[codapro] Tenkan Cloud Signals
Cloud in the Skys — Tenkan Altitude Signals Above the Kumo
Description:
This is not your average Ichimoku script — this is “Cloud in the Skys”, a reimagined way to interpret the Tenkan line as an airplane navigating altitude around the Kumo cloud layer.
Visual Metaphor Explained:
Tenkan = Airplane
The fast-reacting Conversion Line becomes your flight path.
Cloud (Kumo) = Noise / Airspace
The Ichimoku cloud is your visual weather system. When the plane (Tenkan) is:
Above the cloud → Clear skies, likely breakout, nothing overhead
Inside the cloud → Turbulence zone, indecision, avoid trading
Below the cloud → Descending, seeing ground only, bearish sentiment
This script helps you see trend structure like a pilot sees airspace — visually, directionally, and with awareness of turbulence zones.
What It Includes:
Tenkan (Conversion) and Kijun (Base) line calculations
Full Kumo Cloud (Senkou A & B), with customizable displacement
Buy/Sell Flags based on Kijun crossing the forward-displaced Span B
Only plotted after a user-defined number of confirming closes
Full visual controls: cloud fill, line colors, flag display toggle
How to Use It:
Long Bias: When Tenkan rises above the cloud and Buy flag confirms — sky’s clear
Short Bias: When Tenkan descends and Sell flag confirms — plane is losing lift
Stay Out: If Tenkan is inside the cloud, wait — this is chop/noise
Pair this script with price action or volume confirmation for better clarity. Especially effective in trend-following or breakout strategies on mid-to-longer timeframes.
Disclaimer:
This tool was created using the CodaPro Pine Script indicator design system — a modular architecture for building visual signal overlays and automated alerts.
It is provided for educational and informational purposes only and is not financial advice. Always test thoroughly before using in live market conditions.
Analisis Trend
Compression-to-Expansion Early Warning (CEEWS)The Compression → Expansion Early Warning System (CEEWS) is a volatility-structure and market-timing indicator designed to identify periods of statistical price compression and to signal when that compression transitions into directional expansion. Rather than predicting direction in advance, CEEWS focuses on detecting when price action becomes tightly constrained and then confirms when stored energy begins to release.
CEEWS quantifies compression using a composite of volatility contraction, range tightening, candle overlap, and reference-level convergence, producing a normalized Build score (0–100) that reflects the degree of latent price pressure. Elevated Build values indicate that the market is coiled and increasingly susceptible to movement, while expansion signals occur only when volatility begins to expand and price breaks from its recent range.
The indicator is intended as a timing and transition tool, not a standalone trend or directional system. CEEWS is most effective when paired with broader regime or trend-health indicators and is particularly well suited for index funds and highly liquid markets, where prolonged consolidation phases often precede sharp directional moves. Its primary purpose is to help traders identify when the market is likely to move, not to forecast where it will go.
Sessions and Killzones [Tradeuminati]Tradeuminati – Sessions & Killzones is a New York local time based session toolkit designed for traders who want clean, objective session structure on their chart: session boundaries, killzones, session highs/lows, and previous day levels plus a live “liquidity taken” checklist.
Key Features
1) Sessions (New York Time)
London Session (0:00 – 6:00 NY)
- Vertical start/end lines
- Live session High and Low tracking during the session
- High/Low levels extend until 16:00 NY
- Labels: Ls - H and Ls - L
- Option to display only the current day
Asia Session (Previous Day, 18:00 – 00:00 NY)
- Vertical start/end lines for the previous day session
- Live session High and Low tracking
- High/Low levels extend into the next day until 16:00 NY
- Labels: As - H and As - L
- Option to display only the current day
2) Killzones (New York Time)
London Killzone: 2:00 – 5:00 NY
- Optional DAX-only mode: If enabled, DAX uses 3:00 – 5:00 NY (DAX opening), while other assets remain 2:00 – 5:00 NY
New York Killzone (auto-adjust by asset type)
- Indices: 9:30 – 11:00 NY
- Other assets (FX / Commodities / Crypto): 7:00 – 10:00 NY
New York PM Killzone: 14:00 – 15:00 NY (all assets)
ll killzone lines are placed from the start of the NY day, so you can see upcoming killzones in advance (not only after candles appear).
