Cyato Grid Basic Buy & Sell [ALERTSETUP]Private indicator
This Grid bot strategy creates buy orders when the price goes down one level or more, and sell order when the price goes up one level or more.
To avoid useless trades, the lastest traded level is disabled until another level is crossed.
To create the grid, one upper level and one lower level is calculated. Those 2 levels are either given by the user using "MANUAL" mode or automatically calculated by an AI. The space between these two levels are then divided equally into several steps, creating the grid. The number of steps is choosen by the user, from 3 to 20.
How it Works
This is the Alert Setup version meaning this is the one you should use to create alerts (more below).
Select either "MANUAL" or "AI" mode.
When using "MANUAL", you have to configure an upper level and a lower level.
When using "AI", the upper and lower level are automatically calculated from last swing high/low.
Select the grid quantity, from 3 to 20.
Example with 3:
Example with 10:
Example with 20:
Creating the Alerts
When opening the alert popup, select "Cyato Grid" in the condition.
Make sure to use the option "Once per bar close" in order to stay in sync with the graphics on chart. (Only use "Once per bar" if you really know what you are doing).
Available alerts:
- BUY : Buy alert. Green label on chart.
- SELL: Sell alert. Red label on chart.
To get this indicator, use the link in my signature below, thanks!
Cari dalam skrip untuk "ai"
Intelligent Moving Average Private AccessNote: This indicator is intended for those who have been granted private access and may be more frequently updated than the previous versions.
Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Moving Average is the most used indicator on the planet, yet no one really knows what pair of moving average lengths works best in combination with each other.
A reason for this is because no two moving averages are always going to be the best on every instrument, time-frame, and at any given point in time.
The " Intelligent Moving Average " solves the moving average problem by adapting the period length to match the most profitable combination of moving averages in real time.
How does the Intelligent Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent Moving Average. Most will come with time as it is still a new concept.
Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
This indicator will be maintained and many updates will come in the near future! Stay tuned.
View the documentation on this indicator here: www.kenzing.com
Well Rounded Moving AverageIntroduction
There are tons of filters, way to many, and some of them are redundant in the sense they produce the same results as others. The task to find an optimal filter is still a big challenge among technical analysis and engineering, a good filter is the Kalman filter who is one of the more precise filters out there. The optimal filter theorem state that : The optimal estimator has the form of a linear observer , this in short mean that an optimal filter must use measurements of the inputs and outputs, and this is what does the Kalman filter. I have tried myself to Kalman filters with more or less success as well as understanding optimality by studying Linear–quadratic–Gaussian control, i failed to get a complete understanding of those subjects but today i present a moving average filter (WRMA) constructed with all the knowledge i have in control theory and who aim to provide a very well response to market price, this mean low lag for fast decision timing and low overshoots for better precision.
Construction
An good filter must use information about its output, this is what exponential smoothing is about, simple exponential smoothing (EMA) is close to a simple moving average and can be defined as :
output = output(1) + α(input - output(1))
where α (alpha) is a smoothing constant, typically equal to 2/(Period+1) for the EMA.
This approach can be further developed by introducing more smoothing constants and output control (See double/triple exponential smoothing - alpha-beta filter) .
The moving average i propose will use only one smoothing constant, and is described as follow :
a = nz(a ) + alpha*nz(A )
b = nz(b ) + alpha*nz(B )
y = ema(a + b,p1)
A = src - y
B = src - ema(y,p2)
The filter is divided into two components a and b (more terms can add more control/effects if chosen well) , a adjust itself to the output error and is responsive while b is independent of the output and is mainly smoother, adding those components together create an output y , A is the output error and B is the error of an exponential moving average.
Comparison
There are a lot of low-lag filters out there, but the overshoots they induce in order to reduce lag is not a great effect. The first comparison is with a least square moving average, a moving average who fit a line in a price window of period length .
Lsma in blue and WRMA in red with both length = 100 . The lsma is a bit smoother but induce terrible overshoots
ZLMA in blue and WRMA in red with both length = 100 . The lag difference between each moving average is really low while VWRMA is way more precise.
Hull MA in blue and WRMA in red with both length = 100 . The Hull MA have similar overshoots than the LSMA.
Reduced overshoots moving average (ROMA) in blue and WRMA in red with both length = 100 . ROMA is an indicator i have made to reduce the overshoots of a LSMA, but at the end WRMA still reduce way more the overshoots while being smoother and having similar lag.
I have added a smoother version, just activate the extra smooth option in the indicator settings window. Here the result with length = 200 :
This result is a little bit similar to a 2 order Butterworth filter. Our filter have more overshoots which in this case could be useful to reduce the error with edges since other low pass filters tend to smooth their amplitude thus reducing edge estimation precision.
