BuySell-byALHELWANI🔱 BuySell-byALHELWANI | مؤشر التغيرات الاتجاهية الذكية
BuySell-byALHELWANI هو مؤشر احترافي متقدّم يرصد نقاط الانعكاس الحقيقية في حركة السوق، باستخدام خوارزمية تعتمد على تحليل القمم والقيعان الهيكلية للسعر (Structure-Based Detection) وليس على مؤشرات تقليدية.
المؤشر مبني على مكتبة signalLib_yashgode9 القوية، مع تخصيص كامل لأسلوب العرض والتنبيهات.
⚙️ ما يقدمه المؤشر:
🔹 إشارات واضحة للشراء والبيع تعتمد على كسر هيكل السوق.
🔹 تخصيص مرن للعمق والانحراف وخطوات التراجع (Backstep) لتحديد الدقة المطلوبة.
🔹 علامات ذكية (Labels) تظهر مباشرة على الشارت عند كل نقطة قرار.
🔹 تنبيهات تلقائية فورية عند كل تغير في الاتجاه (Buy / Sell).
🧠 الآلية المستخدمة:
DEPTH_ENGINE: يتحكم في مدى عمق النظر لحركة السعر.
DEVIATION_ENGINE: يحدد المسافة المطلوبة لتأكيد نقطة الانعكاس.
BACKSTEP_ENGINE: يضمن أن كل إشارة تستند إلى تغير هيكلي حقيقي في الاتجاه.
📌 المميزات:
✅ لا يعيد الرسم (No Repaint)
✅ يعمل على كل الأطر الزمنية وكل الأسواق (فوركس، مؤشرات، كريبتو، أسهم)
✅ تصميم بصري مرن (ألوان، حجم، شفافية)
✅ يدعم الاستخدام في السكالبينغ والسوينغ
ملاحظة:
المؤشر لا يعطي إشارات عشوائية، بل يستند إلى منطق السعر الحقيقي عبر تتبع التغيرات الحركية للسوق.
يُفضّل استخدامه مع خطة تداول واضحة وإدارة رأس مال صارمة.
🔱 BuySell-byALHELWANI | Smart Reversal Detection Indicator
BuySell-byALHELWANI is a high-precision, structure-based reversal indicator designed to identify true directional shifts in the market. Unlike traditional indicators, it doesn't rely on lagging oscillators but uses real-time swing analysis to detect institutional-level pivot points.
Powered by the robust signalLib_yashgode9, this tool is optimized for traders who seek clarity, timing, and strategic control.
⚙️ Core Engine Features:
🔹 Accurate Buy/Sell signals generated from structural highs and lows.
🔹 Adjustable sensitivity using:
DEPTH_ENGINE: Defines how deep the algorithm looks into past swings.
DEVIATION_ENGINE: Sets the deviation required to confirm a structural change.
BACKSTEP_ENGINE: Controls how many bars are validated before confirming a pivot.
🧠 What It Does:
🚩 Detects market structure shifts and confirms them visually.
🏷️ Plots clear Buy-point / Sell-point labels directly on the chart.
🔔 Sends real-time alerts when a directional change is confirmed.
🎯 No repainting – what you see is reliable and final.
✅ Key Benefits:
Works on all timeframes and all asset classes (FX, crypto, indices, stocks).
Fully customizable: colors, label size, transparency.
Ideal for scalping, swing trading, and strategy automation.
High visual clarity with minimal noise.
🔐 Note:
This script is designed for serious traders.
It highlights real market intent, especially when used with trendlines, zones, and volume analysis.
Pair it with disciplined risk management for best results.
Wyszukaj w skryptach "TRENDLINES"
Fibonacci-Based Volume Flow (VFI)Fibonacci-based Volume Flow is an advanced next-generation evolution of LazyBear’s original VFI script that calculates and averages up to 21 Fibonacci-based VFI pairings to create a smoothed composite volume flow signal. This unique and powerful approach reduces noise, adapts to volatility, and provides a clearer view of trend strength and market structure across all timeframes. It also includes dynamic fibonacci guide levels, adaptive lookbacks, EMA crossovers, and structure-aware pivot labeling to help traders identify high-quality reversals, confirm directional bias, and detect divergences with greater precision. It's ideal for traders looking to enhance momentum analysis through volume-based confirmation.
🧠 Key Features🧠
🔹 Multi-VFI Fibonacci Fusion🔹
Blends up to 21 VFI signals (5, 13, 21, 34… up to 610) into smartly paired averages (e.g., 13/34, 55/144) — forming a smoothed composite VFI that’s more adaptive, less noisy, and highly responsive across market conditions.
🔸🔸 Dynamic Lookbacks🔸 🔸
Automatically adjusts histogram high/low tracking based on your chart’s timeframe — no more static tuning. Perfect for scalping fast charts or confirming long-term trends.
🟥🟩 Color-Coded Histogram🟥🟩
Visualizes VFI momentum with gradient coloring.
🧩🧩 Signal Crossovers 🧩🧩
Color-coded crossover lines persistently show bullish or bearish dominance.
Includes three powerful crossover systems:
➖5/13 VFI: Fast, early reversal detection
➖8/21 VFI: Swing-trading sweet spot
➖55/144 VFI: Trend confirmation across long cycles
🏷️ 🏷️Pivot Structure Labels🏷️🏷️
Labels oscillator swings with full structural logic:
➖HH, HL, LH, LL, EQ
➖Displays percent change, price at pivot, oscillator reading
➖Smart coloring detects divergence & trend continuation
📈 📈Dynamic Histogram Guides📈📈
Optional zero and ±50% bands anchor histogram levels based on real histogram extremes, not static thresholds — visually frame momentum shifts with context.
📍 📍Persistent High/Low Pivot Lines📍📍
Track the most significant histogram pivots (not price) across time, with smart labels:
➖Volume flow structure zones
➖Label shows price at pivot, oscillator level, and bars since event
➖Ideal for spotting divergence zones, momentum failures, and trend exhaustion.
🔍 🔍Volatility Table (ATR%)🔍🔍
💡Shows real-time volatility compression or expansion
💡Uses multiple ATR periods (e.g., 14 & 55) for short- and medium-term comparison
💡Helps traders understand whether momentum is likely to continue or stall
🔩🔩Volume-weighted VFI baselines🔩🔩
🟢A daily session-based VWAP of the VFI, which resets each day and highlights intraday volume flow context.
🟠A rolling VWA of VFI, which acts like a VWMA over a fixed window (e.g., 55 bars), smoothing short-term fluctuations and supporting trend/momentum confirmation.
These VWAP-style overlays help traders identify strength vs. weakness relative to volume-weighted baselines — useful for divergence spotting, mean reversion setups, or breakout confirmation.
🧰 🧰Under the Hood: How It Works🧰🧰
🔧 Core VFI Logic
Based on LazyBear’s foundational VFI:
➖Uses log returns of price (HLC3)
➖Filters insignificant moves using volatility-weighted thresholds
➖Normalizes volume via adaptive capping (e.g., 2.5× average)
🌀 Composite Blend System
Each VFI instance is smoothed and then fused via user-selectable pairs. This creates a customizable average VFI representing short, mid, and long-term pressure — one value, many time horizons.
📊 EMA Signal Layer
Crosses trigger persistent color shifts in signal lines, making trend strength clear at a glance.
VFI blend feeds into EMA crossovers. You can toggle visibility for:
➖Fast (5/13)
➖Medium (8/21)
➖Slow (55/144)
🧭 Pivot Framework
Structure logic only compares pivots on same-side polarity:
➖Highs compare to highs above zero
➖Lows compare to lows below zero
This avoids nonsensical comparisons and preserves logical sequences (HH → LH → HL).
🧱 Dynamic Labels
All pivots and persistent levels display:
➖Oscillator value
➖Price value
➖Structure tag (e.g., LH, HL)
➖% change from prior pivot
➖Lookback info
➖Bar age
Unlike traditional VFI:
✅ It blends timeframes with Fibonacci precision
✅ Uses dynamic, volatility-aware logic
✅ Embeds visual structure & divergence intelligence
✅ Enhances entry confidence and exit timing
🔧 This isn’t just an indicator — it’s a volume-informed decision engine.
Ideal For:
🔶Trend-followers wanting cleaner volume-based confirmation
🔶Reversal traders spotting structure + divergence
🔶Scalpers or investors needing adaptable signals
🔶Those who loved LazyBear's VFI
📌 Final Note:
As powerful as Fibonacci Blended Volume Flow is, no single indicator should be used in isolation. For best results, combine it with price action analysis, higher-timeframe context, and complementary tools like trendlines, moving averages, or support/resistance levels. Use it as part of a well-rounded trading approach to confirm setups — not to define them alone.
ZigZag Based RSIDescription
ZigZag Trend RSI (ZZ-RSI) is an advanced momentum indicator that combines ZigZag-based trend detection with a trend-adjusted RSI to deliver smarter overbought and oversold signals. Unlike traditional RSI that reacts purely to price movement, this indicator adapts its sensitivity based on the prevailing trend structure identified via the ZigZag pattern.
By dynamically adjusting RSI thresholds according to market direction, ZZ-RSI helps filter out false signals and aligns RSI readings with broader trend context—crucial for trend-following strategies, counter-trend entries, and volatility-based timing.
Core Components
ZigZag Pattern Recognition:
Identifies significant swing highs and lows based on price deviation (%) and pivot sensitivity (length). The most recent pivot determines the prevailing trend direction:
🟢 Bullish: last swing is a higher high
🔴 Bearish: last swing is a lower low
⚪ Neutral: no recent significant movement
Trend-Weighted RSI:
Modifies traditional RSI input by emphasizing price changes in the direction of the trend:
In bull trends, upside moves are magnified.
