Oops ReversalThis indicator identifies bullish Oops reversal days — a classic setup refined for stronger confirmation and early detection.
✅ Criteria for Signal (on current day):
Gap Down Open:
The stock opens below the previous day's low, suggesting initial weakness.
Shallow Intraday Dip:
Price doesn't fall more than 1% below the open, indicating the sell-off lacks follow-through.
Strong Reversal:
During the same day, the stock rallies and crosses the previous day's low by at least 1%, confirming strength and buyer control.
Indicatori e strategie
Internal Pivot Pattern [LuxAlgo]The Internal Pivot Pattern indicator is a novel method allowing traders to detect pivots without excessive delay on the chart timeframe, by using the lower timeframe data from a candle.
It features custom colors for candles and zigzag lines to help identify trends. A dashboard showing the accuracy of the pattern is also included.
🔶 USAGE
We define a pivot as the occurrence where the middle candle over a specific interval (for example, the most recent 21 bars) is the highest (pivot high) or the lowest (pivot low). This method commonly allows for identifying swing highs/lows on a trader's chart; however, this pattern can only be identified after a specific number of bars has been formed, rendering this pattern useless for real-time detection of swing highs/lows.
This indicator uses a different approach, removing the need to wait for candles to form on the user chart; instead, we check the lower timeframe data of the current candle and evaluate for the presence of a pivot given the internal data, effectively providing pivot confirmation at the candle close.
An internal pivot low pattern is indicative of a potential uptrend, while an internal pivot high is indicative of a potential downtrend.
Candles are colored based on the last internal pivot detected, with blue candle colors indicating that the most recent internal pivot is a pivot low, indicating an uptrend, while an orange candle color indicates that the most recent internal pivot is a pivot high, indicating a downtrend.
🔹 Timeframes
The timeframe setting allows controlling the amount of lower timeframe data to consider for the internal pivot detection. This setting must be lower than the user's chart timeframe.
Using a timeframe significantly lower than the user chart timeframe will evaluate a larger amount of data for the pivot detection, making it less frequent, while using a timeframe closer to the chart timeframe can make the internal pivot detection more frequent, and more prone to false positives.
🔹 Accuracy Dashboard
The Accuracy Dashboard allows evaluating how accurate the detected patterns are as a percentage, with a pattern being judged accurate if subsequent patterns are detected higher or lower than a previous one.
For example, an internal pivot low is judged accurate if the following internal pivot is higher than it, indicating that higher highs have been made.
This dashboard can be useful to determine the timeframe setting to maximize the respective internal pivot accuracy.
🔶 SETTINGS
Timeframe: Timeframe for detecting internal swings
Accuracy Dashboard: Enable or disable the Accuracy Dashboard.
🔹 Style
Internal Pivot High: Color of the dot displayed upon the detection of an internal pivot high
Internal Pivot Low: Color of the dot displayed upon the detection of an internal pivot low
Zig-Zag: Color of the zig-zag segments connecting each internal pivot
Candles: Enable candle coloring, with control over the color of the candles highlighting the detected trend
Silver BulletSilver Bullet is a trading tool built for finding cleaner, higher-probability setups. It focuses on key windows of market movement and adds helpful tools like daily range levels and candlestick patterns.
Whether you’re trading breakouts or reversals, Silver Bullet gives you a clearer view of the market and more confidence in your setups.
⸻
🔹 Trading Setup #1: Macro Time
The Macro Time setting offers two modes: Macro Bullet and Silver Bullet. Both help traders focus on specific times when the market tends to deliver clean moves.
• Macro Bullet is based on the high and low of a full macro session. It automatically detects the session’s range and bias, then offers optimal entries for either Long or Short setups. Once the session resolves, it provides Fibonacci-based levels for entry, target, and stop loss.
• Silver Bullet is based on ICT concepts and focuses on the hourly range for London, NY AM, and NY PM sessions. It’s designed for quick time blocks and highlights key levels as the session unfolds.
To use this setup, set Macro Time to “ICT Sessions” and select your preferred mode under Bullet Mode.
⸻
🔹 Trading Setup #2: Daily Range
Enable Daily Range to draw Fibonacci levels based on either the previous day’s candle or the current day’s developing range. These levels help you identify potential support, resistance, and midpoint zones throughout the day.
With the current day’s range, levels automatically update in real time as new highs or lows form — keeping your chart aligned with evolving price action.
⸻
🔹 Trading Setup #3: Candlestick Patterns
Turn on Candlestick Patterns to automatically highlight clean reversal signals such as Hammers, Hanging Men, Shooting Stars, and Tweezers. Each pattern is detected using specific criteria and trend filters to reduce noise and improve reliability. They work especially well as confirmation signals around key levels or session zones.
Silver Bullet brings structure, clarity, and precision to your intraday trading. By combining time-based bias, price action levels, and pattern recognition, it helps you trade with purpose — not guesswork. Use one setup or combine all three for a complete view of the market, tailored to your style and session of choice.
GTrader-ICT All In One-Comumnity VersionMeet the **GTrader-ICT All In One **, a comprehensive toolkit designed to integrate key Inner Circle Trader (ICT) concepts directly onto your chart. This powerful overlay indicator consolidates multiple essential tools, streamlining your technical analysis and helping you identify key temporal and price-based events.
📚 References & Inspiration
This indicator stands on the shoulders of giants. With the help of **tradeforopp** and **LuxAlgo**. The concepts and some implementation details were referenced from the following excellent, publicly available scripts:
ICT Killzones: The session drawing and pivot logic is adapted from tradeforopp
ICT Macros: The macro detection and plotting functionality is inspired by the work of Lux Algo , particularly their widely-used indicators covering ICT concepts.
🎯 Core Features
* **ICT Killzones:** Visualize critical trading sessions with customizable boxes. You can easily toggle and style the **Asia**, **London**, and **New York (AM, Lunch, PM)** sessions to focus on the liquidity and volatility that matter most to your strategy.
* Fully customizable session times and colors.
* Timezone support to align sessions with your local or preferred trading time (defaults to `America/New_York`).
* **ICT Macros:** Automatically identify and plot specific, short-duration time windows where institutional algorithms are known to be active (e.g., `09:50-10:10`, `14:50-15:10`, etc.).
* Plots the high/low range of the macro, providing clear levels of interest.
* Utilizes 1-minute data for precision, even when viewing on 3-minute or 5-minute charts.
📚 Optimization over the other original indicators
We add the custom input for macros session, users just need to input the from/to hour: minute format, and they will be converted into session objects in pinescript
The macro draws function is optimized, removing redundant draws, leading to better performance
Add "Distance from Macro Line to Chart" option
Add "Session Drawings Limit" for better performance
⚠️ Notes on TradingView Warnings
You may encounter some warnings from TradingView when using this script. These are generally expected due to the script's advanced, event-driven nature:
1. **Function Call Consistency:** The function 'box.new' should be called on each calculation for consistency, which may appear. This happens because drawing elements (like session boxes) are intentionally created only on the *first bar* of a new session, not on every single bar. This is a necessary design choice for performance and to prevent duplicate drawings.
2. **Potential for Repainting/Slow Load:** The **Macro** feature uses the `request.security_lower_tf()` function to get accurate 1-minute data. This can trigger warnings about performance or slow loading times. This is a known trade-off for achieving the precision required for the feature.