Conclusions
I have presented a well rounded filter in term of smoothness/stability and reactivity. Try to add more terms to have different results, you could maybe end up with interesting results, if its the case share them with the community :)
As for control theory i have seen neural networks integrated to Kalman flters which leaded to great accuracy, AI is everywhere and promise to be a game a changer in real time data smoothing. So i asked myself if it was possible for a neural networks to develop pinescript indicators, if yes then i could be replaced by AI ? Brrr how frightening.
Thanks for reading :)
Optimised Volume-weighted Moving AverageAbout
This tool measures the profitability of every volume-weighted moving average length combination for the entire history of the instrument that it is applied,
and only displays the most profitable combination in real-time which means that this indicator is fully functional for trading.
The Optimised Volume-weighted Moving Average can be tested using a Volume-weighted Moving Average Strategy and the Strategy Tester panel on any instrument or time-stamp. It will always display the lengths of the most profitable exponential moving average lengths at the current moment in time.
This can be used on its own, or paired with the Intelligent Volume-weighted Moving Average (AI) for a better understanding of the indicators movements.
The Intelligent Volume-weighted Moving Average (AI) uses this tool as a predictive method for machine learning.
Optimised Exponential Moving AverageAbout
This tool measures the profitability of every exponential moving average length combination for the entire history of the instrument that it is applied and only displays the most profitable combination in real-time meaning that this indicator is fully functional for trading.
The Optimised Exponential Moving Average can be tested using an Exponential Moving Average strategy and the Strategy Tester panel on any instrument or time-stamp. It will always display the lengths of the most profitable exponential moving average lengths at the current moment in time.
This can be used on its own, or paired with the Intelligent Exponential Moving Average (AI) for a better understanding of the indicators movements.
The Intelligent Exponential Moving Average (AI) uses this tool as a predictive method for machine learning.
Lot Size Calculator (SL Percentage) - Futures ⚠️ IMPORTANT DISCLAIMER
This indicator is provided for educational and informational purposes only. The author assumes no responsibility for any financial losses, code errors, calculation mistakes, or trading decisions based on this tool. Use at your own risk and responsibility. Always manually verify calculations before opening real positions.
Contract size calculations are based on standard full-size futures contracts, not micro contracts (even though micro contracts are supported for identification).
Description
Money management tool for automatic calculation of optimal contract size (lot size) in futures trading. Supports over 50 futures instruments with pre-configured tick sizes and pip values for CME and other exchanges.
Supported Instruments
Currency Futures: 6J, 6E, 6B, 6A, 6C, 6S, 6N
Index Futures: ES, NQ, YM, RTY, MES, MNQ, MYM, M2K, NKD
Energy: CL, NG, HO, RB, QM
Metals: GC, SI, HG, MGC, SIL
Agricultural: ZC, ZS, ZW, HE, LE, ZO, ZR, ZM, ZL
Interest Rates: ZN, ZB, ZT, ZF
Crypto: MBT, MET
Others: VX
Main Parameters
Equity : Total available capital
Risk : Maximum risk percentage per trade
Stop Loss : Percentage distance of stop loss
Risk/Reward Ratio: Ratio to calculate take profit
Entry Price: Entry price (0 = current price)
Stop Loss Modes
Percentage Stop Loss (Use SL in % = ON):
Automatically calculates SL level as percentage from entry price
Example: Entry 100, SL 2% → Long SL at 98, Short SL at 102
Manual Stop Loss (Use SL in % = OFF):
Enter exact stop loss price directly
Greater precision for specific technical levels (support/resistance)
Interactive feature: You can drag the red stop loss line directly on the chart to modify the level in real-time
How to Use
Set equity and risk % according to your trading plan
Choose direction (Long/Short) and stop loss (percentage or price)
Enter entry price (optional)
Read the CONTRACT SIZE in the green table
Verify levels Entry/SL/TP on the graphic lines
Output
Information table with all parameters and highlighted CONTRACT SIZE
Graphic lines: Entry (blue), Stop Loss (red), Take Profit (green)
Configurable alerts with calculated values
Advantages
✅ Automatic calculation of optimal size
✅ Precise tick sizes for each instrument
✅ Systematic risk management
✅ Clear visual interface
✅ Multi-asset support on futures
Warnings
⚠️ Always verify that the instrument is recognized (no orange warning)
⚠️ Manually check calculations before trading
⚠️ Test in demo before using with real money
⚠️ Update regularly for any contract modifications
⚠️ DISCLAIMER IMPORTANTE
Questo indicatore è fornito esclusivamente a scopo educativo e informativo. L'autore non si assume alcuna responsabilità per eventuali perdite finanziarie, errori nel codice, calcoli errati o decisioni di trading basate su questo strumento. L'utilizzo è a proprio rischio e responsabilità. Si raccomanda di verificare sempre manualmente i calcoli prima di aprire posizioni reali.
I calcoli della dimensione del contratto sono basati su contratti futures standard full-size, non micro contratti (anche se i micro contratti sono supportati per l'identificazione).