In bear trends, downside moves are emphasized.
Dynamic RSI Zones:
Overbought and Oversold thresholds adapt to the trend:
In uptrends: higher OB and slightly raised OS → tolerate stronger rallies
In downtrends: lower OS and slightly reduced OB → accommodate stronger sell-offs
In neutral: default OB/OS values apply
How to Use
✅ Entries (Reversal or Mean Reversion Traders):
Look for oversold signals (green triangle) in downtrends or neutrals to catch potential reversals.
Look for overbought signals (red triangle) in uptrends or neutrals to fade momentum.
Confirm with price action or volume for higher conviction.
📈 Trend Continuation (Momentum or Trend-Followers):
Use the trend direction label (Bullish / Bearish / Neutral) to align your trades with the broader move.
Combine with moving averages or price structure for entry timing.
Avoid counter-trend signals unless confirmed by divergence or exhaustion.
🧠 Signal Interpretation Table (top right of chart):
Trend: Indicates the current market direction.
RSI: Real-time trend-adjusted RSI value.
Signal: OB/OS/Neutral classification.
Customization Options
ZigZag Length / Deviation %:
Adjust pivot sensitivity and filter out minor noise.
RSI Length:
Controls how fast RSI responds to trend-adjusted price.
Color Settings:
Personalize visual cues for trend direction and OB/OS backgrounds.
Alerts Included
📢 Overbought/oversold conditions
🔄 Trend reversals (bullish or bearish shift)
These alerts are ideal for automated strategies, mobile notifications, or algorithmic workflows.
Ideal For
Traders seeking smarter RSI signals filtered by market structure
Trend-followers and swing traders looking for reliable reversals
Those frustrated with false OB/OS signals in volatile or trending markets
Best Practices
Use in confluence with price structure, trendlines, or S/R levels.
For intraday: consider lowering ZigZag Length and RSI Length.
For higher timeframes: use higher deviation % and smoother RSI to reduce noise.
Smart RSI Divergence PRO | Auto Lines + Alerts📌 Purpose
This indicator automatically detects Regular and Hidden RSI Divergences between price action and the RSI oscillator.
It plots divergence lines directly on the chart, labels signals, and includes alerts for automated monitoring.
🧠 How It Works
1. RSI Calculation
RSI is calculated using the selected Source (default: Close) and RSI Length (default: 14).
2. Divergence Detection via Fractals
Swing points on both price and RSI are detected using fractal logic (5-bar patterns).
Regular Divergence:
Bearish: Price forms a higher high, RSI forms a lower high.
Bullish: Price forms a lower low, RSI forms a higher low.
Hidden Divergence:
Bearish: Price forms a lower high, RSI forms a higher high.
Bullish: Price forms a higher low, RSI forms a lower low.
3. Auto Drawing Lines
Lines are drawn automatically between divergence points:
Red = Regular Bearish
Green = Regular Bullish
Orange = Hidden Bearish
Blue = Hidden Bullish
Line width and transparency are adjustable.
4. Labels and Alerts
Labels mark divergence points with up/down arrows.
Alerts trigger for each divergence type.
📈 How to Use
Use Regular Divergences to anticipate trend reversals.
Use Hidden Divergences to confirm trend continuation.
Combine with support/resistance, trendlines, or volume for higher probability setups.
Recommended Timeframes: Works on all timeframes; more reliable on 1h, 4h, and Daily.
Markets: Forex, Crypto, Stocks.
⚙️ Inputs
Source (Close, HL2, etc.)
RSI Length
Toggle Regular / Hidden Divergence visibility
Toggle Lines / Labels
Line Width & Line Transparency
⚠️ Disclaimer
This script is for educational purposes only. It does not constitute financial advice.
Always test thoroughly before using in live trading.
[Teyo69] T1 Wyckoff Aggressive A/D Setup📘 Overview
The T1 Wyckoff Aggressive A/D Setup is a dual-mode indicator that detects bullish accumulations and bearish distributions using core principles from the Wyckoff Method. It identifies price/volume behavior during Selling/Buying Climaxes, ARs, SOS/SOW, and triggers based on trend structure.
🔍 Features
✅ Automatic detection of:
Automatic Rally (AR)
Automatic Reaction (AR)
Sign of Strength (SOS) or Sign of Weakness (SOW)
🧠 Trend-sensitive logic with linear regression slope filters
⚙️ Configurable options for Reversal vs Trend Following mode
🎯 Smart structure timing filters using barssince() logic
🔊 Volume spike and wide-range candle detection
📊 Visual cues for bullish (green) and bearish (red) backgrounds
🛠 How to Use
Reversal Mode
Triggers early signals after a Climax + AR
Ideal for catching turning points during consolidations
Trend Following Mode
Requires Climax, AR, and confirmation (SOS or SOW)
Waits for structure confirmation before signaling
Use this when you want higher probability trades
⚙️ Configuration
Volume MA Length - Determines baseline volume to detect spikes
Wick % of Candle - Filters candles with long tails for SC/BC
Close Near Threshold - Ensures candles close near high/low
Breakout Lookback - Sets structure breakout level
Structure Threshold - Controls timing window for setups
Signal Option - Switch between Reversal or Trend Following mode
⚠️ Limitations
Doesn't confirm macro structure like full Wyckoff phase labeling (A–E)
May repaint on lower timeframes during volatile candles
Works best when combined with visual range recognition and market context
🧠 Advanced Tips
Use in confluence with:
Volume Profile ranges
Trendlines and supply/demand areas
Ideal timeframes: 8H to 1D for crypto and forex markets
Combine this with LPS/UTAD patterns for refined entries
📝 Notes
SC/AR/SOS = Bullish
BC/AR/SOW = Bearish
Trend coloring adapts background (green = rising slope, red = falling slope)
🛡️ Disclaimer
This tool is a market structure guide, not financial advice. Past behavior does not guarantee future performance. Always use proper risk management.
Customizable ORB BoxCustomizable ORB Box
📘 Description
A powerful and flexible Opening Range Breakout (ORB) visualization tool designed for intraday traders. This indicator plots the opening range using either the first candle or a user-defined custom timeframe, and updates in real time.
🔧 Key Features
First Candle Mode – Plots the high/low range of the first candle of each new trading day.
Custom Timeframe Mode – Builds the ORB box live over a chosen duration (e.g., 5, 15, 30 minutes) and finalizes it after the timeframe completes.
Dynamic Box Colors – Bullish and bearish color themes based on range closure direction.
Multi-Day Plotting – Displays ORB boxes across all days, not just today.
Alerts Included – Triggers when price breaks above or below the ORB range.
No repainting – Stable and historical-friendly behavior.
🕒 ETH Compatibility
This indicator respects your TradingView chart settings:
✅ If ETH is enabled, ORB begins with the first ETH candle.
✅ If ETH is disabled, ORB begins with Regular Trading Hours (RTH).
Tip: Control this via the chart’s ⚙️ “Session” settings for your instrument.
💡 How to Use
Use First Candle Mode for classic ORB strategy setups (quick early structure).
Use Custom Timeframe Mode on smaller timeframes (e.g., 3min) for dynamic range-building.
Combine with volume, VWAP, trendlines, or price action for breakout confirmation.
IU Inside/Harami candlestick patternDESCRIPTION
The IU Inside/Harami Candlestick Pattern indicator is designed to detect bullish and bearish inside bar formations, also known as Harami patterns. This tool gives users flexibility by allowing pattern detection based on candle wicks, bodies, or a combination of both. It highlights detected patterns using colored boxes and optional text labels on the chart, helping traders quickly identify areas of consolidation and potential reversals.
USER INPUTS :
Pattern Recognition Based on =
Choose between "Wicks", "Body", or "Both" to determine how the inside candle pattern is identified.
Show Box =
Toggle the appearance of colored boxes that highlight the pattern zone.
Show Text =
Toggle on-screen labels for "Bullish Inside" or "Bearish Inside" when patterns are detected.
INDICATOR LOGIC :
Bullish Inside Bar (Harami) is detected when:
* The current candle's high is lower and low is higher than the previous candle (wick-based),
* or the current candle’s open and close are inside the previous candle’s body (body-based),
* and the current candle is bullish while the previous is bearish.
Bearish Inside Bar (Harami) is detected when:
* The current candle's high is lower and low is higher than the previous candle (wick-based),
* or the current candle’s open and close are inside the previous candle’s body (body-based),
* and the current candle is bearish while the previous is bullish.
The user can choose wick-based, body-based, or both logics for pattern confirmation.
Boxes are drawn between the highs and lows of the pattern, and alert messages are generated upon confirmation.
Optional labels show the pattern name for quick visual identification.
WHY IT IS UNIQUE :
Offers three different logic modes: wick-based, body-based, or combined.
Highlights patterns visually with customizable boxes and labels.
Includes built-in alerts for immediate notifications.
Uses clean and transparent plotting without repainting.
HOW USER CAN BENEFIT FROM IT :
Receive real-time alerts when Inside/Harami patterns are formed.
Use the boxes and text labels to spot price compression zones and breakout potential.
Combine it with other tools like trendlines or support/resistance for enhanced accuracy.
Suitable for scalpers, swing traders, and price action traders looking to trade inside bar breakouts or reversals.
DISCLAIMER :
This indicator is not financial advice, it's for educational purposes only highlighting the power of coding( pine script) in TradingView, I am not a SEBI-registered advisor. Trading and investing involve risk, and you should consult with a qualified financial advisor before making any trading decisions. I do not guarantee profits or take responsibility for any losses you may incur.
