, weekly, or monthly), the script automatically adjusts the risk-free rate to a per-period basis.
The Sharpe Ratio is calculated by first determining the asset’s excess returns (returns after subtracting the risk-free return per period), then computing the average and standard deviation of those excess returns over the specified window, and finally annualizing these figures separately — in line with best scientific practices (Sharpe, 1994). The Sortino Ratio follows a similar approach but only considers negative returns, focusing specifically on downside risk (Sortino & Van der Meer, 1991).
To enhance readability, the script visualizes the ratios using a color gradient: strong negative values are shown in red, neutral values in yellow, and strong positive values in green. Additionally, the long-term averages for both Sharpe and Sortino are plotted with steady colors (teal and orange, respectively), making it easier to spot enduring performance trends.
Why calculating Sharpe and Sortino Ratios manually on TradingView is necessary?
While TradingView provides basic Sharpe and Sortino Ratios, they come with significant methodological flaws that can lead to misleading conclusions about an asset’s true risk-adjusted performance.
First, TradingView often computes volatility based on the standard deviation of price levels rather than returns (TradingView, 2023). This method is problematic because it causes the volatility measure to be directly dependent on the asset’s absolute price. For instance, a stock priced at $1,000 will naturally show larger absolute daily price moves than a $10 stock, even if their percentage changes are similar. This artificially inflates the measured standard deviation and, as a result, depresses the calculated Sharpe Ratio.
Second, TradingView frequently neglects to adjust for the risk-free rate. By treating all returns as risky returns, the computed Sharpe Ratio may significantly underestimate risk-adjusted performance, especially when interest rates are high (Sharpe, 1994).
Third, and perhaps most critically, TradingView doesn’t properly annualize the mean excess return and the standard deviation separately. In correct financial math, the mean excess return should be multiplied by the number of periods per year, while the standard deviation should be multiplied by the square root of the number of periods per year (Cont, 2001; Fabozzi et al., 2007). Incorrect annualization skews the Sharpe and Sortino Ratios and can lead to under- or overestimating investment risk.
These flaws lead to three major issues:
• Overstated volatility for high-priced assets.
• Incorrect scaling between returns and risk.
• Sharpe Ratios that are systematically biased downward, especially in high-price or high-interest environments.
How to properly calculate Sharpe and Sortino Ratios in Pine Script?
To get accurate results, the Sharpe and Sortino Ratios must be calculated using the correct methodology:
1. Use returns, not price levels, to calculate volatility. Ideally, use logarithmic returns for better mathematical properties like time additivity (Cont, 2001).
2. Adjust returns by subtracting the risk-free rate on a per-period basis to obtain true excess returns.
3. Annualize separately:
• Multiply the mean excess return by the number of periods per year (e.g., 252 for daily data).
• Multiply the standard deviation by the square root of the number of periods per year.
4. Finally, divide the annualized mean excess return by the annualized standard deviation to calculate the Sharpe Ratio.
The Sortino Ratio follows the same structure but uses downside deviations instead of standard deviations.
By following this scientifically sound method, you ensure that your Sharpe and Sortino Ratios truly reflect the asset’s real-world risk and return characteristics.
References
• Cont, R. (2001). Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance, 1(2), pp. 223–236.
• Fabozzi, F.J., Gupta, F. and Markowitz, H.M. (2007). The Legacy of Modern Portfolio Theory. Journal of Investing, 16(3), pp. 7–22.
• Sharpe, W.F. (1994). The Sharpe Ratio. Journal of Portfolio Management, 21(1), pp. 49–58.
• Sortino, F.A. and Van der Meer, R. (1991). Downside Risk: Capturing What’s at Stake in Investment Situations. Journal of Portfolio Management, 17(4), pp. 27–31.
• TradingView (2023). Help Center - Understanding Sharpe and Sortino Ratios. Available at: www.tradingview.com (Accessed: 25 April 2025).
Sharpe Ratio Forced Selling StrategyThis study introduces the “Sharpe Ratio Forced Selling Strategy”, a quantitative trading model that dynamically manages positions based on the rolling Sharpe Ratio of an asset’s excess returns relative to the risk-free rate. The Sharpe Ratio, first introduced by Sharpe (1966), remains a cornerstone in risk-adjusted performance measurement, capturing the trade-off between return and volatility. In this strategy, entries are triggered when the Sharpe Ratio falls below a specified low threshold (indicating excessive pessimism), and exits occur either when the Sharpe Ratio surpasses a high threshold (indicating optimism or mean reversion) or when a maximum holding period is reached.
The underlying economic intuition stems from institutional behavior. Institutional investors, such as pension funds and mutual funds, are often subject to risk management mandates and performance benchmarking, requiring them to reduce exposure to assets that exhibit deteriorating risk-adjusted returns over rolling periods (Greenwood and Scharfstein, 2013). When risk-adjusted performance improves, institutions may rebalance or liquidate positions to meet regulatory requirements or internal mandates, a behavior that can be proxied effectively through a rising Sharpe Ratio.