3) Previous Day High / Low (PDH / PDL)
- Automatically calculates the full previous NY day range (00:00 – 23:59 NY)
- Plots PDH and PDL into the current day
- Labels: PDH and PDL
4) Live “Liquidity Taken” Table
- A compact table in the bottom-left shows whether price has:
- swept Asia High / Asia Low
- swept London High / London Low
- taken PDH / PDL
A green checkmark appears instantly once a level is broken.
Customization
Fully adjustable colors, widths, and line styles for:
- Session vertical lines
- Session high/low lines
- Killzones
- PDH/PDL
Adjustable label size
Day filtering options (current day only)
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Disclaimer
This indicator is for educational and technical analysis purposes only. It does not constitute financial or investment advice. Trading involves risk.
Premium Money Flow Oscillator [NeuraAlgo]Premium Money Flow Oscillator (PMFO) — NeuraAlgo
The Premium Money Flow Oscillator (PMFO) is an advanced volume-weighted momentum engine designed to reveal true capital flow, not just price movement.
It combines multi-layer smoothing, zero-lag correction, and dynamic normalization to deliver a clean, responsive, and noise-resistant money flow signal suitable for both scalping and swing trading.
Unlike traditional oscillators, PMFO focuses on pressure behind price — showing when smart money accumulation or distribution is actively occurring.
🔹 Core Features
Volume-Weighted Money Flow
Measures real buying and selling pressure using price displacement × volume.
Filters out weak price moves with low participation.
Multi-Layer Smoothing Engine
EMA + SMA hybrid base smoothing
Gaussian noise reduction
Zero-Lag correction
Deep & Super smoothing layers
→ Result: ultra-smooth yet fast reaction to momentum shifts.
Dynamic Normalization
Automatically adapts to volatility.
Keeps signals consistent across all markets and timeframes.
🔹 Smart Zones & Visual Intelligence
Dynamic Overbought / Oversold Zones
Zones strengthen visually as momentum increases.
Strong zones highlight extreme institutional pressure.
Adaptive Gradient Coloring
Color intensity reflects money flow strength.
Instantly see dominance without reading numbers.
Background Pulse
Subtle market bias feedback (bullish / bearish pressure).
🔹 Multi-Timeframe Confirmation
Optional Higher Timeframe Money Flow Confirmation
Align lower-timeframe entries with higher-timeframe capital direction.
Ideal for trend validation and false-signal reduction.
🔹 Professional Dashboard
Live Money Flow Value
Market Flow State
Strength Percentage
MTF Trend Bias
Institutional-style status readout designed for quick decision making.
🔹 Best Use Cases
✔ Trend confirmation
✔ Momentum continuation entries
✔ Reversal exhaustion detection
✔ Divergence analysis
✔ Smart money flow tracking
⚠️ Notes
PMFO works best when combined with price structure, support/resistance, or trend context.
Extreme readings indicate pressure, not immediate reversal — always wait for confirmation.
Designed for traders who want clarity, not clutter.
Built for precision, not lag.
Minervini Ultimate +VCPMinervini Ultimate Suite (SEPA Dashboard)
This indicator implements Mark Minervini's "Trend Template" criteria combined with a Volatility Contraction Pattern (VCP) detector and a custom Relative Strength rating. It is designed to help traders visualize the technical health of a stock based on stage analysis concepts.
This indicator serves as a complete Control System (Dashboard) for Mark Minervini's SEPA trading strategy. Instead of manually checking five different metrics on every chart, this indicator performs the mathematical calculations and presents the "bottom line" in a single, organized table.
1. What This Indicator Does
The goal is to ensure you never enter a trade blindly. It verifies the stock against Minervini's strict requirements:
Trend: Is the stock in a healthy Stage 2 Uptrend?
Relative Strength: Is it stronger than the general market?
Buy Risk: Is it the right time to buy, or is the price extended?
Pressure: Are institutions accumulating or distributing?
VCP: Is there a breakout opportunity (volatility contraction) right now?
2. Key Benefits
Time-Saving: Instead of drawing lines and calculating percentages manually, you get immediate visual feedback (Green/Red).
Discipline: The indicator will flag "Extended" (Red) if you attempt to buy a stock that has run up too much, saving you from late entries and unnecessary losses.
Precision Timing: The VCP feature (Blue Dots) helps you identify the "calm before the storm"—the exact moment volatility contracts, which often precedes a major breakout.