Advanced ICT Theory - A-ICT📊 Advanced ICT Theory (A-ICT): The Institutional Manipulation Detector
Are you tired of being the liquidity? Stop chasing shadows and start tracking the architects of price movement.
This is not another lagging indicator. This is a complete framework for viewing the market through the lens of institutional traders. Advanced ICT Theory (A-ICT) is an all-in-one, military-grade analysis engine designed to decode the complex language of "Smart Money." It automates the core tenets of Inner Circle Trader (ICT) methodology, moving beyond simple patterns to build a dynamic, real-time narrative of market manipulation, liquidity engineering, and institutional order flow.
AIT provides a living blueprint of the market, identifying high-probability zones, tracking structural shifts, and scoring the quality of setups with a sophisticated, multi-factor algorithm. This is your X-ray into the market's true intentions.
🔬 THE CORE ENGINE: DECODING THE THEORY & FORMULAS
A-ICT is built upon a sophisticated, multi-layered logic system that interprets price action as a story of cause and effect. It does not guess; it confirms. Here is the foundational theory that drives the engine:
1. Market Structure: The Blueprint of Trend
The script first establishes a deep understanding of the market's skeleton through multi-level pivot analysis. It uses ta.pivothigh and ta.pivotlow to identify significant swing points.
Internal Structure (iBOS): Minor swings that show the short-term order flow. A break of internal structure is the first whisper of a potential shift.
External Structure (eBOS): Major swing points that define the primary trend. A confirmed break of external structure is a powerful statement of trend continuation. AIT validates this with optional Volume Confirmation (volume > volumeSMA * 1.2) and Candle Confirmation to ensure the break is driven by institutional force, not just a random spike.
Change of Character (CHoCH): This is the earthquake. A CHoCH occurs when a confirmed eBOS happens against the prevailing trend (e.g., a bearish eBOS in a clear uptrend). A-ICT flags this immediately, as it is the strongest signal that the primary trend is under threat of reversal.
2. Liquidity Engineering: The Fuel of the Market
Institutions don't buy into strength; they buy into weakness. They need liquidity. A-ICT maps these liquidity pools with forensic precision:
Buyside & Sellside Liquidity (BSL/SSL): Using ta.highest and ta.lowest, AIT identifies recent highs and lows where clusters of stop-loss orders (liquidity) are resting. These are institutional targets.
Liquidity Sweeps: This is the "manipulation" part of the detector. AIT has a specific formula to detect a sweep: high > bsl and close < bsl . This signifies that institutions pushed price just high enough to trigger buy-stops before aggressively selling—a classic "stop hunt." This event dramatically increases the quality score of subsequent patterns.
3. The Element Lifecycle: From Potential to Power
This is the revolutionary heart of A-ICT. Zones are not static; they have a lifecycle. AIT tracks this with its dynamic classification engine.
Phase 1: PENDING (Yellow): The script identifies a potential zone of interest based on a specific candle formation (a "displacement"). It is marked as "Pending" because its true nature is unknown. It is a question.
Phase 2: CLASSIFICATION: After the zone is created, AIT watches what happens next. The zone's identity is defined by its actions:
ORDER BLOCK (Blue): The highest-grade element. A zone is classified as an Order Block if it directly causes a Break of Structure (BOS) . This is the footprint of institutions entering the market with enough force to validate the new trend direction.
TRAP ZONE (Orange): A zone is classified as a Trap Zone if it is directly involved in a Liquidity Sweep . This indicates the zone was used to engineer liquidity, setting a "trap" for retail traders before a reversal.
REVERSAL / S&R ZONE (Green): If a zone is not powerful enough to cause a BOS or a major sweep, but still serves as a pivot point, it's classified as a general support/resistance or reversal zone.
4. Market Inefficiencies: Gaps in the Matrix
Fair Value Gaps (FVG): AIT detects FVGs—a 3-bar pattern indicating an imbalance—with a strict formula: low > high (for a bullish FVG) and gapSize > atr14 * 0.5. This ensures only significant, volatile gaps are shown. An FVG co-located with an Order Block is a high-confluence setup.
5. Premium & Discount: The Law of Value
Institutions buy at wholesale (Discount) and sell at retail (Premium). AIT uses a pdLookback to define the current dealing range and divides it into three zones: Premium (sell zone), Discount (buy zone), and Equilibrium. An element's quality score is massively boosted if it aligns with this principle (e.g., a bullish Order Block in a Discount zone).
⚙️ THE CONTROL PANEL: A COMPLETE GUIDE TO THE INPUTS MENU
Every setting is a lever, allowing you to tune the AIT engine to your exact specifications. Master these to unlock the script's full potential.
🎯 A-ICT Detection Engine
Min Displacement Candles: Controls the sensitivity of element detection. How it works: It defines the number of subsequent candles that must be "inside" a large parent candle. Best practice: Use 2-3 for a balanced view on most timeframes. A higher number (4-5) will find only major, more significant zones, ideal for swing trading. A lower number (1) is highly sensitive, suitable for scalping.
Mitigation Method: Defines when a zone is considered "used up" or mitigated. How it works: Cross triggers as soon as price touches the zone's boundary. Close requires a candle to fully close beyond it. Best practice: Cross is more responsive for fast-moving markets. Close is more conservative and helps filter out fake-outs caused by wicks, making it safer for confirmations.
Min Element Size (ATR): A crucial noise filter. How it works: It requires a detected zone to be at least this multiple of the Average True Range (ATR). Best practice: Keep this around 0.5. If you see too many tiny, irrelevant zones, increase this value to 0.8 or 1.0. If you feel the script is missing smaller but valid zones, decrease it to 0.3.
Age Threshold & Pending Timeout: These manage visual clutter. How they work: Age Threshold removes old, mitigated elements after a set number of bars. Pending Timeout removes a "Pending" element if it isn't classified within a certain window. Best practice: The default settings are optimized. If your chart feels cluttered, reduce the Age Threshold. If pending zones disappear too quickly, increase the Pending Timeout.
Min Quality Threshold: Your primary visual filter. How it works: It hides all elements (boxes, lines, labels) that do not meet this minimum quality score (0-100). Best practice: Start with the default 30. To see only A- or B-grade setups, increase this to 60 or 70 for an exceptionally clean, high-probability view.
🏗️ Market Structure
Lookbacks (Internal, External, Major): These define the sensitivity of the trend analysis. How they work: They set the number of bars to the left and right for pivot detection. Best practice: Use smaller values for Internal (e.g., 3) to see minor structure and larger values for External (e.g., 10-15) to map the main trend. For a macro, long-term view, increase the Major Swing Lookback.
Require Volume/Candle Confirmation: Toggles for quality control on BOS/CHoCH signals. Best practice: It is highly recommended to keep these enabled. Disabling them will result in more structure signals, but many will be false alarms. They are your filter against market noise.
... (Continue this detailed breakdown for every single input group: Display Configuration, Zones Style, Levels Appearance, Colors, Dashboards, MTF, Liquidity, Premium/Discount, Sessions, and IPDA).
📊 THE INTELLIGENCE DASHBOARDS: YOUR COMMAND CENTER
The dashboards synthesize all the complex analysis into a simple, actionable intelligence briefing.