Momentum Regression [BackQuant]Momentum Regression
The Momentum Regression is an advanced statistical indicator built to empower quants, strategists, and technically inclined traders with a robust visual and quantitative framework for analyzing momentum effects in financial markets. Unlike traditional momentum indicators that rely on raw price movements or moving averages, this tool leverages a volatility-adjusted linear regression model (y ~ x) to uncover and validate momentum behavior over a user-defined lookback window.
Purpose & Design Philosophy
Momentum is a core anomaly in quantitative finance — an effect where assets that have performed well (or poorly) continue to do so over short to medium-term horizons. However, this effect can be noisy, regime-dependent, and sometimes spurious.
The Momentum Regression is designed as a pre-strategy analytical tool to help you filter and verify whether statistically meaningful and tradable momentum exists in a given asset. Its architecture includes:
Volatility normalization to account for differences in scale and distribution.
Regression analysis to model the relationship between past and present standardized returns.
Deviation bands to highlight overbought/oversold zones around the predicted trendline.
Statistical summary tables to assess the reliability of the detected momentum.
Core Concepts and Calculations
The model uses the following:
Independent variable (x): The volatility-adjusted return over the chosen momentum period.
Dependent variable (y): The 1-bar lagged log return, also adjusted for volatility.
A simple linear regression is performed over a large lookback window (default: 1000 bars), which reveals the slope and intercept of the momentum line. These values are then used to construct:
A predicted momentum trendline across time.
Upper and lower deviation bands , representing ±n standard deviations of the regression residuals (errors).
These visual elements help traders judge how far current returns deviate from the modeled momentum trend, similar to Bollinger Bands but derived from a regression model rather than a moving average.
Key Metrics Provided
On each update, the indicator dynamically displays:
Momentum Slope (β₁): Indicates trend direction and strength. A higher absolute value implies a stronger effect.
Intercept (β₀): The predicted return when x = 0.
Pearson’s R: Correlation coefficient between x and y.
R² (Coefficient of Determination): Indicates how well the regression line explains the variance in y.
Standard Error of Residuals: Measures dispersion around the trendline.
t-Statistic of β₁: Used to evaluate statistical significance of the momentum slope.
These statistics are presented in a top-right summary table for immediate interpretation. A bottom-right signal table also summarizes key takeaways with visual indicators.
Features and Inputs
✅ Volatility-Adjusted Momentum : Reduces distortions from noisy price spikes.
✅ Custom Lookback Control : Set the number of bars to analyze regression.
✅ Extendable Trendlines : For continuous visualization into the future.
✅ Deviation Bands : Optional ±σ multipliers to detect abnormal price action.
✅ Contextual Tables : Help determine strength, direction, and significance of momentum.
✅ Separate Pane Design : Cleanly isolates statistical momentum from price chart.
How It Helps Traders
📉 Quantitative Strategy Validation:
Use the regression results to confirm whether a momentum-based strategy is worth pursuing on a specific asset or timeframe.
🔍 Regime Detection:
Track when momentum breaks down or reverses. Slope changes, drops in R², or weak t-stats can signal regime shifts.
📊 Trade Filtering:
Avoid false positives by entering trades only when momentum is both statistically significant and directionally favorable.
📈 Backtest Preparation:
Before running costly simulations, use this tool to pre-screen assets for exploitable return structures.
When to Use It
Before building or deploying a momentum strategy : Test if momentum exists and is statistically reliable.
During market transitions : Detect early signs of fading strength or reversal.
As part of an edge-stacking framework : Combine with other filters such as volatility compression, volume surges, or macro filters.
Conclusion
The Momentum Regression indicator offers a powerful fusion of statistical analysis and visual interpretation. By combining volatility-adjusted returns with real-time linear regression modeling, it helps quantify and qualify one of the most studied and traded anomalies in finance: momentum.
Contrarian RSIContrarian RSI Indicator
Pairs nicely with Contrarian 100 MA (optional hide/unhide buy/sell signals)
Description
The Contrarian RSI is a momentum-based technical indicator designed to identify potential reversal points in price action by combining a unique RSI calculation with a predictive range model inspired by the "Contrarian 5 Levels" logic. Unlike traditional RSI, which measures price momentum based solely on price changes, this indicator integrates a smoothed, weighted momentum calculation and predictive price ranges to generate contrarian signals. It is particularly suited for traders looking to capture reversals in trending or range-bound markets.
This indicator is versatile and can be used across various timeframes, though it performs best on higher timeframes (e.g., 1H, 4H, or Daily) due to reduced noise and more reliable signals. Lower timeframes may require additional testing and careful parameter tuning to optimize performance.
How It Works
The Contrarian RSI combines two primary components:
Predictive Ranges (5 Levels Logic): This calculates a smoothed price average that adapts to market volatility using an ATR-based mechanism. It helps identify significant price levels that act as potential support or resistance zones.
Contrarian RSI Calculation: A modified RSI calculation that uses weighted momentum from the predictive ranges to measure buying and selling pressure. The result is smoothed and paired with a user-defined moving average to generate clear signals.
The indicator generates buy (long) and sell (exit) signals based on crossovers and crossunders of user-defined overbought and oversold levels, making it ideal for contrarian trading strategies.
Calculation Overview
Predictive Ranges (5 Levels Logic):
Uses a custom function (pred_ranges) to calculate a dynamic price average (avg) based on the ATR (Average True Range) multiplied by a user-defined factor (mult).
The average adjusts only when the price moves beyond the ATR threshold, ensuring responsiveness to significant price changes while filtering out noise.
This calculation is performed on a user-specified timeframe (tf5Levels) for multi-timeframe analysis.
Contrarian RSI:
Compares consecutive predictive range values to calculate gains (g) and losses (l) over a user-defined period (crsiLength).
Applies a Gaussian weighting function (weight = math.exp(-math.pow(i / crsiLength, 2))) to prioritize recent price movements.
Computes a "wave ratio" (net_momentum / total_energy) to normalize momentum, which is then scaled to a 0–100 range (qrsi = 50 + 50 * wave_ratio).
Smooths the result with a 2-period EMA (qrsi_smoothed) for stability.
Moving Average:
Applies a user-selected moving average (SMA, EMA, WMA, SMMA, or VWMA) with a customizable length (maLength) to the smoothed RSI (qrsi_smoothed) to generate the final indicator value (qrsi_ma).
Signal Generation:
Long Entry: Triggered when qrsi_ma crosses above the oversold level (oversoldLevel, default: 1).
Long Exit: Triggered when qrsi_ma crosses below the overbought level (overboughtLevel, default: 99).
Entry and Exit Rules
Long Entry: Enter a long position when the Contrarian RSI (qrsi_ma) crosses above the oversold level (default: 1). This suggests the asset is potentially oversold and due for a reversal.
Long Exit: Exit the long position when the Contrarian RSI (qrsi_ma) crosses below the overbought level (default: 99), indicating a potential overbought condition and a reversal to the downside.
Customization: Adjust overboughtLevel and oversoldLevel to fine-tune sensitivity. Lower timeframes may benefit from tighter levels (e.g., 20 for oversold, 80 for overbought), while higher timeframes can use extreme levels (e.g., 1 and 99) for stronger reversals.
Timeframe Considerations
Higher Timeframes (Recommended): The indicator is optimized for higher timeframes (e.g., 1H, 4H, Daily) due to its reliance on predictive ranges and smoothed momentum, which perform best with less market noise. These timeframes typically yield more reliable reversal signals.
Lower Timeframes: The indicator can be used on lower timeframes (e.g., 5M, 15M), but signals may be noisier and require additional confirmation (e.g., from price action or other indicators). Extensive backtesting and parameter optimization (e.g., adjusting crsiLength, maLength, or mult) are recommended for lower timeframes.
Inputs
Contrarian RSI Length (crsiLength): Length for RSI momentum calculation (default: 5).
RSI MA Length (maLength): Length of the moving average applied to the RSI (default: 1, effectively no MA).
MA Type (maType): Choose from SMA, EMA, WMA, SMMA, or VWMA (default: SMA).
Overbought Level (overboughtLevel): Upper threshold for exit signals (default: 99).
Oversold Level (oversoldLevel): Lower threshold for entry signals (default: 1).
Plot Signals on Main Chart (plotOnChart): Toggle to display signals on the price chart or the indicator panel (default: false).
Plotted on Lower:
Plotted on Chart:
5 Levels Length (length5Levels): Length for predictive range calculation (default: 200).
Factor (mult): ATR multiplier for predictive ranges (default: 6.0).
5 Levels Timeframe (tf5Levels): Timeframe for predictive range calculation (default: chart timeframe).
Visuals
Contrarian RSI MA: Plotted as a yellow line, representing the smoothed Contrarian RSI with the applied moving average.
Overbought/Oversold Lines: Red line for overbought (default: 99) and green line for oversold (default: 1).
Signals: Blue circles for long entries, white circles for long exits. Signals can be plotted on the main chart (plotOnChart = true) or the indicator panel (plotOnChart = false).
Usage Notes
Use the indicator in conjunction with other tools (e.g., support/resistance, trendlines, or volume) to confirm signals.
Test extensively on your chosen timeframe and asset to optimize parameters like crsiLength, maLength, and mult.
Be cautious with lower timeframes, as false signals may occur due to market noise.
The indicator is designed for contrarian strategies, so it works best in markets with clear reversal patterns.
Disclaimer
This indicator is provided for educational and informational purposes only. Always conduct thorough backtesting and risk management before using any indicator in live trading. The author is not responsible for any financial losses incurred.