3. Indicator Parameters & Features
A. Minervini Pressure (Buying vs. Selling)
What it checks: Money flow over the last 20 days.
Calculation: Sums up volume on "Up Days" (Green) versus volume on "Down Days" (Red).
Meaning:
🟢 Buying: More money is entering than leaving. A sign of institutional accumulation.
🔴 Selling: Selling pressure dominates. The price may be rising, but without strong volume backing.
B. Buy Risk (Price Extension)
What it checks: The distance of the current price from the 50-Day Moving Average. Minervini strictly warns against "chasing" stocks.
Signals:
🟢 Low Risk: Price is within 0% – 15% of the 50MA. This is the ideal "Buy Zone".
🟡 Caution: Price is 15% – 25% away. Buy with increased caution.
🔴 Extended: Price is >25% from the MA. Do not buy. The probability of a pullback is high.
⚪ Broken: Price is below the 50MA. The short-term trend is damaged.
C. TPR - Trend Template (Trend Power Rating)
What it checks: Is the stock in a Stage 2 Uptrend?
Strict Rules (All must be true for a PASS):
Price > 50MA > 150MA > 200MA.
The 200MA is trending UP (positive slope).
Price is near the 52-Week High (within 25%).
Price is above the 52-Week Low (at least 25%).
Meaning:
🟢 PASSED: Technically healthy and ready to move.
🔴 FAILED: The trend structure is broken (e.g., MAs are entangled).
D. RPR Score (Relative Performance Rating)
What it checks: How strong the stock is compared to the general market (S&P 500 / SPY).
Calculation: Weighted performance over 3, 6, 9, and 12 months vs. the SPY. The score ranges from 1 to 99.
Meaning:
🟢 80-99: Market Leader. These are the stocks Minervini targets.
🟡 70-80: Good, but not elite.
⚪ Below 70: Laggard (weaker than the market).
E. VCP Action (Volatility Contraction Pattern)
What it checks: Monitors price tightness. It calculates the range between the highest close and lowest close over the last 5 days.
Meaning:
🔵 SQUEEZE (Blue Text + Blue Dot on Chart): The price range has contracted to less than 2.5%.
Why it matters: When a stock stops moving wildly and trades in a tight range ("Flat Line"), it indicates supply has dried up. A high-volume breakout often follows immediately.
Structural Trend Integrity Score (STIS)The Structural Trend Integrity Score (STIS) is a market regime and trend-quality indicator designed to evaluate the health and durability of a price trend, rather than its direction or momentum. Instead of focusing on overbought or oversold conditions, STIS measures whether a trend is structurally supported by consistent organization, persistence above trend, controlled pullbacks, and smooth progression.
STIS outputs a normalized score from 0 to 100, where higher values indicate stronger and more reliable trend structure, and lower values signal increasing fragility or structural breakdown. This makes it especially well suited for index funds and highly liquid markets, where trends tend to persist or fail based on internal structure rather than short-term price acceleration.
The indicator is intended to be used as a risk and confidence framework, not as a direct buy or sell signal. STIS helps traders and investors determine when it is efficient to maintain or increase exposure and when caution is warranted. It works best when paired with separate timing or entry tools and is particularly effective for long-only or trend-following strategies.
N-Wave Structure v1.0N-Wave Structure is a trend-filtered price action indicator designed to identify N-wave market structures in real time.
The indicator uses an EMA-based trend filter to define market direction and then detects clean N-wave (A–B–C) price structures aligned with that trend.
When price is above the EMA, only bullish N-wave setups are displayed. When price is below the EMA, only bearish N-wave setups are shown.
Signals are generated at the B-point breakout, following classic N-wave theory, making the indicator suitable for practical trading rather than theoretical analysis.
This indicator focuses on clarity and reproducibility:
Clear A, B, and C structure visualization
Distinct long and short setups
Trend-direction background coloring
Non-repainting logic using confirmed pivots
Fully compatible with all timeframes
Orto N-Wave Structure is especially effective for FX and index trading and is intended for traders who prefer structure-based decision making over indicator-heavy systems.
Ultimate Major Contextual Dashboard (Multi-Asset)Overview : The Ultimate Major Dashboard is a performance-optimized market overview tool designed to provide a consolidated snapshot of the 7 major Forex pairs and Gold. It aggregates correlation, trend, momentum, and volatility data into a single, clean table, allowing users to view broader market context without switching charts.