By systematically monitoring the Sharpe Ratio, the strategy anticipates when “forced selling” pressure is likely to abate, allowing for opportunistic entries into assets priced below fundamental value. Exits are equally mechanized, either triggered by Sharpe Ratio improvements or by a strict time-based constraint, acknowledging that institutional rebalancing and window-dressing activities are often time-bound (Coval and Stafford, 2007).
The Sharpe Ratio is particularly suitable for this framework due to its ability to standardize excess returns per unit of risk, ensuring comparability across timeframes and asset classes (Sharpe, 1994). Furthermore, adjusting returns by a dynamically updating short-term risk-free rate (e.g., US 3-Month T-Bills from FRED) ensures that macroeconomic conditions, such as shifting interest rates, are accurately incorporated into the risk assessment.
While the Sharpe Ratio is an efficient and widely recognized measure, the strategy could be enhanced by incorporating alternative or complementary risk metrics:
• Sortino Ratio: Unlike the Sharpe Ratio, the Sortino Ratio penalizes only downside volatility (Sortino and van der Meer, 1991). This would refine entries and exits to distinguish between “good” and “bad” volatility.
• Maximum Drawdown Constraints: Integrating a moving window maximum drawdown filter could prevent entries during persistent downtrends not captured by volatility alone.
• Conditional Value at Risk (CVaR): A measure of expected shortfall beyond the Value at Risk, CVaR could further constrain entry conditions by accounting for tail risk in extreme environments (Rockafellar and Uryasev, 2000).
• Dynamic Thresholds: Instead of static Sharpe thresholds, one could implement dynamic bands based on the historical distribution of the Sharpe Ratio, adjusting for volatility clustering effects (Cont, 2001).
Each of these risk parameters could be incorporated into the current script as additional input controls, further tailoring the model to different market regimes or investor risk appetites.
References
• Cont, R. (2001) ‘Empirical properties of asset returns: stylized facts and statistical issues’, Quantitative Finance, 1(2), pp. 223-236.
• Coval, J.D. and Stafford, E. (2007) ‘Asset Fire Sales (and Purchases) in Equity Markets’, Journal of Financial Economics, 86(2), pp. 479-512.
• Greenwood, R. and Scharfstein, D. (2013) ‘The Growth of Finance’, Journal of Economic Perspectives, 27(2), pp. 3-28.
• Rockafellar, R.T. and Uryasev, S. (2000) ‘Optimization of Conditional Value-at-Risk’, Journal of Risk, 2(3), pp. 21-41.
• Sharpe, W.F. (1966) ‘Mutual Fund Performance’, Journal of Business, 39(1), pp. 119-138.
• Sharpe, W.F. (1994) ‘The Sharpe Ratio’, Journal of Portfolio Management, 21(1), pp. 49-58.
• Sortino, F.A. and van der Meer, R. (1991) ‘Downside Risk’, Journal of Portfolio Management, 17(4), pp. 27-31.
Micro Gaps DetectorSimple Micro Gap Indicator: A Technical Analysis Tool
The Simple Micro Gap Indicator is a specialized momentum indicator designed to identify and analyze micro gaps between consecutive candlesticks in financial charts. Unlike traditional gap analysis that focuses on larger price gaps, this indicator specifically targets smaller, less noticeable spaces between candles.
Key Features:
Detects minimal price disparities between consecutive candlesticks
Helps identify potential short-term momentum shifts
Useful for high-frequency trading and scalping strategies
Functions as a momentum indicator for short-term price movements
COTE 1composite scan of bist stocks
You can set the condition in the screening code as you wish according to the data defined in the code.
Triple Confirmation Buy/Sell Engine VWAP + MACD + RSIDescription:
This custom-built indicator generates high-confidence Buy/Sell signals using a powerful combination of MACD momentum, RSI strength, and VWAP trend confirmation — designed for cleaner entries and fewer false signals.
Unlike traditional scripts that rely on only one indicator (and produce noisy or early signals), this system requires triple confirmation, greatly increasing signal quality and reducing false trades.
✅ Buy Signal Conditions:
MACD histogram turns green (momentum shift positive)
RSI crosses above 50 (bullish strength confirmation)
Price closes above VWAP (trend confirmation)
🔻 Sell Signal Conditions:
MACD histogram turns red (momentum shift negative)
RSI crosses below 50 (weakening trend)
Price closes below VWAP (bearish confirmation)
🛠 Best For:
Trend traders seeking higher probability entries
Swing traders who want to catch bigger moves
Crypto, stocks, forex traders looking for simple, effective signals
🔔 Credit Spread Monitor: HY & IG vs US10Y🔔 Credit Spread Monitor: HY & IG vs US10Y
This macroeconomic tool tracks credit risk sentiment by plotting the yield spreads between:
🔵 Investment Grade (IG): BAMLC0A0CMEY → ICE BofA US Corporate Index Effective Yield. Reflects average yield for US investment-grade corporate bonds.