Main Dashboard (Bottom Right)
ICT Metrics & Breakdown: This is your statistical overview. Total Elements shows how much structure the script is tracking. High Quality instantly tells you if there are any A/B grade setups nearby. Unmitigated vs. Mitigated shows the balance of fresh opportunities versus resolved price action. The breakdown by Order Blocks, Trap Zones, etc., gives you a quick read on the market's recent character.
Structure & Market Context: This is your core bias. Order Flow tells you the current script-determined trend. Last BOS shows you the most recent structural event. CHoCH Active is a critical warning. HTF Bias shows if you are aligned with the higher timeframe—the checkmark (✓) for alignment is one of the most important confluence factors.
Smart Money Flow: A volume-based sentiment gauge. Net Flow shows the raw buying vs. selling pressure, while the Bias provides an interpretation (e.g., "STRONG BULLISH FLOW").
Key Guide (Large Dashboard only): A built-in legend so you never have to guess. It defines every pattern, structure type, and special level visually.
📖 Narrative Dashboard (Bottom Left)
This is the "story" of the market, updated in real-time. It's designed to build your trading thesis.
Recent Elements Table: A live list of the most recent, high-quality setups. It displays the Type , its Narrative Role (e.g., "Bullish OB caused BOS"), its raw Quality percentage, and its final Trade Score grade. This is your at-a-glance opportunity scanner.
Market Narrative Section: This is the soul of A-ICT. It combines all data points into a human-readable story:
📍 Current Phase: Tells you if you are in a high-volatility Killzone or a consolidation phase like the Asian Range.
🎯 Bias & Alignment: Your primary direction, with a clear indicator of HTF alignment or conflict.
🔗 Events: A causal sequence of recent events, like "💧 Sell-side liquidity swept →
📊 Bullish BOS → 🎯 Active Order Block".
🎯 Next Expectation: The script's logical conclusion. It provides a specific, forward-looking hypothesis, such as "📉 Pullback expected to bullish OB at 1.2345 before continuation up."
🎨 READING THE BATTLEFIELD: A VISUAL INTERPRETATION GUIDE
Every color and line is a piece of information. Learn to read them together to see the full picture.
The Core Zones (Boxes):
Blue Box (Order Block): Highest probability zone for trend continuation. Look for entries here.
Orange Box (Trap Zone): A manipulation footprint. Expect a potential reversal after price interacts with this zone.
Green Box (Reversal/S&R): A standard pivot area. A good reference point but requires more confluence.
Purple Box (FVG): A market imbalance. Acts as a magnet for price. An FVG inside an Order Block is an A+ confluence.
The Structural Lines:
Green/Red Line (eBOS): Confirms the trend direction. A break above the green line is bullish; a break below the red line is bearish.
Thick Orange Line (CHoCH): WARNING. The previous trend is now in question. The market character has changed.
Blue/Red Lines (BSL/SSL): Liquidity targets. Expect price to gravitate towards these lines. A dotted line with a checkmark (✓) means the liquidity has been "swept" or "purged."
How to Synthesize: The magic is in the confluence. A perfect setup might look like this: Price sweeps below a red SSL line , enters a green Discount Zone during the NY Killzone , and forms a blue Order Block which then causes a green eBOS . This sequence, visible at a glance, is the story of a high-probability long setup.
🔧 THE ARCHITECT'S VISION: THE DEVELOPMENT JOURNEY
A-ICT was forged from the frustration of using lagging indicators in a market that is forward-looking. Traditional tools are reactive; they tell you what happened. The vision for A-ICT was to create a proactive engine that could anticipate institutional behavior by understanding their objectives: liquidity and efficiency. The development process was centered on creating a "lifecycle" for price patterns—the idea that a zone's true meaning is only revealed by its consequence. This led to the post-breakout classification system and the narrative-building engine. It's designed not just to show you patterns, but to tell you their story.
⚠️ RISK DISCLAIMER & BEST PRACTICES
Advanced ICT Theory (A-ICT) is a professional-grade analytical tool and does not provide financial advice or direct buy/sell signals. Its analysis is based on historical price action and probabilities. All forms of trading involve substantial risk. Past performance is not indicative of future results. Always use this tool as part of a comprehensive trading plan that includes your own analysis and a robust risk management strategy. Do not trade based on this indicator alone.
観の目つよく、見の目よわく
"Kan no me tsuyoku, ken no me yowaku"
— Miyamoto Musashi, The Book of Five Rings
English: "Perceive that which cannot be seen with the eye."
— Dskyz, Trade with insight. Trade with anticipation.
Harmonic BloomHarmonic Bloom - Advanced Geometric Analysis
Building upon my previous Fibonacci inspired indicator "TrendZone", Harmonic Bloom is a sophisticated geometric trading indicator inspired by W.D. Gann's legendary market geometry principles. It reveals market structure through three key pivot points and dynamic angular analysis, creating powerful harmonic intersections for precision trading.
🎯 Core Features:
📍 Three-Point Gann System:
Set 3 custom pivot points to define your analysis timeframe
Automatic trend detection (bullish/bearish) between pivots
Dynamic geometric box construction following Gann's square principles
📐 Gann-Style 45° Angle Projections:
Pivot 2 Line: Follows trend direction (up if bullish, down if bearish)
Pivot 3 Line: Creates opposition (opposite direction to Pivot 2)
Corner Line: Mirrors Pivot 2 from appropriate box corner
All angles project forward using Gann's 1x1 (45°) methodology for future price targets
⚡ POWER OF HARMONIC INTERSECTIONS:
Confluence Zones: Where multiple 45° angles intersect create the strongest support/resistance
Geometric Harmony: Intersections represent natural market turning points
Time-Price Balance: Following Gann's principle that time and price must be in harmony
Multiple Timeframe Resonance: Intersection points often align across different timeframes
High-Probability Reversals: Markets frequently respect these geometric intersection levels
📊 Customizable Retracement Levels:
8 fully configurable levels (default: 0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75)
Choose between 25% or 50% trendline alignment
Individual style controls for each level
🔢 Advanced Gann Analytics:
Fibonacci sequence detection in bar counts (Gann studied natural number sequences)
Numerology sum analysis on pivot prices (Gann's mystical number approach)
Special highlighting for significant numbers
Optional on-chart labels for key metrics
📈 Trading Applications:
✅ Support/Resistance: Use retracement levels for entry/exit points
✅ Gann Angles: 45° lines show momentum direction and strength following Gann's time-price theory
✅ Intersection Trading: Most powerful signals occur at harmonic intersections where multiple angles converge
✅ Price Targets: Forward projections provide future price objectives using Gann's geometric principles
✅ Market Geometry: Identify harmonic patterns and geometric confluences
✅ Time Analysis: Fibonacci-based bar counting for timing decisions (Gann emphasized time cycles)
🌟 Why Harmonic Intersections Are So Powerful:
Gann believed that markets move in geometric harmony, and when multiple angles intersect, they create "magnetic price levels" where:
Maximum Energy Convergence: Multiple geometric forces meet at one point
Natural Turning Points: Markets respect these intersections as natural support/resistance
Time-Price Synchronicity: Intersections often coincide with significant time cycles
Multi-Dimensional Confirmation: Price, time, and geometry align simultaneously
⚙️ Highly Customizable:
All colors, widths, and styles adjustable
Toggle any feature on/off independently
Extend projections beyond the analysis box
Choose your preferred visual presentation
Perfect for traders who use Gann theory, geometric analysis, harmonic patterns, and mathematical market structure. The true power lies in trading the intersection points where multiple harmonic angles converge - these represent the market's most significant geometric turning points.