Technical Logic & Components : This indicator utilizes a modular function to analyze EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, USDCAD, NZDUSD, and XAUUSD across four key dimensions:
Intermarket Correlation (Pearson Coefficient): Uses ta.correlation() to compare each asset against the symbol currently on your main chart.
Logic: Values above 0.7 (Dark Green) suggest a strong positive relationship, while values below -0.7 (Dark Red) suggest inverse behavior. This is calculated over a rolling 50-period window to balance stability with current market sensitivity.
Trend Bias (EMA-200): Evaluates the long-term trend by checking price position relative to the 200-period Exponential Moving Average.
Visuals: An upward arrow (⬆) indicates price is above the EMA; a downward arrow (⬇) indicates it is below.
Momentum (RSI-14): Calculates the Relative Strength Index. The dashboard automatically highlights readings above 70 (OB) or below 30 (OS) to help identify potential momentum extremes.
Volatility (ATR-14): Displays the Average True Range as a reference for the current active range of each market, helping users compare volatility levels across the majors.
How to Interpret the Dashboard
Asset Alignment: Correlation values help identify when pairs are moving in "unison" versus when a specific currency is diverging from the group.
Directional Context: Combining the Trend (EMA) and Momentum (RSI) columns provides a quick view of whether a market is trending strongly or reaching an exhaustion point.
Volatility Benchmarking: The ATR values offer perspective on which pairs are currently the most active, assisting in market comparison based on volatility preference.
Data Handling & Customization
Multi-Symbol Sync: Data is fetched using request.security(). The calculations are synchronized with the chart's current bar state for real-time accuracy.
Dynamic TF: Users can select the analysis timeframe (60, 240, D, W) via the settings menu.
Flexibility: The dashboard position can be toggled between all four corners of the chart to avoid overlapping with price action.
Disclaimer
This tool is provided for analytical and educational purposes only. It does not generate trading signals and should not be considered financial advice.
Multi KI Agenten Strategie (Final V2)What's included in the Pine Script (Technical Analysis)
These features are mathematically implemented in the script and function as "agent logic":
• Trend Following: Integrated via EMAs (50, 100, 200).
• Volume Analysis: An agent checks for institutional volume spikes.
• Supply & Demand: Zones are calculated based on price extremes.
• RSI & Fibonacci: Both are built in as decision criteria for the agents.
• Controlling AI: The "veto logic" in the code acts as a controlling instance, blocking signals if the risk is too high or divergences exist.
• Alerts: The "LONG" and "SHORT" alerts are only triggered after approval by the controlling mechanism.
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.
Continuation Gauge - Bull vs BearDivergence/ strength detector - great for tracking entry at key divergences and visualizing volatility.
Dashboard Alerts0
Dashboard Alerts is a trend-focused trading indicator that highlights high-probability buy and sell signals.
What it uses:
📈 EMA trend alignment to define market direction
⚡ RSI momentum to identify strength and exhaustion
🔄 Stochastic confirmation for timing entries
🧨 Squeeze volatility to detect breakouts and momentum expansion
Signals shown on chart:
🔵 Strong Buy
🟢 Buy / Pullback Buy
🟡 Trend Reversal
🟠 Take Profit
🔴 Sell / Strong Sell
Features:
🔔 Optional alerts (intrabar or candle close)
👁️ Clear arrow-based visual signals
⏱️ Works on intraday and swing timeframes
Highly recommended to use with Heikin Ashi candles.
[CT] Highest/Lowest Close Midline Candle ColorThis indicator looks back a user defined number of bars, the default is 14, and finds the highest closing price and the lowest closing price in that lookback window. Those two values form a rolling closing range. The script then calculates a midpoint of that range by averaging the highest close and the lowest close. That midpoint is plotted as “o”, and it acts like a simple, adaptive balance line for where the market is trading within its recent closing range.
On every bar, the candle color is driven by where the current close finishes relative to that midpoint. When price closes above the midpoint, the script colors the candle green, which tells you that the close is occurring in the upper half of the most recent closing range. When price closes below the midpoint, the candle is colored red, which tells you the close is occurring in the lower half of the most recent closing range. If the close lands exactly on the midpoint, the script leaves the bar uncolored, which is a quick way to spot “neutral” closes that are sitting right at the balance point.
