NeuraEdge ORB - Opening Range Breakout IndicatorOVERVIEW
NeuraEdge ORB is an open-source Opening Range Breakout indicator that automates the classic 15-minute ORB strategy. The indicator tracks the first 15 minutes of market action (9:30-9:45 AM ET), identifies breakouts above or below this range, and generates trading signals with automated stop loss and take profit calculations.
The Opening Range Breakout concept is based on the observation that the initial price action after market open often establishes directional bias for the trading session, as institutional order flow and overnight gap reactions manifest during this window.
CORE METHODOLOGY
Opening Range Construction:
The indicator uses session-based time detection to identify the 9:30-9:45 AM Eastern Time window. During this period, it tracks the highest high and lowest low to establish the opening range boundaries. The range is marked complete when the 15-minute window closes.
Calculation process:
OR High = Maximum high value during the 15-minute window
OR Low = Minimum low value during the 15-minute window
OR Midpoint = (OR High + OR Low) / 2
Range Size = OR High - OR Low (compared to 14-period ATR for context)
Breakout Detection:
The indicator identifies breakouts using close-price confirmation to reduce false signals from wicks:
Bullish breakout: Close above OR High (with previous close at or below OR High)
Bearish breakout: Close below OR Low (with previous close at or above OR Low)
The indicator tracks whether each direction has already broken to prevent duplicate signals on the same range.
Entry Type Logic:
Two entry methodologies are supported:
Breakout Mode - Signals immediately upon range break. Enters on the breakout bar when close confirms direction.
Retest Mode - Waits for price to break the range, then pullback to touch the range level before entering. Cancels if price moves too far beyond midpoint. This provides better entry prices with tighter stop losses.
Volume Confirmation:
Optional volume filter compares current bar volume to 20-period simple moving average. Requires volume > 1.2x average to validate breakout strength and filter low-conviction moves.
Fair Value Gap (FVG) Integration:
Optional confluence filter that checks for unfilled FVG in the breakout direction:
Bullish FVG detected when: current bar's low > two bars ago high (creating gap)
Bearish FVG detected when: current bar's high < two bars ago low (creating gap)
Minimum FVG size: 0.3x ATR to filter noise
FVG considered filled when price retraces to gap midpoint
Signals only generate when an unfilled FVG exists in the breakout direction, adding institutional order flow confluence.
Risk Management Calculations:
Three stop loss placement methods:
Opposite Side - SL at opposite end of opening range (classic ORB approach)
Midpoint - SL at range midpoint (tighter risk, lower reward potential)
ATR Based - SL at 1.5x ATR from entry (adaptive to volatility)
Take profit calculated as: Entry ± (Entry - Stop Loss) × Risk:Reward Ratio
Default 1.5:1 R:R ratio, adjustable from 1.0 to 5.0.
Performance Tracking:
The indicator maintains a trade history using Pine Script's type system:
Records entry price, stop loss, take profit, and direction for each signal
Tracks outcome when price hits stop loss or take profit levels
Auto-closes after 80 bars if neither level hit
Calculates rolling win rate from last 50 trades maximum
Displays W/L record in real-time dashboard
VISUAL COMPONENTS
Opening Range Box:
Semi-transparent blue box drawn from range start bar to current bar + 20, showing the established range boundaries visually.
Range Levels:
Green line at OR High (potential long entry level)
Red line at OR Low (potential short entry level)
Gray dotted line at OR Midpoint (reference level)
All lines extend 50 bars forward for anticipation.
Trade Signals:
Green up arrow with "LONG ORB Break" label below price
Red down arrow with "SHORT ORB Break" label above price
Dashed lines showing SL and TP levels extending 30 bars
Small labels marking SL and TP endpoints
Real-Time Dashboard:
Top-right panel displaying:
OR formation status (Forming / Complete / Waiting)
Current OR High, Low, and Range size (with ATR multiple)
Breakout status (Long / Short / None)
Volume status (High / Normal)
FVG presence (Bull / Bear / None)
Entry settings (Breakout/Retest, R:R, SL type)
Win rate percentage and W/L record
PRACTICAL APPLICATION
Ideal Market Conditions:
Liquid instruments: SPY, QQQ, IWM, high-volume stocks
Recommended timeframes: 1-minute or 5-minute charts for precise entries
Most effective during trending days with clear directional bias
Range size between 0.5-1.5x ATR typically provides best risk:reward
Usage Workflow:
Apply indicator at market open (9:30 AM ET)
Observe range formation during first 15 minutes
Wait for "Complete" status in dashboard
Monitor for breakout signals with volume/FVG confirmation
Enter on signal, place stop loss and take profit as marked
Avoid taking opposing signals on same day (trend following approach)
Retest vs Breakout Selection:
Use Breakout mode on high-momentum days with strong overnight gaps
Use Retest mode on slower days or when seeking better entry prices
Retest mode reduces signal frequency but improves entry quality
Time-of-Day Considerations:
The indicator includes a trading cutoff setting (default 3:00 PM ET) to avoid late-day chop and reduced liquidity. First-hour breakouts (10:00-11:00 AM) historically show strongest follow-through.
SETTINGS & CUSTOMIZATION
Display Options:
Toggle signals, opening range box, and dashboard independently
Clean visual design to reduce chart clutter
Opening Range Settings:
Opening range duration (5-60 minutes in 5-minute increments)
Default 15 minutes aligns with classic ORB methodology
Trading cutoff hour (10-16, representing 10:00 AM - 4:00 PM ET)
Entry Configuration:
Entry type (Breakout / Retest)
Volume confirmation toggle (requires 1.2x average volume)
FVG confluence toggle (requires unfilled gap in breakout direction)
Risk Management:
Stop loss placement (Opposite Side / Midpoint / ATR Based)
Risk:reward ratio (1.0 - 5.0, default 1.5)
Future: Trail stop after partial TP (currently placeholder)
Alert System:
Five alert conditions available:
Opening Range Complete
ORB Long Signal
ORB Short Signal
Breakout Up (range broken, regardless of signal)
Breakout Down (range broken, regardless of signal)
BEST PRACTICES
Recommended Usage:
Focus on highly liquid instruments with tight spreads
Use 1-5 minute charts for entry precision
Respect calculated stop losses (range defines maximum risk)
Typically 1-2 quality setups per day maximum
Consider overall market trend (SPY/QQQ direction)
Risk Considerations:
Very small ranges (< 0.3x ATR) prone to false breakouts
Very large ranges (> 2x ATR) may indicate gap day requiring adjusted expectations
Low volume breakouts fail more frequently
Avoid trading both directions on same day (pick strongest setup)
IMPORTANT DISCLOSURES
This indicator is provided free and open-source for educational purposes. The Opening Range Breakout strategy is a well-documented public domain trading concept. This implementation adds automation, visual clarity, and optional confluence filters.
No indicator guarantees profitable trades. Past performance does not predict future results. Traders are responsible for their own trading decisions and risk management. Always use appropriate position sizing and never risk more than you can afford to lose.
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SuperTrend AI + PVSRA Full DashboardI tried to combine various indicators already created in a single version that can also guarantee a certain customization on colors, intensity of tables, etc. etc. The functioning, the operation is similar to the previous ones, I won't go into detail, at most take a look at the previous versions.
1. The "AI" Component: Multi-SuperTrend Clustering
Instead of using a single SuperTrend with a fixed multiplier, this script:
Simultaneously runs multiple SuperTrends with different sensitivities (multipliers).
Evaluates Performance: It tracks which multiplier would have been most profitable in recent bars.
K-Means Clustering: It uses an AI algorithm to group these multipliers into "Best," "Average," and "Worst" clusters.
Adaptive Trailing Stop: It automatically selects the "Best" multiplier to plot the AI Trailing Stop line on your chart, making it more responsive to changing market volatility than a standard indicator.
2. PVSRA Logic (Institutional Volumes)
PVSRA stands for Price Volume Support Resistance Analysis. The script re-colors candles based on volume intensity:
Climax Bull (Bright Green): Extremely high volume on a bullish candle. Usually indicates institutional buying or a trend climax.
Climax Bear (Magenta/Purple): Extremely high volume on a bearish candle. Usually indicates institutional selling or a panic bottom.
Rising (Grey/Silver): Above-average volume, showing increasing interest.
3. The "Super Confluence" Signal
This is the "Golden Signal" of the script. It triggers a BUY or SELL label only when several conditions align:
AI Trend Switch: The AI Trailing Stop flips direction.
SMA 20 Cross: The AI line crosses the 20-period Simple Moving Average.
Volume Confirmation: A PVSRA Climax or Rising volume must occur on that specific bar.
Directional Alignment: The candle color must match the trend direction.
4. Summary Dashboard (Top Right)
The dashboard provides a "Quick Glance" at the market structure:
AI Trend: Shows if the machine learning model is currently Bullish or Bearish.
PVSRA Vol: Identifies the current volume signature (Normal vs. Climax).
SMA 20/50: Shows medium-term momentum (Bullish if 20 > 50).
Trend 200: Shows the macro trend. ABOVE means long-term bullish; BELOW means long-term bearish.
How to Trade with This Script
Signal Strategy
"SUPER CONFLUENCE BUY" Look for entries. High probability if Trend 200 is "ABOVE".
"SUPER CONFLUENCE SELL" Look for shorts. High probability if Trend 200 is "BELOW".
Magenta/Green Candles Caution: These are "Stop Hunts" or "Institutional Entries." Do not
trade against these candles without a clear reversal pattern.
Technical Tip
The variable target_f is the "AI-optimized multiplier." If you see this value changing frequently in the dashboard, it means the market is volatile, and the AI is struggling to find a stable trend. If it stays consistent, the trend is likely solid.
Thanks everyone and happy trading
Ultimate Futures Daytrade Suite v1 - The Strategy GuideHere is the complete **Strategy Guide** translated into English.
---
# 📘 Ultimate Futures Daytrade Suite – The Strategy Guide
### 1. The Visual Legend (What is what?)
Before you trade, you need to understand the hierarchy of your lines. Not every line has the same importance.
* **🟣 Daily EMA 50 (Neon Violet):** The **"Big Boss"**. It determines the **Macro Trend**.
* *Price above:* We are primarily looking for Longs.
* *Price below:* We are primarily looking for Shorts.
* **🟢 4h EMA 50 (Neon Green):** The **"Swing Trend"**. Your most important level for **Pullback Entries** (Re-entries).
* **🟡 POC (Gold) & TPO:** The **"Magnet"**. Price often returns here.
* *Rule:* Never open a trade directly *on* the POC (Risk of "Chop"). Use it as a **Target** (Take Profit).
* **🟠 IB High/Low (Orange Lines):** The **"Daily Structure"**.
* A breakout from the IB (Initial Balance) often indicates the trend direction for the day.
* **🟥/🟩 Boxes (Supply/Demand):** Resistance and Support zones from the 1h timeframe.
* **⬜ FVG Boxes:** "Gaps" in the market that are often filled.
---
### 2. The Trading Workflow (Top-Down Method)
Go through this mental checklist before every trade:
#### Step 1: Trend Check (The Traffic Light)
Look at the **Violet Line (Daily)** and the **Green Line (4h)**.
* **Bullish:** Price is above Violet AND above Green. -> *Focus: Buy dips.*
* **Bearish:** Price is below Violet AND below Green. -> *Focus: Sell rallies.*
* **Mixed:** Price is between Violet and Green. -> *Caution! Market is undecided (Range Trading).*
#### Step 2: Location (The Context)
Where is the price currently located?
* Are we at a **Green Demand Zone**?
* Are we testing the **4h EMA 50 (Green)** from above?
* Are we at the **VWAP**?
* *Never trade in "No Man's Land"!* Wait until the price touches one of your lines.
#### Step 3: Trigger (The Execution)
Now zoom into your lower timeframe (e.g., 5min or 15min).
* Wait for a reaction at the zone.
* Use the **EMA 9 (Yellow)** as a momentum trigger. If price breaks the EMA 9 and closes above/below it, that is your "Go".
---
### 3. The Setup Blueprints
Here are the two most profitable scenarios you can trade with this script:
#### A) The "Golden Trend" Setup (Long)
* **Context:** Price > **Daily EMA (Violet)**.
* **Preparation:** Price corrects (drops) back to the **4h EMA 50 (Green)** or to the **VWAP**.
* **Confluence:** Ideally, there is also a **Demand Zone (Green Box)** or an **FVG** at that level.
* **Entry:** As soon as a candle touches the zone and closes bullish again (or reclaims the EMA 9).
* **Stop-Loss:** Below the 4h EMA 50.
* **Take-Profit:** Next **Supply Zone (Red)** or the **IB High (Orange)**.
#### B) The "Daytrade Breakout" (Intraday)
* **Context:** Price opens inside yesterday's Value Area.
* **Signal:** Price breaks through the **IB High (Orange)** with momentum.
* **Filter:** Price must be above the **VWAP**.
* **Entry:** On the retest of the IB High or directly on the breakout.
* **Target:** Price often trends in that direction for the rest of the day.
---
### 4. Warning Signals (When NOT to trade)
1. **The "Concrete Ceiling":** If you want to go Long, but the **Violet Daily EMA 50** is running directly above you. This is massive resistance. Better wait until it is broken.
2. **The "POC Dance":** If price is dancing sideways around the **Gold Line (POC)**. This is a "No-Trade Zone". Day traders lose the most money here due to fees and whipsaws.
3. **Overextension:** If price is extremely far away from the **4h EMA 50 (Green)** (Rubber Band Effect). Do not enter in the trend direction here; wait for a pullback to the line.
### Summary
Your chart is now telling you a story:
* **Violet** tells you the Direction.
* **Green** gives you the Entry.
* **Red/Green Boxes** show you the Obstacles.
* **Yellow (EMA 9)** gives you the Timing.
Good luck with the Suite! This is a setup similar to what institutional traders use.
The Strat - Multi-Timeframe Combo Analyzer## 📊 The Strat - Multi-Timeframe Combo Analyzer
This open-source indicator implements **The Strat** methodology, a universal price action framework developed by Rob Smith (@RobInTheBlack).
---
### 🎯 What is The Strat?
The Strat categorizes every candle into one of three scenarios based on its relationship to the previous bar:
| Type | Name | Definition |
|------|------|------------|
| **1** | Inside Bar | High < Previous High AND Low > Previous Low |
| **2** | Directional | Breaks only one side (2↑ = broke high, 2↓ = broke low) |
| **3** | Outside Bar | Breaks BOTH previous high AND low |
By tracking these bar types across timeframes, traders can identify actionable setups with defined entry triggers and target levels.
---
### ✨ Features
**Daily Timeframe Analysis:**
- Real-time 3-bar combo detection (2-1-2, 3-1-2, 1-2-2, etc.)
- Pattern classification: Bullish/Bearish Continuation or Reversal
- Entry and Target levels based on Strat rules
- Pattern status: ACTIONABLE, IN-FORCE, TRIGGERED, or WATCHING
**ATR Context:**
- Range % used (how much of daily ATR has been consumed)
- Entry quality assessment (Excellent → Exhausted)
- Day type classification (Quiet → Trend Day)
- Remaining range estimation
**15-Minute Analysis:**
- Separate combo tracking for intraday precision
- Pattern detection on lower timeframe
**Visuals:**
- Customizable info tables
- Entry/Target horizontal lines
- Signal labels on chart
- Alert conditions
---
### 🔧 How to Use
1. Look for **ACTIONABLE** patterns - these are setups waiting for a trigger
2. Entry triggers when price breaks the designated level
3. Target is the next logical Strat level (typically prior bar's high/low)
4. Use **Range%** to assess if there's room left in the daily range
5. Combine Daily and 15-Min combos for trade confluence
---
### ⚠️ Disclaimer
This indicator is for **educational purposes only**. It does not constitute financial advice or guarantee profitable trades. Trading involves substantial risk of loss. Past performance is not indicative of future results. Always conduct your own research and trade responsibly.
---
### 🙏 Credits
**The Strat** methodology was created by Rob Smith (@RobInTheBlack).
This implementation is open-source. Feel free to study, modify, and improve the code!
SMA BUY/SELL SignalsStrategy using SMA to identify BUY/SELL Signals which is the most Powerful, accurate , and highly profitable trading strategy.
IV Rank & Percentile Suite V1.0What This Indicator Does
The IV Rank & Percentile Suite provides the volatility context options traders need to time entries. It calculates two complementary metrics—IV Rank and IV Percentile—using historical volatility as a proxy, then displays clear visual zones to identify favorable conditions for premium selling strategies.
Stop guessing if volatility is "high" or "low." This indicator tells you exactly where current volatility sits relative to recent history.
The Two Metrics Explained
IV Rank (0-100) Measures where current volatility sits within its 52-week high-low range.
IV Rank = (Current HV - 52w Low) / (52w High - 52w Low) × 100
70 means current volatility is 70% of the way between the yearly low and high
Sensitive to extreme spikes (a single high reading affects the range)
IV Percentile (0-100) Measures what percentage of days in the lookback period had lower volatility than today.
IV Percentile = (Days with lower HV / Total days) × 100
70 means volatility was lower than today on 70% of days in the past year
More stable, less affected by outlier spikes
Why Both?
IV Rank reacts faster to volatility changes. IV Percentile is more stable and statistically robust. When both agree (e.g., both above 50), you have stronger confirmation. Divergence between them can signal transitional periods.
Zone System
The indicator divides readings into three zones:
Zone ------- Default Range ---- Meaning ------------------ Premium Selling
🟢 High ≥ 50 Elevated volatility Favorable
🟡 Neutral 25-50 Normal volatility Selective
🔴 Low ≤ 25 Compressed volatility Avoid
An additional Extreme threshold (default 75) highlights prime conditions when volatility is significantly elevated.
Zone thresholds are fully customizable in settings.
How to Use It
For Premium Sellers (Iron Condors, Credit Spreads, Strangles)
Wait for IV Rank to enter the green zone (≥50)
Confirm IV Percentile agrees (also elevated)
Enter premium selling positions when both metrics align
Avoid initiating new positions when in the red zone
For Premium Buyers (Long Options, Debit Spreads)
Low IV Rank/Percentile means cheaper options
Red zone can favor directional debit strategies
Avoid buying premium when both metrics are in the green zone
General Principle:
Sell premium when volatility is high (it tends to revert to mean). Buy premium when volatility is low (if you have a directional thesis).