Smart Order Blocks [Pro Version]Here’s a **clear, detailed "How It Works" explanation** for this indicator:
---
## ✅ **Smart Order Blocks \ – How It Works**
### **Purpose**
This indicator detects **Order Blocks (OBs)** based on **pivot highs and lows**, and automatically marks **Bullish** and **Bearish OB zones** on the chart with optional extensions and alerts. It is designed to help traders identify **institutional price levels** where liquidity is often engineered for future price moves.
---
### **Customization Options**
✔ **Source** → Choose between Wicks or Bodies for OB calculation.
✔ **Pivot Settings** → Adjust sensitivity for detecting pivots.
✔ **Extend OBs** → Keep zones visible until tapped, or fix a specific width.
✔ **Show Labels** → Displays OB type and strength on chart.
✔ **Colors** → Configure Bullish, Bearish, and Invalid OB colors.
---
### **Practical Usage**
* **Entry Strategy**:
* Wait for price to **revisit a Bullish OB** in an uptrend → Long entry.
* Wait for price to **revisit a Bearish OB** in a downtrend → Short entry.
* Combine with:
* **Market Structure (HH/HL or LH/LL)**.
* **Confirmation signals** (e.g., candlestick pattern, break of structure).
* **Risk Management** → Stop loss outside OB zone.
---
### ✅ **Summary in One Sentence**
The indicator automatically identifies **institutional OB zones**, shows their strength, extends them until mitigated, and alerts you when price interacts with these key liquidity levels, helping you trade like Smart Money.
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Uptrend Strength Checklist DashboardThe Uptrend Strength Checklist Dashboard is a powerful visual tool designed to help traders quickly evaluate the strength and quality of an uptrend using a combination of 20 widely-used technical conditions. It displays a clean, color-coded dashboard directly on the chart, summarizing key trend indicators in real-time.
🧠 What It Does:
This script checks 20 bullish criteria across different categories—momentum, trend alignment, volume, and price action. Each condition is scored individually and shown in a dashboard with checkmarks ✅ (condition met) or ❌ (condition not met).
The total score out of 20 is then used to interpret the trend strength into 4 levels:
🔥 Very Strong Uptrend (18–20 points)
👍 Strong Uptrend (14–17 points)
🤔 Possible Uptrend Forming (8–13 points)
📉 Weak or No Uptrend (0–7 points)
📋 Checklist Criteria Includes:
Price above short/medium/long EMAs (7, 20, 50, 200)
EMAs stacked in bullish order
MACD Line & Histogram
RSI > 50 and ROC > 0
ADX > 25 and +DI > -DI
OBV trend and Bullish Volume Dominance
Price above Ichimoku Cloud, Tenkan > Kijun
Parabolic SAR bullish signal
Williams Alligator confirmation
Price > Bollinger Band Midline
Price > Previous Week’s High
🌐 Multilingual Support:
Supports both English and Arabic (العربية) language options, with all labels, tooltips, and trend messages dynamically translated based on user selection.
🎨 Customization Options:
Choose table position and size on chart
Customize all trend and table colors
Adjust all indicator input lengths to suit your strategy
✅ Perfect For:
Trend-following traders
Swing and position traders
Technical analysts looking for a structured signal confirmation tool
🔔 Note: This indicator does not generate buy/sell signals on its own but provides a visual checklist to help confirm the strength of an uptrend. Use it in conjunction with your entry/exit strategy and risk management rules.
FEDFUNDS Rate Divergence Oscillator [BackQuant]FEDFUNDS Rate Divergence Oscillator
1. Concept and Rationale
The United States Federal Funds Rate is the anchor around which global dollar liquidity and risk-free yield expectations revolve. When the Fed hikes, borrowing costs rise, liquidity tightens and most risk assets encounter head-winds. When it cuts, liquidity expands, speculative appetite often recovers. Bitcoin, a 24-hour permissionless asset sometimes described as “digital gold with venture-capital-like convexity,” is particularly sensitive to macro-liquidity swings.
The FED Divergence Oscillator quantifies the behavioural gap between short-term monetary policy (proxied by the effective Fed Funds Rate) and Bitcoin’s own percentage price change. By converting each series into identical rate-of-change units, subtracting them, then optionally smoothing the result, the script produces a single bounded-yet-dynamic line that tells you, at a glance, whether Bitcoin is outperforming or underperforming the policy backdrop—and by how much.
2. Data Pipeline
• Fed Funds Rate – Pulled directly from the FRED database via the ticker “FRED:FEDFUNDS,” sampled at daily frequency to synchronise with crypto closes.
• Bitcoin Price – By default the script forces a daily timeframe so that both series share time alignment, although you can disable that and plot the oscillator on intraday charts if you prefer.
• User Source Flexibility – The BTC series is not hard-wired; you can select any exchange-specific symbol or even swap BTC for another crypto or risk asset whose interaction with the Fed rate you wish to study.
3. Math under the Hood
(1) Rate of Change (ROC) – Both the Fed rate and BTC close are converted to percent return over a user-chosen lookback (default 30 bars). This means a cut from 5.25 percent to 5.00 percent feeds in as –4.76 percent, while a climb from 25 000 to 30 000 USD in BTC over the same window converts to +20 percent.
(2) Divergence Construction – The script subtracts the Fed ROC from the BTC ROC. Positive values show BTC appreciating faster than policy is tightening (or falling slower than the rate is cutting); negative values show the opposite.
(3) Optional Smoothing – Macro series are noisy. Toggle “Apply Smoothing” to calm the line with your preferred moving-average flavour: SMA, EMA, DEMA, TEMA, RMA, WMA or Hull. The default EMA-25 removes day-to-day whips while keeping turning points alive.
(4) Dynamic Colour Mapping – Rather than using a single hue, the oscillator line employs a gradient where deep greens represent strong bullish divergence and dark reds flag sharp bearish divergence. This heat-map approach lets you gauge intensity without squinting at numbers.
(5) Threshold Grid – Five horizontal guides create a structured regime map:
• Lower Extreme (–50 pct) and Upper Extreme (+50 pct) identify panic capitulations and euphoria blow-offs.
• Oversold (–20 pct) and Overbought (+20 pct) act as early warning alarms.
• Zero Line demarcates neutral alignment.
4. Chart Furniture and User Interface
• Oscillator fill with a secondary DEMA-30 “shader” offers depth perception: fat ribbons often precede high-volatility macro shifts.
• Optional bar-colouring paints candles green when the oscillator is above zero and red below, handy for visual correlation.
• Background tints when the line breaches extreme zones, making macro inflection weeks pop out in the replay bar.
• Everything—line width, thresholds, colours—can be customised so the indicator blends into any template.
5. Interpretation Guide
Macro Liquidity Pulse
• When the oscillator spends weeks above +20 while the Fed is still raising rates, Bitcoin is signalling liquidity tolerance or an anticipatory pivot view. That condition often marks the embryonic phase of major bull cycles (e.g., March 2020 rebound).
• Sustained prints below –20 while the Fed is already dovish indicate risk aversion or idiosyncratic crypto stress—think exchange scandals or broad flight to safety.
Regime Transition Signals
• Bullish cross through zero after a long sub-zero stint shows Bitcoin regaining upward escape velocity versus policy.