On the chart you will see three plots. The “hi” line is the highest close over the lookback period, so it behaves like a dynamic ceiling for closes. The “lo” line is the lowest close over the lookback period, so it behaves like a dynamic floor for closes. The “o” line is the midpoint between those two, and it will move up when the rolling highest and lowest closes lift, and it will move down when they fall. Because all three are based on closing prices instead of highs and lows, they reflect where the market is actually accepting value at the end of each bar rather than momentary wicks.
In practical use, the midpoint line is your decision line and the candle colors are your bias filter. A sequence of green candles means closes are consistently happening above the midpoint, which implies bullish control of the recent closing range and can be used as a confirmation to favor long setups, trend continuation trades, or pullbacks that hold above the midpoint. A sequence of red candles means closes are consistently happening below the midpoint, which implies bearish control of the recent closing range and can be used to favor short setups or bearish continuation until price can reclaim the midpoint. When candles flip color around the midpoint repeatedly, that is a visual cue that the market is rotating and the midpoint is acting like a balance area rather than support or resistance, which often aligns with consolidation or choppier conditions.
The “hi” and “lo” lines can be treated as context levels. If price is closing above the midpoint and pressing toward the “hi” line, you are seeing strength within the closing range and the prior highest close becomes the next level where continuation may stall or break. If price is closing below the midpoint and pressing toward the “lo” line, you are seeing weakness within the closing range and the prior lowest close becomes the next level where continuation may pause or accelerate through. Breaks beyond the “hi” or “lo” line indicate that the rolling closing range is expanding, which can coincide with trend continuation or a breakout from a prior range.
This tool is simple by design and is best used as a directional filter and a structure guide rather than a standalone entry system. It does not repaint past bars because it only uses completed historical closes within the selected lookback window, and it updates normally as each new bar closes. You can increase the period to smooth it for higher time frames or more stable trends, and decrease it to make it more sensitive for faster markets or scalping, with the tradeoff that shorter periods will flip colors more often in chop.
Adjusted RSI - [JTCAPITAL]Adjusted RSI – is a modified and enhanced way to use the Relative Strength Index (RSI) combined with double normalization, adaptive exponential smoothing, and range compression to create a smoother, more readable, and more structurally consistent momentum oscillator for Trend-Following and momentum analysis.
This indicator is designed to solve several common RSI issues at once:
Excessive noise in raw RSI values
Inconsistent scaling across different market conditions
Difficulty identifying true momentum shifts versus random fluctuations
By re-centering, compressing, normalizing, and smoothing RSI data twice , this script produces a highly refined momentum curve that reacts smoothly while still respecting directional changes.
The indicator works by calculating in the following steps:
Raw RSI Calculation
The script begins by calculating a standard RSI using the selected RSI Length . This RSI is based on the closing price and measures relative strength by comparing average gains and losses over the defined period.
RSI Re-Centering
After the RSI is calculated, the script subtracts 50 from the RSI value.
This converts the RSI from its native scale into a centered oscillator ranging around 0 , making positive values bullish momentum and negative values bearish momentum.
Initial RSI Smoothing
The re-centered RSI is then smoothed using a Simple Moving Average (SMA) over the defined RSI Smoothing Length .
This step removes high-frequency noise and stabilizes short-term RSI fluctuations before further processing.
Range Compression (Clipping)
To prevent extreme outliers from dominating future calculations, the RSI values are clipped:
Values below -10 are forced to -10
Values above +10 are forced to +10
This creates a controlled and consistent RSI range, ensuring later normalization behaves reliably.
First Normalization (Min-Max Scaling)
The clipped RSI values are normalized over the selected Smoothing Length :
The lowest RSI value in the window is detected
The highest RSI value in the window is detected
Current RSI is scaled to a 0–100 range based on this dynamic range
This allows the indicator to adapt automatically to changing volatility and momentum environments.
First Adaptive Smoothing
The normalized RSI is then smoothed using a custom exponential smoothing formula controlled by the Smoothing Factor .
This smoothing behaves similarly to an EMA but allows explicit control over responsiveness.
Second Normalization
The smoothed values undergo a second min-max normalization over the same length.
This further stabilizes the oscillator and ensures consistent amplitude and structure, regardless of market regime.
Second Adaptive Smoothing
A second exponential smoothing pass is applied to the normalized data, further refining the curve and reducing residual noise.