🔴 High Yield (HY): BAMLH0A0HYM2EY → ICE BofA US High Yield Index Effective Yield. Measures average yield for US high-yield (non-investment grade) corporate bonds.
⚪ Treasury 10Y: US10Y → 10-Year US Treasury Yield. Benchmark rate for US government long-term debt.
Spreads calculated:
IG Spread = IG Yield - US10Y
HY Spread = HY Yield - US10Y
🔎 Key Alert Zones:
🔴 HY Spread > +2σ → Potential financial stress / risk-off event
🟠 Inverted yield curve (10Y < 2Y) + HY Spread > 2% → Recession signal
🟢 HY Spread < 1.5% → Risk-on behavior, strong credit sentiment
This indicator is ideal for:
✅ Macro traders looking to anticipate economic inflection points
✅ Portfolio managers monitoring systemic risk or credit cycles
✅ Fixed-income analysts tracking the cost of corporate borrowing
Sourced from FRED (Federal Reserve Economic Data) and TradingView’s bond feeds. Designed to work on daily resolution using open prices for best consistency across series.
Nifty 3-min Options Pro Strategy (Fixed Version)This strategy is designed specifically for high-probability intraday options trading on the Nifty 3-5 minute chart.
It intelligently combines CPR (Central Pivot Range) and VWAP to define the market's bias (bullish or bearish) and detects Inside Bar Breakouts to pinpoint low-risk, high-reward entries.
The strategy automatically:
Identifies Buy Signals for CE (Call Options) when conditions are bullish.
Identifies Buy Signals for PE (Put Options) when conditions are bearish.
Plots dynamic CPR and VWAP levels on the chart.
Applies ATR-based Stop Loss and trailing stop loss for risk management.
Generates real-time alerts for quick trading actions.
The trading logic is time-filtered to operate only during optimal intraday hours (9:00 AM to 2:30 PM), avoiding low-volume traps and volatile close sessions.
Designed to help traders capture strong directional moves early, this strategy is perfect for Nifty scalpers and intraday options traders aiming for consistent profitability.
MM Day Trader Levels Signal IndicatorVisual elements (CALL/PUT labels and markers) are now prioritized at the top of the chart for improved readability and immediate trade signal clarity.
DOC & DOS 30m Rangesthe lines on the screen indicate the 30 min rande on the daily opens for stocks and crypto
DOC & DOS 30m RangesDailyOpenCrypto & DailyOpenStocks 30m Ranges once you confirm closes outside or range a daily bias is determined
CISD [TakingProphets]🧠 Indicator Purpose:
The "CISD - Change in State of Delivery" is a precision tool designed for traders utilizing ICT (Inner Circle Trader) conecpets. It detects critical shifts in delivery conditions after liquidity sweeps — helping you spot true smart money activity and optimal trade opportunities. This script is especially valuable for traders applying liquidity concepts, displacement recognition, and market structure shifts at both intraday and swing levels.
🌟 What Makes This Indicator Unique:
Unlike basic trend-following or scalping tools, CISD operates through a two-phase smart money logic:
Liquidity Sweep Detection (sweeping Buyside or Sellside Liquidity).
State of Delivery Change Identification (through bearish or bullish displacement after the sweep).
It intelligently tracks candle sequences and only signals a CISD event after true displacement — offering a much deeper context than ordinary indicators.
⚙️ How the Indicator Works:
Swing Point Detection: Identifies recent pivot highs/lows to map Buyside Liquidity (BSL) and Sellside Liquidity (SSL) zones.
Liquidity Sweeps: Watches for price breaches of these liquidity points to detect institutional stop hunts.
Sequence Recognition: Finds series of same-direction candles before sweeps to mark institutional accumulation/distribution.
Change of Delivery Confirmation: Confirms CISD only after significant displacement moves price against the initial candle sequence.
Visual Markings: Automatically plots CISD lines and optional labels, customizable in color, style, and size.
🎯 How to Use It:
Identify Liquidity Sweeps: Watch for CISD levels plotted after a liquidity sweep event.
Plan Entries: Look for retracements into CISD lines for high-probability entries.
Manage Risk: Use CISD levels to refine your stop-loss and profit-taking zones.
Best Application:
After stop hunts during Killzones (London Open, New York AM).
As part of the Flow State Model: identify higher timeframe PD Arrays ➔ wait for lower timeframe CISD confirmation.
🔎 Underlying Concepts:
Liquidity Pools: Highs and lows cluster stop orders, attracting institutional sweeps.