Inputs
Volatility Calculation
HV Period — Lookback for historical volatility calculation (default: 20)
Trading Days/Year — 252 for stocks, 365 for crypto
Lookback Periods
IV Rank Lookback — Period for high/low range (default: 252 = 1 year)
IV Percentile Lookback — Period for percentile calculation (default: 252)
Zone Thresholds
High IV Zone — Readings above this are highlighted green (default: 50)
Low IV Zone — Readings below this are highlighted red (default: 25)
Extreme High — Threshold for "prime" conditions alert (default: 75)
Display Options
Toggle IV Rank, IV Percentile, and raw HV display
Show/hide zone backgrounds
Show/hide info panel
Panel position selection
Info Panel
The panel displays:
Field ------- Description
IV Rank ------- Current reading with color coding
IV Pctl ------- Current percentile with color coding
HV 20d ------- Raw historical volatility percentage
52w Range ------- Lowest to highest HV in lookback period
Zone ------- Current zone status
Premium ------- Signal quality for premium selling
Lookback ------- Days used for calculations
R/P Spread ------- Difference between Rank and Percentile
Alerts
Six alerts are available:
Zone Transitions
IV Entered High Zone — Favorable for premium selling
IV Reached Extreme Levels — Prime conditions
IV Dropped to Low Zone — Caution for premium sellers
Threshold Crosses
IV Rank Crossed Above High Threshold
IV Rank Crossed Below Low Threshold
IV Percentile Above 75
IV Percentile Below 25
Set up alerts to get notified when conditions change without watching charts.
Technical Notes
Volatility Calculation Method
This indicator uses close-to-close historical volatility as an IV proxy:
Calculate log returns: ln(Close / Previous Close)
Take standard deviation over HV Period
Annualize: multiply by √(Trading Days)
This method correlates well with implied volatility for most liquid instruments. On highly liquid options underlyings (SPY, QQQ, major stocks), HV and IV tend to move together, making this a reliable proxy for IV Rank analysis.
Non-Repainting
All calculations use confirmed bar data. Values are fixed once a bar closes.
Lookback Requirement
The indicator needs sufficient history to calculate accurately. For a 252-day lookback, ensure your chart has at least 300+ bars of data.
Best Used On
ETFs: SPY, QQQ, IWM, DIA
Indices: SPX, NDX
High-volume stocks: AAPL, TSLA, NVDA, AMD, META
Timeframe: Daily (recommended), Weekly for longer-term view
The indicator works on any instrument but is most meaningful on underlyings with active options markets.
Important Notes
⚠️ This indicator uses historical volatility as a proxy for implied volatility. While HV and IV are correlated, they are not identical. For precise IV data, consult your options broker's platform.
⚠️ High IV Rank does not guarantee profitable premium selling. It indicates favorable conditions, not guaranteed outcomes. Position sizing and risk management remain essential.
⚠️ Past volatility patterns do not guarantee future behavior. Volatility regimes can shift, and historical ranges may not predict future ranges.
Suggested Workflow
Add to daily chart of your preferred underlying
Set up alert for "IV Entered High Zone"
When alerted, check both IV Rank and IV Percentile
If both elevated, evaluate premium selling opportunities
Use your broker's actual IV data for final entry decisions
Questions? Leave a comment below.
Red Bull Wings [JOAT]RED BULL WINGS - Bullish-Only Institutional Overlay
Introduction and Purpose
RED BULL WINGS is an open-source overlay indicator that combines five distinct bullish detection methods into a single composite scoring system. The core problem this indicator solves is that individual bullish signals (patterns, volume, zones, trendlines) often disagree or fire in isolation. A bullish engulfing pattern means little if volume is weak and price is far from support. Traders need confluence across multiple dimensions to identify high-probability setups.
This indicator addresses that by scoring each bullish component separately, then combining them into a weighted WINGS score (0-100) that reflects overall bullish conviction. When multiple components align, the score rises; when they disagree, the score stays low.
Why These Five Modules Work Together
Each module measures a different aspect of bullish market structure:
1. Module A - Bullish Candlestick Engine - Detects classic reversal patterns (engulfing, marubozu, hammer, 3-bar cluster). These patterns identify WHERE buyers are stepping in.
2. Module B - PVSRA Volume Climax - Measures spread x volume to detect institutional participation. This tells you WHETHER smart money is involved.
3. Module C - Demand Zone Detection - Identifies and tracks order block zones where buyers previously overwhelmed sellers. This shows you WHERE institutional support exists.
4. Module D - Trendline Channel - Builds dynamic support/resistance from pivot points. This reveals the STRUCTURE of the current trend.
5. Module E - Ichimoku Assist - Optional filter using Tenkan/Kijun cross, cloud position, and Chikou confirmation. This provides TREND PERMISSION context.
The combination works because:
Patterns alone can fail without volume confirmation
Volume alone means nothing without price structure context
Zones alone are static without pattern/volume triggers
Trendlines alone miss the micro-level entry timing
When 3+ modules agree, the probability of a valid bullish setup increases significantly
How the Calculations Work
Module A - Pattern Detection:
Bullish Engulfing - Current bullish bar completely engulfs prior bearish bar:
bool engulfingCond = isBullish() and
isBearish() and
open <= close and
close >= open and
bodySize() > bodySize()
Marubozu - Strong body with minimal wicks (body >= 1.8x average, wick ratio < 20%):
float wickRatio = candleRange() > 0 ? (upperWick() + lowerWick()) / candleRange() : 0
bool marubozuCond = isBullish() and
bodySize() >= bodySizeAvg * i_maruMult and
wickRatio < i_wickRatioMax
Hammer - Long lower wick (>= 2.5x body), close in upper third, volume confirmation:
bool hammerWick = lowerWick() >= i_hammerWickMult * bodySize()
bool hammerClose = close >= low + (candleRange() * 0.66)
bool hammerVol = volume >= i_pvsraRisingMult * volAvg
3-Bar Cluster - Three consecutive bullish closes with increasing prices and volume spike:
bool threeBarBullish = isBullish() and isBullish() and isBullish()
bool increasingCloses = close > close and close > close
bool volSpike3Bar = volume >= i_pvsraRisingMult * volAvg or
volume >= i_pvsraRisingMult * volAvg
Module B - PVSRA Volume Analysis:
Uses spread x volume to detect climax conditions:
float spreadVol = candleRange() * volume
float maxSpreadVol = ta.highest(spreadVol, ADJ_PVSRA_LOOKBACK)
bool volClimax = volume >= i_pvsraClimaxMult * volAvg or spreadVol >= maxSpreadVol
bool volRising = volume >= i_pvsraRisingMult * volAvg and volume < i_pvsraClimaxMult * volAvg
Volume only scores when the candle is bullish, preventing false signals on bearish volume spikes.
Module C - Demand Zone Detection:
Identifies zones using a two-candle structure:
// Small bearish candle A followed by larger bullish candle B
bool candleA_bearish = isBearish()
bool candleB_bullish = isBullish()
bool newZoneCond = candleA_bearish and candleB_bullish and
candleB_size >= i_zoneSizeMult * candleA_size
Zones are drawn as rectangles and tracked for retests. Score increases when price is near or inside an active zone, with bonus points for rejection candles.
Module D - Trendline Channel:
Builds dynamic channel from confirmed pivot points:
float ph = ta.pivothigh(high, i_pivotLeft, i_pivotRight)
float pl = ta.pivotlow(low, i_pivotLeft, i_pivotRight)
Pivots are stored and connected to form upper/lower channel lines. The indicator detects breakouts when price closes beyond the channel with volume confirmation.
Module E - Ichimoku Assist:
Standard Ichimoku calculations with bullish scoring:
float tenkan = (ta.highest(high, i_tenkanLen) + ta.lowest(low, i_tenkanLen)) / 2
float kijun = (ta.highest(high, i_kijunLen) + ta.lowest(low, i_kijunLen)) / 2
bool tkCross = ta.crossover(tenkan, kijun)
bool priceAboveCloud = close > cloudTop
bool chikouAbovePrice = chikou > close
Module F - WINGS Composite Score:
All module scores are combined using adjustable weights:
float WINGS_score = 100 * (nW_pattern * S_pattern +
nW_volume * S_vol +
nW_zone * S_zone +
nW_trend * S_trend +
nW_ichi * S_ichi)
Default weights: Pattern 30%, Volume 25%, Zone 20%, Trend 15%, Ichimoku 10%.
Signal Thresholds
WATCH (30-49) - Interesting bullish context forming, not yet actionable
MOMENTUM (50-74) - Strong bullish conditions, multiple modules agreeing
LIFT-OFF (75+) - High-confidence bullish confluence across most modules
WINGS Badge (Dashboard)
The right-side panel displays:
WINGS Score - Current composite score (0-100)
Pattern - Active pattern name and strength, or neutral placeholder
Volume - Normal / Rising / CLIMAX status
Zone - ACTIVE if price is near a demand zone
Trend - Channel position or BREAK status
Ichimoku - OFF / Weak / Bullish / STRONG
Status - Overall signal level (Neutral / WATCH / MOMENTUM / LIFT-OFF)
Input Parameters
Module Toggles:
Enable Bullish Patterns (true) - Toggle pattern detection
Enable PVSRA Volume (true) - Toggle volume analysis
Enable Order Blocks (true) - Toggle demand zone detection
Enable Trendlines (true) - Toggle pivot channel
Enable Ichimoku Assist (false) - Toggle Ichimoku filter (off by default for performance)
Enable Visual Effects (false) - Toggle labels, trails, and visual elements
LIVE MODE (false) - Enable intrabar signals (WARNING: signals may repaint)
Pattern Engine:
Pattern Lookback (5) - Bars for body size averaging
Marubozu Body Multiplier (1.8) - Minimum body size vs average
Hammer Wick Multiplier (2.5) - Minimum lower wick vs body
Max Wick Ratio (0.2) - Maximum wick percentage for marubozu
Volume / PVSRA:
PVSRA Lookback (10) - Period for volume averaging
Climax Multiplier (2.0) - Volume threshold for climax detection
Rising Volume Multiplier (1.5) - Volume threshold for rising detection
Order Blocks:
Zone Size Multiplier (2.0) - Minimum bullish candle size vs bearish
Zone Extend Bars (200) - How far zones project forward
Max Zones (12) - Maximum active zones displayed
Remove Zone on Close Below (true) - Delete broken zones
Trendlines:
Pivot Left/Right Bars (3/3) - Pivot detection sensitivity
Min Slope % (0.25) - Minimum trendline angle
Max Trendlines (5) - Maximum pivot points stored
Trendline Projection Bars (60) - Forward projection distance
Ichimoku:
Tenkan Length (9) - Conversion line period
Kijun Length (26) - Base line period
Senkou B Length (52) - Leading span B period
Displacement (26) - Cloud displacement
WINGS Score:
Weight: Pattern (0.30) - Pattern contribution to score
Weight: Volume (0.25) - Volume contribution to score
Weight: Zone (0.20) - Zone contribution to score
Weight: Trend (0.15) - Trendline contribution to score
Weight: Ichimoku (0.10) - Ichimoku contribution to score
Lift-Off Threshold (75) - Score required for LIFT-OFF signal
Momentum Watch Threshold (50) - Score required for MOMENTUM signal
Visuals:
Signal Cooldown (8) - Minimum bars between labels
Show WINGS Score Badge (true) - Toggle dashboard
Show Wing Combos (true) - Show DOUBLE/MEGA WINGS streaks
Red Background Wash (true) - Tint chart background
Show Lift-Off Trails (false) - Toggle golden trail visuals
How to Use This Indicator
For Bullish Entry Identification:
1. Monitor the WINGS badge for score changes
2. Wait for MOMENTUM (50+) or LIFT-OFF (75+) signals
3. Check which modules are contributing (Pattern + Volume + Zone = stronger)
4. Use demand zones and trendlines as structural reference for entries
For Confluence Confirmation:
1. Use alongside your existing analysis
2. LIFT-OFF signals indicate multiple bullish factors aligning
3. Low scores (< 30) suggest weak bullish context even if one factor looks good
For Zone-Based Trading:
1. Watch for price approaching active demand zones
2. Look for pattern + volume confirmation at zone retests
3. Zone score increases with successful retests
For Trendline Analysis:
1. Monitor the pivot-based channel for trend structure
2. Breakouts with volume confirmation trigger TREND BREAK alerts
3. Price inside channel with bullish patterns = trend continuation setup
1M and lower timeframes:
Alerts Available
LIFT-OFF - High-confidence bullish confluence
MOMENTUM - Strong bullish conditions
Zone Retest - Bullish rejection from demand zone
Trendline Break - Breakout with volume confirmation
Individual patterns (Engulfing, Marubozu, Hammer, 3-Bar Cluster)
Volume Climax - Institutional volume spike
DOUBLE WINGS / MEGA WINGS - Consecutive lift-off signals
Repainting Behavior
By default, the indicator uses confirmed bars only (barstate.isconfirmed), meaning signals appear after the bar closes and do not repaint. However:
LIVE MODE - When enabled, signals can appear intrabar but may disappear if conditions change before bar close. A warning label displays when LIVE MODE is active.
Trendlines - Pivot detection requires lookback bars, so the most recent trendline segments may adjust as new pivots confirm. This is inherent to pivot-based analysis.
Demand Zones - Zones are created on confirmed bars and do not repaint, but they can be removed if price closes below the zone bottom (configurable).
Live Mode with 'Enable Visual Effect' turned off in settings:
Limitations
This is a bullish-only indicator. It does not detect bearish setups or provide short signals.
The WINGS score is a confluence measure, not a prediction. High scores indicate favorable conditions, not guaranteed outcomes.
Pattern detection uses simplified logic. Not all candlestick nuances are captured.
Volume analysis requires reliable volume data. Results may vary on instruments with inconsistent volume reporting.
Ichimoku calculations add processing overhead. Disable if not needed.
Demand zones are based on a specific two-candle structure. Other valid zones may not be detected.
Trendlines use linear regression between pivots. Curved or complex channels are not supported.
Timeframe Recommendations
15m-1H: More frequent signals, useful for intraday analysis. Higher noise.
4H-Daily: Best balance of signal quality and frequency for swing trading.
Weekly: Fewer but more significant signals for position trading.
Adjust lookback periods and thresholds based on your timeframe. Shorter timeframes may benefit from shorter lookbacks.
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each module works.
This indicator does not constitute financial advice. The WINGS score and signals do not guarantee profitable trades. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses. Test thoroughly on your preferred instruments and timeframes before using in live trading.
- Made with passion by officialjackofalltrades
WoAlgo Premium v3.0
WoAlgo Premium v3.0 - Smart Money Analysis
Overview
** WoAlgo Premium v3.0 ** is an advanced technical analysis indicator designed for educational purposes. This tool combines Smart Money Concepts with multi-factor confluence analysis to help traders identify potential market opportunities across multiple timeframes.
The indicator integrates market structure analysis, order flow concepts, and technical momentum indicators into a comprehensive dashboard system. It is designed to assist traders in understanding institutional trading patterns and market dynamics through visual analysis tools.
### What It Does
This indicator provides:
**1. Smart Money Concepts Analysis**
- Market structure identification (Break of Structure and Change of Character patterns)
- Order block detection with volume confirmation
- Fair value gap recognition
- Liquidity zone mapping (equal highs and lows)
- Premium and discount zone calculations
**2. Multi-Factor Confluence Scoring**
The indicator calculates a proprietary confluence score (0-100) based on five key components:
- Price action analysis (30% weight)
- Volume confirmation (20% weight)
- Momentum indicators (25% weight)
- Trend strength measurement (15% weight)
- Money flow analysis (10% weight)
**3. Multi-Timeframe Analysis**
- Scans 5 different timeframes (5M, 15M, 1H, 4H, Daily)
- Calculates alignment percentage across timeframes
- Displays trend and structure status for each period
**4. Visual Dashboard System**
- Comprehensive main dashboard with 13 metrics
- Real-time screener table with 10 data columns
- Multi-timeframe scanner
- Performance tracking panel
### How It Works
**Market Structure Detection**
The indicator identifies key structural changes in price action:
- **BOS (Break of Structure)**: Indicates trend continuation when price breaks previous swing points
- **CHoCH (Change of Character)**: Signals potential trend reversal when market structure shifts
**Order Block Identification**
Order blocks are detected when:
- Significant volume appears at swing points
- Price shows strong directional movement from these levels
- Enhanced detection with extreme volume confirmation (OB++ markers)
**Fair Value Gap Recognition**
Gaps between candles are identified when:
- Price leaves inefficiencies in the market
- Three consecutive candles create a gap pattern
- Gap size exceeds minimum threshold based on ATR
**Confluence Calculation**
The system evaluates multiple technical factors:
1. **Price Position**: Relative to moving averages (EMA 20, 50, 200)
2. **Volume Analysis**: Standard deviation-based volume spikes
3. **Momentum**: RSI, MACD, Stochastic indicators
4. **Trend Strength**: ADX measurements
5. **Money Flow**: MFI indicator readings
Each factor contributes weighted points to create an overall confluence score that helps assess signal strength.