Final Re-Centering
Finally, the indicator subtracts 50 from the smoothed normalized values, re-centering the oscillator around zero .
This produces the final Adjusted RSI line used for visualization and analysis.
Common interpretations for use include:
Bullish Momentum :
When the Adjusted RSI is above zero and rising, indicating strengthening bullish pressure.
Bearish Momentum :
When the Adjusted RSI is below zero and falling, indicating strengthening bearish pressure.
Momentum Shifts :
A change in slope (from falling to rising or vice versa) often signals an early momentum transition.
Divergences :
Differences between price direction and Adjusted RSI direction can highlight potential reversals.
Because the indicator is normalized and smoothed, it pairs exceptionally well with:
Trend filters (moving averages, trend lines)
Volatility filters
Higher-timeframe confirmation
Features and Parameters:
RSI Length
Defines the lookback period for the initial RSI calculation.
RSI Smoothing Length
Controls the SMA smoothing applied directly to the re-centered RSI.
Smoothing Length
Determines the lookback window used for both normalization passes.
Smoothing Factor
Controls the responsiveness of the adaptive exponential smoothing.
Lower values = smoother, slower reaction
Higher values = faster, more responsive reaction
Specifications:
Relative Strength Index (RSI)
RSI is a momentum oscillator that measures the speed and magnitude of recent price changes. By re-centering RSI around zero, the script converts it into a directional momentum oscillator that is easier to interpret for trend-following.
Simple Moving Average (SMA)
The SMA reduces short-term fluctuations in RSI, ensuring that only meaningful momentum changes proceed to later calculations.
Range Clipping
By limiting RSI values to a defined range, extreme spikes are prevented from skewing normalization. This keeps the indicator stable across different assets and timeframes.
Min-Max Normalization
Normalization rescales values into a fixed range (0–100), allowing momentum behavior to remain consistent regardless of volatility conditions.
Adaptive Exponential Smoothing
This smoothing technique gradually adjusts values toward new data based on the smoothing factor. It allows the indicator to remain smooth while still reacting to genuine momentum shifts.
Double Normalization and Double Smoothing
Applying normalization and smoothing twice significantly improves structural stability. The result is a refined oscillator that filters noise without sacrificing trend awareness.
Why This Combination Works
By combining RSI with controlled compression, adaptive smoothing, and dynamic normalization, this indicator transforms raw momentum data into a highly structured and trend-aligned oscillator. The result is an RSI-based tool that:
Reduces noise
Adapts to volatility
Maintains consistent scaling
Highlights true momentum direction
This makes the Adjusted RSI particularly effective for swing trading, trend confirmation, and momentum-based strategies across all markets and timeframes.
Enjoy!
TrendSurfer Lite TrendSurfer Lite ⚡
Advanced Multi-Signal Trading Indicator for Precision Market Analysis
TrendSurfer Pro LITE is a comprehensive trading system combining multiple technical analysis tools into one powerful indicator. Designed for traders seeking high-probability setups with customizable filters.
Key Features:
📊 Core Signals
Triangle Signals (▲▼): Volume-weighted momentum entries with 10-level volume scoring
Master Trend System (△▽): Multi-EMA confirmation with RSI validation
Order Blocks (🟩🟥): Smart money institutional zones with rejection detection
Take Profit System (🎯): 8-indicator confluence system (RSI, Stochastic, Supertrend, CCI, MACD, BB, EMA Cross, Price Action)
🎯 Rejection Signals
Master Trend Rejections: Dynamic support/resistance from trend lines
EMA750 Rejections (White "R"): Major trend filter bounces
VWAP Rejections (Pink "W"): Institutional level reactions
Butterworth Filter Rejections (🟡): Advanced smoothing algorithm reversals
Session Rejections (⚡): Tokyo/London/NY session high/low bounces
Session Midline Rejections (Orange "M"): Half-range mean reversion
🌍 Session Analysis
Tokyo Session (💴): Asian market range with automatic extensions
London Session (💶): European volatility zones
New York Session (💵): US market key levels
Auto-adjusting timezone with UTC offset support
🔧 Advanced Filters
EMA750 Master Filter: Global trend alignment for all signals
VWAP Filter: Institutional bias confirmation
Yellow Box Filter (🟨): Consolidation zone proximity detection
3 Time Filters: Customizable trading windows with visual backgrounds
Volume Filter: Signal strength validation (6-10 scale)
📈 Visual Tools
VWAP Purple Candles: Special candle coloring for VWAP crosses above EMA750
Stochastic-based Candle Colors: Overbought/oversold visual cues
Previous Day Close Line: Key reference level
Master Trend Table: Real-time multi-indicator dashboard
⚙️ Customization
Full color customization for all elements
Adjustable line thickness and transparency
Configurable alert system for every signal type
19 independent alert conditions
Best For:
Intraday scalping and swing trading
Multi-timeframe analysis
Confluence-based trading strategies
Institutional level detection
Version 1.0 | Clean interface | Maximum flexibility | Professional-grade signals
Sameer Bandhara AlertsThis Sameer Bandhara (SB Trader) indicator is a dynamic trailing stop-loss system based on the Average True Range (ATR). Here's a comprehensive breakdown:
It uses ATR to create an adaptive trailing stop that adjusts to market volatility, generating buy/sell signals when price breaks through this dynamic stop level.