Bollinger Bands Entry/Exit ThresholdsBollinger Bands Entry/Exit Thresholds
Author of enhancements: chuckaschultz
Inspired and adapted from the original 'Bollinger Bands Breakout Oscillator' by LuxAlgo
Overview
Pairs nicely with Contrarian 100 MA
The Bollinger Bands Entry/Exit Thresholds is a powerful momentum-based indicator designed to help traders identify potential entry and exit points in trending or breakout markets. By leveraging Bollinger Bands, this indicator quantifies price deviations from the bands to generate bullish and bearish momentum signals, displayed as an oscillator. It includes customizable entry and exit signals based on user-defined thresholds, with visual cues plotted either on the oscillator panel or directly on the price chart.
This indicator is ideal for traders looking to capture breakout opportunities or confirm trend strength, with flexible settings to adapt to various markets and trading styles.
How It Works
The Bollinger Bands Entry/Exit Thresholds calculates two key metrics:
Bullish Momentum (Bull): Measures the extent to which the price exceeds the upper Bollinger Band, expressed as a percentage (0–100).
Bearish Momentum (Bear): Measures the extent to which the price falls below the lower Bollinger Band, also expressed as a percentage (0–100).
The indicator generates:
Long Entry Signals: Triggered when the bearish momentum (bear) crosses below a user-defined Long Threshold (default: 40). This suggests weakening bearish pressure, potentially indicating a reversal or breakout to the upside.
Exit Signals: Triggered when the bullish momentum (bull) crosses below a user-defined Sell Threshold (default: 80), indicating a potential reduction in bullish momentum and a signal to exit long positions.
Signals are visualized as tiny colored dots:
Long Entry: Blue dots, plotted either at the bottom of the oscillator or below the price bar (depending on user settings).
Exit Signal: White dots, plotted either at the top of the oscillator or above the price bar.
Calculation Methodology
Bollinger Bands:
A user-defined Length (default: 14) is used to calculate an Exponential Moving Average (EMA) of the source price (default: close).
Standard deviation is computed over the same length, multiplied by a user-defined Multiplier (default: 1.0).
Upper Band = EMA + (Standard Deviation × Multiplier)
Lower Band = EMA - (Standard Deviation × Multiplier)
Bull and Bear Momentum:
For each bar in the lookback period (length), the indicator calculates:
Bullish Momentum: The sum of positive deviations of the price above the upper band, normalized by the total absolute deviation from the upper band, scaled to a 0–100 range.
Bearish Momentum: The sum of positive deviations of the price below the lower band, normalized by the total absolute deviation from the lower band, scaled to a 0–100 range.
Formula:
bull = (sum of max(price - upper, 0) / sum of abs(price - upper)) * 100
bear = (sum of max(lower - price, 0) / sum of abs(lower - price)) * 100
Signal Generation:
Long Entry: Triggered when bear crosses below the Long Threshold.
Exit: Triggered when bull crosses below the Sell Threshold.
Settings
Length: Lookback period for EMA and standard deviation (default: 14).
Multiplier: Multiplier for standard deviation to adjust Bollinger Band width (default: 1.0).
Source: Input price data (default: close).
Long Threshold: Bearish momentum level below which a long entry signal is generated (default: 40).
Sell Threshold: Bullish momentum level below which an exit signal is generated (default: 80).
Plot Signals on Main Chart: Option to display entry/exit signals on the price chart instead of the oscillator panel (default: false).
Style:
Bullish Color: Color for bullish momentum plot (default: #f23645).
Bearish Color: Color for bearish momentum plot (default: #089981).
Visual Features
Bull and Bear Plots: Displayed as colored lines with gradient fills for visual clarity.
Midline: Horizontal line at 50 for reference.
Threshold Lines: Dashed green line for Long Threshold and dashed red line for Sell Threshold.
Signal Dots:
Long Entry: Tiny blue dots (below price bar or at oscillator bottom).
Exit: Tiny white dots (above price bar or at oscillator top).
How to Use
Add to Chart: Apply the indicator to your TradingView chart.
Adjust Settings: Customize the Length, Multiplier, Long Threshold, and Sell Threshold to suit your trading strategy.
Interpret Signals:
Enter a long position when a blue dot appears, indicating bearish momentum dropping below the Long Threshold.
Exit the long position when a white dot appears, indicating bullish momentum dropping below the Sell Threshold.
Toggle Plot Location: Enable Plot Signals on Main Chart to display signals on the price chart for easier integration with price action analysis.
Combine with Other Tools: Use alongside other indicators (e.g., trendlines, support/resistance) to confirm signals.
Notes
This indicator is inspired by LuxAlgo’s Bollinger Bands Breakout Oscillator but has been enhanced with customizable entry/exit thresholds and signal plotting options.
Best used in conjunction with other technical analysis tools to filter false signals, especially in choppy or range-bound markets.
Adjust the Multiplier to make the Bollinger Bands wider or narrower, affecting the sensitivity of the momentum calculations.
Disclaimer
This indicator is provided for educational and informational purposes only.
Gann Support and Resistance LevelsThis indicator plots dynamic Gann Degree Levels as potential support and resistance zones around the current market price. You can fully customize the Gann degree step (e.g., 45°, 30°, 90°), the number of levels above and below the price, and the price movement per degree to fine-tune the levels to your strategy.
Key Features:
✅ Dynamic levels update automatically with the live price
✅ Adjustable degree intervals (Gann steps)
✅ User control over how many levels to display above and below
✅ Fully customizable label size, label color, and text color for mobile-friendly visibility
✅ Clean visual design for easy chart analysis
How to Use:
Gann levels can act as potential support and resistance zones.
Watch for price reactions at major degrees like 0°, 90°, 180°, and 270°.
Can be combined with other technical tools like price action, trendlines, or Gann fans for deeper analysis.
📌 This tool is perfect for traders using Gann theory, grid-based strategies, or those looking to enhance their visual trading setups with structured levels.
Cumulative Volume Delta📊 Indicator Name:
Cumulative Volume Delta (CVD) + Candle Divergence (Color DIfference)
📌 Purpose:
This indicator visualizes volume delta over a user-defined time anchor and highlights divergence between volume-based momentum and price movement. It's especially useful for identifying potential reversals, fakeouts, or hidden buying/selling pressure.
🔍 How It Works:
1. Volume Delta Calculation (CVD Candles):
The script uses ta.requestVolumeDelta() to approximate volume delta data over a chosen anchor period (e.g., 1D).
Volume delta = Buy Volume – Sell Volume
Each candle on the CVD chart represents changes in cumulative volume delta, with OHLC-style values:
openVolume: cumulative delta at the start of the bar
lastVolume: cumulative delta at the end of the bar
maxVolume, minVolume: intra-bar high and low
2. Visual Representation (CVD Candles):
Green/Teal candle: Delta is increasing (buying pressure dominates)
Red candle: Delta is decreasing (selling pressure dominates)
3. Divergence Detection:
The script compares the direction of the price candle with the direction of the CVD candle:
Price Up + CVD Down → Possible hidden selling (bearish divergence)
Price Down + CVD Up → Possible hidden buying (bullish divergence)
4. Color Highlighting:
Orange candle on the CVD chart signals divergence between price and volume delta.
This color override helps you quickly spot potential discrepancies between price movement and underlying volume pressure.
5. Alerting:
An alertcondition is added so you can receive a notification whenever a divergence occurs.
⚙️ User Inputs:
Anchor period (e.g., 1D): Timeframe over which the CVD is anchored.
Use custom timeframe: Allows you to override and define the internal lower timeframe used for volume estimation (e.g., 1-min).
📈 How to Use It:
✅ Bullish Divergence (Price down, CVD up)
This may indicate:
Buyers absorbing selling pressure.
A potential reversal to the upside.
Hidden accumulation.
🚫 Bearish Divergence (Price up, CVD down)
This may indicate:
Sellers stepping in despite upward price.
A potential reversal to the downside.
Hidden distribution.
🧠 Trading Insights:
CVD is often used by order flow traders or those analyzing market depth and volume imbalances.
This version lets you visually align price action with underlying volume, improving decision-making.
The divergence signal can be combined with other technical tools like support/resistance, candlestick patterns, or trendlines for confirmation.
Demand Index (Hybrid Sibbet) by TradeQUODemand Index (Hybrid Sibbet) by TradeQUO \
\Overview\
The Demand Index (DI) was introduced by James Sibbet in the early 1990s to gauge “real” buying versus selling pressure by combining price‐change information with volume intensity. Unlike pure price‐based oscillators (e.g. RSI or MACD), the DI highlights moves backed by above‐average volume—helping traders distinguish genuine demand/supply from false breakouts or low‐liquidity noise.
\Calculation\
\
\ \Step 1: Weighted Price (P)\
For each bar t, compute a weighted price:
```
Pₜ = Hₜ + Lₜ + 2·Cₜ
```
where Hₜ=High, Lₜ=Low, Cₜ=Close of bar t.
Also compute Pₜ₋₁ for the prior bar.
\ \Step 2: Raw Range (R)\
Calculate the two‐bar range:
```
Rₜ = max(Hₜ, Hₜ₋₁) – min(Lₜ, Lₜ₋₁)
```
This Rₜ is used indirectly in the exponential dampener below.
\ \Step 3: Normalize Volume (VolNorm)\
Compute an EMA of volume over n₁ bars (e.g. n₁=13):
```
EMA_Volₜ = EMA(Volume, n₁)ₜ
```
Then
```
VolNormₜ = Volumeₜ / EMA_Volₜ
```
If EMA\_Volₜ ≈ 0, set VolNormₜ to a small default (e.g. 0.0001) to avoid division‐by‐zero.
\ \Step 4: BuyPower vs. SellPower\
Calculate “raw” BuyPowerₜ and SellPowerₜ depending on whether Pₜ > Pₜ₋₁ (bullish) or Pₜ < Pₜ₋₁ (bearish). Use an exponential dampener factor Dₜ to moderate extreme moves when true range is small. Specifically:
• If Pₜ > Pₜ₋₁,
```
BuyPowerₜ = (VolNormₜ) / exp
```
otherwise
```
BuyPowerₜ = VolNormₜ.