### Signal Types
**Confirmation Signals (▲ / ▼)**
Generated when:
- EMA crossovers occur (20/50 cross)
- Volume confirmation is present
- RSI is in appropriate zone
- Confluence score exceeds 50%
**Strong Signals (▲+ / ▼+)**
Higher-confidence signals requiring:
- Confluence score above 70%
- Extreme volume confirmation
- Alignment with 200 EMA trend
- MACD confirmation
- Bullish or bearish market structure
**Contrarian Signals (⚡)**
Reversal indicators appearing when:
- RSI reaches extreme levels (<30 or >70)
- Stochastic shows oversold/overbought conditions
- Price touches Bollinger Band extremes
- Potential divergence patterns emerge
**Reversal Zones**
Visual boxes highlighting areas where:
- Market structure conflicts with momentum
- High probability of directional change
- Key support/resistance levels interact
**Smart Trail**
Dynamic stop-loss indicator that:
- Adjusts based on ATR (Average True Range)
- Follows trend direction
- Updates automatically as price moves
- Provides risk management reference points
### Dashboard Components
**Main Dashboard (13 Metrics)**
1. **Confluence Score**: Current bull/bear percentage (0-100)
2. **Market Regime**: Trend classification (Strong Up/Down, Range, Squeeze)
3. **Signal Status**: Active buy/sell signal indication
4. **Structure State**: Current market structure (Bullish/Bearish/Neutral)
5. **Trend Strength**: ADX-based measurement
6. **RSI Level**: Momentum indicator with overbought/oversold zones
7. **MACD Direction**: Trend momentum confirmation
8. **Money Flow Index**: Smart money sentiment
9. **Volume Status**: Current volume relative to average
10. **Volatility Rating**: ATR percentage measurement
11. **ATR Value**: Average true range for position sizing
12. **MTF Alignment**: Multi-timeframe agreement percentage
**Screener Table (10 Columns)**
- Current symbol and timeframe
- Real-time price and percentage change
- Quality rating (star system)
- Active signal type
- Smart trail status
- Market structure state
- MACD direction
- Trend strength percentage
- Bollinger Band squeeze detection
**MTF Scanner (5 Timeframes)**
Displays for each timeframe:
- Trend direction indicator
- Market structure classification
- Visual confirmation with color coding
**Performance Metrics**
- Win rate percentage (simplified calculation)
- Total signals generated
- Current confluence score
- MTF alignment status
- Volatility level
### Settings and Customization
**Preset Styles**
Choose from predefined configurations:
- **Conservative**: Fewer, higher-quality signals
- **Moderate**: Balanced approach (recommended)
- **Aggressive**: More frequent signals
- **Scalper**: Short-term focused
- **Swing**: Longer-term oriented
- **Custom**: Full manual control
**Smart Money Concepts Controls**
- Toggle each feature independently
- Adjust swing length (3-50 periods)
- Enable/disable internal structure
- Control order block display
- Manage breaker block visibility
- Show/hide fair value gaps
- Display liquidity zones
- Premium/discount zone visualization
**Signal Configuration**
- Enable/disable confirmation signals
- Toggle strong signal markers
- Control contrarian signal display
- Show/hide reversal zones
- Smart trail activation
- Sensitivity adjustment (5-50)
**Visual Customization**
- Moving average display options
- MA period adjustments (Fast: 20, Slow: 50, Trend: 200)
- Support/resistance line toggle
- Dynamic S/R lookback period
- Candle coloring based on trend
- Color scheme customization
- Dashboard size options (Small/Normal/Large)
- Position placement (4 corners)
### How to Use
**Step 1: Initial Setup**
1. Add indicator to chart
2. Select appropriate preset or use Custom
3. Adjust timeframe to match trading style
4. Configure dashboard visibility preferences
**Step 2: Analysis Workflow**
1. Check MTF Scanner for timeframe alignment
2. Review Main Dashboard confluence score
3. Observe Market Regime classification
4. Identify active signals on chart
5. Confirm with Smart Money Concepts (order blocks, FVG, structure)
**Step 3: Trade Consideration**
Strong signals (▲+ / ▼+) require:
- Confluence score >70%
- MTF alignment >60%
- Confirmation from multiple dashboard metrics
- Support from Smart Money Concepts
- Appropriate volume levels
**Step 4: Risk Management**
- Use Smart Trail as dynamic stop-loss reference
- Consider ATR for position sizing
- Monitor volatility rating
- Respect support/resistance levels
- Combine with personal risk parameters
### Best Practices
**For Scalping (1M-5M timeframes)**
- Use Scalper preset
- Reduce swing length to 5-7
- Focus on strong signals only
- Monitor MTF alignment closely
- Quick entries near order blocks
**For Intraday Trading (15M-1H timeframes)**
- Use Moderate preset (recommended)
- Default swing length (10)
- Combine confirmation and strong signals
- Check MTF scanner before entry
- Use fair value gaps for entries
**For Swing Trading (4H-D timeframes)**
- Use Swing preset
- Increase swing length to 15-20
- Focus on strong signals
- Require high MTF alignment
- Patient approach with major structure levels
### Technical Specifications
**Indicators Used**
- Exponential Moving Averages (20, 50, 200)
- Hull Moving Average
- Relative Strength Index (14)
- MACD (12, 26, 9)
- Money Flow Index (14)
- Stochastic Oscillator (14, 3)
- ADX / DMI (14)
- Bollinger Bands (20, 2)
- ATR (14)
- Volume Analysis (SMA 20 with standard deviation)
**Calculation Methods**
- Swing detection using pivot high/low functions
- Volume confirmation via statistical analysis
- Multi-factor scoring with weighted components
- Dynamic support/resistance using highest/lowest functions
- Real-time MTF data via security() function
### Limitations and Considerations
**Important Notes**
1. This indicator is designed for educational and analytical purposes only
2. Historical performance does not guarantee future results
3. Signals should be confirmed with additional analysis
4. Market conditions vary and affect indicator performance
5. Not all signals will be profitable
6. Risk management is essential for all trading
**Known Limitations**
- Confluence scoring is algorithmic and not predictive
- MTF analysis requires sufficient historical data
- Effectiveness varies across different market conditions
- Sideways markets may produce conflicting signals
- High volatility can affect signal reliability
- Backtesting results shown are simplified calculations
**Not Suitable For**
- Automated trading without human oversight
- Sole basis for trading decisions
- Guaranteed profit expectations
- Inexperienced traders without proper education
- Trading without risk management plans
### Market Applicability
**Effective On**
- Trending markets (any direction)
- Clear structure formation periods
- Liquid instruments with consistent volume
- Multiple asset classes (forex, stocks, crypto, commodities)
- Various timeframes with appropriate settings
**Less Effective During**
- Extended ranging/choppy conditions
- Extremely low volume periods
- Major news events causing gaps
- Early market open with high spread
- Illiquid instruments with erratic price action
### Risk Disclaimer
**⚠️ IMPORTANT NOTICE**
This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment recommendations, or trading signals.
**Key Risk Factors:**
- Trading financial instruments involves substantial risk of loss
- Past performance does not indicate future results
- No indicator can predict market movements with certainty
- Users should conduct independent research and analysis
- Professional financial advice should be sought when appropriate
- Risk management and position sizing are critical to successful trading
- Users are solely responsible for their trading decisions
**Responsible Usage:**
- Combine with comprehensive market analysis
- Use appropriate stop-loss orders
- Never risk more than you can afford to lose
- Maintain realistic expectations
- Continue education on technical analysis principles
- Test thoroughly on demo accounts before live trading
- Understand all indicator features before using
### Educational Resources
**Understanding Smart Money Concepts**
Smart Money Concepts analyze how institutional traders and large market participants operate. Key principles include:
- Institutional order flow patterns
- Market structure changes
- Liquidity manipulation
- Supply and demand imbalances
- Order block formations
**Multi-Timeframe Analysis Theory**
Analyzing multiple timeframes helps:
- Identify overall market direction
- Improve entry timing
- Confirm trend strength
- Recognize consolidation periods
- Reduce conflicting signals
**Confluence Trading Approach**
Using multiple confirming factors:
- Increases signal reliability
- Reduces false signals
- Provides conviction for trades
- Helps with position sizing
- Improves risk-reward ratios
### Version History
**v3.0 (Current)**
- Multi-factor confluence scoring system
- Complete Smart Money Concepts implementation
- Real-time multi-timeframe analysis
- Four professional dashboard panels
- Enhanced order block detection
- Breaker block identification
- Premium/discount zone calculations
- Smart trail stop-loss system
- Customizable preset configurations
- Performance tracking metrics
**Development Philosophy**
This indicator was developed with focus on:
- Educational value for traders
- Transparent methodology
- Comprehensive feature set
- User-friendly interface
- Flexible customization options
### Technical Support
**For Questions About:**
- Indicator functionality
- Parameter optimization
- Signal interpretation
- Dashboard metrics
- Best practice recommendations
Please use TradingView's comment section below. The developer monitors comments and provides assistance to users learning to use the indicator effectively.
### Acknowledgments
This indicator implements concepts from:
- Smart Money Concepts trading methodology
- Multi-timeframe analysis techniques
- Technical indicator theory
- Market structure analysis principles
- Institutional order flow concepts
All implementations are original code and calculations based on established technical analysis principles.
---
## ADDITIONAL INFORMATION SECTION
**Category**: Indicators
**Type**: Market Structure / Multi-Timeframe Analysis
**Complexity**: Intermediate to Advanced
**Open Source**: Code visible for transparency and education
**Pine Script Version**: v6
**Chart Overlay**: Yes
**Maximum Objects**: 500 boxes, 500 lines, 500 labels
Zenith MACD Evolution [JOAT]
Zenith MACD Evolution - Volatility-Normalized Momentum Oscillator
Introduction and Purpose
Zenith MACD Evolution is an open-source oscillator indicator that takes the classic MACD and normalizes it by ATR (Average True Range) to create consistent overbought/oversold levels across different market conditions. The core problem this indicator solves is that traditional MACD values are incomparable across different volatility regimes. A MACD reading of 50 might be extreme in a quiet market but normal in a volatile one.
This indicator addresses that by dividing MACD by ATR and scaling to a consistent range, allowing traders to use fixed overbought/oversold levels that work across all market conditions.
Why ATR Normalization Works
Traditional MACD problems:
- Values vary wildly based on price and volatility
- No consistent overbought/oversold levels
- Hard to compare across different instruments
- Extreme readings in one period may be normal in another
ATR-normalized MACD (Zenith) solves these:
- Values scaled to consistent range
- Fixed overbought/oversold levels work across all conditions
- Comparable across different instruments
- Extreme readings are truly extreme regardless of volatility
How the Normalization Works
// Classic MACD
= ta.macd(close, fastLength, slowLength, signalLength)
// ATR for normalization
float atrValue = ta.atr(atrNormLength)
// Volatility-Normalized MACD
float zenithMACD = atrValue != 0 ? (histLine / atrValue) * 100 : 0
float zenithSignal = ta.ema(zenithMACD, signalLength)
The result is a MACD that typically ranges from -200 to +200, with consistent levels:
- Above +150 = Overbought
- Below -150 = Oversold
- Above +200 = Extreme overbought
- Below -200 = Extreme oversold
Signal Types
Zero Cross Up/Down - Zenith crosses zero line (trend change)
Overbought/Oversold Entry - Zenith enters extreme zones
Overbought/Oversold Exit - Zenith leaves extreme zones (potential reversal)
Momentum Shift - Histogram direction changes (early warning)
Divergence - Price makes new high/low but Zenith does not
Histogram Coloring
The histogram uses four colors to show momentum state:
- Strong Bull (Teal) - Positive and rising
- Weak Bull (Light Teal) - Positive but falling
- Strong Bear (Red) - Negative and falling
- Weak Bear (Light Red) - Negative but rising
This helps identify momentum shifts before crossovers occur.
Dashboard Information
Zenith - Current normalized MACD value with signal line
Zone - Current zone (EXTREME OB/OVERBOUGHT/NORMAL/OVERSOLD/EXTREME OS)
Momentum - Direction (RISING/FALLING/FLAT)
Histogram - Current histogram value
ATR Norm - Current ATR value used for normalization
Classic - Traditional MACD value for reference
How to Use This Indicator
For Mean-Reversion:
1. Wait for Zenith to reach extreme zones (+200/-200)
2. Look for momentum shift (histogram color change)
3. Enter counter-trend when exiting extreme zone
For Trend Following:
1. Enter long on zero cross up
2. Enter short on zero cross down
3. Use histogram color to gauge momentum strength
For Divergence Trading:
1. Watch for DIV labels (price vs Zenith divergence)
2. Bullish divergence at support = potential long
3. Bearish divergence at resistance = potential short
Input Parameters
Fast/Slow/Signal Length (12/26/9) - Standard MACD parameters
ATR Normalization Period (26) - Period for ATR calculation
Overbought/Oversold Zone (150/-150) - Zone thresholds
Extreme Level (200) - Extreme threshold
Show Classic MACD Lines (false) - Toggle traditional lines
Show Divergence Detection (true) - Toggle divergence signals
Divergence Lookback (14) - Bars to scan for divergence
Timeframe Recommendations
All timeframes work due to normalization
Higher timeframes provide smoother signals
Normalization makes cross-timeframe comparison meaningful
Limitations
ATR normalization adds slight lag
Divergence detection is simplified
Extreme zones can persist in strong trends
Works best when combined with price action analysis
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Momentum analysis does not guarantee profitable trades. Always use proper risk management.
- Made with passion by officialjackofalltrades
Adaptive Market Wave TheoryAdaptive Market Wave Theory
🌊 CORE INNOVATION: PROBABILISTIC PHASE DETECTION WITH MULTI-AGENT CONSENSUS
Adaptive Market Wave Theory (AMWT) represents a fundamental paradigm shift in how traders approach market phase identification. Rather than counting waves subjectively or drawing static breakout levels, AMWT treats the market as a hidden state machine —using Hidden Markov Models, multi-agent consensus systems, and reinforcement learning algorithms to quantify what traditional methods leave to interpretation.
The Wave Analysis Problem:
Traditional wave counting methodologies (Elliott Wave, harmonic patterns, ABC corrections) share fatal weaknesses that AMWT directly addresses:
1. Non-Falsifiability : Invalid wave counts can always be "recounted" or "adjusted." If your Wave 3 fails, it becomes "Wave 3 of a larger degree" or "actually Wave C." There's no objective failure condition.
2. Observer Bias : Two expert wave analysts examining the same chart routinely reach different conclusions. This isn't a feature—it's a fundamental methodology flaw.
3. No Confidence Measure : Traditional analysis says "This IS Wave 3." But with what probability? 51%? 95%? The binary nature prevents proper position sizing and risk management.
4. Static Rules : Fixed Fibonacci ratios and wave guidelines cannot adapt to changing market regimes. What worked in 2019 may fail in 2024.
5. No Accountability : Wave methodologies rarely track their own performance. There's no feedback loop to improve.
The AMWT Solution:
AMWT addresses each limitation through rigorous mathematical frameworks borrowed from speech recognition, machine learning, and reinforcement learning:
• Non-Falsifiability → Hard Invalidation : Wave hypotheses die permanently when price violates calculated invalidation levels. No recounting allowed.
• Observer Bias → Multi-Agent Consensus : Three independent analytical agents must agree. Single-methodology bias is eliminated.
• No Confidence → Probabilistic States : Every market state has a calculated probability from Hidden Markov Model inference. "72% probability of impulse state" replaces "This is Wave 3."
• Static Rules → Adaptive Learning : Thompson Sampling multi-armed bandits learn which agents perform best in current conditions. The system adapts in real-time.
• No Accountability → Performance Tracking : Comprehensive statistics track every signal's outcome. The system knows its own performance.
The Core Insight:
"Traditional wave analysis asks 'What count is this?' AMWT asks 'What is the probability we are in an impulsive state, with what confidence, confirmed by how many independent methodologies, and anchored to what liquidity event?'"
🔬 THEORETICAL FOUNDATION: HIDDEN MARKOV MODELS
Why Hidden Markov Models?
Markets exist in hidden states that we cannot directly observe—only their effects on price are visible. When the market is in an "impulse up" state, we see rising prices, expanding volume, and trending indicators. But we don't observe the state itself—we infer it from observables.
This is precisely the problem Hidden Markov Models (HMMs) solve. Originally developed for speech recognition (inferring words from sound waves), HMMs excel at estimating hidden states from noisy observations.
HMM Components:
1. Hidden States (S) : The unobservable market conditions
2. Observations (O) : What we can measure (price, volume, indicators)
3. Transition Matrix (A) : Probability of moving between states
4. Emission Matrix (B) : Probability of observations given each state
5. Initial Distribution (π) : Starting state probabilities
AMWT's Six Market States:
State 0: IMPULSE_UP
• Definition: Strong bullish momentum with high participation
• Observable Signatures: Rising prices, expanding volume, RSI >60, price above upper Bollinger Band, MACD histogram positive and rising
• Typical Duration: 5-20 bars depending on timeframe
• What It Means: Institutional buying pressure, trend acceleration phase
State 1: IMPULSE_DN
• Definition: Strong bearish momentum with high participation
• Observable Signatures: Falling prices, expanding volume, RSI <40, price below lower Bollinger Band, MACD histogram negative and falling
• Typical Duration: 5-20 bars (often shorter than bullish impulses—markets fall faster)
• What It Means: Institutional selling pressure, panic or distribution acceleration
State 2: CORRECTION
• Definition: Counter-trend consolidation with declining momentum
• Observable Signatures: Sideways or mild counter-trend movement, contracting volume, RSI returning toward 50, Bollinger Bands narrowing
• Typical Duration: 8-30 bars
• What It Means: Profit-taking, digestion of prior move, potential accumulation for next leg
State 3: ACCUMULATION
• Definition: Base-building near lows where informed participants absorb supply
• Observable Signatures: Price near recent lows but not making new lows, volume spikes on up bars, RSI showing positive divergence, tight range
• Typical Duration: 15-50 bars
• What It Means: Smart money buying from weak hands, preparing for markup phase
State 4: DISTRIBUTION
• Definition: Top-forming near highs where informed participants distribute holdings
• Observable Signatures: Price near recent highs but struggling to advance, volume spikes on down bars, RSI showing negative divergence, widening range
• Typical Duration: 15-50 bars
• What It Means: Smart money selling to late buyers, preparing for markdown phase
State 5: TRANSITION
• Definition: Regime change period with mixed signals and elevated uncertainty
• Observable Signatures: Conflicting indicators, whipsaw price action, no clear momentum, high volatility without direction
• Typical Duration: 5-15 bars
• What It Means: Market deciding next direction, dangerous for directional trades
The Transition Matrix:
The transition matrix A captures the probability of moving from one state to another. AMWT initializes with empirically-derived values then updates online:
From/To IMP_UP IMP_DN CORR ACCUM DIST TRANS
IMP_UP 0.70 0.02 0.20 0.02 0.04 0.02
IMP_DN 0.02 0.70 0.20 0.04 0.02 0.02
CORR 0.15 0.15 0.50 0.10 0.10 0.00
ACCUM 0.30 0.05 0.15 0.40 0.05 0.05
DIST 0.05 0.30 0.15 0.05 0.40 0.05
TRANS 0.20 0.20 0.20 0.15 0.15 0.10
Key Insights from Transition Probabilities:
• Impulse states are sticky (70% self-transition): Once trending, markets tend to continue
• Corrections can transition to either impulse direction (15% each): The next move after correction is uncertain
• Accumulation strongly favors IMP_UP transition (30%): Base-building leads to rallies
• Distribution strongly favors IMP_DN transition (30%): Topping leads to declines
The Viterbi Algorithm:
Given a sequence of observations, how do we find the most likely state sequence? This is the Viterbi algorithm—dynamic programming to find the optimal path through the state space.
Mathematical Formulation:
δ_t(j) = max_i × B_j(O_t)
Where:
δ_t(j) = probability of most likely path ending in state j at time t
A_ij = transition probability from state i to state j
B_j(O_t) = emission probability of observation O_t given state j
AMWT Implementation:
AMWT runs Viterbi over a rolling window (default 50 bars), computing the most likely state sequence and extracting:
• Current state estimate
• State confidence (probability of current state vs alternatives)
• State sequence for pattern detection
Online Learning (Baum-Welch Adaptation):
Unlike static HMMs, AMWT continuously updates its transition and emission matrices based on observed market behavior:
f_onlineUpdateHMM(prev_state, curr_state, observation, decay) =>
// Update transition matrix
A *= decay
A += (1.0 - decay)
// Renormalize row
// Update emission matrix
B *= decay
B += (1.0 - decay)
// Renormalize row
The decay parameter (default 0.85) controls adaptation speed:
• Higher decay (0.95): Slower adaptation, more stable, better for consistent markets
• Lower decay (0.80): Faster adaptation, more reactive, better for regime changes
Why This Matters for Trading:
Traditional indicators give you a number (RSI = 72). AMWT gives you a probabilistic state assessment :
"There is a 78% probability we are in IMPULSE_UP state, with 15% probability of CORRECTION and 7% distributed among other states. The transition matrix suggests 70% chance of remaining in IMPULSE_UP next bar, 20% chance of transitioning to CORRECTION."