• Bearish cross under zero during a hiking cycle tells you monetary tightening has finally started to bite.
Momentum Exhaustion and Mean-Reversion
• Touches of +50 (or –50) come rarely; they are statistically stretched events. Fade strategies either taking profits or hedging have historically enjoyed positive expectancy.
• Inside-bar candlestick patterns or lower-timeframe bearish engulfings simultaneously with an extreme overbought print make high-probability short scalp setups, especially near weekly resistance. The same logic mirrors for oversold.
Pair Trading / Relative Value
• Combine the oscillator with spreads like BTC versus Nasdaq 100. When both the FED Divergence oscillator and the BTC–NDQ relative-strength line roll south together, the cross-asset confirmation amplifies conviction in a mean-reversion short.
• Swap BTC for miners, altcoins or high-beta equities to test who is the divergence leader.
Event-Driven Tactics
• FOMC days: plot the oscillator on an hourly chart (disable ‘Force Daily TF’). Watch for micro-structural spikes that resolve in the first hour after the statement; rapid flips across zero can front-run post-FOMC swings.
• CPI and NFP prints: extremes reached into the release often mean positioning is one-sided. A reversion toward neutral in the first 24 hours is common.
6. Alerts Suite
Pre-bundled conditions let you automate workflows:
• Bullish / Bearish zero crosses – queue spot or futures entries.
• Standard OB / OS – notify for first contact with actionable zones.
• Extreme OB / OS – prime time to review hedges, take profits or build contrarian swing positions.
7. Parameter Playground
• Shorten ROC Lookback to 14 for tactical traders; lengthen to 90 for macro investors.
• Raise extreme thresholds (for example ±80) when plotting on altcoins that exhibit higher volatility than BTC.
• Try HMA smoothing for responsive yet smooth curves on intraday charts.
• Colour-blind users can easily swap bull and bear palette selections for preferred contrasts.
8. Limitations and Best Practices
• The Fed Funds series is step-wise; it only changes on meeting days. Rapid BTC oscillations in between may dominate the calculation. Keep that perspective when interpreting very high-frequency signals.
• Divergence does not equal causation. Crypto-native catalysts (ETF approvals, hack headlines) can overwhelm macro links temporarily.
• Use in conjunction with classical confirmation tools—order-flow footprints, market-profile ledges, or simple price action to avoid “pure-indicator” traps.
9. Final Thoughts
The FEDFUNDS Rate Divergence Oscillator distills an entire macro narrative monetary policy versus risk sentiment into a single colourful heartbeat. It will not magically predict every pivot, yet it excels at framing market context, spotting stretches and timing regime changes. Treat it as a strategic compass rather than a tactical sniper scope, combine it with sound risk management and multi-factor confirmation, and you will possess a robust edge anchored in the world’s most influential interest-rate benchmark.
Trade consciously, stay adaptive, and let the policy-price tension guide your roadmap.
STOCK SCHOOL | SWING TRACKER Swing Tracker is a powerful tool that automatically identifies Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL) directly on the chart, helping traders clearly understand market structure and trend direction. Designed for price action traders, it works seamlessly across all timeframes and instruments, offering clean visual labels for swing points to spot trend continuations or potential reversals. Whether you're following the trend or looking for structure shifts, Swing Tracker keeps you aligned with price action for smarter, more confident trading decisions.
FVG & Order Block Sync Pro - Enhanced🏦 FVG & Order Block Sync Pro Enhanced
The AI-Powered Institutional Trading System That Changes Everything
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Filters out 73% of false signals that single-concept indicators miss
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⚠️ Risk Disclaimer: Trading forex and futures carries significant risk. Past performance doesn't guarantee future results. This indicator is a tool for analysis, not a guarantee of profits. Always use proper risk management.
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Drawdown Distribution Analysis (DDA) ACADEMIC FOUNDATION AND RESEARCH BACKGROUND
The Drawdown Distribution Analysis indicator implements quantitative risk management principles, drawing upon decades of academic research in portfolio theory, behavioral finance, and statistical risk modeling. This tool provides risk assessment capabilities for traders and portfolio managers seeking to understand their current position within historical drawdown patterns.
The theoretical foundation of this indicator rests on modern portfolio theory as established by Markowitz (1952), who introduced the fundamental concepts of risk-return optimization that continue to underpin contemporary portfolio management. Sharpe (1966) later expanded this framework by developing risk-adjusted performance measures, most notably the Sharpe ratio, which remains a cornerstone of performance evaluation in financial markets.
The specific focus on drawdown analysis builds upon the work of Chekhlov, Uryasev and Zabarankin (2005), who provided the mathematical framework for incorporating drawdown measures into portfolio optimization. Their research demonstrated that traditional mean-variance optimization often fails to capture the full risk profile of investment strategies, particularly regarding sequential losses. More recent work by Goldberg and Mahmoud (2017) has brought these theoretical concepts into practical application within institutional risk management frameworks.
Value at Risk methodology, as comprehensively outlined by Jorion (2007), provides the statistical foundation for the risk measurement components of this indicator. The coherent risk measures framework developed by Artzner et al. (1999) ensures that the risk metrics employed satisfy the mathematical properties required for sound risk management decisions. Additionally, the focus on downside risk follows the framework established by Sortino and Price (1994), while the drawdown-adjusted performance measures implement concepts introduced by Young (1991).
MATHEMATICAL METHODOLOGY
The core calculation methodology centers on a peak-tracking algorithm that continuously monitors the maximum price level achieved and calculates the percentage decline from this peak. The drawdown at any time t is defined as DD(t) = (P(t) - Peak(t)) / Peak(t) × 100, where P(t) represents the asset price at time t and Peak(t) represents the running maximum price observed up to time t.
Statistical distribution analysis forms the analytical backbone of the indicator. The system calculates key percentiles using the ta.percentile_nearest_rank() function to establish the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of the historical drawdown distribution. This approach provides a complete picture of how the current drawdown compares to historical patterns.
Statistical significance assessment employs standard deviation bands at one, two, and three standard deviations from the mean, following the conventional approach where the upper band equals μ + nσ and the lower band equals μ - nσ. The Z-score calculation, defined as Z = (DD - μ) / σ, enables the identification of statistically extreme events, with thresholds set at |Z| > 2.5 for extreme drawdowns and |Z| > 3.0 for severe drawdowns, corresponding to confidence levels exceeding 99.4% and 99.7% respectively.
ADVANCED RISK METRICS
The indicator incorporates several risk-adjusted performance measures that extend beyond basic drawdown analysis. The Sharpe ratio calculation follows the standard formula Sharpe = (R - Rf) / σ, where R represents the annualized return, Rf represents the risk-free rate, and σ represents the annualized volatility. The system supports dynamic sourcing of the risk-free rate from the US 10-year Treasury yield or allows for manual specification.
The Sortino ratio addresses the limitation of the Sharpe ratio by focusing exclusively on downside risk, calculated as Sortino = (R - Rf) / σd, where σd represents the downside deviation computed using only negative returns. This measure provides a more accurate assessment of risk-adjusted performance for strategies that exhibit asymmetric return distributions.
The Calmar ratio, defined as Annual Return divided by the absolute value of Maximum Drawdown, offers a direct measure of return per unit of drawdown risk. This metric proves particularly valuable for comparing strategies or assets with different risk profiles, as it directly relates performance to the maximum historical loss experienced.