```
• If Pₜ < Pₜ₋₁,
```
SellPowerₜ = (VolNormₜ) / exp
```
otherwise
```
SellPowerₜ = VolNormₜ.
```
Here, H₀ and L₀ are the very first bar’s High/Low—used to calibrate the scale of the dampening. If the denominator of the exponential is near zero, substitute a small epsilon (e.g. 1e-10).
\ \Step 5: Smooth Buy/Sell Power\
Apply a short EMA (n₂ bars, typically n₂=2) to each:
```
EMA_Buyₜ = EMA(BuyPower, n₂)ₜ
EMA_Sellₜ = EMA(SellPower, n₂)ₜ
```
\ \Step 6: Raw Demand Index (DI\_raw)\
```
DI_rawₜ = EMA_Buyₜ – EMA_Sellₜ
```
A positive DI\_raw indicates that buying force (normalized by volume) exceeds selling force; a negative value indicates the opposite.
\ \Step 7: Optional EMA Smoothing on DI (DI)\
To reduce choppiness, compute an EMA over DI\_raw (n₃ bars, e.g. n₃ = 1–5):
```
DIₜ = EMA(DI_raw, n₃)ₜ.
```
If n₃ = 1, DI = DI\_raw (no further smoothing).
\
\Interpretation\
\
\ \Crossing Zero Line\
• DI\_raw (or DI) crossing from below to above zero signals that cumulative buying pressure (over the chosen smoothing window) has overcome selling pressure—potential Long signal.
• Crossing from above to below zero signals dominant selling pressure—potential Short signal.
\ \DI\_raw vs. DI (EMA)\
• When DI\_raw > DI (the EMA of DI\_raw), bullish momentum is accelerating.
• When DI\_raw < DI, bullish momentum is weakening (or bearish acceleration).
\ \Divergences\
• If price makes new highs while DI fails to make higher highs (DI\_raw or DI declining), this hints at weakening buying power (“bearish divergence”), possibly preceding a reversal.
• If price makes new lows while DI fails to make lower lows (“bullish divergence”), this may signal waning selling pressure and a potential bounce.
\ \Volume Confirmation\
• A strong price move without a corresponding rise in DI often indicates low‐volume “fake” moves.
• Conversely, a modest price move with a large DI spike suggests true institutional participation—often a more reliable breakout.
\
\Usage Notes & Warnings\
\
\ \Never Use DI in Isolation\
It is a \filter\ and \confirmation\ tool—combine with price‐action (trendlines, support/resistance, candlestick patterns) and risk management (stop‐losses) before executing trades.
\ \Parameter Selection\
• \Vol EMA length (n₁)\: Commonly 13–20 bars. Shorter → more responsive to volume spikes, but noisier.
• \Buy/Sell EMA length (n₂)\: Typically 2 bars for fast smoothing.
• \DI smoothing (n₃)\: Usually 1 (no smoothing) or 3–5 for moderate smoothing. Long DI\_EMA (e.g. 20–50) gives a slower signal.
\ \Market Adaptation\
Works well in liquid futures, indices, and heavily traded stocks. In thinly traded or highly erratic markets, adjust n₁ upward (e.g., 20–30) to reduce noise.
---
\In Summary\
The Demand Index (James Sibbet) uses a three‐stage smoothing (volume → Buy/Sell Power → DI) to reveal true demand/supply imbalance. By combining normalized volume with price change, Sibbet’s DI helps traders identify momentum backed by real participation—filtering out “empty” moves and spotting early divergences. Always confirm DI signals with price action and sound risk controls before trading.
Adaptive Volume‐Demand‐Index (AVDI)Demand Index (according to James Sibbet) – Short Description
The Demand Index (DI) was developed by James Sibbet to measure real “buying” vs. “selling” strength (Demand vs. Supply) using price and volume data. It is not a standalone trading signal, but rather a filter and trend confirmer that should always be used together with chart structure and additional indicators.
---
\ 1. Calculation Basis\
1. Volume Normalization
$$
\text{normVol}_t
= \frac{\text{Volume}_t}{\mathrm{EMA}(\text{Volume},\,n_{\text{Vol}})_t}
\quad(\text{e.g., }n_{\text{Vol}} = 13)
$$
This smooths out extremely high volume spikes and compares them to the average (≈ 1 means “average volume”).
2. Price Factor
$$
\text{priceFactor}_t
= \frac{\text{Close}_t - \text{Open}_t}{\text{Open}_t}.
$$
Positive values for bullish bars, negative for bearish bars.
3. Component per Bar
$$
\text{component}_t
= \text{normVol}_t \times \text{priceFactor}_t.
$$
If volume is above average (> 1) and the price rises slightly, this yields a noticeably positive value; conversely if the price falls.
4. Raw DI (Rolling Sum)
Over a window of \$w\$ bars (e.g., 20):
$$
\text{RawDI}_t
= \sum_{i=0}^{w-1} \text{component}_{\,t-i}.
$$
Alternatively, recursively for \$t \ge w\$:
$$
\text{RawDI}_t
= \text{RawDI}_{t-1}
+ \text{component}_t
- \text{component}_{\,t-w}.
$$
5. Optional EMA Smoothing
An EMA over RawDI (e.g., \$n\_{\text{DI}} = 50\$) reduces short-term fluctuations and highlights medium-term trends:
$$
\text{EMA\_DI}_t
= \mathrm{EMA}(\text{RawDI},\,n_{\text{DI}})_t.
$$
6.Zero Line
Handy guideline:
RawDI > 0: Accumulated buying power dominates.
RawDI < 0: Accumulated selling power dominates.
2. Interpretation & Application
Crossing Zero
RawDI above zero → Indication of increasing buying pressure (potential long signal).
RawDI below zero → Indication of increasing selling pressure (potential short signal).
Not to be used alone for entry—always confirm with price action.
RawDI vs. EMA_DI
RawDI > EMA\_DI → Acceleration of demand.
RawDI < EMA\_DI → Weakening of demand.
Divergences
Price makes a new high, RawDI does not make a higher high → potential weakness in the uptrend.
Price makes a new low, RawDI does not make a lower low → potential exhaustion of the downtrend.
3. Typical Signals (for Beginners)
\ 1. Long Setup\
RawDI crosses zero from below,
RawDI > EMA\_DI (acceleration),
Price closes above a short-term swing high or resistance.
Stop-Loss: just below the last swing low, Take-Profit/Trailing: on reversal signals or fixed R\:R.
2. Short Setup
RawDI crosses zero from above,
RawDI < EMA\_DI (increased selling pressure),
Price closes below a short-term swing low or support.
Stop-Loss: just above the last swing high.
---
4. Notes and Parameters
Recommended Values (Beginners):
Volume EMA (n₍Vol₎) = 13
RawDI window (w) = 20
EMA over DI (n₍DI₎) = 50 (medium-term) or 1 (no smoothing)
Attention:\
NEVER use in isolation. Always in combination with price action analysis (trendlines, support/resistance, candlestick patterns).
Especially during volatile news phases, RawDI can fluctuate strongly → EMA\_DI helps to avoid false signals.
---
Conclusion The Demand Index by James Sibbet is a powerful filter to assess price movements by their volume backing. It shows whether a rally is truly driven by demand or merely a short-term volume anomaly. In combination with classic chart analysis and risk management, it helps to identify robust entry points and potential trend reversals earlier.
Simple Auto Trend LinesOpinionated way of drawing automatic trend lines. It draws automatically trend lines based on specified top/bottom strengths with multiple sets in order to keep track of multiple levels of interest.
Has the ability to hide invalidated trendlines if price moves away from it.
RSI Crossover Signal Companion - Alerts + Visuals🔷 RSI Crossover Signal Companion — Alerts + Visuals
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of recent price movements. It helps traders identify overbought or oversold conditions, possible trend reversals, and momentum strength.
This utility builds on TradingView’s classic Relative Strength Index (RSI) by adding real-time alerts and triangle markers when the RSI crosses its own moving average — a common technique for early momentum detection.
It is designed as a lightweight, visual companion tool for traders using RSI/MA crossover logic in manual or semi-automated strategies.
🔍 Features
✅ Preserves the full original RSI layout, including:
• Gradient fill and overbought/oversold zones
• Standard RSI input settings (length, source, etc.)
• MA smoothing options with user-defined type and length
🔺 Adds visual triangle markers:
🔼 Up triangle when RSI crosses above its MA
🔽 Down triangle when RSI crosses below its MA
📢 Built-in alerts for RSI/MA crosses:
“RSI Crossed Above MA”
“RSI Crossed Below MA”
📈 How to Use
This script is ideal for:
• Spotting early momentum shifts
• Confirming entries or exits in other systems (price action, trendlines, breakouts)
• Building alert-based automation (webhooks, bots, etc.)
Popular use cases:
• Combine with trend indicators like MA200 or MA12
• Use in confluence with price structure and divergence
• Validate breakout moves with momentum confirmation
⚙️ Customization
RSI length, MA length, MA type, and source are fully adjustable
Triangle marker size, shape, and color can be edited under Style
Alerts are pre-built and ready for use
Tight Range Display with Background🌟 Tight Range Transparency Display with Background
What Is This Indicator?
Hey traders! Ever wanted a simple way to spot those quiet, low-volatility moments in the market that often signal a big move is coming? The Tight Range Transparency Display with Background does exactly that! This indicator highlights periods where the price is moving in a tight range—think of it as the calm before the storm. It paints the chart background blue to show these zones, with the shade getting darker the tighter the range becomes. It’s like having a visual cue to say, “Hey, something might be brewing here!”