This enables:
• Position sizing by confidence : 90% confidence = full size; 60% confidence = half size
• Risk management by transition probability : High correction probability = tighten stops
• Strategy selection by state : IMPULSE = trend-follow; CORRECTION = wait; ACCUMULATION = scale in
🎰 THE 3-BANDIT CONSENSUS SYSTEM
The Multi-Agent Philosophy:
No single analytical methodology works in all market conditions. Trend-following excels in trending markets but gets chopped in ranges. Mean-reversion excels in ranges but gets crushed in trends. Structure-based analysis works when structure is clear but fails in chaotic markets.
AMWT's solution: employ three independent agents , each analyzing the market from a different perspective, then use Thompson Sampling to learn which agents perform best in current conditions.
Agent 1: TREND AGENT
Philosophy : Markets trend. Follow the trend until it ends.
Analytical Components:
• EMA Alignment: EMA8 > EMA21 > EMA50 (bullish) or inverse (bearish)
• MACD Histogram: Direction and rate of change
• Price Momentum: Close relative to ATR-normalized movement
• VWAP Position: Price above/below volume-weighted average price
Signal Generation:
Strong Bull: EMA aligned bull AND MACD histogram > 0 AND momentum > 0.3 AND close > VWAP
→ Signal: +1 (Long), Confidence: 0.75 + |momentum| × 0.4
Moderate Bull: EMA stack bull AND MACD rising AND momentum > 0.1
→ Signal: +1 (Long), Confidence: 0.65 + |momentum| × 0.3
Strong Bear: EMA aligned bear AND MACD histogram < 0 AND momentum < -0.3 AND close < VWAP
→ Signal: -1 (Short), Confidence: 0.75 + |momentum| × 0.4
Moderate Bear: EMA stack bear AND MACD falling AND momentum < -0.1
→ Signal: -1 (Short), Confidence: 0.65 + |momentum| × 0.3
When Trend Agent Excels:
• Trend days (IB extension >1.5x)
• Post-breakout continuation
• Institutional accumulation/distribution phases
When Trend Agent Fails:
• Range-bound markets (ADX <20)
• Chop zones after volatility spikes
• Reversal days at major levels
Agent 2: REVERSION AGENT
Philosophy: Markets revert to mean. Extreme readings reverse.
Analytical Components:
• Bollinger Band Position: Distance from bands, percent B
• RSI Extremes: Overbought (>70) and oversold (<30)
• Stochastic: %K/%D crossovers at extremes
• Band Squeeze: Bollinger Band width contraction
Signal Generation:
Oversold Bounce: BB %B < 0.20 AND RSI < 35 AND Stochastic < 25
→ Signal: +1 (Long), Confidence: 0.70 + (30 - RSI) × 0.01
Overbought Fade: BB %B > 0.80 AND RSI > 65 AND Stochastic > 75
→ Signal: -1 (Short), Confidence: 0.70 + (RSI - 70) × 0.01
Squeeze Fire Bull: Band squeeze ending AND close > upper band
→ Signal: +1 (Long), Confidence: 0.65
Squeeze Fire Bear: Band squeeze ending AND close < lower band
→ Signal: -1 (Short), Confidence: 0.65
When Reversion Agent Excels:
• Rotation days (price stays within IB)
• Range-bound consolidation
• After extended moves without pullback
When Reversion Agent Fails:
• Strong trend days (RSI can stay overbought for days)
• Breakout moves
• News-driven directional moves
Agent 3: STRUCTURE AGENT
Philosophy: Market structure reveals institutional intent. Follow the smart money.
Analytical Components:
• Break of Structure (BOS): Price breaks prior swing high/low
• Change of Character (CHOCH): First break against prevailing trend
• Higher Highs/Higher Lows: Bullish structure
• Lower Highs/Lower Lows: Bearish structure
• Liquidity Sweeps: Stop runs that reverse
Signal Generation:
BOS Bull: Price breaks above prior swing high with momentum
→ Signal: +1 (Long), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bull: First higher low after downtrend, breaking structure
→ Signal: +1 (Long), Confidence: 0.75
BOS Bear: Price breaks below prior swing low with momentum
→ Signal: -1 (Short), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bear: First lower high after uptrend, breaking structure
→ Signal: -1 (Short), Confidence: 0.75
Liquidity Sweep Long: Price sweeps below swing low then reverses strongly
→ Signal: +1 (Long), Confidence: 0.80
Liquidity Sweep Short: Price sweeps above swing high then reverses strongly
→ Signal: -1 (Short), Confidence: 0.80
When Structure Agent Excels:
• After liquidity grabs (stop runs)
• At major swing points
• During institutional accumulation/distribution
When Structure Agent Fails:
• Choppy, structureless markets
• During news events (structure becomes noise)
• Very low timeframes (noise overwhelms structure)
Thompson Sampling: The Bandit Algorithm
With three agents giving potentially different signals, how do we decide which to trust? This is the multi-armed bandit problem —balancing exploitation (using what works) with exploration (testing alternatives).
Thompson Sampling Solution:
Each agent maintains a Beta distribution representing its success/failure history:
Agent success rate modeled as Beta(α, β)
Where:
α = number of successful signals + 1
β = number of failed signals + 1
On Each Bar:
1. Sample from each agent's Beta distribution
2. Weight agent signals by sampled probabilities
3. Combine weighted signals into consensus
4. Update α/β based on trade outcomes
Mathematical Implementation:
// Beta sampling via Gamma ratio method
f_beta_sample(alpha, beta) =>
g1 = f_gamma_sample(alpha)
g2 = f_gamma_sample(beta)
g1 / (g1 + g2)
// Thompson Sampling selection
for each agent:
sampled_prob = f_beta_sample(agent.alpha, agent.beta)
weight = sampled_prob / sum(all_sampled_probs)
consensus += agent.signal × agent.confidence × weight
Why Thompson Sampling?
• Automatic Exploration : Agents with few samples get occasional chances (high variance in Beta distribution)
• Bayesian Optimal : Mathematically proven optimal solution to exploration-exploitation tradeoff
• Uncertainty-Aware : Small sample size = more exploration; large sample size = more exploitation
• Self-Correcting : Poor performers naturally get lower weights over time
Example Evolution:
Day 1 (Initial):
Trend Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Reversion Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Structure Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
After 50 Signals:
Trend Agent: Beta(28,23) → samples ~0.55 (moderate confidence)
Reversion Agent: Beta(18,33) → samples ~0.35 (underperforming)
Structure Agent: Beta(32,19) → samples ~0.63 (outperforming)
Result: Structure Agent now receives highest weight in consensus
Consensus Requirements by Mode:
Aggressive Mode:
• Minimum 1/3 agents agreeing
• Consensus threshold: 45%
• Use case: More signals, higher risk tolerance
Balanced Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 55%
• Use case: Standard trading
Conservative Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 65%
• Use case: Higher quality, fewer signals
Institutional Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 75%
• Additional: Session quality >0.65, mode adjustment +0.10
• Use case: Highest quality signals only
🌀 INTELLIGENT CHOP DETECTION ENGINE
The Chop Problem:
Most trading losses occur not from being wrong about direction, but from trading in conditions where direction doesn't exist . Choppy, range-bound markets generate false signals from every methodology—trend-following, mean-reversion, and structure-based alike.
AMWT's chop detection engine identifies these low-probability environments before signals fire, preventing the most damaging trades.
Five-Factor Chop Analysis:
Factor 1: ADX Component (25% weight)
ADX (Average Directional Index) measures trend strength regardless of direction.
ADX < 15: Very weak trend (high chop score)
ADX 15-20: Weak trend (moderate chop score)
ADX 20-25: Developing trend (low chop score)
ADX > 25: Strong trend (minimal chop score)
adx_chop = (i_adxThreshold - adx_val) / i_adxThreshold × 100
Why ADX Works: ADX synthesizes +DI and -DI movements. Low ADX means price is moving but not directionally—the definition of chop.
Factor 2: Choppiness Index (25% weight)
The Choppiness Index measures price efficiency using the ratio of ATR sum to price range:
CI = 100 × LOG10(SUM(ATR, n) / (Highest - Lowest)) / LOG10(n)
CI > 61.8: Choppy (range-bound, inefficient movement)
CI < 38.2: Trending (directional, efficient movement)
CI 38.2-61.8: Transitional
chop_idx_score = (ci_val - 38.2) / (61.8 - 38.2) × 100
Why Choppiness Index Works: In trending markets, price covers distance efficiently (low ATR sum relative to range). In choppy markets, price oscillates wildly but goes nowhere (high ATR sum relative to range).
Factor 3: Range Compression (20% weight)
Compares recent range to longer-term range, detecting volatility squeezes:
recent_range = Highest(20) - Lowest(20)
longer_range = Highest(50) - Lowest(50)
compression = 1 - (recent_range / longer_range)
compression > 0.5: Strong squeeze (potential breakout imminent)
compression < 0.2: No compression (normal volatility)
range_compression_score = compression × 100
Why Range Compression Matters: Compression precedes expansion. High compression = market coiling, preparing for move. Signals during compression often fail because the breakout hasn't occurred yet.
Factor 4: Channel Position (15% weight)
Tracks price position within the macro channel:
channel_position = (close - channel_low) / (channel_high - channel_low)
position 0.4-0.6: Center of channel (indecision zone)
position <0.2 or >0.8: Near extremes (potential reversal or breakout)
channel_chop = abs(0.5 - channel_position) < 0.15 ? high_score : low_score
Why Channel Position Matters: Price in the middle of a range is in "no man's land"—equally likely to go either direction. Signals in the channel center have lower probability.
Factor 5: Volume Quality (15% weight)
Assesses volume relative to average:
vol_ratio = volume / SMA(volume, 20)
vol_ratio < 0.7: Low volume (lack of conviction)
vol_ratio 0.7-1.3: Normal volume
vol_ratio > 1.3: High volume (conviction present)
volume_chop = vol_ratio < 0.8 ? (1 - vol_ratio) × 100 : 0
Why Volume Quality Matters: Low volume moves lack institutional participation. These moves are more likely to reverse or stall.
Combined Chop Intensity:
chopIntensity = (adx_chop × 0.25) + (chop_idx_score × 0.25) +
(range_compression_score × 0.20) + (channel_chop × 0.15) +
(volume_chop × i_volumeChopWeight × 0.15)
Regime Classifications:
Based on chop intensity and component analysis:
• Strong Trend (0-20%): ADX >30, clear directional momentum, trade aggressively
• Trending (20-35%): ADX >20, moderate directional bias, trade normally
• Transitioning (35-50%): Mixed signals, regime change possible, reduce size
• Mid-Range (50-60%): Price trapped in channel center, avoid new positions
• Ranging (60-70%): Low ADX, price oscillating within bounds, fade extremes only
• Compression (70-80%): Volatility squeeze, expansion imminent, wait for breakout
• Strong Chop (80-100%): Multiple chop factors aligned, avoid trading entirely
Signal Suppression:
When chop intensity exceeds the configurable threshold (default 80%), signals are suppressed entirely. The dashboard displays "⚠️ CHOP ZONE" with the current regime classification.
Chop Box Visualization:
When chop is detected, AMWT draws a semi-transparent box on the chart showing the chop zone. This visual reminder helps traders avoid entering positions during unfavorable conditions.
💧 LIQUIDITY ANCHORING SYSTEM
The Liquidity Concept:
Markets move from liquidity pool to liquidity pool. Stop losses cluster at predictable locations—below swing lows (buy stops become sell orders when triggered) and above swing highs (sell stops become buy orders when triggered). Institutions know where these clusters are and often engineer moves to trigger them before reversing.
AMWT identifies and tracks these liquidity events, using them as anchors for signal confidence.
Liquidity Event Types:
Type 1: Volume Spikes
Definition: Volume > SMA(volume, 20) × i_volThreshold (default 2.8x)
Interpretation: Sudden volume surge indicates institutional activity
• Near swing low + reversal: Likely accumulation
• Near swing high + reversal: Likely distribution
• With continuation: Institutional conviction in direction
Type 2: Stop Runs (Liquidity Sweeps)
Definition: Price briefly exceeds swing high/low then reverses within N bars
Detection:
• Price breaks above recent swing high (triggering buy stops)
• Then closes back below that high within 3 bars
• Signal: Bullish stop run complete, reversal likely
Or inverse for bearish:
• Price breaks below recent swing low (triggering sell stops)
• Then closes back above that low within 3 bars
• Signal: Bearish stop run complete, reversal likely
Type 3: Absorption Events
Definition: High volume with small candle body
Detection:
• Volume > 2x average
• Candle body < 30% of candle range
• Interpretation: Large orders being filled without moving price
• Implication: Accumulation (at lows) or distribution (at highs)
Type 4: BSL/SSL Pools (Buy-Side/Sell-Side Liquidity)
BSL (Buy-Side Liquidity):
• Cluster of swing highs within ATR proximity
• Stop losses from shorts sit above these highs
• Breaking BSL triggers short covering (fuel for rally)
SSL (Sell-Side Liquidity):
• Cluster of swing lows within ATR proximity
• Stop losses from longs sit below these lows
• Breaking SSL triggers long liquidation (fuel for decline)
Liquidity Pool Mapping:
AMWT continuously scans for and maps liquidity pools:
// Detect swing highs/lows using pivot function
swing_high = ta.pivothigh(high, 5, 5)
swing_low = ta.pivotlow(low, 5, 5)
// Track recent swing points
if not na(swing_high)
bsl_levels.push(swing_high)
if not na(swing_low)
ssl_levels.push(swing_low)
// Display on chart with labels
Confluence Scoring Integration:
When signals fire near identified liquidity events, confluence scoring increases:
• Signal near volume spike: +10% confidence
• Signal after liquidity sweep: +15% confidence
• Signal at BSL/SSL pool: +10% confidence
• Signal aligned with absorption zone: +10% confidence
Why Liquidity Anchoring Matters:
Signals "in a vacuum" have lower probability than signals anchored to institutional activity. A long signal after a liquidity sweep below swing lows has trapped shorts providing fuel. A long signal in the middle of nowhere has no such catalyst.
📊 SIGNAL GRADING SYSTEM
The Quality Problem:
Not all signals are created equal. A signal with 6/6 factors aligned is fundamentally different from a signal with 3/6 factors aligned. Traditional indicators treat them the same. AMWT grades every signal based on confluence.
Confluence Components (100 points total):
1. Bandit Consensus Strength (25 points)
consensus_str = weighted average of agent confidences
score = consensus_str × 25
Example:
Trend Agent: +1 signal, 0.80 confidence, 0.35 weight
Reversion Agent: 0 signal, 0.50 confidence, 0.25 weight
Structure Agent: +1 signal, 0.75 confidence, 0.40 weight
Weighted consensus = (0.80×0.35 + 0×0.25 + 0.75×0.40) / (0.35 + 0.40) = 0.77
Score = 0.77 × 25 = 19.25 points
2. HMM State Confidence (15 points)
score = hmm_confidence × 15
Example:
HMM reports 82% probability of IMPULSE_UP
Score = 0.82 × 15 = 12.3 points
3. Session Quality (15 points)
Session quality varies by time:
• London/NY Overlap: 1.0 (15 points)
• New York Session: 0.95 (14.25 points)
• London Session: 0.70 (10.5 points)
• Asian Session: 0.40 (6 points)
• Off-Hours: 0.30 (4.5 points)
• Weekend: 0.10 (1.5 points)
4. Energy/Participation (10 points)
energy = (realized_vol / avg_vol) × 0.4 + (range / ATR) × 0.35 + (volume / avg_volume) × 0.25
score = min(energy, 1.0) × 10
5. Volume Confirmation (10 points)
if volume > SMA(volume, 20) × 1.5:
score = 10
else if volume > SMA(volume, 20):
score = 5
else:
score = 0
6. Structure Alignment (10 points)
For long signals:
• Bullish structure (HH + HL): 10 points
• Higher low only: 6 points
• Neutral structure: 3 points
• Bearish structure: 0 points
Inverse for short signals
7. Trend Alignment (10 points)
For long signals:
• Price > EMA21 > EMA50: 10 points
• Price > EMA21: 6 points
• Neutral: 3 points
• Against trend: 0 points
8. Entry Trigger Quality (5 points)
• Strong trigger (multiple confirmations): 5 points
• Moderate trigger (single confirmation): 3 points
• Weak trigger (marginal): 1 point
Grade Scale:
Total Score → Grade
85-100 → A+ (Exceptional—all factors aligned)
70-84 → A (Strong—high probability)
55-69 → B (Acceptable—proceed with caution)
Below 55 → C (Marginal—filtered by default)
Grade-Based Signal Brightness:
Signal arrows on the chart have transparency based on grade:
• A+: Full brightness (alpha = 0)
• A: Slight fade (alpha = 15)
• B: Moderate fade (alpha = 35)
• C: Significant fade (alpha = 55)
This visual hierarchy helps traders instantly identify signal quality.
Minimum Grade Filter:
Configurable filter (default: C) sets the minimum grade for signal display:
• Set to "A" for only highest-quality signals
• Set to "B" for moderate selectivity
• Set to "C" for all signals (maximum quantity)
🕐 SESSION INTELLIGENCE
Why Sessions Matter:
Markets behave differently at different times. The London open is fundamentally different from the Asian lunch hour. AMWT incorporates session-aware logic to optimize signal quality.
Session Definitions:
Asian Session (18:00-03:00 ET)
• Characteristics: Lower volatility, range-bound tendency, fewer institutional participants
• Quality Score: 0.40 (40% of peak quality)
• Strategy Implications: Fade extremes, expect ranges, smaller position sizes
• Best For: Mean-reversion setups, accumulation/distribution identification
London Session (03:00-12:00 ET)
• Characteristics: European institutional activity, volatility pickup, trend initiation
• Quality Score: 0.70 (70% of peak quality)
• Strategy Implications: Watch for trend development, breakouts more reliable
• Best For: Initial trend identification, structure breaks
New York Session (08:00-17:00 ET)
• Characteristics: Highest liquidity, US institutional activity, major moves
• Quality Score: 0.95 (95% of peak quality)
• Strategy Implications: Best environment for directional trades
• Best For: Trend continuation, momentum plays
London/NY Overlap (08:00-12:00 ET)
• Characteristics: Peak liquidity, both European and US participants active
• Quality Score: 1.0 (100%—maximum quality)
• Strategy Implications: Highest probability for successful breakouts and trends
• Best For: All signal types—this is prime time
Off-Hours
• Characteristics: Thin liquidity, erratic price action, gaps possible
• Quality Score: 0.30 (30% of peak quality)
• Strategy Implications: Avoid new positions, wider stops if holding
• Best For: Waiting
Smart Weekend Detection:
AMWT properly handles the Sunday evening futures open:
// Traditional (broken):
isWeekend = dayofweek == saturday OR dayofweek == sunday
// AMWT (correct):
anySessionActive = not na(asianTime) or not na(londonTime) or not na(nyTime)
isWeekend = calendarWeekend AND NOT anySessionActive
This ensures Sunday 6pm ET (when futures open) correctly shows "Asian Session" rather than "Weekend."