Forex/Stocks: Key Value 1.5-2.5, ATR Period 14-20
Crypto: Key Value 2.0-3.0 (higher volatility)
Timeframes: 1H and above (reduces noise)
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.
Percentage Level TargetsDisplays dynamic percentage-based price target levels at ±2.5% and ±5% from current price.
⭐ FEATURES:
✓ Real-time level updates on every candle
✓ Customizable label positioning (left/right)
✓ Adjustable offset for precise placement
✓ Works on ALL timeframes and assets
✓ Color-coded levels (green/red)
🎯 USE CASES:
→ Identify profit targets quickly
→ Set stop-loss levels automatically
→ Risk/reward ratio planning
→ Scalping & swing trading
⚙️ CUSTOMIZATION:
• Adjust percentage levels (default: ±2.5%, ±5%)
• Toggle labels on/off
• Change colors for positive/negative levels
• Control label position & offset
📊 COMPATIBLE WITH:
Stocks • Crypto • Forex • Commodities
All timeframes (1m, 5m, 1h, 4h, Daily, Weekly, Monthly)
Feedback welcome! 🙌
Nixxo Custom IchimokuCustom Ichimoku settings for stock market or the crypto universe! Also has the capability to 2x the settings from the indicator settings (preset) so that settings don't have to be changed all the time.
MACD Matrix: Angle & SettlementThis indicator is a comprehensive Multi-Timeframe (MTF) Dashboard designed for technical traders who rely on MACD not just for crossovers, but for Momentum Angle and Settlement (Hooks).
Instead of cluttering your screen with 5 different MACD charts, this Matrix calculates the math in the background and presents a clean "Heads-Up Display" of the MACD state across your specific timeframes (Default: 3m, 15m, 1h, 4h, 16h).
The Concept: "Angle Settlement"
Standard MACD indicators only show you when a cross happens. By then, the move is often halfway over. This script focuses on the Angle (Slope) of the MACD line to predict turns before they happen:
Steep Angle: Momentum is accelerating. (Strong Trend)
Settling Angle: The slope is flattening out. The MACD line is "hooking." (Reversal/Cross Imminent)
Dashboard Columns Explained
TF (Timeframe): Auto-formats your settings into readable text (e.g., "240" becomes "4h").
Zone:
> 0 (Green): MACD is above the Zero Line (Bullish Trend context).
< 0 (Red): MACD is below the Zero Line (Bearish Trend context).
Cross:
PCO (Green): Positive Crossover (MACD > Signal).
NCO (Red): Negative Crossover (MACD < Signal).
Deg (°):
The calculated mathematical angle of the MACD line.
Positive (+): Momentum is rising.
Negative (-): Momentum is falling.
State (The Strategy):
STEEP (Bright Color): The angle is increasing. Do not trade against this momentum.
SETTLE (Dim Color): The angle is decreasing compared to the previous bar. The momentum is "cooling off," often signaling a "Hook" or an upcoming crossover.
Settings & Customization
Custom Timeframes: You can freely change TF-1, TF-2, etc., in the settings. The table labels will auto-update (e.g., if you change 4h to 1D, the table will display "1D").
MACD Lengths: Fully customizable (Default 12, 26, 9).
Angle Sensitivity: A multiplier to calibrate the "Degrees" to your specific asset class (Crypto, Forex, or Indices). If angles look too small, increase this value.