Why You’ll Love It
Spot Key Moments Easily: The blue background makes it super easy to see when the market is in a tight range, which often happens before breakouts or big trends.
Customizable Settings: You can tweak the range thresholds to match your trading style—whether you’re looking for super tight zones or slightly broader ones.
Visual Clarity: The background gets darker when the range is tighter, giving you a quick sense of how compressed the price action is.
Perfect for Any Market: Works on stocks, forex, crypto, or any chart you trade, across any timeframe.
How to Use It
Add It to Your Chart:
Just copy this script into TradingView’s Pine Editor and hit "Add to Chart." It’ll overlay right on your price chart.
Tweak the Settings:
Open the indicator settings and use the dropdown menus to pick your preferred "Tight Range %" and "Wide Range %." For example, set a Tight Range % of 2.0% to catch smaller ranges, or go higher like 10.0% for broader ones.
You can also adjust the ATR Period (default is 5) to make the indicator more or less sensitive to recent price swings.
Watch for the Blue Background:
When the price enters a tight range, the chart background turns blue. The darker the blue, the tighter the range—meaning a potential breakout could be closer!
Trade Smarter:
Use these tight range zones to prepare for potential breakouts. For example, if you see a dark blue background, it might be a good time to watch for a big price move.
Pair this with other tools like support/resistance levels or volume spikes to confirm your trades.
Who Is This For?
Swing Traders: Perfect for spotting consolidation zones before a big swing.
Breakout Traders: Tight ranges often lead to breakouts—use this to time your entries.
Smart Money Followers: If you’re into smart money concepts, tight ranges can signal accumulation or distribution phases.
Beginners & Pros Alike: It’s easy to use for new traders but powerful enough for seasoned pros.
Real-World Example
Imagine you’re trading a stock on a 1-hour chart. You notice the background turns blue, and it’s getting darker over a few bars. This tells you the price range is tightening—maybe the stock is consolidating after a big move. You check your other indicators, see a volume spike, and spot a breakout above resistance. Boom! You catch the next big trend, all because this indicator helped you focus on the right moment.
Tips for Best Results
Try Different Timeframes: Tight ranges on a 15-minute chart might signal short-term moves, while a daily chart could highlight bigger trends.
Adjust for Your Market: For volatile markets like crypto, you might want a higher Tight Range % (e.g., 10.0%). For calmer markets like forex, try a lower setting (e.g., 2.0%).
Combine with Other Tools: Use this alongside trendlines, moving averages, or volume indicators to confirm your setups.
Why I Made This
I created this indicator because I wanted a simple, visual way to spot those critical low-volatility zones without cluttering my chart. The dynamic background color makes it intuitive to see when the market is “coiling up” for a potential move. I hope it helps you find better trading opportunities just like it does for me!
Let’s Connect
If you find this indicator helpful, I’d love to hear about it! Drop a comment or a rating to let me know how it’s working for you. Got ideas to make it even better? Feel free to message me on TradingView—I’m always open to suggestions.
Published On
Date: May 22, 2025
Happy trading, and may your charts always be in your favor! 🚀
How to Publish on TradingView
Open Pine Editor:
On TradingView, open a chart and go to the Pine Editor tab at the bottom.
Paste the Code:
Copy the script you provided and paste it into the Pine Editor.
Compile:
Click "Add to Chart" to ensure it compiles without errors.
Publish:
Click the "Publish Script" button (paper plane icon) in the Pine Editor.
Select "Publish New Script."
Add the Description:
Title: "Tight Range Transparency Display with Background"
Description: Copy the content above into the description field.
Visibility: Choose "Public" to share with everyone (or "Invite-Only" for restricted access).
Tags: Add tags like "tight range", "breakout", "smart money", "volatility", "swing trading".
Screenshot: Add a screenshot of the indicator on a chart, showing the blue background during a tight range.
Submit:
Click "Publish" to submit. TradingView will review it and make it live if it meets their guidelines.
Additional Notes
Screenshot Tip: Use a chart where the blue background is clearly visible (e.g., during a consolidation period) to make the indicator’s effect stand out.
Engage with Users: After publishing, respond to comments and feedback to build a positive reputation on TradingView.
This content is designed to be approachable and engaging, helping traders understand the value of your indicator and encouraging them to try it out.
(OFPI) Order Flow Polarity Index - Momentum Gauge (DAFE) (OFPI) Order Flow Polarity Index - Momentum Gauge: Decode Market Aggression
The (OFPI) Gauge Bar is your front-row seat to the battle between buyers and sellers. This isn’t just another indicator—it’s a momentum tracker that reveals market aggression through a sleek, centered gauge bar and a smart dashboard. Built for traders who want clarity without clutter, it’s your edge for spotting who’s driving price, bar by bar.
What Makes It Unique?
Order Flow Pressure Index (OFPI): Splits volume into buy vs. sell pressure based on candle body position. It’s not just volume—it’s intent, showing who’s got the upper hand.
T3 Smoothing Magic: Uses a Tilson T3 moving average to keep signals smooth yet responsive. No laggy SMA nonsense here.
Centered Gauge Bar: A 20-segment bar splits bullish (lime) and bearish (red) momentum around a neutral center. Empty segments scream indecision—it’s like a visual heartbeat of the market.
Momentum Shift Alerts: Catches reversals with “Momentum Shift” flags when the OFPI crests, so you’re not caught off guard.
Clean Dashboard: A compact, bottom-left table shows momentum status, the gauge bar, and the OFPI value. Color-coded, transparent, and no chart clutter.
Inputs & Customization
Lookback Length (default 10): Set the window for pressure calculations. Short for scalps, long for trends.
T3 Smoothing Length (default 5): Tune the smoothness. Tight for fast markets, relaxed for chill ones.
T3 Volume Factor (default 0.7): Crank it up for snappy signals or down for silky trends.
Toggle the dashboard for minimalist setups or mobile trading.
How to Use It
Bullish Momentum (Lime, Right-Filled): Buyers are flexing. Look for breakouts or trend continuations. Pair with support levels.
Bearish Momentum (Red, Left-Filled): Sellers are in charge. Scout for breakdowns or shorts. Check resistance zones.
Neutral (Orange, Near Center): Market’s chilling. Avoid big bets—wait for a breakout or play the range.
Momentum Shift: A reversal might be brewing. Confirm with price action before jumping in.
Not a Solo Act: Combine with your strategy—trendlines, RSI, whatever. It’s a momentum lens, not a buy/sell bot.
Why Use the OFPI Gauge?
See the Fight: Most tools just count volume. OFPI shows who’s winning with a visual that slaps.
Works Anywhere: Crypto, stocks, forex, any timeframe. Tune it to your style.
Clean & Pro: No chart spam, just a sharp gauge and a dashboard that delivers.
Unique Edge: No other indicator blends body-based pressure, T3 smoothing, and a centered gauge like this.
The OFPI Gauge catches the market’s pulse so you can trade with confidence. It’s not about predicting the future—it’s about knowing who’s in control right now.
For educational purposes only. Not financial advice. Always use proper risk management.
Use with discipline. Trade your edge.
— Dskyz , for DAFE Trading Systems
Why EMA Isn't What You Think It IsMany new traders adopt the Exponential Moving Average (EMA) believing it's simply a "better Simple Moving Average (SMA)". This common misconception leads to fundamental misunderstandings about how EMA works and when to use it.
EMA and SMA differ at their core. SMA use a window of finite number of data points, giving equal weight to each data point in the calculation period. This makes SMA a Finite Impulse Response (FIR) filter in signal processing terms. Remember that FIR means that "all that we need is the 'period' number of data points" to calculate the filter value. Anything beyond the given period is not relevant to FIR filters – much like how a security camera with 14-day storage automatically overwrites older footage, making last month's activity completely invisible regardless of how important it might have been.
EMA, however, is an Infinite Impulse Response (IIR) filter. It uses ALL historical data, with each past price having a diminishing - but never zero - influence on the calculated value. This creates an EMA response that extends infinitely into the past—not just for the last N periods. IIR filters cannot be precise if we give them only a 'period' number of data to work on - they will be off-target significantly due to lack of context, like trying to understand Game of Thrones by watching only the final season and wondering why everyone's so upset about that dragon lady going full pyromaniac.
If we only consider a number of data points equal to the EMA's period, we are capturing no more than 86.5% of the total weight of the EMA calculation. Relying on he period window alone (the warm-up period) will provide only 1 - (1 / e^2) weights, which is approximately 1−0.1353 = 0.8647 = 86.5%. That's like claiming you've read a book when you've skipped the first few chapters – technically, you got most of it, but you probably miss some crucial early context.
▶️ What is period in EMA used for?
What does a period parameter really mean for EMA? When we select a 15-period EMA, we're not selecting a window of 15 data points as with an SMA. Instead, we are using that number to calculate a decay factor (α) that determines how quickly older data loses influence in EMA result. Every trader knows EMA calculation: α = 1 / (1+period) – or at least every trader claims to know this while secretly checking the formula when they need it.
Thinking in terms of "period" seriously restricts EMA. The α parameter can be - should be! - any value between 0.0 and 1.0, offering infinite tuning possibilities of the indicator. When we limit ourselves to whole-number periods that we use in FIR indicators, we can only access a small subset of possible IIR calculations – it's like having access to the entire RGB color spectrum with 16.7 million possible colors but stubbornly sticking to the 8 basic crayons in a child's first art set because the coloring book only mentioned those by name.