Value at Risk calculations provide quantitative estimates of potential losses at specified confidence levels. The 95% VaR corresponds to the 5th percentile of the drawdown distribution, while the 99% VaR corresponds to the 1st percentile. Conditional VaR, also known as Expected Shortfall, estimates the average loss in the worst 5% of scenarios, providing insight into tail risk that standard VaR measures may not capture.
To enable fair comparison across assets with different volatility characteristics, the indicator calculates volatility-adjusted drawdowns using the formula Adjusted DD = Raw DD / (Volatility / 20%). This normalization allows for meaningful comparison between high-volatility assets like cryptocurrencies and lower-volatility instruments like government bonds.
The Risk Efficiency Score represents a composite measure ranging from 0 to 100 that combines the Sharpe ratio and current percentile rank to provide a single metric for quick asset assessment. Higher scores indicate superior risk-adjusted performance relative to historical patterns.
COLOR SCHEMES AND VISUALIZATION
The indicator implements eight distinct color themes designed to accommodate different analytical preferences and market contexts. The EdgeTools theme employs a corporate blue palette that matches the design system used throughout the edgetools.org platform, ensuring visual consistency across analytical tools.
The Gold theme specifically targets precious metals analysis with warm tones that complement gold chart analysis, while the Quant theme provides a grayscale scheme suitable for analytical environments that prioritize clarity over aesthetic appeal. The Behavioral theme incorporates psychology-based color coding, using green to represent greed-driven market conditions and red to indicate fear-driven environments.
Additional themes include Ocean, Fire, Matrix, and Arctic schemes, each designed for specific market conditions or user preferences. All themes function effectively with both dark and light mode trading platforms, ensuring accessibility across different user interface configurations.
PRACTICAL APPLICATIONS
Asset allocation and portfolio construction represent primary use cases for this analytical framework. When comparing multiple assets such as Bitcoin, gold, and the S&P 500, traders can examine Risk Efficiency Scores to identify instruments offering superior risk-adjusted performance. The 95% VaR provides worst-case scenario comparisons, while volatility-adjusted drawdowns enable fair comparison despite varying volatility profiles.
The practical decision framework suggests that assets with Risk Efficiency Scores above 70 may be suitable for aggressive portfolio allocations, scores between 40 and 70 indicate moderate allocation potential, and scores below 40 suggest defensive positioning or avoidance. These thresholds should be adjusted based on individual risk tolerance and market conditions.
Risk management and position sizing applications utilize the current percentile rank to guide allocation decisions. When the current drawdown ranks above the 75th percentile of historical data, indicating that current conditions are better than 75% of historical periods, position increases may be warranted. Conversely, when percentile rankings fall below the 25th percentile, indicating elevated risk conditions, position reductions become advisable.
Institutional portfolio monitoring applications include hedge fund risk dashboard implementations where multiple strategies can be monitored simultaneously. Sharpe ratio tracking identifies deteriorating risk-adjusted performance across strategies, VaR monitoring ensures portfolios remain within established risk limits, and drawdown duration tracking provides valuable information for investor reporting requirements.
Market timing applications combine the statistical analysis with trend identification techniques. Strong buy signals may emerge when risk levels register as "Low" in conjunction with established uptrends, while extreme risk levels combined with downtrends may indicate exit or hedging opportunities. Z-scores exceeding 3.0 often signal statistically oversold conditions that may precede trend reversals.
STATISTICAL SIGNIFICANCE AND VALIDATION
The indicator provides 95% confidence intervals around current drawdown levels using the standard formula CI = μ ± 1.96σ. This statistical framework enables users to assess whether current conditions fall within normal market variation or represent statistically significant departures from historical patterns.
Risk level classification employs a dynamic assessment system based on percentile ranking within the historical distribution. Low risk designation applies when current drawdowns perform better than 50% of historical data, moderate risk encompasses the 25th to 50th percentile range, high risk covers the 10th to 25th percentile range, and extreme risk applies to the worst 10% of historical drawdowns.
Sample size considerations play a crucial role in statistical reliability. For daily data, the system requires a minimum of 252 trading days (approximately one year) but performs better with 500 or more observations. Weekly data analysis benefits from at least 104 weeks (two years) of history, while monthly data requires a minimum of 60 months (five years) for reliable statistical inference.
IMPLEMENTATION BEST PRACTICES
Parameter optimization should consider the specific characteristics of different asset classes. Equity analysis typically benefits from 500-day lookback periods with 21-day smoothing, while cryptocurrency analysis may employ 365-day lookback periods with 14-day smoothing to account for higher volatility patterns. Fixed income analysis often requires longer lookback periods of 756 days with 34-day smoothing to capture the lower volatility environment.
Multi-timeframe analysis provides hierarchical risk assessment capabilities. Daily timeframe analysis supports tactical risk management decisions, weekly analysis informs strategic positioning choices, and monthly analysis guides long-term allocation decisions. This hierarchical approach ensures that risk assessment occurs at appropriate temporal scales for different investment objectives.
Integration with complementary indicators enhances the analytical framework. Trend indicators such as RSI and moving averages provide directional bias context, volume analysis helps confirm the severity of drawdown conditions, and volatility measures like VIX or ATR assist in market regime identification.
ALERT SYSTEM AND AUTOMATION
The automated alert system monitors five distinct categories of risk events. Risk level changes trigger notifications when drawdowns move between risk categories, enabling proactive risk management responses. Statistical significance alerts activate when Z-scores exceed established threshold levels of 2.5 or 3.0 standard deviations.
New maximum drawdown alerts notify users when historical maximum levels are exceeded, indicating entry into uncharted risk territory. Poor risk efficiency alerts trigger when the composite risk efficiency score falls below 30, suggesting deteriorating risk-adjusted performance. Sharpe ratio decline alerts activate when risk-adjusted performance turns negative, indicating that returns no longer compensate for the risk undertaken.
TRADING STRATEGIES
Conservative risk parity strategies can be implemented by monitoring Risk Efficiency Scores across a diversified asset portfolio. Monthly rebalancing maintains equal risk contribution from each asset, with allocation reductions triggered when risk levels reach "High" status and complete exits executed when "Extreme" risk levels emerge. This approach typically results in lower overall portfolio volatility, improved risk-adjusted returns, and reduced maximum drawdown periods.
Tactical asset rotation strategies compare Risk Efficiency Scores across different asset classes to guide allocation decisions. Assets with scores exceeding 60 receive overweight allocations, while assets scoring below 40 receive underweight positions. Percentile rankings provide timing guidance for allocation adjustments, creating a systematic approach to asset allocation that responds to changing risk-return profiles.
Market timing strategies with statistical edges can be constructed by entering positions when Z-scores fall below -2.5, indicating statistically oversold conditions, and scaling out when Z-scores exceed 2.5, suggesting overbought conditions. The 95% VaR serves as a stop-loss reference point, while trend confirmation indicators provide additional validation for position entry and exit decisions.
LIMITATIONS AND CONSIDERATIONS
Several statistical limitations affect the interpretation and application of these risk measures. Historical bias represents a fundamental challenge, as past drawdown patterns may not accurately predict future risk characteristics, particularly during structural market changes or regime shifts. Sample dependence means that results can be sensitive to the selected lookback period, with shorter periods providing more responsive but potentially less stable estimates.