Session Transition Boosts:
Certain session transitions create trading opportunities:
• Asian → London transition: +15% confidence boost (volatility expansion likely)
• London → Overlap transition: +20% confidence boost (peak liquidity approaching)
• Overlap → NY-only transition: -10% confidence adjustment (liquidity declining)
• Any → Off-Hours transition: Signal suppression recommended
📈 TRADE MANAGEMENT SYSTEM
The Signal Spam Problem:
Many indicators generate signal after signal, creating confusion and overtrading. AMWT implements a complete trade lifecycle management system that prevents signal spam and tracks performance.
Trade Lock Mechanism:
Once a signal fires, the system enters a "trade lock" state:
Trade Lock Duration: Configurable (default 30 bars)
Early Exit Conditions:
• TP3 hit (full target reached)
• Stop Loss hit (trade failed)
• Lock expiration (time-based exit)
During lock:
• No new signals of same type displayed
• Opposite signals can override (reversal)
• Trade status tracked in dashboard
Target Levels:
Each signal generates three profit targets based on ATR:
TP1 (Conservative Target)
• Default: 1.0 × ATR
• Purpose: Quick partial profit, reduce risk
• Action: Take 30-40% off position, move stop to breakeven
TP2 (Standard Target)
• Default: 2.5 × ATR
• Purpose: Main profit target
• Action: Take 40-50% off position, trail stop
TP3 (Extended Target)
• Default: 5.0 × ATR
• Purpose: Runner target for trend days
• Action: Close remaining position or continue trailing
Stop Loss:
• Default: 1.9 × ATR from entry
• Purpose: Define maximum risk
• Placement: Below recent swing low (longs) or above recent swing high (shorts)
Invalidation Level:
Beyond stop loss, AMWT calculates an "invalidation" level where the wave hypothesis dies:
invalidation = entry - (ATR × INVALIDATION_MULT × 1.5)
If price reaches invalidation, the current market interpretation is wrong—not just the trade.
Visual Trade Management:
During active trades, AMWT displays:
• Entry arrow with grade label (▲A+, ▼B, etc.)
• TP1, TP2, TP3 horizontal lines in green
• Stop Loss line in red
• Invalidation line in orange (dashed)
• Progress indicator in dashboard
Persistent Execution Markers:
When targets or stops are hit, permanent markers appear:
• TP hit: Green dot with "TP1"/"TP2"/"TP3" label
• SL hit: Red dot with "SL" label
These persist on the chart for review and statistics.
💰 PERFORMANCE TRACKING & STATISTICS
Tracked Metrics:
• Total Trades: Count of all signals that entered trade lock
• Winning Trades: Signals where at least TP1 was reached before SL
• Losing Trades: Signals where SL was hit before any TP
• Win Rate: Winning / Total × 100%
• Total R Profit: Sum of R-multiples from winning trades
• Total R Loss: Sum of R-multiples from losing trades
• Net R: Total R Profit - Total R Loss
Currency Conversion System:
AMWT can display P&L in multiple formats:
R-Multiple (Default)
• Shows risk-normalized returns
• "Net P&L: +4.2R | 78 trades" means 4.2 times initial risk gained over 78 trades
• Best for comparing across different position sizes
Currency Conversion (USD/EUR/GBP/JPY/INR)
• Converts R-multiples to currency based on:
- Dollar Risk Per Trade (user input)
- Tick Value (user input)
- Selected currency
Example Configuration:
Dollar Risk Per Trade: $100
Display Currency: USD
If Net R = +4.2R
Display: Net P&L: +$420.00 | 78 trades
Ticks
• For futures traders who think in ticks
• Converts based on tick value input
Statistics Reset:
Two reset methods:
1. Toggle Reset
• Turn "Reset Statistics" toggle ON then OFF
• Clears all statistics immediately
2. Date-Based Reset
• Set "Reset After Date" (YYYY-MM-DD format)
• Only trades after this date are counted
• Useful for isolating recent performance
🎨 VISUAL FEATURES
Macro Channel:
Dynamic regression-based channel showing market boundaries:
• Upper/lower bounds calculated from swing pivot linear regression
• Adapts to current market structure
• Shows overall trend direction and potential reversal zones
Chop Boxes:
Semi-transparent overlay during high-chop periods:
• Purple/orange coloring indicates dangerous conditions
• Visual reminder to avoid new positions
Confluence Heat Zones:
Background shading indicating setup quality:
• Darker shading = higher confluence
• Lighter shading = lower confluence
• Helps identify optimal entry timing
EMA Ribbon:
Trend visualization via moving average fill:
• EMA 8/21/50 with gradient fill between
• Green fill when bullish aligned
• Red fill when bearish aligned
• Gray when neutral
Absorption Zone Boxes:
Marks potential accumulation/distribution areas:
• High volume + small body = absorption
• Boxes drawn at these levels
• Often act as support/resistance
Liquidity Pool Lines:
BSL/SSL levels with labels:
• Dashed lines at liquidity clusters
• "BSL" label above swing high clusters
• "SSL" label below swing low clusters
Six Professional Themes:
• Quantum: Deep purples and cyans (default)
• Cyberpunk: Neon pinks and blues
• Professional: Muted grays and greens
• Ocean: Blues and teals
• Matrix: Greens and blacks
• Ember: Oranges and reds
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Learning the System (Week 1)
Goal: Understand AMWT concepts and dashboard interpretation
Setup:
• Signal Mode: Balanced
• Display: All features enabled
• Grade Filter: C (see all signals)
Actions:
• Paper trade ONLY—no real money
• Observe HMM state transitions throughout the day
• Note when agents agree vs disagree
• Watch chop detection engage and disengage
• Track which grades produce winners vs losers
Key Learning Questions:
• How often do A+ signals win vs B signals? (Should see clear difference)
• Which agent tends to be right in current market? (Check dashboard)
• When does chop detection save you from bad trades?
• How do signals near liquidity events perform vs signals in vacuum?
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to your instrument and timeframe
Signal Mode Testing:
• Run 5 days on Aggressive mode (more signals)
• Run 5 days on Conservative mode (fewer signals)
• Compare: Which produces better risk-adjusted returns?
Grade Filter Testing:
• Track A+ only for 20 signals
• Track A and above for 20 signals
• Track B and above for 20 signals
• Compare win rates and expectancy
Chop Threshold Testing:
• Default (80%): Standard filtering
• Try 70%: More aggressive filtering
• Try 90%: Less filtering
• Which produces best results for your instrument?
Phase 3: Strategy Development (Weeks 3-4)
Goal: Develop personal trading rules based on system signals
Position Sizing by Grade:
• A+ grade: 100% position size
• A grade: 75% position size
• B grade: 50% position size
• C grade: 25% position size (or skip)
Session-Based Rules:
• London/NY Overlap: Take all A/A+ signals
• NY Session: Take all A+ signals, selective on A
• Asian Session: Only A+ signals with extra confirmation
• Off-Hours: No new positions
Chop Zone Rules:
• Chop >70%: Reduce position size 50%
• Chop >80%: No new positions
• Chop <50%: Full position size allowed
Phase 4: Live Micro-Sizing (Month 2)
Goal: Validate paper trading results with minimal risk
Setup:
• 10-20% of intended full position size
• Take ONLY A+ signals initially
• Follow trade management religiously
Tracking:
• Log every trade: Entry, Exit, Grade, HMM State, Chop Level, Agent Consensus
• Calculate: Win rate by grade, by session, by chop level
• Compare to paper trading (should be within 15%)
Red Flags:
• Win rate diverges significantly from paper trading: Execution issues
• Consistent losses during certain sessions: Adjust session rules
• Losses cluster when specific agent dominates: Review that agent's logic
Phase 5: Scaling Up (Months 3-6)
Goal: Gradually increase to full position size
Progression:
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
Scale-Up Requirements:
• Minimum 30 trades at current size
• Win rate ≥50%
• Net R positive
• No revenge trading incidents
• Emotional control maintained
💡 DEVELOPMENT INSIGHTS
Why HMM Over Simple Indicators:
Early versions used standard indicators (RSI >70 = overbought, etc.). Win rates hovered at 52-55%. The problem: indicators don't capture state. RSI can stay "overbought" for weeks in a strong trend.
The insight: markets exist in states, and state persistence matters more than indicator levels. Implementing HMM with state transition probabilities increased signal quality significantly. The system now knows not just "RSI is high" but "we're in IMPULSE_UP state with 70% probability of staying in IMPULSE_UP."
The Multi-Agent Evolution:
Original version used a single analytical methodology—trend-following. Performance was inconsistent: great in trends, destroyed in ranges. Added mean-reversion agent: now it was inconsistent the other way.
The breakthrough: use multiple agents and let the system learn which works . Thompson Sampling wasn't the first attempt—tried simple averaging, voting, even hard-coded regime switching. Thompson Sampling won because it's mathematically optimal and automatically adapts without manual regime detection.
Chop Detection Revelation:
Chop detection was added almost as an afterthought. "Let's filter out obviously bad conditions." Testing revealed it was the most impactful single feature. Filtering chop zones reduced losing trades by 35% while only reducing total signals by 20%. The insight: avoiding bad trades matters more than finding good ones.
Liquidity Anchoring Discovery:
Watched hundreds of trades. Noticed pattern: signals that fired after liquidity events (stop runs, volume spikes) had significantly higher win rates than signals in quiet markets. Implemented liquidity detection and anchoring. Win rate on liquidity-anchored signals: 68% vs 52% on non-anchored signals.
The Grade System Impact:
Early system had binary signals (fire or don't fire). Adding grading transformed it. Traders could finally match position size to signal quality. A+ signals deserved full size; C signals deserved caution. Just implementing grade-based sizing improved portfolio Sharpe ratio by 0.3.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What AMWT Is NOT:
• NOT a Holy Grail : No system wins every trade. AMWT improves probability, not certainty.
• NOT Fully Automated : AMWT provides signals and analysis; execution requires human judgment.
• NOT News-Proof : Exogenous shocks (FOMC surprises, geopolitical events) invalidate all technical analysis.
• NOT for Scalping : HMM state estimation needs time to develop. Sub-minute timeframes are not appropriate.
Core Assumptions:
1. Markets Have States : Assumes markets transition between identifiable regimes. Violation: Random walk markets with no regime structure.
2. States Are Inferable : Assumes observable indicators reveal hidden states. Violation: Market manipulation creating false signals.
3. History Informs Future : Assumes past agent performance predicts future performance. Violation: Regime changes that invalidate historical patterns.
4. Liquidity Events Matter : Assumes institutional activity creates predictable patterns. Violation: Markets with no institutional participation.
Performs Best On:
• Liquid Futures : ES, NQ, MNQ, MES, CL, GC
• Major Forex Pairs : EUR/USD, GBP/USD, USD/JPY
• Large-Cap Stocks : AAPL, MSFT, TSLA, NVDA (>$5B market cap)
• Liquid Crypto : BTC, ETH on major exchanges
Performs Poorly On:
• Illiquid Instruments : Low volume stocks, exotic pairs
• Very Low Timeframes : Sub-5-minute charts (noise overwhelms signal)
• Binary Event Days : Earnings, FDA approvals, court rulings
• Manipulated Markets : Penny stocks, low-cap altcoins
Known Weaknesses:
• Warmup Period : HMM needs ~50 bars to initialize properly. Early signals may be unreliable.
• Regime Change Lag : Thompson Sampling adapts over time, not instantly. Sudden regime changes may cause short-term underperformance.
• Complexity : More parameters than simple indicators. Requires understanding to use effectively.
⚠️ RISK DISCLOSURE
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Adaptive Market Wave Theory, while based on rigorous mathematical frameworks including Hidden Markov Models and multi-armed bandit algorithms, does not guarantee profits and can result in significant losses.
AMWT's methodologies—HMM state estimation, Thompson Sampling agent selection, and confluence-based grading—have theoretical foundations but past performance is not indicative of future results.
Hidden Markov Model assumptions may not hold during:
• Major news events disrupting normal market behavior
• Flash crashes or circuit breaker events
• Low liquidity periods with erratic price action
• Algorithmic manipulation or spoofing
Multi-agent consensus assumes independent analytical perspectives provide edge. Market conditions change. Edges that existed historically can diminish or disappear.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively before risking capital. Start with micro position sizing.
Never risk more than you can afford to lose completely. Use proper position sizing. Implement stop losses without exception.
By using this indicator, you acknowledge these risks and accept full responsibility for all trading decisions and outcomes.
"Elliott Wave was a first-order approximation of market phase behavior. AMWT is the second—probabilistic, adaptive, and accountable."
Initial Public Release
Core Engine:
• True Hidden Markov Model with online Baum-Welch learning
• Viterbi algorithm for optimal state sequence decoding
• 6-state market regime classification
Agent System:
• 3-Bandit consensus (Trend, Reversion, Structure)
• Thompson Sampling with true Beta distribution sampling
• Adaptive weight learning based on performance
Signal Generation:
• Quality-based confluence grading (A+/A/B/C)
• Four signal modes (Aggressive/Balanced/Conservative/Institutional)
• Grade-based visual brightness
Chop Detection:
• 5-factor analysis (ADX, Choppiness Index, Range Compression, Channel Position, Volume)
• 7 regime classifications
• Configurable signal suppression threshold
Liquidity:
• Volume spike detection
• Stop run (liquidity sweep) identification
• BSL/SSL pool mapping
• Absorption zone detection
Trade Management:
• Trade lock with configurable duration
• TP1/TP2/TP3 targets
• ATR-based stop loss
• Persistent execution markers
Session Intelligence:
• Asian/London/NY/Overlap detection
• Smart weekend handling (Sunday futures open)
• Session quality scoring
Performance:
• Statistics tracking with reset functionality
• 7 currency display modes
• Win rate and Net R calculation
Visuals:
• Macro channel with linear regression
• Chop boxes
• EMA ribbon
• Liquidity pool lines
• 6 professional themes
Dashboards:
• Main Dashboard: Market State, Consensus, Trade Status, Statistics
📋 AMWT vs AMWT-PRO:
This version includes all core AMWT functionality:
✓ Full Hidden Markov Model state estimation
✓ 3-Bandit Thompson Sampling consensus system
✓ Complete 5-factor chop detection engine
✓ All four signal modes
✓ Full trade management with TP/SL tracking
✓ Main dashboard with complete statistics
✓ All visual features (channels, zones, pools)
✓ Identical signal generation to PRO
✓ Six professional themes
✓ Full alert system
The PRO version adds the AMWT Advisor panel—a secondary dashboard providing:
• Real-time Market Pulse situation assessment
• Agent Matrix visualization (individual agent votes)
• Structure analysis breakdown
• "Watch For" upcoming setups
• Action Command coaching
Both versions generate identical signals . The Advisor provides additional guidance for interpreting those signals.
Taking you to school. - Dskyz, Trade with probability. Trade with consensus. Trade with AMWT.
Vortex Trend Matrix [JOAT]Vortex Trend Matrix - Multi-Factor Trend Confluence System
Introduction and Purpose
Vortex Trend Matrix is an open-source overlay indicator that combines Ichimoku-style equilibrium analysis with the Vortex Indicator to create a comprehensive trend confluence system. The core problem this indicator solves is that single trend indicators often give conflicting signals. Price might be above a moving average but momentum might be weakening.
This indicator addresses that by combining five different trend factors into a single composite score, making it easy to identify when multiple factors align for high-probability trend trades.
Why These Components Work Together
Each component measures trend from a different perspective:
1. Cloud Position - Price above/below the equilibrium cloud indicates overall trend bias. The cloud acts as dynamic support/resistance.
2. TK Relationship - Conversion line vs Base line (like Tenkan/Kijun in Ichimoku). Conversion above Base = bullish momentum.
3. Lagging Span - Current price compared to price N bars ago. Confirms whether current move has follow-through.
4. Vortex Indicator - VI+ vs VI- measures directional movement strength. Provides momentum confirmation.
5. Base Direction - Whether the base line is rising or falling. Indicates medium-term trend direction.
How the Trend Score Works
float trendScore = 0.0
// Cloud position (+2/-2)
trendScore += aboveCloud ? 2.0 : belowCloud ? -2.0 : 0.0
// TK relationship (+1/-1)
trendScore += conversionLine > baseLine ? 1.0 : conversionLine < baseLine ? -1.0 : 0.0
// Lagging span (+1/-1)
trendScore += laggingBull ? 1.0 : laggingBear ? -1.0 : 0.0
// Vortex (+1.5/-1.5)
trendScore += vortexBull ? 1.5 : vortexBear ? -1.5 : 0.0
// Base direction (+0.5/-0.5)
trendScore += baseDirection * 0.5
Score ranges from approximately -6 to +6:
- +4 or higher = STRONG BULL
- +2 to +4 = BULL
- -2 to +2 = NEUTRAL
- -4 to -2 = BEAR
- -4 or lower = STRONG BEAR
Signal Types
TK Cross Up/Down - Conversion line crosses Base line (momentum shift)
Base Direction Change - Base line changes direction (medium-term shift)
Strong Bull/Bear Trend - Score reaches +4/-4 (high confluence)
Dashboard Information
Trend - Overall status with composite score
Cloud - Price position (ABOVE/BELOW/INSIDE)
TK Cross - Conversion vs Base relationship
Lagging - Lagging span bias
Vortex - VI+/VI- relationship
VI+/VI- - Individual vortex values
How to Use This Indicator
For Trend Following:
1. Enter long when trend score reaches +4 or higher (STRONG BULL)
2. Enter short when trend score reaches -4 or lower (STRONG BEAR)
3. Use cloud as dynamic support/resistance for entries
For Momentum Timing:
1. Watch for TK Cross signals for entry timing
2. Base direction changes indicate medium-term shifts
3. Vortex confirmation adds conviction
For Risk Management:
1. Exit when trend score drops to neutral
2. Use cloud edges as stop-loss references
3. Reduce position when score weakens
Input Parameters
Conversion Period (9) - Fast equilibrium line
Base Period (26) - Slow equilibrium line
Lead Span Period (52) - Cloud projection period
Displacement (26) - Cloud and lagging span offset
Vortex Period (14) - Period for vortex calculation
VI+ Strength (1.10) - Threshold for strong bullish vortex
VI- Strength (0.90) - Threshold for strong bearish vortex
Timeframe Recommendations
4H-Daily: Best for equilibrium-based analysis
1H: Good for intraday trend following
Lower timeframes may require adjusted periods
Limitations
Equilibrium calculations have inherent lag
Cloud displacement means signals are delayed
Works best in trending markets
May whipsaw in ranging conditions
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Trend analysis does not guarantee profitable trades. Always use proper risk management.
- Made with passion by officialjackofalltrades
Vector Volume Delta Candles [Capitalize Labs]Vector Volume Delta Candles is a visual market analysis indicator designed to highlight relative volume activity directly on price candles. The indicator classifies candles based on volume intensity and price range expansion compared to recent historical data and applies color coding for visual context only.