Displacement: Powerful price moves post-sweep confirm smart money involvement.
Market Structure: CISD frequently precedes major Change of Character (CHoCH) or Break of Structure (BOS) shifts.
🎨 Customization Options:
Adjustable line color, width, and style (solid, dashed, dotted).
Optional label display with customizable color and sizing.
Line extension settings to keep CISD zones visible for future reference.
✅ Recommended for:
Traders studying ICT Smart Money Concepts.
Intraday scalpers and higher timeframe swing traders.
Traders who want to improve entries around liquidity sweeps and institutional displacement moves.
🚀 Bonus Tip:
For maximum confluence, pair this with the HTF POI, ICT Liquidity Levels, and HTF Market Structure indicators available at TakingProphets.com! 🔥
🌎 Modern Economic Eras - Visual Backgrounds & LabelsModern Economic Eras - Visual Backgrounds & Labels
This indicator highlights key modern economic eras with distinct background shading and floating labels, based on the structural macroeconomic periods identified by Deutsche Bank in their Long-Term Asset Return Study (2020).
🌎 First Era of Globalization (1860–1914)
A period of strong global growth, trade expansion, and low inflation, ending with World War I.
⚔️ Great Wars and the Depression (1914–1945)
The most turbulent period in modern history, marked by conflict, economic hardship, and volatile inflation.
🪙 Bretton Woods & Gold System (1945–1971)
Post-war stability driven by gold-backed currencies, strong growth, and the creation of modern welfare states.
💸 Fiat Money & High Inflation Era (1971–1980)
After the collapse of Bretton Woods, fiat currencies led to global inflation surges and economic instability.
🌍 Second Era of Globalization (1980–2020?)
A golden age of asset returns, global trade boom, China's reintegration, and falling inflation supported by demographic trends.
⚡ Age of Disorder (2020–????)
Characterized by rising geopolitical tensions (especially US-China), high debt levels, political fragmentation, demographic reversals, inequality challenges, and environmental pressures.
Each era is visually segmented and labeled above the chart for intuitive historical context.
This tool helps traders and investors understand the broader macro context behind asset price movements across different long-term regimes.
Useful for:
✅ Macro analysis
✅ Historical financial studies
✅ Long-term strategic planning
Compatible with any asset and timeframe, although it is intended primarily for use on indices like the S&P 500 (SPX).
Kalman Filtered RSI | [DeV]The Kalman Filtered RSI indicator is an advanced tool designed for traders who want precise, noise-free market insights. By enhancing the classic Relative Strength Index (RSI) with a Kalman filter, this indicator delivers a smoother, more reliable view of market momentum, helping you identify trends, reversals, and overbought/oversold conditions with greater accuracy. It’s an ideal choice for traders seeking clear signals amidst market volatility, giving you a competitive edge across any trading environment.
The RSI measures momentum by analyzing price movements over a set period, typically 14 bars. It calculates the average of price gains on up days and the average of price losses on down days, then compares these to produce a value between 0 and 100. An RSI above 70 often indicates an overbought market that may reverse downward, while below 30 suggests an oversold market that could reverse upward. RSI is great for spotting momentum shifts, potential reversals, and trend strength, but it can be noisy in choppy markets, leading to misleading signals.
That's where the Kalman filter comes in; it enhances the RSI by applying a sophisticated smoothing process that predicts the RSI’s next value based on its historical trend, then updates this prediction with the actual RSI reading. It operates in two phases: prediction and correction. In the prediction phase, it uses the previous filtered RSI and adds uncertainty from process noise (Q), which is derived from the historical variance of RSI changes, reflecting how much the RSI might unexpectedly shift. In the correction phase, it calculates a Kalman gain based on the ratio of prediction uncertainty to measurement noise (R), which is determined from the variance between raw RSI and a smoothed version, indicating the raw data’s noisiness. This gain weights how much the filter trusts the new RSI versus the prediction, blending them to produce a smoothed RSI that reduces noise while staying responsive to real trends, outperforming simpler methods like moving averages that often lag or oversmooth.
With the Kalman Filtered RSI, you get a refined view of momentum, making it easier to spot trends and reversals with clarity. This indicator’s ability to dynamically adapt to market changes delivers timely, reliable signals, making it a powerful addition to your trading strategy for any market or timeframe.
Daily Alert at Specific TimeThis script will just trigger an alert at the end of the market session at 3:55 PM EST. If we need to flattened all existing open positions at the end of the day, we can use this alert.
Global Liquidity Index with Dynamic TimeframeThis is the M2 Global Money supply indicator with added functionality of moving the graph sideways (increment of days) in order to find a potential price correlation with any chart
BTC / USEU (FX-Adjusted)first version btc/k adjustable
filters out usd movments to see raw btc changes