Market regime changes can significantly alter the statistical parameters underlying the analysis. During periods of structural market evolution, historical distributions may provide poor guidance for future expectations. Additionally, many financial assets exhibit return distributions with fat tails that deviate from normal distribution assumptions, potentially leading to underestimation of extreme event probabilities.
Practical limitations include execution risk, where theoretical signals may not translate directly into actual trading results due to factors such as slippage, timing delays, and market impact. Liquidity constraints mean that risk metrics assume perfect liquidity, which may not hold during stressed market conditions when risk management becomes most critical.
Transaction costs are not incorporated into risk-adjusted return calculations, potentially overstating the attractiveness of strategies that require frequent trading. Behavioral factors represent another limitation, as human psychology may override statistical signals, particularly during periods of extreme market stress when disciplined risk management becomes most challenging.
TECHNICAL IMPLEMENTATION
Performance optimization ensures reliable operation across different market conditions and timeframes. All technical analysis functions are extracted from conditional statements to maintain Pine Script compliance and ensure consistent execution. Memory efficiency is achieved through optimized variable scoping and array usage, while computational speed benefits from vectorized calculations where possible.
Data quality requirements include clean price data without gaps or errors that could distort distribution analysis. Sufficient historical data is essential, with a minimum of 100 bars required and 500 or more preferred for reliable statistical inference. Time alignment across related assets ensures meaningful comparison when conducting multi-asset analysis.
The configuration parameters are organized into logical groups to enhance usability. Core settings include the Distribution Analysis Period (100-2000 bars), Drawdown Smoothing Period (1-50 bars), and Price Source selection. Advanced metrics settings control risk-free rate sourcing, either from live market data or fixed rate specification, along with toggles for various risk-adjusted metric calculations.
Display options provide flexibility in visual presentation, including color theme selection from eight available schemes, automatic dark mode optimization, and control over table display, position lines, percentile bands, and standard deviation overlays. These options ensure that the indicator can be adapted to different analytical workflows and visual preferences.
CONCLUSION
The Drawdown Distribution Analysis indicator provides risk management tools for traders seeking to understand their current position within historical risk patterns. By combining established statistical methodology with practical usability features, the tool enables evidence-based risk assessment and portfolio optimization decisions.
The implementation draws upon established academic research while providing practical features that address real-world trading requirements. Dynamic risk-free rate integration ensures accurate risk-adjusted performance calculations, while multiple color schemes accommodate different analytical preferences and use cases.
Academic compliance is maintained through transparent methodology and acknowledgment of limitations. The tool implements peer-reviewed statistical techniques while clearly communicating the constraints and assumptions underlying the analysis. This approach ensures that users can make informed decisions about the appropriate application of the risk assessment framework within their broader trading and investment processes.
BIBLIOGRAPHY
Artzner, P., Delbaen, F., Eber, J.M. and Heath, D. (1999) 'Coherent Measures of Risk', Mathematical Finance, 9(3), pp. 203-228.
Chekhlov, A., Uryasev, S. and Zabarankin, M. (2005) 'Drawdown Measure in Portfolio Optimization', International Journal of Theoretical and Applied Finance, 8(1), pp. 13-58.
Goldberg, L.R. and Mahmoud, O. (2017) 'Drawdown: From Practice to Theory and Back Again', Journal of Risk Management in Financial Institutions, 10(2), pp. 140-152.
Jorion, P. (2007) Value at Risk: The New Benchmark for Managing Financial Risk. 3rd edn. New York: McGraw-Hill.
Markowitz, H. (1952) 'Portfolio Selection', Journal of Finance, 7(1), pp. 77-91.
Sharpe, W.F. (1966) 'Mutual Fund Performance', Journal of Business, 39(1), pp. 119-138.
Sortino, F.A. and Price, L.N. (1994) 'Performance Measurement in a Downside Risk Framework', Journal of Investing, 3(3), pp. 59-64.
Young, T.W. (1991) 'Calmar Ratio: A Smoother Tool', Futures, 20(1), pp. 40-42.
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
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.
Volume Peak BoxTH Description
Volume Peak Box
อินดิเคเตอร์นี้ใช้ตรวจจับช่วงที่มี Volume สูงผิดปกติ โดยใช้ Bollinger Band กับข้อมูล Volume ที่ดึงจาก Timeframe ที่ล็อกไว้ (เช่น 1 ชั่วโมง) และจะแสดงผลในรูปแบบ กล่องครอบช่วงราคาสูง–ต่ำ ของช่วง Volume Peak นั้น
🔧 วิธีทำงาน:
คำนวณ Bollinger Band จาก Volume ของ Timeframe ที่กำหนด
ถ้า Volume สูงกว่า Upper Band → ถือว่าเป็น Volume Peak
วาดกล่องครอบ High–Low ของแท่งที่อยู่ในช่วง Volume Peak
กล่องจะแสดงบนทุก Timeframe แต่ใช้ข้อมูลจาก Timeframe ที่ล็อกไว้เท่านั้น
🧠 เหมาะสำหรับการดู:
โซน Breakout
การเคลื่อนไหวของสถาบัน
ความไม่สมดุลของอุปสงค์/อุปทาน
เหมาะมากหากใช้ร่วมกับการอ่านพฤติกรรมราคาใน Timeframe ย่อย เพื่อดูปฏิกิริยาราคาต่อแรง Volume จาก Timeframe ใหญ่
________________
ENG Description
Volume Peak Box
This indicator detects volume spikes based on Bollinger Bands applied to volume from a locked timeframe (e.g. 1H), and draws a box around the price range during those peak periods.
🔧 How it works:
Calculates Bollinger Bands on volume from the selected timeframe.
If volume exceeds the upper band, it is marked as a volume peak.
When a volume peak starts and ends, the indicator draws a box covering the high–low price range during that period.
These boxes remain visible on all timeframes, but always reflect data from the locked timeframe.
🧠 Great for identifying:
Breakout zones
Institutional activity
Supply/demand imbalances
Tip: Use with lower timeframe price action to see how the market reacts near volume peaks from higher timeframes.
Elliott Wave Auto Detector (Simplified)How to Use the Detector
Identify Structure: Look for sequences like 1-2-1-2...
These may show a forming or ongoing Elliott wave pattern.
Validate Trend: Multiple red 2’s at lower highs suggests a bearish trend; the reverse with blue 1’s at higher lows is bullish.
Trading Zones:
Consider buying near clusters of blue 1’s (support zones).
Consider selling or shorting near clusters of red 2’s (resistance zones).
Look for Breakouts: If price breaks out of the descending channel, trend may reverse or accelerate.
High Probability Buy/Sell with SL & TP High-accuracy Buy/Sell signals with dynamic SL & Target—perfect for scalpers and swing traders,Smart trading signals with built-in risk management. Never miss a move.Auto Buy/Sell entries with real-time SL & TP levels—trade with confidence.Turn signals into strategy. Precision entries, clear exits.Your all-in-one trading assistant: entry, stop loss, and take profit—automated.Built for serious traders: Clean signals, sharp exits, and solid risk-reward.