This indicator functions strictly as a candle-coloring overlay. It does not generate trade signals, entries, exits, alerts, forecasts, or predictions. No automated trading decisions are made or implied.
How it works
Evaluates current candle volume relative to a moving average of recent volume
Optionally incorporates a volume × price range comparison to identify unusually active candles
Classifies candles as:
Climactic when volume activity is significantly above recent norms
Elevated when volume is above average but not climactic
Applies configurable colors to candles based on classification and candle direction
Includes optional color customization and the ability to revert candle coloring
Uses historical data only and does not repaint or reference future bars
Intended use
This indicator is intended for educational and analytical purposes only. It may be used as a visual reference alongside other tools or discretionary analysis methods. All interpretations are subjective and must be evaluated independently by the user.
No assumptions are made regarding market direction, probability, or outcome.
Disclaimer and Risk Notice
This indicator is provided strictly for educational and informational purposes. It is not intended to constitute financial advice, investment recommendations, or an offer or solicitation to buy or sell any financial instrument or security.
Financial markets involve substantial risk, and trading decisions can result in losses that exceed initial expectations. Market conditions can change rapidly due to volatility, liquidity constraints, economic events, or other external factors. No representation is made that the use of this indicator will result in profitable outcomes or that any interpretation of its output will be accurate or complete in all market conditions.
This indicator does not take into account individual financial circumstances, objectives, or risk tolerance. Users are solely responsible for evaluating the suitability of any analysis or methodology derived from this tool and for managing their own risk, position sizing, and execution decisions.
All calculations are based on historical price and volume data. Historical or simulated behavior should not be interpreted as a guarantee or prediction of future performance. The absence of repainting or lookahead logic does not imply predictive capability.
By using this indicator, the user acknowledges that all trading decisions are made at their own discretion and risk, and that the creator assumes no responsibility or liability for any losses, damages, or outcomes arising from its use.
Pulse Volume Commitment [JOAT]
Pulse Volume Commitment - Three-Dimensional Momentum Analysis
Introduction and Purpose
Pulse Volume Commitment is an open-source oscillator indicator that analyzes price action through three distinct dimensions: Quantity (candle count), Quality (body structure), and Commitment (volume-weighted quality). The core problem this indicator solves is that simple bullish/bearish candle counts miss important context. A market can have more green candles but still be weak if those candles have small bodies and low volume.
This indicator addresses that by requiring all three dimensions to align before generating strong signals, filtering out weak moves that lack conviction.
Why These Three Dimensions Work Together
Each dimension measures a different aspect of market conviction:
1. Quantity - Counts bullish vs bearish candles over the lookback period. Tells you WHO is winning the candle count battle.
2. Quality - Scores candles by body size relative to total range. Full-bodied candles (small wicks) indicate stronger conviction than doji-like candles. Tells you HOW decisively price is moving.
3. Commitment - Weights quality scores by volume. High-quality candles on high volume indicate institutional participation. Tells you WHETHER smart money is involved.
When all three align (e.g., more bullish candles + bullish quality + bullish commitment), the signal is significantly more reliable.
How the Calculations Work
Quantity Analysis:
int greenCount = 0
int redCount = 0
for i = 0 to lookbackPeriod - 1
if close > open
greenCount += 1
if close < open
redCount += 1
bool quantityBull = greenCount > redCount
Quality Analysis (body-to-range scoring):
for i = 0 to lookbackPeriod - 1
float candleBody = close - open // Signed (positive = bull)
float candleRange = high - low
float bodyQuality = candleRange > 0 ? (candleBody / candleRange * 100) * candleRange : 0.0
sumBodyQuality += bodyQuality
bool qualityBull = sumBodyQuality > 0
Signal Types
FULL BULL - All three dimensions bullish (Quantity + Quality + Commitment)
FULL BEAR - All three dimensions bearish
LEAN BULL/BEAR - 2 of 3 dimensions agree
MIXED - No clear consensus
STRONG BUY/SELL - Full confluence + ADX confirms trending market
ADX Integration
The indicator includes ADX (Average Directional Index) to filter signals:
- ADX >= 20 = TRENDING market (signals more reliable)
- ADX < 20 = RANGING market (signals may whipsaw)
Strong signals only trigger when full confluence occurs in a trending environment.
Dashboard Information
Quantity - BULL/BEAR/FLAT with green/red candle ratio
Quality - Directional bias based on body quality scoring
Commit - Volume-weighted commitment reading
ADX - Trend strength (TRENDING/RANGING)
Signal - Confluence status (FULL BULL/FULL BEAR/LEAN/MIXED)
Action - STRONG BUY/STRONG SELL/WAIT
How to Use This Indicator
For High-Conviction Entries:
1. Wait for FULL BULL or FULL BEAR confluence
2. Confirm ADX shows TRENDING
3. Enter when Action shows STRONG BUY or STRONG SELL
For Filtering Weak Setups:
1. Avoid entries when signal shows MIXED
2. Be cautious when ADX shows RANGING
3. Require at least 2 of 3 dimensions to agree
For Divergence Analysis:
1. Watch for Quantity bullish but Commitment bearish (distribution)
2. Watch for Quantity bearish but Commitment bullish (accumulation)
Input Parameters
Lookback Period (9) - Bars to analyze for all three dimensions
ADX Smoothing (14) - Period for ADX calculation
ADX DI Length (14) - Period for directional indicators
Timeframe Recommendations
15m-1H: Good for intraday momentum analysis
4H-Daily: Best for swing trading confluence
Lookback period may need adjustment for different timeframes
Limitations
Lookback period affects signal responsiveness vs reliability tradeoff
Volume data quality varies by exchange
ADX filter may cause missed entries in early trends
Works best on liquid instruments with consistent volume
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Confluence signals do not guarantee profitable trades. Always use proper risk management.
- Made with passion by officialjackofalltrades
SPX Iron Fly Session TrackerOverview
This indicator provides visual tracking for iron fly option structures designed for SPX 0-day-to-expiration (0DTE) intraday trading. It implements a two-phase position management system that adapts to different market conditions throughout the trading day.
This is a visualization and tracking tool only. It does not execute trades, access real options data, or calculate actual profit and loss. All displayed positions are theoretical representations based on underlying price movement.
Strategy Goal and Context
The Core Objective:
The strategy aims to have SPX price expire within your iron fly positions at end of day. When price expires inside a fly's profit zone (between the wings), that position captures maximum premium. The challenge is that price moves throughout the day, so static positioning rarely succeeds.
The Solution: Active Management
Rather than setting positions and hoping price cooperates, this approach continuously manages and repositions flies to keep price centered within your profit zones. As SPX drifts during the trading session, you add new flies at current price levels and close flies that price has moved away from.
The Goal: Multiple Profitable Expirations
By session end, you want as many flies as possible to have price expire within their center zones. This requires:
Adding new flies as price moves away from existing positions
Closing flies when price crosses beyond their optimal range
Building layered coverage in the afternoon to increase probability of capture
Adapting wing widths to time of day and volatility
The Reality: Capital and Time Intensive
This is not a passive strategy. Successful implementation requires:
Substantial capital (each fly requires margin, multiple flies compound this)
Active monitoring throughout trading sessions
Quick decision-making as positions trigger
Multiple position adjustments per session
Disciplined adherence to management rules
How This Indicator Helps:
For backtesting:
Use replay mode to study how positions would have managed on historical sessions
Test different parameter combinations to find optimal settings
Observe position behavior during various market conditions
Understand timing and frequency of position adds and closes
Validate whether your capital can support the required position count
For live session support:
Real-time visual tracking shows current position coverage
Alerts notify you immediately when new positions should be added
Position closure alerts help you manage exits promptly
Reference strike tracking shows where you're measuring movement from
History table provides audit trail of all position activity
The indicator handles the complex tracking and rule application, allowing you to focus on execution and risk management.
Key Use Cases
1. Replay Mode - Backtest and Study
Use TradingView's replay feature to validate the strategy on historical sessions:
Step through past SPX sessions bar-by-bar
See exactly when positions would have opened and closed
Count how many flies would have expired profitably
Analyze different parameter settings on the same historical data
Study position behavior during trending vs ranging conditions
Calculate approximate capital requirements for your setup
Refine your parameters before risking real capital
2. Live Session Alerts
Set up real-time notifications for active trading sessions:
Get alerted immediately when new positions trigger
Receive notifications when positions close
Alerts include strike level, wing width, and closure reason
Works on mobile, desktop, email, or webhook
Never miss a position signal during active trading
Maintain awareness even when away from screens briefly
3. Fully Customizable Parameters
Adapt every aspect to your risk tolerance and capital:
Adjust trigger distances for more or fewer position adds
Modify wing widths for different volatility environments
Change session timing to match your trading schedule
Set maximum concurrent positions to your capital limits
Fine-tune spacing to match available strike increments
Iron Fly Structure
An iron fly is a neutral options strategy with four legs:
- Short 1 ATM Call
- Short 1 ATM Put
- Long 1 OTM Call (upper wing protection)
- Long 1 OTM Put (lower wing protection)
The structure creates a defined risk zone. Maximum profit occurs when price expires at the center strike. Loss increases as price moves toward the wings (breakeven points). Maximum loss is defined and occurs beyond the wings.
Expiration Goal:
You want SPX to close inside the fly's wings. If SPX expires at the strike, you capture maximum premium. If SPX expires between the strike and either wing, you still profit (reduced). If SPX expires beyond the wings, you realize a loss (but it's defined and limited by the wings).
Two-Phase Management System
The indicator tracks positions across two distinct trading phases with different management rules:
Phase 1: TWO_GLASS - Morning Session (Default 10am-1pm ET)
Conservative positioning with active repositioning:
- Trigger new positions when price moves 7.5 points from reference strike (configurable)
- Maintain maximum 2 concurrent positions (configurable)
- 10-point spacing between position strikes (configurable)
- 40-point wing width (configurable)
- Exit rule: When two positions are active and price crosses to one strike level, close the OTHER position
This phase uses a "follow the price" approach. You're not trying to stack multiple positions yet - you're maintaining one or two flies centered on wherever price currently is. As price drifts, you add a new fly at the current level and close the old one when price moves too far away.
Phase 2: THREE_GLASS - Afternoon Session (Default 1pm-4pm ET)
Accumulation mode with layered coverage:
- Trigger new positions every 2.5 points of price movement (configurable)
- Maintain maximum 6 concurrent positions (configurable)
- 5-point spacing between strikes (configurable)
- 20-point wings early, reducing to 10 points after 3pm (configurable)
- Exit rule: Positions only close when price reaches wing extremes
This phase builds a stacked profit zone. Instead of swapping positions, you accumulate multiple flies as price moves. The goal is to have several flies active at expiration, creating a wider net to capture price. Tighter spacing and more frequent triggers create this layered coverage.
Why Two Different Phases?
Morning (Phase 1):
Earlier in the day, price has more time to move substantially. Maintaining many concurrent positions is riskier because price could trend and hit multiple wings. The strategy uses selective positioning with wider wings and active replacement.
Afternoon (Phase 2):
Closer to expiration, price movements typically compress. Time for large moves decreases. The strategy shifts to accumulation, building a net of positions to increase probability that final expiration price falls within at least one (ideally several) of your flies. Tighter wings and more positions become appropriate.
Exit Mechanisms
Strike Cross Exit (Phase 1 Only)
When two positions are active, if price moves to or beyond one position's strike level, the OTHER position closes. This keeps your coverage centered on current price action rather than maintaining positions price has moved away from.
Example: Flies at 5900 and 5910 are open. Price moves to 5910. The fly at 5900 closes because price has moved to the 5910 level. You're now positioned at current price (5910) rather than maintaining coverage at old price (5900).
Wing Extreme Exit (Both Phases)
Any position closes immediately when price touches its upper or lower wing boundary. This represents the breakeven/maximum loss point, so the position is closed to prevent further deterioration.
Dynamic Wing Adjustment
Wing widths automatically adjust based on time of day:
- Phase 1 (Morning): 40 points (customizable)
- Phase 2 Early (1pm-3pm): 20 points (customizable)
- Phase 2 Late (3pm-4pm): 10 points (customizable)
This progressive tightening reflects decreasing price movement potential as expiration approaches. Wider wings earlier provide more protection when price could move substantially. Tighter wings later allow more precise positioning when price movements typically compress.
All values are fully adjustable to match your risk parameters and observed market volatility.
Customization Guide
Every parameter can be modified to suit your trading style, risk tolerance, and capital:
Session Timing
- TWO_GLASS Start Hour: When Phase 1 begins (default: 10am ET)
- THREE_GLASS Start Hour: When Phase 2 begins (default: 1pm ET)
- Wing Width Change Hour: When wings tighten (default: 3pm ET)
- Session End Hour: When tracking stops (default: 4pm ET)
Phase 1 Parameters (Fully Adjustable)
- Trigger Distance: How far price must move from reference strike to add new position (default: 7.5, range: 0.1+)
- Fly Spacing: Distance between position strikes (default: 10, range: 1.0+)
- Wing Width: Distance from strike to wings (default: 40, range: 5.0+)
- Max Flies: Maximum concurrent positions (default: 2, range: 1-10)
Phase 2 Early Parameters (Fully Adjustable)
- Trigger Distance: Movement needed to add new position (default: 2.5, range: 0.1+)
- Fly Spacing: Distance between strikes (default: 5, range: 1.0+)
- Wing Width: Strike to wing distance (default: 20, range: 5.0+)
- Max Flies: Maximum concurrent positions (default: 6, range: 1-20)
Phase 2 Late Parameters
- Wing Width: Reduced width after 3pm (default: 10, range: 5.0+)
General Settings
- Strike Rounding: Round strikes to nearest multiple (default: 5.0, range: 1.0+)
- Bars Before Check: Bars to wait before allowing closure (default: 2, prevents premature exits)
Display Options
- Show History Table: Toggle detailed position log (default: on)
- History Table Rows: Number of positions displayed (default: 15, range: 5-30)
Alert Settings
- Enable Alerts: Toggle notifications for opens/closes (default: on)
How to Use
For Backtesting in Replay Mode:
Select a historical SPX trading session
Apply indicator to 1-5 minute timeframe
Configure your preferred parameters
Activate TradingView's replay feature
Play through the session (step-by-step or continuous)
Observe when positions open (green boxes appear)
Watch position closures (boxes turn gray)
Count how many flies would have expired with price inside (green at session end)
Note total number of position adds throughout session
Calculate approximate capital needed (positions × margin per fly)
Test different parameter combinations on same historical data
Study position behavior during trending vs ranging sessions
For Live Trading Sessions:
Apply indicator to SPX on 1-5 minute timeframe
Configure parameters based on your backtest results
Create alerts for "Iron Fly Opened" and "Iron Fly Closed"
Set alert frequency to "Once Per Bar Close"
Choose notification method (popup, mobile app, email, webhook)
Monitor the status table (top-right) for current session and reference strike
Review history table (bottom-right) for position log with timestamps
When alert triggers, use visual cues to manually place actual option orders
Execute position adds and closes as indicated by the tracker
Visual Interpretation:
Green boxes = Active positions (theoretical profit zones)
White lines (Phase 1) / Aqua lines (Phase 2) = Strike levels
Red/Blue dotted lines = Wing boundaries (breakeven/risk limits)
Gray boxes = Closed positions (historical reference)
Current SPX price line = Shows where price is relative to positions
Top-right table = Current session status, reference strike, open/closed counts
Bottom-right table = Complete position history with open/close timestamps
Alert System Details
The indicator generates detailed alert messages for position management:
Position Opened:
- Strike level where fly should be placed
- Wing width (±points from strike)
- Session phase (Phase 1 or Phase 2)
- Alert format example: "Iron Fly OPENED | Strike: 5900 | Wings: ±40 | Session: TWO_GLASS"
Position Closed:
- Strike level of fly being closed
- Closure reason (strike cross, wing extreme, etc.)
- Session phase
- Alert format example: "Iron Fly CLOSED | Strike: 5900 | Reason: Price crossed to lower fly | Session: TWO_GLASS"
Configure alerts once before market open, then receive automatic notifications as positions trigger throughout the trading session.
Parameter Optimization Suggestions
For Higher Volatility Environments:
- Increase trigger distances (e.g., Phase 1: 10-15 points, Phase 2: 3-5 points)
- Widen wing widths (e.g., Phase 1: 50-60 points, Phase 2: 25-30 points early, 15-20 late)
- Increase strike spacing to reduce position frequency
For Lower Volatility Environments:
- Decrease trigger distances (e.g., Phase 1: 5-7 points, Phase 2: 1.5-2 points)
- Tighten wing widths (e.g., Phase 1: 30-35 points, Phase 2: 15-18 points early, 8-10 late)
- Reduce strike spacing for more granular coverage
For Conservative Risk Management:
- Reduce maximum concurrent positions (Phase 1: 1, Phase 2: 3-4)
- Widen wing widths for more breathing room
- Increase bars before check to avoid whipsaws
- Use wider trigger distances to reduce position frequency
For Aggressive Positioning:
- Increase maximum concurrent positions (Phase 2: 8-10)
- Tighten trigger distances for more frequent adds
- Reduce bars before check for faster responses
- Use tighter spacing to create denser coverage
Capital Considerations:
Remember that each fly requires margin. If Phase 2 allows 6 concurrent flies and each requires $10,000 margin, you need $60,000 in available capital just for position requirements, plus additional cushion for adverse movement.
Use replay mode to count maximum concurrent positions that would have occurred on historical sessions with your parameters, then calculate total capital needed.
Practical Application
This tool provides visual guidance and management support. To implement the strategy:
Backtest thoroughly in replay mode first
Validate capital requirements for your parameter settings
Confirm you can actively monitor positions during trading hours
Use displayed positions as reference for manual order placement
Match indicator parameters to your actual option contracts
Account for real-world factors: commissions, slippage, bid-ask spreads, option availability
Implement proper position sizing based on available capital
Set up alerts before market open to catch all signals
Execute actual trades manually in your brokerage platform
Track actual results versus indicator expectations
Important Limitations
Theoretical tracking only - not an automated trading system
No access to real option prices, Greeks, or implied volatility
No profit/loss calculations or risk metrics
Does not account for time decay (theta), delta, gamma, vega changes
Assumes continuous price action - gaps or halts not handled
Designed for 0DTE SPX options - not suitable for other timeframes or instruments
Assumes option availability at all strike levels - may not reflect reality
Does not model actual option bid/ask spreads or liquidity
Assumes instant execution at desired strikes - slippage not considered
Historical replay shows theoretical behavior only - actual market conditions may differ
Does not adjust for changing implied volatility throughout session
Position count and timing may not match what's executable in real markets
Capital and Time Requirements
This strategy is resource-intensive:
Capital Requirements:
Each iron fly requires margin (varies by broker and strike width)
Multiple concurrent positions multiply capital needs
Example: 6 flies at $10,000 each = $60,000 minimum
Additional cushion needed for adverse movement
Pattern Day Trader rules may apply (requires $25,000 minimum)
Time Requirements:
Active monitoring during trading hours (typically 10am-4pm ET)
Quick response to position add/close signals
Multiple position adjustments per session possible
Cannot be passive or set-and-forget
Requires ability to place orders promptly when alerted
Use replay mode to understand the commitment level before attempting live implementation.