HTF Double BOS + Inducement (XAU) ebenThis indicator is a market structure and inducement scanner designed to assist discretionary traders.
It identifies:
• Higher-timeframe market regime using a double Break of Structure (BOS) on the Daily and 4H timeframes.
• Lower-timeframe Break of Structure (BOS).
• Valid inducement based on a minimum 70% retracement rule.
The script is intended to be used as a confirmation and alert tool, not as a standalone buy/sell system.
⸻
How It Works
1. The indicator first confirms directional bias using Daily and 4H BOS alignment.
2. When higher-timeframe bias is valid, it scans the active chart timeframe for:
• a Break of Structure,
• followed by inducement using a retracement-based rule.
3. When conditions align, the script displays a visual marker and can trigger an alert.
⸻
Important Notes
• This indicator does not predict price.
• It does not automatically execute trades.
• It should be used in conjunction with proper risk management and personal analysis.
• Signals may appear less frequently due to strict filtering logic.
⸻
Recommended Usage
• Best suited for trend-following strategies.
• Works well on Gold (XAUUSD) and other liquid markets.
• Designed for use on 30m, 15m, and 5m charts.
• Alerts should be treated as areas of interest, not direct trade instructions.
⸻
Disclaimer
This script is provided for educational and analytical purposes only.
The author is not responsible for trading losses. Use at your own risk.
D FLEX PullbackIntraday trend-following pullback scanner using EMA structure, VWAP positioning, and Fair Value Gap (FVG) logic.
Designed for fast timeframes.
Includes NO-TRADE filtering, confirmation candles, and hybrid take-profit logic (1R + nearest FVG / swing).
Best used on indices and liquid stocks.
KDJ Momentum Matrix ProKDJ Momentum Matrix Pro (Trend Filter & Structural Divergence)
Overview
This is a professional-grade KDJ indicator script designed for systematic traders. It transcends the basic KDJ logic by integrating advanced technical analysis features, including dynamic trend filtering and structural divergence alerts. The script leverages intuitive color schemes and visual markers to help traders identify high-probability setups amidst market noise.
Key Features
Dynamic J-Line Coloring: The J-line switches between Green (Bullish) and Red (Bearish) based on momentum, providing instant feedback on market strength.
Visual Overbought/Oversold Zones: Shaded 80/20 regions help traders identify market extremes and potential exhaustion points.
Structural Divergence Alerts: Built-in detection for potential Bullish Divergence, serving as a powerful confluence tool for Chan Lun (Zen Theory) Type 1 entries.
Precision Signal Markers: Identifies high-conviction Gold Crosses in oversold zones and Death Crosses in overbought zones.
Strategic Integration
Chan Lun (Zen Theory): Use KDJ divergence to validate "Central Segment" (Zhong Shu) exhaustion and identify potential trend reversals.
Turtle Trading Rules: Utilize the script to find pullbacks within a major trend for scaling in, or use J-line exhaustion as an early warning for trend exits.
Advanced Analysis: Apply the 80/20 rule combined with divergence patterns to build a robust framework for navigating both trending and ranging markets.
KDJ 进阶策略分析脚本 (趋势过滤与结构背离版)
简介
这是一个专为进阶交易者设计的 KDJ 指标脚本。它不仅完美呈现了传统的 K、D、J 三线逻辑，更融入了现代高级技术分析中的动态趋势过滤与背离预警功能。脚本通过视觉化的颜色切换与符号标记，帮助交易者在复杂的市场波动中识别高质量的入场机会。
核心功能
动态 J 线变色：J 线根据动量强弱实时切换红绿颜色，直观反映多空博弈状态。
超买/超卖视觉化：自动填充 80/20 警戒区域，辅助识别极端市场情绪。
结构性背离预警：内置逻辑可识别价格与指标间的疑似底背离，为缠论第一类买点提供辅助参考。
信号标记：精确捕捉低位金叉与高位死叉，过滤无效杂波。
交易系统结合点
缠论结合：通过 KDJ 在超卖区的背离表现，辅助确认中枢背驰或小级别转大级别的转折点。
海龟交易法：利用 KDJ 辅助寻找趋势回调后的补仓位置（顺势金叉），或作为趋势衰竭的早期预警离场参考。
高级技术分析：结合 80/20 区域规则，利用指标钝化与交叉逻辑，构建完整的震荡与趋势切换框架。