For example:
Period 10 → alpha = 0.1818
Period 11 → alpha = 0.1667
What about wanting an alpha of 0.17, which might yield superior returns in your strategy that uses EMA? No whole-number period can provide this! Direct α parameterization offers more precision, much like how an analog tuner lets you find the perfect radio frequency while digital presets force you to choose only from predetermined stations, potentially missing the clearest signal sitting right between channels.
Sidenote: the choice of α = 1 / (1+period) is just a convention from 1970s, probably started by J. Welles Wilder, who popularized the use of the 14-day EMA. It was designed to create an approximate equivalence between EMA and SMA over the same number of periods, even thought SMA needs a period window (as it is FIR filter) and EMA doesn't. In reality, the decay factor α in EMA should be allowed any valye between 0.0 and 1.0, not just some discrete values derived from an integer-based period! Algorithmic systems should find the best α decay for EMA directly, allowing the system to fine-tune at will and not through conversion of integer period to float α decay – though this might put a few traditionalist traders into early retirement. Well, to prevent that, most traditionalist implementations of EMA only use period and no alpha at all. Heaven forbid we disturb people who print their charts on paper, draw trendlines with rulers, and insist the market "feels different" since computers do algotrading!
▶️ Calculating EMAs Efficiently
The standard textbook formula for EMA is:
EMA = CurrentPrice × alpha + PreviousEMA × (1 - alpha)
But did you know that a more efficient version exists, once you apply a tiny bit of high school algebra:
EMA = alpha × (CurrentPrice - PreviousEMA) + PreviousEMA
The first one requires three operations: 2 multiplications + 1 addition. The second one also requires three ops: 1 multiplication + 1 addition + 1 subtraction.
That's pathetic, you say? Not worth implementing? In most computational models, multiplications cost much more than additions/subtractions – much like how ordering dessert costs more than asking for a water refill at restaurants.
Relative CPU cost of float operations :
Addition/Subtraction: ~1 cycle
Multiplication: ~5 cycles (depending on precision and architecture)
Now you see the difference? 2 * 5 + 1 = 11 against 5 + 1 + 1 = 7. That is ≈ 36.36% efficiency gain just by swapping formulas around! And making your high school math teacher proud enough to finally put your test on the refrigerator.
▶️ The Warmup Problem: how to start the EMA sequence right
How do we calculate the first EMA value when there's no previous EMA available? Let's see some possible options used throughout the history:
Start with zero : EMA(0) = 0. This creates stupidly large distortion until enough bars pass for the horrible effect to diminish – like starting a trading account with zero balance but backdating a year of missed trades, then watching your balance struggle to climb out of a phantom debt for months.
Start with first price : EMA(0) = first price. This is better than starting with zero, but still causes initial distortion that will be extra-bad if the first price is an outlier – like forming your entire opinion of a stock based solely on its IPO day price, then wondering why your model is tanking for weeks afterward.
Use SMA for warmup : This is the tradition from the pencil-and-paper era of technical analysis – when calculators were luxury items and "algorithmic trading" meant your broker had neat handwriting. We first calculate an SMA over the initial period, then kickstart the EMA with this average value. It's widely used due to tradition, not merit, creating a mathematical Frankenstein that uses an FIR filter (SMA) during the initial period before abruptly switching to an IIR filter (EMA). This methodology is so aesthetically offensive (abrupt kink on the transition from SMA to EMA) that charting platforms hide these early values entirely, pretending EMA simply doesn't exist until the warmup period passes – the technical analysis equivalent of sweeping dust under the rug.
Use WMA for warmup : This one was never popular because it is harder to calculate with a pencil - compared to using simple SMA for warmup. Weighted Moving Average provides a much better approximation of a starting value as its linear descending profile is much closer to the EMA's decay profile.
These methods all share one problem: they produce inaccurate initial values that traders often hide or discard, much like how hedge funds conveniently report awesome performance "since strategy inception" only after their disastrous first quarter has been surgically removed from the track record.
▶️ A Better Way to start EMA: Decaying compensation
Think of it this way: An ideal EMA uses an infinite history of prices, but we only have data starting from a specific point. This creates a problem - our EMA starts with an incorrect assumption that all previous prices were all zero, all close, or all average – like trying to write someone's biography but only having information about their life since last Tuesday.
But there is a better way. It requires more than high school math comprehension and is more computationally intensive, but is mathematically correct and numerically stable. This approach involves compensating calculated EMA values for the "phantom data" that would have existed before our first price point.
Here's how phantom data compensation works:
We start our normal EMA calculation:
EMA_today = EMA_yesterday + α × (Price_today - EMA_yesterday)
But we add a correction factor that adjusts for the missing history:
Correction = 1 at the start
Correction = Correction × (1-α) after each calculation
We then apply this correction:
True_EMA = Raw_EMA / (1-Correction)
This correction factor starts at 1 (full compensation effect) and gets exponentially smaller with each new price bar. After enough data points, the correction becomes so small (i.e., below 0.0000000001) that we can stop applying it as it is no longer relevant.
Let's see how this works in practice:
For the first price bar:
Raw_EMA = 0
Correction = 1
True_EMA = Price (since 0 ÷ (1-1) is undefined, we use the first price)
For the second price bar:
Raw_EMA = α × (Price_2 - 0) + 0 = α × Price_2
Correction = 1 × (1-α) = (1-α)
True_EMA = α × Price_2 ÷ (1-(1-α)) = Price_2
For the third price bar:
Raw_EMA updates using the standard formula
Correction = (1-α) × (1-α) = (1-α)²
True_EMA = Raw_EMA ÷ (1-(1-α)²)
With each new price, the correction factor shrinks exponentially. After about -log₁₀(1e-10)/log₁₀(1-α) bars, the correction becomes negligible, and our EMA calculation matches what we would get if we had infinite historical data.
This approach provides accurate EMA values from the very first calculation. There's no need to use SMA for warmup or discard early values before output converges - EMA is mathematically correct from first value, ready to party without the awkward warmup phase.
Here is Pine Script 6 implementation of EMA that can take alpha parameter directly (or period if desired), returns valid values from the start, is resilient to dirty input values, uses decaying compensator instead of SMA, and uses the least amount of computational cycles possible.
// Enhanced EMA function with proper initialization and efficient calculation
ema(series float source, simple int period=0, simple float alpha=0)=>
// Input validation - one of alpha or period must be provided
if alpha<=0 and period<=0
runtime.error("Alpha or period must be provided")
// Calculate alpha from period if alpha not directly specified
float a = alpha > 0 ? alpha : 2.0 / math.max(period, 1)
// Initialize variables for EMA calculation
var float ema = na // Stores raw EMA value
var float result = na // Stores final corrected EMA
var float e = 1.0 // Decay compensation factor
var bool warmup = true // Flag for warmup phase
if not na(source)
if na(ema)
// First value case - initialize EMA to zero
// (we'll correct this immediately with the compensation)
ema := 0
result := source
else
// Standard EMA calculation (optimized formula)
ema := a * (source - ema) + ema
if warmup
// During warmup phase, apply decay compensation
e *= (1-a) // Update decay factor
float c = 1.0 / (1.0 - e) // Calculate correction multiplier
result := c * ema // Apply correction
// Stop warmup phase when correction becomes negligible
if e <= 1e-10
warmup := false
else
// After warmup, EMA operates without correction
result := ema
result // Return the properly compensated EMA value
▶️ CONCLUSION
EMA isn't just a "better SMA"—it is a fundamentally different tool, like how a submarine differs from a sailboat – both float, but the similarities end there. EMA responds to inputs differently, weighs historical data differently, and requires different initialization techniques.
By understanding these differences, traders can make more informed decisions about when and how to use EMA in trading strategies. And as EMA is embedded in so many other complex and compound indicators and strategies, if system uses tainted and inferior EMA calculatiomn, it is doing a disservice to all derivative indicators too – like building a skyscraper on a foundation of Jell-O.
The next time you add an EMA to your chart, remember: you're not just looking at a "faster moving average." You're using an INFINITE IMPULSE RESPONSE filter that carries the echo of all previous price actions, properly weighted to help make better trading decisions.
EMA done right might significantly improve the quality of all signals, strategies, and trades that rely on EMA somewhere deep in its algorithmic bowels – proving once again that math skills are indeed useful after high school, no matter what your guidance counselor told you.
Precision LevelsThis open-source Support and Resistance Indicator helps traders plot key price levels where the market may reverse or consolidate. By plotting support and resistance zones based on historical price action, it provides clear visual cues for potential entry and exit points across various timeframes.
Customizable Settings: Adjust visual styles to suit your trading strategy.
Multi-Timeframe Support: View and plot levels from higher timeframes using the monthly and weekly levels.
User-Friendly: Lightweight design with clear plotting for easy integration into any setup.
How It Works:
The indicator plots simple Support and resistance. Zones are labeled monthly, weekly, and daily
Usage:
Apply the indicator to your chart.
Enter a value for each support and resistance level. Drag and Adjust on the chart to your liking.
Use the plotted levels to identify potential reversals, breakouts, or stop-loss placements.
Combine with other tools (e.g., trendlines or oscillators) for confirmation.
Note: This is the open-source version of my previously protected Support and Resistance Indicator. The protected version is flagged and hidden from community and no longer maintained. Feel free to explore and modify the code to fit your needs! For feedback or suggestions, leave a comment below or message me direct.
SuperTrend: Silent Shadow 🕶️ SuperTrend: Silent Shadow — Operate in trend. Vanish in noise.
Overview
SuperTrend: Silent Shadow is an enhanced trend-following system designed for traders who demand clarity in volatile markets and silence during indecision.
It combines classic Supertrend logic with a proprietary ShadowTrail engine and an adaptive Silence Protocol to filter noise and highlight only the cleanest signals.