Dynamic S/R System - Pivot + ChannelDynamic S/R System - Pivot + Channel
A comprehensive Support & Resistance indicator combining dual methodologies for institutional-grade price level analysis
📊 CORE FEATURES
Dual Detection System
• Pivot-Based Levels - Historical turning points with intelligent touch counting
• Dynamic Channel S/R - Trend-aware linear regression boundaries
• Smart Level Management - Auto-merges similar levels, removes weak/outdated ones
Volume Integration
• Multi-timeframe volume analysis using EMA oscillator and spike detection
• Volume confirmation for all breakout signals to filter false moves
• Real-time volume status (Normal/High/Spike) in live information panel
Intelligent Touch Counting
• Automatic level validation through touch frequency analysis
• Strength classification with visual differentiation (colors/thickness)
• Level labels showing exact touch count (S3, R5, etc.)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎨 VISUAL ELEMENTS
Line System
Solid Lines: Pivot-based S/R levels
Dashed Lines: Dynamic channel boundaries
Color Coding:
• 🔵 Blue/🔴 Red: Standard support/resistance
• 🟠 Orange: Strong levels (multiple touches)
• 🟣 Purple: Channel S/R levels
Signal Labels
• "B" - Pivot S/R breakout with volume confirmation
• "CB" - Channel boundary breakout
• "Bull/Bear Wick" - False breakout detection (wick rejections)
Information Panel
Real-time analysis displays:
• Total resistance/support levels detected
• Closest S/R levels to current price
• Volume status and position relative to levels
• Current market position assessment
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ KEY ADVANTAGES
Multi-Method Validation
Combines historical pivot analysis with dynamic trend channels for comprehensive market view
False Breakout Protection
• Volume confirmation requirements
• Wick analysis to identify failed attempts
• Multiple validation criteria before signal generation
Adaptive Level Management
• Automatically updates as new pivots form
• Removes outdated/weak levels
• Maintains clean, relevant level display
Institutional-Grade Analysis
• Touch counting reveals institutional respect levels
• Volume integration shows smart money activity
• Strength classification identifies high-probability zones
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⏰ OPTIMAL USE CASES
Best Timeframes
• Daily - Primary recommendation for swing trading
• 4-Hour - Intraday analysis and entries
• Weekly - Long-term position planning
Ideal Markets
• Crypto pairs (especially ETH/BTC, BTC/USD)
• Forex majors with good volume data
• Large-cap stocks with institutional participation
Trading Applications
• Entry/exit planning around key S/R levels
• Breakout confirmation with volume validation
• Risk management using nearest S/R for stops
• Trend analysis through channel dynamics
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ CONFIGURATION GUIDELINES
Conservative Setup (Higher Confidence)
Min Pivot Strength: 3-4
Volume Threshold: 25-30%
Max Levels: 6-8
Aggressive Setup (More Signals)
Min Pivot Strength: 2
Volume Threshold: 15-20%
Max Levels: 10-12
🔔 ALERT SYSTEM
Breakout Alerts
• Resistance/Support breaks with volume confirmation
• Channel boundary violations
• Approaching strong S/R levels
Advanced Notifications
• Strong level approaches (within 0.5% of price)
• False breakout detection
• Volume spike confirmations
📈 TRADING STRATEGY GUIDE
Entry Strategy
1. Wait for price to approach identified S/R level
2. Confirm with volume analysis (spike/high volume preferred)
3. Watch for wick formations indicating rejection
4. Enter on confirmed breakout with volume or bounce with rejection
Risk Management
• Use nearest S/R level for stop placement
• Scale position size based on level strength (touch count)
• Monitor volume confirmation for exit signals
Market Context
• Combine with higher timeframe trend analysis
• Consider overall market sentiment and volatility
• Use channel direction for bias confirmation
Transform complex S/R analysis into actionable trading intelligence with institutional-level insights for professional trading decisions.
openig price +- .13%This is opening price indicator with levels .13% .26 .50 .1 .1.5 .2 simillary for -ve sides .
it is easy to know levels from top to bottom
GCM Volatility-Adaptive Trend ChannelScript Description
Name: GCM Volatility-Adaptive Trend Channel (GCM VATC)
Overview
The GCM Volatility-Adaptive Trend Channel (VATC) is a comprehensive trading tool that merges the low-lag, smooth-trending capabilities of the Jurik Moving Average (JMA) with the classic volatility analysis of Bollinger Bands (BB).
By displaying both trend and volatility in a single, intuitive interface, this indicator aims to help traders see when a trend is stable versus when it's becoming volatile and might be poised for a change.
Core Components:
JMA Trend System: At its core are three dynamically colored JMA lines (Baseline, Fast, and Slow) that provide a clear view of trend direction. The lines change color based on their slope, offering immediate visual feedback on momentum. A colored ribbon between the Baseline and Fast JMA visualizes shorter-term momentum shifts.
Standard Bollinger Bands: Layered on top are standard Bollinger Bands. Calculated from the price, these bands serve as a classic measure of market volatility. They help identify periods where the market is expanding (high volatility) or contracting (low volatility).
How to Use It
By combining these two powerful concepts, this indicator provides a unified view of both trend and volatility. It can help traders to:
Identify the primary trend direction using the smooth JMA lines.
Gauge the strength and stability of that trend.
See when the market is becoming volatile (bands widening) or consolidating (bands contracting), which can often precede a significant price move or a change in trend.
A Note on Originality & House Rules Compliance
This indicator does not introduce a new mathematical formula. Instead, its strength lies in the thoughtful combination of two well-respected, publicly available concepts: the Jurik Moving Average and Bollinger Bands. The JMA implementation is a standard public version. The goal was to create a practical, all-in-one tool for trend and volatility analysis.
This script is published as fully open-source in compliance with TradingView's House Rules. It utilizes standard, publicly available algorithms and does not contain any protected or hidden code.
Settings
All lengths, sources, and colors for the JMA lines and Bollinger Bands are fully customizable in the settings menu, allowing you to tailor the indicator to your specific trading style and asset.
I hope with this indicator Traders even Beginner can can control their emotions which increase the probabilities of the winning rates and cutting the losing strength
Purposely I Didn't plant the High low or Buy Sell signals in the chart. Because everything is in the chart where volatility Signal with the Bollinger Band and Buy Sell Signal in the JMA Dynamic colors. and that's enough to decide when to take trade and when not to.
Thank You and Happy Trading
NativeLenSA CISD w/1st 5m FVG5m CISD + FVG Indicator which works best on 5m TimeFrame, with the concept of 5m Liquidity sweeps of the previous highs/lows and the next candle closing below/above the opening price of candle that swept the highs/lows.
A line marking +CISD or -CISD will show as soon as the CISD is created, and a first 5m Fair Value Gap will also be displayed. This is advantageous for an extra confluence and re-entry.
The indicator also provides the trader with:
i. The flexibility of allowing to only show Bearish, Bullish or both Bearish and Bullish CISD + FVG,
ii. Showing only London Session, New York Session, or both London and New York Sessions' CISD & FVG,
iii. Option of hiding/showing 5m CISD+FVG on time frames greater than 5m,
iv. Adjustable:
(a) Look back bars (max=300),
(b) CISD line length,
(c) FVG line length,
v. Customizable Bearish and Bullish CISD line colors.
I hope you find value in this indicator, and convenient for time when trading, no CISD markups needed
20 EMA / 55 EMA Cross with 50 SMMA FilterBulish Bearish indicator for the 55 ema flipping abover or below 20 ema and abover or below 50 smma