Risk Considerations
Iron fly trading involves substantial risk. This indicator provides visualization and management support only - it does not constitute financial advice or trading recommendations.
Options trading can result in total loss of capital. The indicator's theoretical positions do not reflect actual trading results. Backtest analysis and historical visualization do not guarantee similar future outcomes. Multiple concurrent positions multiply both profit potential and loss risk.
Always conduct independent research, understand all risks, validate capital requirements, and never trade with funds you cannot afford to lose. Consider starting with paper trading to validate execution capability before risking real capital.
Technical Notes
The indicator uses price-based triggers only. It does not:
Connect to options data feeds
Calculate theoretical option values or Greeks
Execute trades automatically
Provide specific trading signals or recommendations
Account for option-specific factors (implied volatility, time decay, bid/ask spreads)
All displayed information represents theoretical position placement based solely on underlying SPX price movement and user-configured parameters. The tool helps visualize the management framework but requires the trader to handle all actual execution and risk management decisions.
This is an educational and analytical tool for understanding iron fly position management concepts. It requires active interpretation, backtesting validation, and manual implementation by the user.
ORB Breakout Strategy with VWAP and Volume FiltersOverview
This strategy implements the classic Opening Range Breakout (ORB) methodology, a well-documented approach in trading literature that has been used by institutional and retail traders for decades. The strategy identifies the high and low of the first 15 minutes of the trading session, then trades breakouts with defined risk management.
This implementation includes multiple customizable filters (VWAP, Volume, Candle Strength) that traders can enable, disable, and tune to find configurations that work for their specific markets and trading style.
How It Works
Opening Range Calculation
The strategy captures the high and low of the first N bars after the session open (default: 3 bars on a 5-minute chart = 15 minutes). These levels become the breakout triggers for the session.
Entry Logic
Long Entry: When a bar closes above the ORB High and all enabled filters pass
Short Entry: When a bar closes below the ORB Low and all enabled filters pass
Exit Logic
Take Profit: Configurable multiple of the ORB range (default: 1x = full range beyond breakout level)
Stop Loss: Opposite side of the ORB range
Breakeven: Optional stop adjustment to entry price when trade reaches configurable profit threshold
Session Close: All positions automatically closed at end of trading session
Configurable Filters
All filters can be independently enabled or disabled:
1. VWAP Filter
Requires price above/below session-anchored VWAP
Requires VWAP slope confirmation (configurable lookback and minimum slope)
Purpose: Align trades with intraday trend direction
2. Volume Filter
Requires minimum volume on the breakout bar
Purpose: Confirm institutional participation in the breakout
3. Candle Strength Filter
Requires close in upper/lower portion of the bar range
Purpose: Filter out weak breakouts with poor conviction
Strategy Properties
Initial Capital - $50.000USD
Position Size - 1 contract (fixed)
Commission - $4.00 per contract
Slippage - 2 ticks
Margin - 1%
Pyramiding - Disabled
Backtest Results (NQ)
Recent Performance (Jan 2025 - Jan 2026)
Total Trades - 243
Win Rate - 39.09%
Profit Factor - 1.03
Net P&L - $3,581 (+7.16%)
Max Drawdown - $25,447 (39.96%)
Long-Term Performance (2010 - 2026)
Total Trades - 1699
Win Rate - 37.61%
Profit Factor - 0.756
Net P&L - ($49,632) (-99.26%)
Max Drawdown - $50,262 (99.27%)
Important: Long-term results show negative expectancy with default settings. This strategy is published as a research framework, not a ready-to-trade system. Users are encouraged to experiment with different configurations to find their edge.
Settings Guide
Main Settings
ORB Bars: Number of bars for opening range (3 = 15 min on 5-min chart)
Trading Session: Time window for trading (e.g., 0930-1200 for morning only)
Timezone: Your market's timezone
Take Profit: Multiple of ORB range for target
Breakeven Trigger: Distance to move stop to entry
Max Trades Per Day: Daily trade limit
VWAP Filter
Use VWAP Filter: Enable/disable
VWAP Slope Lookback: Bars to measure VWAP direction
Min VWAP Slope: Minimum slope threshold
Volume Filter
Use Volume Filter: Enable/disable
Min Breakout
Volume: Minimum contracts required
Candle Strength Filter
Use Candle Strength Filter: Enable/disable
Min Candle Strength: Required close position (0.7 = top/bottom 30%)
Research Suggestions
This strategy provides a foundation for exploring ORB-based approaches. Consider testing:
Different ORB periods: 5, 10, 15, or 30 minutes
Session variations: Morning only (0930-1200), afternoon, or full day
Direction bias: Long-only or short-only based on daily trend
Filter combinations: Different mixes of VWAP, volume, and candle filters
Take profit ratios: 0.5x, 1x, 1.5x, or 2x ORB range
Market regimes: Performance may vary in trending vs ranging markets
Different instruments: Test on ES, NQ, MNQ, or other futures
Visual Elements
Orange Background: ORB forming period
Green Background: Active trading session
Green Line: ORB High level
Red Line: ORB Low level
VWAP Line: Green = upslope, Red = downslope, Gray = flat
White Line: Trade entry price
Lime Line: Take profit level
Red Line: Stop loss level
Orange Line: Breakeven trigger level
Blue Background: Breakeven activated
Triangles: Entry signals (only appear when trade executes)
Limitations
Negative long-term expectancy: Default settings do not produce profitable results over extended periods
Parameter sensitivity: Results highly dependent on filter settings and market conditions
Market regime dependent: May perform differently in trending vs choppy markets
Commission impact: Frequent trading accumulates significant transaction costs
Curve fitting risk: Optimized settings may not persist in future markets
Disclaimer
This strategy is provided for educational and research purposes only. It does not constitute financial advice.
Past performance does not guarantee future results
Backtested results may not reflect actual trading conditions
The long-term backtest shows significant negative returns
Always paper trade before risking real capital
Never risk more than you can afford to lose
Conduct your own research and due diligence
This is a research framework designed for traders to explore and customize, not a plug-and-play trading system.
CAP - CSI [Auto-MTF]The CAP - CSI is a Digital Signal Processing (DSP) tool based on the principles of Lars von Thienen’s "Dynamic Cycles." While traditional oscillators often fail in trending markets by staying "pinned" at extremes, the CSI uses a recursive dual-thrust processor to isolate the underlying market rhythm, helping traders identify when a cycle is genuinely exhausted.
Core Methodology
This script implements a Cycle Swing Momentum processor. It calculates the difference between short-term and long-term "thrusts" to extract the dominant cycle from price action. Unlike static indicators, it uses Dynamic Percentile Banding to adapt its overbought and oversold levels based on the market's recent "cyclic memory."
Key Features
Pivot Point Detection: Identifies exhaustion when the CSI extends outside its dynamic bands and begins to pivot back toward the mean.
Trend-Aware Coloring: The area fill uses slope-based logic to differentiate between "Rising/Falling" momentum and "Bullish/Bearish" strong zones.
HTF (5x): Built-in logic to define the larger cycle trend. I recommend using a 5x multiplier (e.g., viewing 4H cycles on a 1H chart) to ensure you are trading with the macro flow.
Zero Line Equilibrium: Clear visualization of the cycle's position relative to its center-point to determine the current market regime.
The "Trending" Challenge
A common pitfall with DSP-based cycle tools is that they can generate "phantom" signals during powerful, linear trending conditions. This script is my attempt to solve that by integrating HTF confluence and slope-based filtering. It is specifically optimized for:
Futures: ES, NQ, RTY, and GC.
US Equities: (NVDA, TSLA, etc.).
Additional tip, search for Strong relative strength Symbols, I've created this script : CAP - Mansfield Relative Strength, but there are many there "Mansfield Relative Strength" indicators available.
Why I am sharing this
This is an ongoing project. I am releasing this to the public to connect with other traders interested in Lars von Thienen’s work or John Ehlers’ DSP techniques. My goal is to collaborate with the community to refine the processor further and build a consistent, profitable system that can distinguish between a cycle turn and a trend continuation.
Nexus Momentum Flow [JOAT]
Nexus Momentum Flow - ADX-Based Trend Strength Analysis
Introduction and Purpose
Nexus Momentum Flow is an open-source oscillator indicator that combines the ADX (Average Directional Index) with directional movement indicators (+DI/-DI) to create a comprehensive trend strength and direction analysis tool. The core problem this indicator solves is that ADX alone tells you trend strength but not direction, while +DI/-DI alone tells you direction but not strength. Traders need both pieces of information together.
This indicator addresses that by combining ADX strength classification with directional bias into a single confluence score, making it easy to identify when strong trends exist and which direction they favor.
Why These Components Work Together
1. ADX (Average Directional Index) - Measures trend strength regardless of direction. Values above 25 indicate trending; below 20 indicate ranging.
2. +DI (Positive Directional Indicator) - Measures upward price movement strength.
3. -DI (Negative Directional Indicator) - Measures downward price movement strength.
4. Confluence Score - Combines ADX strength with DI bias to create a single actionable metric.
The combination works because:
ADX filters out ranging markets where DI crossovers produce whipsaws
DI relationship provides direction when ADX confirms trend
Confluence score simplifies the analysis into one number
How the Calculation Works
float directionBias = diPlus - diMinus
float confluenceScore = (adx / 100) * directionBias
The confluence score is positive when +DI > -DI (bullish) and negative when -DI > +DI (bearish), with magnitude scaled by ADX strength.
Trend State Classification
EXTREME - ADX > 50 (very strong trend)
STRONG - ADX 35-50 (strong trend)
TRENDING - ADX 25-35 (moderate trend)
RANGING - ADX < 25 (no clear trend)
Dashboard Information
Status - Current trend state (EXTREME/STRONG/TRENDING/RANGING)
Direction - BULLISH or BEARISH based on DI relationship
ADX - Current ADX value
DI Bias - Difference between +DI and -DI
Confluence - Combined score with directional context
How to Use This Indicator
For Trend Following:
1. Wait for ADX to show TRENDING or higher
2. Check direction matches your trade bias
3. Enter on pullbacks when confluence remains positive/negative
4. Exit when ADX drops to RANGING
For Avoiding Whipsaws:
1. Do not trade DI crossovers when ADX shows RANGING
2. Only trust directional signals when ADX confirms trend
3. Use RANGING periods for mean-reversion strategies instead
For Trend Exhaustion:
1. Watch for EXTREME ADX readings
2. Extreme trends often precede reversals
3. Consider taking profits when ADX reaches extreme levels
Input Parameters
ADX Length (14) - Period for ADX calculation
DI Length (14) - Period for directional indicators
ADX Smoothing (14) - Smoothing period for ADX
Trend Threshold (25) - ADX level for trend confirmation
Strong Threshold (35) - ADX level for strong trend
Extreme Threshold (50) - ADX level for extreme trend
Timeframe Recommendations
Daily/4H: Best for swing trading trend analysis
1H: Good for intraday trend following
15m: More signals but requires faster reaction
Limitations
ADX is a lagging indicator - trends are confirmed after they start
DI crossovers can whipsaw even with ADX filter
Works best in markets that trend clearly
May miss early trend entries due to confirmation requirement
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Trend analysis does not guarantee profitable trades. Always use proper risk management.
- Made with passion by officialjackofalltrades
CANSLIM Indicators plus FCF and stocks momentumThis is a comprehensive Trading View indicator that combines technical analysis with fundamental analysis to help you identify high-quality stock opportunities, inspired by IBD/CANSLIM methodology.
This indicator is an enhancement from @Fred6724 code base. Thanks @Fred6724 a lot!! With Claude assistance I enhanced to suit my need.
You now have a really powerful indicator that combines:
✅ Technical chart patterns (Cup, Double Bottom, Bases)
✅ Relative Strength analysis
✅ Complete fundamental dashboard with EPS, Sales, FCF, Margins, ROE
✅ Toggle ON/OFF the dashboard for clean charts
✅ Color-coded negative values
✅ Stock Bee momentum indicator
This is a professional-grade tool for finding high-quality growth stocks with strong fundamentals breaking out of proper bases. The FCF addition was done based on some model stocks study - it's one of the best indicators of real business quality!
First, I check for sales growth, if accelerating more good. Then if profitable(EPS) excellent, if not how is FCF.
With sales growth and FCF improving - you don't want to miss a strong monster stock - Study NYSE:CVNA and NASDAQ:ROOT
And finally— KISS . You don’t need to be a wizard of indicators or memorize every stock on the planet. Your real edge is staying simple: take clean setups, manage your risk like a pro, and let disciplined long‑term or swing trades compound your money.
If you need any other enhancements in the future, feel free to reach out. Happy trading! 📈
Master Crypto Overlay [R2D2]The Gemini Master Crypto Overlay: User Guide
1. Introduction
The Gemini Master Crypto Overlay is a professional-grade TradingView script designed to consolidate six powerful institutional indicators into a single, clean "heads-up display" (HUD).
Instead of cluttering your chart with multiple sub-windows (which shrinks your view of the price), this script uses smart overlays and a data dashboard to provide actionable data instantly. It is optimized for the Daily timeframe as requested, but functions on all timeframes.
Included Indicators:
Ichimoku Cloud: Identifies the primary trend and support/resistance zones.
MACD (Custom Crypto Settings): Optimized (3-10-16) for catching fast crypto moves.
WaveTrend Oscillator: Visual signals for Overbought/Oversold entries.
Supertrend: A trailing stop-loss line to keep you in profitable trades.
Ultimate RSI (MTF): Multi-timeframe analysis to ensure you are trading with the higher trend.
Volume Reference (VWAP): An on-chart proxy for Volume Profile to spot fair value.
2. Installation Instructions
Step 1: Open Pine Editor
Launch your chart on TradingView.
At the bottom of the screen, click the tab labeled Pine Editor.
Step 2: Paste the Code
Delete any text currently in the editor window.
Copy the code block at the bottom of this response.
Paste it into the editor.
Step 3: Save and Add
Click "Save" (top right of the editor) and name it "Master Crypto Overlay".
Click "Add to chart".
Note: You may hide the "Pine Editor" panel now by clicking the arrow at the bottom center of the screen.
3. How to Use the Interface
The script is designed to be intuitive. Here is what you are looking at:
A. The Dashboard (Bottom Right)
This is your "Confluence Checker." It summarizes the status of the major indicators in real-time.
GREEN: Bullish (Buy/Hold)
RED: Bearish (Sell/Short)
GRAY: Neutral/Choppy (Stay out)
Pro Tip: Do not enter a trade unless at least 3 out of 4 signals on the dashboard match your direction.
B. On-Chart Signals
Clouds (Red/Green): If the cloud is Green and rising, only look for Long trades. If Red, only look for Short trades.
Supertrend Line: This continuous line trails the price. If price is above it (Green line), you are safe. If price closes below it, the trend has reversed.
MACD Labels: Small "MACD" text appears when momentum flips.
WaveTrend Circles:
Blue Circle (Bottom): Price is "Oversold." Good time to buy if the trend is up.
Orange Circle (Top): Price is "Overbought." Good time to take profit.
4. Strategy: Maximizing Trading Returns
To make money with this script, you need a rule-based system. Do not just blindly click when you see a label. Use this "Trend & Trigger" strategy:
The "Golden Entry" (High Probability Long)
Trend Check: Ensure price is ABOVE the Ichimoku Cloud.
Dashboard Check: Verify the RSI Status says "BULL (>50)".
The Trigger: Wait for a pullback where price touches the Supertrend Line (Green) or the top of the Cloud.
The Entry: Enter the trade when a Blue WaveTrend Circle appears OR a MACD Buy Label prints.
Stop Loss: Place your stop loss slightly below the Supertrend line.
The "Exit Strategy" (Protecting Profits)
Conservative: Sell half your position when an Orange WaveTrend Circle appears.
Trend Follower: Hold the rest of your position until the Supertrend Line turns RED.
Black-Scholes Gamma Scalping Strategy# Black-Scholes Gamma Scalping Strategy
## Overview
This strategy applies options market-making principles to spot/futures trading using the Black-Scholes pricing model. It simulates the behavior of a delta-hedged straddle position, generating buy and sell signals based on how a market maker would hedge their gamma exposure.
---
## The Concept: Gamma Scalping
Professional options traders who hold long straddles (long call + long put at the same strike) profit when the underlying moves significantly in either direction. Here's why:
- A straddle has **positive gamma**, meaning its delta increases as price rises and decreases as price falls
- To stay delta-neutral, traders must **buy after dips** and **sell after rallies**
- If **realized volatility > implied volatility**, the profits from these hedging trades exceed the daily theta (time decay) cost
This strategy captures that edge by:
1. Calculating theoretical Greeks using Black-Scholes
2. Monitoring when delta deviates from neutral
3. Trading to "hedge" back to neutral — buying weakness, selling strength
---
## Black-Scholes Greeks Calculated
| Greek | Symbol | What It Measures |
|-------|--------|------------------|
| Delta | Δ | Directional exposure |
| Gamma | Γ | Rate of delta change |
| Vega | ν | Sensitivity to volatility |
| Theta | Θ | Time decay per day |
All Greeks are calculated in real-time using the standard Black-Scholes formula with configurable inputs for strike, expiration, implied volatility, and risk-free rate.
---
## Entry Signals
**Long Entry** (buy the underlying):
- Price drops significantly (gamma scalp trigger), OR
- Straddle delta falls below the lower hedge band
- Volatility filter confirms favorable regime (HV > IV)
**Short Entry** (sell the underlying):
- Price rises significantly (gamma scalp trigger), OR
- Straddle delta rises above the upper hedge band
- Volatility filter confirms favorable regime
---
## Volatility Regime Filter
The strategy compares **Historical Volatility (HV)** to **Implied Volatility (IV)**:
- **HV/IV > 1.2** → Long volatility regime (gamma scalping profitable) → Trading enabled
- **HV/IV < 0.8** → Short volatility regime (theta wins) → Trading paused or reversed
- **Between** → Neutral, proceed with caution
This filter helps avoid trading when market conditions don't favor the strategy.