Key Features
✅ Core Supertrend Logic
Built on Average True Range (ATR), this trend engine identifies directional bias with visual clarity. Lines adjust dynamically with price action and flip when meaningful reversals occur.
✅ ShadowTrail: Stepped Counter-Barrier
ShadowTrail doesn’t predict reversals — it reinforces structure.
When price is trending, ShadowTrail forms a stepped ceiling in downtrends and a stepped floor in uptrends. This visual containment zone helps define the edges of price behavior and offers a clear visual anchor for stop-loss placement and trade containment.
✅ Silence Protocol: Adaptive Noise Filtering
During low-volatility zones, the system enters “stealth mode”:
• Trend lines turn white to indicate reduced signal quality
• Fill disappears to reduce distraction
This helps avoid choppy entries and keeps your focus sharp when the market isn’t.
✅ Visual Support & Stop-Loss Utility
When trendlines flatten or pause, they naturally highlight price memory zones. These flat sections often align with:
• Logical stop-loss levels
• Prior support/resistance areas
• Zones of reduced volatility where price recharges or rejects
✅ Custom Styling
Full control over line colors, width, transparency, fill visibility, and silence behavior. Tailor it to your strategy and visual preferences.
How to Use
• Use Supertrend color to determine bias — flips mark momentum shifts
• ShadowTrail mirrors the primary trend as a structural ceiling/floor
• Use flat segments of both lines to identify consolidation zones or place stops
• White lines = low-quality signal → stand by
• Combine with RSI, volume, divergence, or your favorite tools for confirmation
Recommended For:
• Traders seeking clearer trend signals
• Avoiding false entries in sideways or silent markets
• Identifying key support/resistance visually
• Structuring stops around real market containment levels
• Scalping, swing, or position trading with adaptive clarity
Built by Sherlock Macgyver
Forged for precision. Designed for silence.
When the market speaks, you listen.
When it doesn’t — you wait in the shadows.
BK AK-47 Divergence🚨 Introducing BK AK-47 Divergence — Multi-Timeframe Precision Firepower for True Traders 🚨
After months of development, I’m proud to release my fifth weapon in the arsenal — BK AK-47 Divergence.
💥 Why “AK-47”? The Meaning Behind the Name
The AK-47 isn’t just a rifle. It’s the symbol of reliability, versatility, and raw stopping power. It performs in every environment — from the mud to the mountains — just like this indicator cuts through noise on any timeframe, any asset, any condition.
🔸 “AK” honors the same legacy as before — my mentor, A.K., whose discipline and vision forged my trading edge.
🔸 “47” signifies layered precision: 4 = structure, 7 = spiritual completion. Together, it’s the weapon of divine order that adapts, reacts, and strikes with purpose.
🔍 What Is BK AK-47 Divergence?
It’s a next-generation divergence detector — a smart hybrid of MACD, Bollinger Bands, and multi-timeframe divergence logic wrapped in a custom volatility engine and real-time flash alerts.
Designed for snipers in the market — those who only take the highest-probability shots.
⚙️ Core Weapon Systems
✅ MACD + BB Precision Overlay → MACD plotted inside dynamic Bollinger Bands — reveals hidden pressure zones where most indicators fail.
✅ Smart Histogram Scaling → Adaptive amplification based on volatility. No more weak histograms in strong markets.
✅ Full Multi-Timeframe Divergence Detection:
🔻 Current TF Divergence
🕐 Higher TF Divergence
⏱️ Lower TF Divergence
Each plotted with clean visual alerts, color-coded by direction and timeframe. You get instant divergence recognition across dimensions.
✅ Background Flash Alerts → When MACD hits BB extremes, the background lights up in red or green. Eyes instantly lock in on key moments.
✅ Advanced Pivot Lookback Control → New lookback system compares multiple pivot layers, not just the last swing. This gives true structural divergence, not just noise.
✅ Dynamic Fill Zones:
🔴 Oversold
🟢 Overbought
🔵 Neutral
Built to filter false signals and highlight hidden edge.
🛡️ Why This Indicator Changes the Game
🔹 Built for divergence snipers — not lagging MACD watchers.
🔹 Perfect for traders who sync with:
• Elliott Waves
• Fibonacci Time/Price Clusters
• Harmonic Patterns
• Gann Angles or Squares
• Price Action & Trendlines
🔹 Lets you visually map:
• Converging divergences (multi-TF confirmation)
• High-volatility histograms in low-volatility price zones (entry sweet spots)
• Flash-momentum warnings at BB pressure zones
🎯 How to Use BK AK-47 Divergence
🔹 Breakout Confirmation → MACD breaches upper BB with bullish divergence = signal to ride momentum.
🔹 Mean Reversion Reversals → MACD breaks lower BB + bullish div = setup for sniper long.
🔹 Top/Bottom Detection → Bearish divergence + MACD failure at upper BB = early reversal signal.
🔹 TF Sync Strategy → Align current TF with higher or lower divergences for laser-confirmed entries.
🧠 Final Thoughts
This isn’t just a divergence tool. It’s a battlefield reconnaissance system — one that lets you see when, where, and why the next pivot is forming.
🔹 Built in honor of the AK-legacy — reliability, discipline, and firepower.
🔹 Designed to cut through noise, expose structure, and alert you to what really matters.
🔹 Crafted for those who trade with intent, vision, and respect for the craft.
🙏 And most importantly: All glory to Gd — the One who gives wisdom, clarity, and purpose.
Without Him, the markets are chaos. With Him, we move in structure, order, and divine timing.
—
⚡ Stay dangerous. Stay precise. Stay aligned.
🔥 BK AK-47 Divergence — Locked. Loaded. Laser-focused. 🔥
May the markets bend to your discipline.
Gd bless. 🙏
Rocky's Dynamic DikFat Supply & Demand ZonesDynamic Supply & Demand Zones
Overview
The Dynamic Supply & Demand Zones indicator identifies key supply and demand levels on your chart by detecting pivot highs and lows. It draws customizable boxes around these zones, helping traders visualize areas where price may react. With flexible display options and dynamic box behavior, this tool is designed to assist in identifying potential support and resistance levels for various trading strategies.
Key Features
Pivot-Based Zones: Automatically detects supply (resistance) and demand (support) zones using pivot highs and lows on the chart’s timeframe.
Dynamic Box Sizing: Boxes shrink when price enters them, reflecting reduced zone strength, and stop adjusting once price fully crosses through.
Customizable Display: Choose to show current-day boxes, historical boxes, or all boxes, with an option to update past box colors dynamically.
Session-Based Extension: Boxes can extend to the current bar or stop at 4:00 PM of the creation day’s 9:30 AM–4:00 PM trading session (ideal for stock markets).
Color Coding: Borders change color based on price position:
Green for demand zones (price above the box).
Red for supply zones (price below the box).
White for neutral zones (price inside the box).
User-Friendly Inputs: Adjust pivot lookback periods, box visibility, extension behavior, and colors via intuitive input settings.
How It Works
Zone Detection: The indicator uses pivot highs and lows to define supply and demand zones, plotting boxes between these levels.
Box Behavior:
Boxes are created when pivot highs and lows are confirmed, with no overlap with the previous box.
When price enters a box, it shrinks to reflect interaction, stopping once price exits completely.
Boxes can extend to the current bar or end at 4:00 PM of the creation day (or next trading day if created after 4:00 PM or on weekends).
Display Options:
Current Only: Shows boxes created on the current day.
Historical Only: Shows boxes from previous days, with optional color updates.
All Boxes: Shows all boxes, with an option to hide historical box color updates.
Performance: Limits the number of boxes to 200 to ensure smooth performance, removing older boxes as needed.
Inputs
Pivot Look Right/Left: Set the number of bars (default: 2) to confirm pivot highs and lows.
What Boxes to Show: Select Current Only, Historical Only, or All Boxes (default: Current Only).
Boxes On/Off: Toggle box visibility (default: on).
Extend Boxes to Current Bar: Choose whether boxes extend to the current bar or stop at 4:00 PM (default: off, stops at 4:00 PM).
Update Past Box Colors: Enable/disable color updates for historical boxes (default: on).
Demand/Supply/Neutral Box Color: Customize border colors (default: green, red, white).
How to Use
Add the indicator to your chart.
Adjust inputs to match your trading style (e.g., pivot lookback, box extension, colors).
Use the boxes to identify potential support (demand) and resistance (supply) zones:
Green-bordered boxes (price above) may act as support.
Red-bordered boxes (price below) may act as resistance.
White-bordered boxes (price inside) indicate active price interaction.
Combine with other analysis tools (e.g., trendlines, indicators) to confirm trade setups.
Monitor box shrinking to gauge zone strength and watch for breakouts when price fully crosses a box.
Understanding Supply and Demand in Stock Trading
In stock trading, supply and demand are fundamental forces driving price movements. Demand refers to the willingness of buyers to purchase a stock at a given price, often creating support levels where buying interest prevents further price declines. Supply represents the willingness of sellers to offload a stock, forming resistance levels where selling pressure halts price increases. These zones are critical because they highlight areas where significant buying or selling activity has occurred, influencing future price behavior.
The importance of supply and demand lies in their ability to reveal where institutional traders, with large orders, have entered or exited the market. Demand zones, often seen at pivot lows, indicate strong buying interest and potential areas for price reversals or bounces. Supply zones, typically at pivot highs, signal heavy selling and possible reversal points for downward moves. By identifying these zones, traders can anticipate where price is likely to stall, reverse, or break out, enabling better entry and exit decisions. This indicator visualizes these zones as dynamic boxes, making it easier to spot high-probability trading opportunities while emphasizing the core market dynamics of supply and demand.
Feedback
This indicator is designed to help traders visualize supply and demand zones effectively. If you have suggestions for improvements, please share your feedback in the comments!