---
## Key Inputs
**Option Parameters:**
- Strike Offset % — Distance from ATM (0 = at-the-money)
- Days to Expiration — Synthetic option tenor (affects gamma magnitude)
- Implied Volatility — Your estimate of fair IV
- Risk-Free Rate — For BS calculation
**Trading Parameters:**
- Gamma Scalp Threshold — ATR multiple to trigger trades
- Delta Hedge Band % — How far delta must deviate to signal
- Volatility Regime Filter — Enable/disable HV/IV filter
**Risk Management:**
- Stop Loss / Take Profit (ATR multiples)
- Max Drawdown % — Pauses trading if exceeded
- Max Concurrent Positions
---
## How to Use
1. **Set Implied Volatility** to match current market IV (check options chain or VIX for reference)
2. **Adjust Days to Expiration** — Shorter = higher gamma, more signals; Longer = smoother
3. **Tune the Hedge Band** — Tighter bands = more trades; Wider = fewer, larger moves
4. **Enable Volatility Filter** for trend-following vol regimes, disable for pure mean-reversion
**Best suited for:**
- Range-bound or choppy markets
- High realized volatility environments
- Liquid instruments with tight spreads
**Avoid using when:**
- Strong directional trends (gamma scalping loses to delta)
- Volatility is collapsing
- Low liquidity / wide spreads
---
## Information Table
The on-chart table displays real-time:
- Current strike price
- Straddle Delta, Gamma, Vega, Theta
- Historical vs Implied Volatility
- HV/IV Ratio
- Current volatility regime
---
## Alerts
Built-in alert conditions for:
- Long entry signals
- Short entry signals
- Max drawdown protection triggered
---
## Disclaimer
This strategy is provided for **educational purposes only**. It demonstrates how Black-Scholes option pricing theory can be applied to generate trading signals.
- Past performance does not guarantee future results
- Backtest results may not reflect live trading conditions
- Always use proper position sizing and risk management
- Paper trade extensively before using real capital
**No financial advice is given or implied.**
---
## Credits
Based on the Black-Scholes-Merton option pricing model (1973) and gamma scalping techniques used by professional options market makers.
---
*If you find this useful, please leave a like or comment. Suggestions for improvements are welcome!*
EMA Slope - RSI Indicator# EMA Slope - RSI Indicator
## Script Description (for Publishing Page)
**EMA Slope - RSI Indicator** combines normalized EMA slope momentum analysis with RSI divergence detection and momentum comparison to create a visual signal indicator with five distinct signal types. The indicator's originality lies in its unique "No Trade Zone" (NTZ) concept applied to slope momentum, combined with centered RSI format for direct comparison, and multiple complementary signal methods that work together to identify both trend-following and reversal opportunities across different market conditions.
**Core Concept - EMA Slope Normalization:** Calculates rate of change of long MA (default 160 EMA) by comparing current value to N bars ago (default 3 bars). Raw slope difference normalized to -100 to +100 scale using 500-bar rolling range: normalizedSlope = 100 * (longMA - longMA ) / (highest(maDF, 500) - lowest(maDF, 500)). Creates consistent momentum oscillator comparable across price levels and timeframes.
**No Trade Zone (NTZ) Logic:** NTZ (±8 default) creates neutral zone where slope momentum is too weak for reliable signals. Indicator only triggers NTZ Cross signals when slope crosses out of threshold zone, ensuring signals occur only when momentum is sufficiently strong.
**Centered RSI Format (RSI-50):** Traditional RSI (0-100 range) difficult to compare with slope. This indicator uses centered RSI = (RSI - 50), creating -50 to +50 range zero-centered on same scale as normalized slope. Enables direct visual and mathematical comparison between RSI and slope momentum, enabling Slope-RSI exhaustion detection and RSI-Slope Oscillator signals.
**Component Integration:** Five signal types target different market conditions. NTZ Cross and Acceleration target trend-following when momentum strong. RSI Divergence and Slope-RSI Divergence target reversals when price/momentum diverge. RSI-Slope Oscillator targets momentum alignment when RSI and slope converge. Multi-method approach provides signals across trending, reversing, and ranging markets.
### 📊 Technical Calculations
**Slope Normalization:** maDF = longMA - longMA , normalized: maDf = 100 * maDF / (highest(maDF, 500) - lowest(maDF, 500)), ranges -100 to +100.
**Acceleration Detection:** maAcce = abs(maDf - maDf ) * smoothBars * 2, normalized: maAcc = 50 * maAcce / highest(maAcce, 200). Values above threshold (35 display, 40 signals) indicate sudden momentum shifts. Visualized as colored circles: cyan (bullish), red (bearish).
**RSI Calculation:** rsi = sma(rsi(source, length), smoothing), centered: cRsi = rsi - 50 (ranges -50 to +50). Smoothed using SMA (default 3 bars) to reduce noise.
**RSI Divergence:** Uses pivot high/low detection on smoothed RSI. Pivot lookback = 16 - sensitivityInput (inverse: sensitivity 6 = 10-bar lookback, sensitivity 10 = 6-bar lookback). Compares price pivots (actual high/low including wicks) against RSI pivots. Bullish: priceLowerLow AND rsiHigherLow. Bearish: priceHigherHigh AND rsiLowerHigh. Stores multiple previous pivots (default 8 max) for comparison.
**Slope-RSI Exhaustion:** Compares normalized slope against centered RSI on same scale. Bearish: slope accelerating up (delta > 0, slope > NTZ) BUT RSI declining (cRsi < cRsi AND cRsi < cRsi ). Bullish: slope accelerating down (delta < 0, slope < -NTZ) BUT RSI rising. Gap threshold (default 10.0 points) filters noise. Visualized with dashed lines and gap labels.
**RSI-Slope Oscillator:** State machine tracks cross events (rsiSlopeCrossUp = cRsi > maDf AND cRsi <= maDf ), waits for confirmation: both RSI and slope heading same direction. Long: RSI crosses above slope AND both heading UP. Short: RSI crosses below slope AND both heading DOWN. Useful for range-bound markets.
**Stretch Filter:** maPercentDiff = (longMA - shortMA) / shortMA * 100. Blocks long signals if longMA > shortMA by threshold (overextended up). Blocks short signals if shortMA > longMA by threshold (overextended down). Default 0.45% prevents signals when MAs too far apart.
**Delta Calculation:** Measures change in normalized slope between bars. Timeframe mode: compares current confirmed slope with previous confirmed (more reliable, slight delay). Standard mode: compares current with previous bar (faster, may use unconfirmed). Minimum threshold (default 3.4) filters weak momentum changes.
**Trailing Stop (Blackflag FTS Swingarm):** Uses Wilder's MA of true range. Modified mode: trueRange = max(HiLo, HRef, LRef) with enhanced gap handling. Unmodified: standard true range. Trailing stop calculated based on ATR factor and price trend direction. Separate settings for divergence signals (wider stops, grace periods).
### 🚀 Signal Types and Conditions
**1. NTZ Cross Signals:** Long: Slope crosses above +NTZ (default +8) AND positive delta ≥ threshold (default 3.4) AND stretch filter allows AND optional trend confirmation (short MA > long MA). Short: Slope crosses below -NTZ AND negative delta ≥ threshold AND filters allow. Exit: Slope re-enters NTZ OR reverses direction for confirmation bars OR trailing stop.
**2. Acceleration Signals:** Long: Acceleration ≥ threshold (default 40) AND slope above NTZ AND positive delta sufficient AND filters allow. Short: Acceleration ≥ threshold AND slope below -NTZ AND negative delta sufficient AND filters allow. Visual: Colored circles (cyan bullish, red bearish). Works independently to catch sudden momentum bursts.
**3. RSI Divergence Signals:** Bullish: Price lower low while smoothed RSI higher low, detected via pivot comparison (default up to 8 pivots). Bearish: Price higher high while RSI lower high. Optional Slope-RSI confirmation. Visual: Purple lines (bearish), lime lines (bullish). Exit: Divergence-specific trailing stop (wider ATR, grace period).
**4. Slope-RSI Divergence Signals:** Bullish: Slope accelerating down (negative delta, slope < -NTZ) BUT RSI rising over lookback AND gap exceeds threshold (default 10.0 points). Bearish: Slope accelerating up (positive delta, slope > NTZ) BUT RSI declining AND gap exceeds threshold. Visual: Orange triangles (bullish exhaustion), yellow triangles (bearish exhaustion) with dashed lines. Exit: Divergence-specific trailing stop.
**5. RSI-Slope Oscillator Signals:** Long: RSI crosses above slope AND both heading upward. Short: RSI crosses below slope AND both heading downward. State machine tracks cross then confirms direction. Exit: Opposite oscillator condition (allows reversal) OR trailing stop after grace period.
### 📖 How to Use
**Adding to Chart:** TradingView → Indicators → Search "EMA Slope - RSI Indicator" → Add (displays in separate pane below price).
**Visual Elements:** Colored area = normalized EMA slope (Green = bullish above NTZ, Red = bearish below -NTZ, Gray = NTZ zone). Blue line = Centered RSI (-50 to +50). Colored circles = Acceleration (Cyan = bullish, Red = bearish). Green triangles (↑) = Long signals (bottom). Red triangles (↓) = Short signals (top). Orange X = Exit signals. Dashed lines = NTZ boundaries. Purple/Lime lines = RSI divergences. Orange/Yellow triangles = Slope-RSI exhaustion. Table (top-right) = Current Slope, RSI, Gap values.
**Parameter Configuration:** MA Settings: Short 40 (stretch filter), Long 160 (slope), Types: SMA/EMA/DEMA/TEMA/WMA/VWMA/SMWMA/SWMA/HMA. Ratios: 20/80 (fast), 40/160 (standard), 50/200 (slow). Core: NTZ Threshold 8 (5-6 more signals, 10-12 stronger), Min Delta 3.4 (5-10 stronger, 1-3 sensitive), Max Stretch 0.45% (0.3% conservative, 1.0% permissive, 0 disable), Use Timeframe Delta true (confirmed bar vs previous bar). RSI: Length 14, Smoothing 3, Source close. Divergence: Sensitivity 6 (higher = more sensitive, 6 = 10-bar lookback, 10 = 6-bar lookback), Max Peaks 8 (2-15 range), Show Divergences true. Slope-RSI: Lookback 4 (2-10, higher = conservative), Min Gap 10.0 pts (0-100, higher = strong only, 0 disable), Show Exhaustion true. Signal Enables: NTZ Cross true, Acceleration true, RSI Divergence false, Slope-RSI Divergence true, RSI-Slope Oscillator true, Require Slope-RSI Confirmation false. Exit: Confirmation Bars 4 (0-10, 0 immediate, 2-4 filters false), Show Trailing Stop true, Trail Type Modified/Unmodified, ATR Period 10, ATR Factor 4.0 (2-3 tight, 4 standard, 5-6 wide), Divergence Grace 3 bars, Divergence ATR 4.0 (recommend 5-8), Oscillator Grace 3 bars, Oscillator ATR 4.0.
**Alerts:** Right-click indicator pane → Add Alert → Choose condition (Long/Short Entry/Exit) → Configure notifications.
**Interpreting Signals:** Trending Markets: Focus NTZ Cross and Acceleration, higher NTZ (10-12) for stronger signals, use trend confirmation. Reversal Opportunities: Enable RSI Divergence and Slope-RSI Divergence, look for exhaustion markers and divergence lines, use wider stops. Range-Bound: Enable RSI-Slope Oscillator, signals when RSI and slope align, allows position reversal. Multi-Timeframe: Higher TF for trend, lower TF for timing, stronger when aligned. Market Adjustments: Crypto 20/80 MA, NTZ 6-7, Delta 4-5 | Forex 40/160 MA, NTZ 8, Delta 3.4 | Stocks 50/200 MA, NTZ 10-12, Delta 2-3.
### 📈 Use Cases
Day Trading (5m-15m, fast MAs 20/80), Swing Trading (1h-4h, standard 40/160), Position Trading (4h-Daily, slow 50/200), Trend Following (NTZ Cross/Acceleration in trends), Reversal Trading (RSI Divergence/Slope-RSI at reversals), Range Trading (RSI-Slope Oscillator in choppy markets), Momentum Analysis (Centered RSI and normalized slope comparison), Trend Exhaustion Detection (Slope-RSI exhaustion markers).
### ⚠️ Important Disclaimer
**THIS IS NOT FINANCIAL ADVICE**
This indicator is for educational and informational purposes only. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results. No guarantee of accuracy - signals may be false. Not professional financial advice - consult a qualified advisor. Use only as part of comprehensive analysis. Always use proper risk management. Combine with other analysis techniques before making trading decisions. Indicator signals don't guarantee profitable trades. You are solely responsible for trading decisions and risk management. By using this indicator, you acknowledge understanding the risks and that you use it at your own risk. Never invest more than you can afford to lose. Works on all markets: Crypto, Forex, Stocks, Commodities, Futures
## Short Description (for Script Header - 200-300 chars)
Visual signal indicator combining normalized EMA slope momentum (No Trade Zone concept) with centered RSI format for direct comparison. Five signal types: NTZ momentum crosses, acceleration bursts, price-RSI divergences, slope-RSI exhaustion reversals, and RSI-slope oscillator alignment. Includes stretch filter, exit confirmation bars, and trailing stop exits with separate settings per signal type.
## Tags (for Publishing)
EMA, Moving Average, Slope, Momentum, No Trade Zone, NTZ, Indicator, Technical Analysis, RSI, Relative Strength Index, Centered RSI, RSI-50, Divergence, Slope-RSI, Exhaustion, RSI-Slope Oscillator, Normalized Comparison, Stretch Filter, Trend Confirmation, Exit Confirmation, Trailing Stop, Alerts, Signals, Visual Signals, Entry Signals, Exit Signals, Crypto, Forex, Stocks, Futures, Swing Trading, Day Trading, Reversal Trading, Range Trading, Momentum Analysis
## Category
**Indicators** → **Momentum**
Institutional Intermarket Score PRO V3.3 (Presets)This indicator is built on an unusual, non-traditional intermarket concept and is designed to provide market context rather than trading signals.
Institutional Intermarket Score – Indicator Description
Overview
The Institutional Intermarket Score is a contextual market indicator designed to provide a macro and intermarket perspective on the current market environment.
It aggregates information from multiple user-selected correlated and inversely correlated assets to determine whether the broader market context favors risk-on, risk-off, or neutral conditions.
This indicator is not a buy or sell signal.
It does not attempt to predict short-term price movements, entries, or exits.
Its sole purpose is to help the trader understand the broader market context before making any trading decisions.
Core Concept
Markets do not move in isolation.
Institutional participants continuously monitor multiple related markets to assess risk, liquidity, and conviction before deploying capital.
This indicator replicates that process by:
Monitoring several correlated assets (assets that tend to move in the same direction)
Monitoring several inversely correlated assets (assets that typically move in the opposite direction)
Combining their behavior into a single, normalized intermarket score
The result is a context filter, not a trading system.
Asset Groups
The indicator supports up to:
5 correlated assets
5 inversely correlated assets
All assets are fully configurable by the user and can be enabled or disabled individually.
Only active assets are included in all calculations.
Market State Evaluation
Each asset is evaluated using a Price vs VWAP relationship:
Price above VWAP → bullish state
Price below VWAP → bearish state
This binary state is used consistently across all assets to maintain clarity and robustness.
Intermarket Score
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The Intermarket Score represents the average directional alignment of all active assets and is normalized between -1 and +1.
Positive values indicate a risk-on environment
Negative values indicate a risk-off environment
Values near zero indicate balance, rotation, or uncertainty
The score is smoothed to reduce noise and highlight regime persistence rather than short-term fluctuations.
Confirmation Metric (X / Y)
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In addition to the score, the indicator calculates a confirmation ratio:
Y = total number of active assets
X = number of assets aligned with the current regime
Alignment is evaluated relative to the current regime:
In bullish regimes, assets above VWAP confirm
In bearish regimes, assets below VWAP confirm
This metric reflects the quality and conviction of the intermarket consensus.
High confirmation indicates broad agreement across markets.
Low confirmation indicates divergence, uncertainty, or fragile conditions.
Heatmap
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A compact heatmap visually displays the state of each individual asset:
Green indicates alignment with the regime
Red indicates opposition
Neutral indicates inactive assets
This allows immediate identification of:
Which markets are confirming
Which markets are diverging
Whether consensus is broad or fragmented
Intended Use
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This indicator is designed to be used:
Before evaluating trade setups
As a filter, not a trigger
In combination with price action, structure, and risk management
Typical applications include:
Avoiding trades against the broader market context
Distinguishing strong trends from fragile moves
Identifying periods of institutional alignment or hesitation
What This Indicator Is Not
It is not a buy or sell indicator
It does not provide entry or exit signals
It does not predict price direction on its own
It does not guarantee profitable trades
Any trading decisions remain entirely the responsibility of the user.
Summary
The Institutional Intermarket Score provides a high-level market image based on assets selected by the user.
It reflects context, alignment, and conviction, not timing.
Used correctly, it helps traders avoid low-quality trades, understand when markets are aligned or fragmented, and make decisions with greater awareness of the broader environment.
It is a decision support tool, not a trading system.
This indicator, is still evolving and its structure will continue to develop as new insights are tested...
ETH Vol Breakout - NO ERROR VERSIONThis strategy examines the impact of Eth.d Vol on Ethereum price. Looking at ETHDVOL -60 (Support) and 78 (Resistance)—tell a very specific story - analyzing a High Volatility Regime.
The support level around 60 and resistance 78, tend to only occurs during Bull Runs or Market Crashes.
In the "Quiet Years", ETHDVOL rarely touched 60, let alone 78.
Trying to develop a strategy that is perfectly tuned for a Bull Market or a Crisis,
1. The "60 Floor" (Support)
Context: In a high-volatility regime, when ETHDVOL drops to 60, it indicates the market has "cooled off" just enough to reload leverage.
Historical Behavior (2021-2022 Context):
July 2021: After the May crash, ETHDVOL compressed down and found support at ~65.
Result: This marked the local bottom before the massive run-up to the November All-Time Highs ($4,800).
Outcome: Strong Buy Signal (Trend Continuation).
January 2022: ETHDVOL dropped to ~58-60 while price was hovering around $3,000.
Result: The floor broke, volatility spiked to 80+, and price crashed to $2,200.
Outcome: Trap / Warning Signal.
The Pattern: When Volatility hits 60 (Support), price is usually Coiling.
If Price is trending UP: This is a "dip buy" opportunity. The coil resolves upwards.
If Price is trending DOWN: This is the "calm before the flush." The coil resolves downwards.
2. The "78 Ceiling" (Resistance)
Context: 78 is an extreme reading. It represents panic (bottom) or euphoria (blow-off top).
Historical Behavior:
May 2021 (The Crash): ETHDVOL smashed through 78, peaking at 100+.
Price Action: Price collapsed from $4,000 to $1,700.
Signal: If Vol > 78, you are in a capitulation event. Buying spot here is usually profitable within 3-6 months (buying the blood).
November 2022 (FTX Collapse): ETHDVOL spiked to ~75-80.
Price Action: ETH hit $1,100 (Cycle Lows).
Signal: Hitting 78 marked the Absolute Bottom.
November 2021 (The Top): Interestingly, at the $4,800 price peak, Volatility was NOT at 78. It was lower (~60-70).
Insight: Bull market tops often happen on lower volatility than bear market bottoms.