Descrizione
Strumento di money management per il calcolo automatico della dimensione ottimale del contratto (lot size) nel trading di futures. Supporta oltre 50 strumenti futures con tick size e pip value pre-configurati per mercati CME e altri exchange.
Strumenti Supportati
Currency Futures: 6J, 6E, 6B, 6A, 6C, 6S, 6N
Index Futures: ES, NQ, YM, RTY, MES, MNQ, MYM, M2K, NKD
Energy: CL, NG, HO, RB, QM
Metals: GC, SI, HG, MGC, SIL
Agricultural: ZC, ZS, ZW, HE, LE, ZO, ZR, ZM, ZL
Interest Rates: ZN, ZB, ZT, ZF
Crypto: MBT, MET
Altri: VX
Parametri Principali
Equity : Capitale totale disponibile
Risk : Percentuale massima di rischio per trade
Stop Loss : Distanza percentuale dello stop loss
Risk/Reward Ratio: Rapporto per calcolare il take profit
Entry Price: Prezzo di entrata (0 = prezzo corrente)
Modalità Stop Loss
Stop Loss Percentuale (Use SL in % = ON):
Calcola automaticamente il livello SL come percentuale dal prezzo di entrata
Esempio: Entry 100, SL 2% → SL Long a 98, SL Short a 102
Stop Loss Manuale (Use SL in % = OFF):
Inserisci direttamente il prezzo esatto dello stop loss
Maggiore precisione per livelli tecnici specifici (supporti/resistenze)
Funzione interattiva: Puoi trascinare direttamente la linea rossa dello stop loss sul grafico per modificare il livello in tempo reale
Come Usare
Imposta equity e risk % secondo il tuo piano di trading
Scegli direzione (Long/Short) e stop loss (percentuale o prezzo)
Inserisci entry price (opzionale)
Leggi il CONTRACT SIZE nella tabella verde
Verifica i livelli Entry/SL/TP sulle linee grafiche
Output
Tabella informativa con tutti i parametri e il CONTRACT SIZE evidenziato
Linee grafiche: Entry (blu), Stop Loss (rosso), Take Profit (verde)
Alert configurabile con i valori calcolati
Vantaggi
✅ Calcolo automatico della size ottimale
✅ Tick size precisi per ogni strumento
✅ Risk management sistematico
✅ Interfaccia visiva chiara
✅ Supporto multi-asset su futures
Avvertenze
⚠️ Verifica sempre che lo strumento sia riconosciuto (no warning arancione)
⚠️ Controlla manualmente i calcoli prima di tradare
⚠️ Testa in demo prima dell'uso con denaro reale
⚠️ Aggiorna regolarmente per eventuali modifiche ai contratti
Rotation Strong HoldersStrong Holders Rotation
A mean reversion indicator with volatility-adjusted levels.
Concept:
The indicator is based on Mean Reversion Theory, which states that asset prices eventually return to their long-term average value. The greater the deviation from this mean value, the higher the probability of correction.
Unlike classical approaches that simply assume "the larger the deviation, the stronger the reversal," we've identified key threshold levels where reversal probability increases dramatically, generating high-confidence reversal signals.
Through extensive testing, we discovered that different stocks exhibit unique volatility profiles, making fixed threshold values ineffective. Our indicator dynamically adjusts overbought/oversold zones using:
- Beta coefficient (asset's sensitivity to market volatility)
- Multi-timeframe trend analysis (trend confirmation on higher timeframes)
- Adaptive Smoothed Moving Averages (SMMA)
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HOW TO USE
The indicator identifies three key zones:
1. Red (Upper) - Overbought zone, likely price reversal downward
2. Blue (Middle) - Shows the asset's current position relative to green and red zones, indicating overbought or oversold conditions
3. Green (Lower) - Oversold zone, potential upward bounce
Signals:
- Buy: When the blue line enters the zone where the stock price is too low to ignore (green band indicates oversold condition)
- Sell: When the blue line enters the zone where the stock price is too high to ignore (red band indicates overbought condition)
Dynamic Levels:
The overbought/oversold zone boundaries automatically adjust based on the beta coefficient (higher volatility assets have wider ranges)
Key Settings:
- `Base Index` (SPX, NDX, DJI) - Volatility comparison benchmark
- `Beta Calculation Period` - Lookback period (default: 252 days)
---
The indicator's background serves as a supplementary confirmation signal, using higher timeframe moving average crosses:
- Red background: Consider avoiding or selling the stock
- Green background: Favorable buying conditions
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Limitations:
- May generate false signals for:
✓ Stocks in extreme trends (e.g., NVDA during AI chip boom)
✓ Companies at risk of bankruptcy
- Not optimized for:
✓ Index trading
✓ Healthcare sector stocks
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Lux Qari AI Pro Master – By Rifaat QariFeature Details
✅ Smart Buy/Sell Signals Supported by trend, genuine breakouts, strong candles, and false signal filtering
✅ Dynamic Support/Resistance Automatically updated daily — displayed in a table
✅ Automatic TP/SL Automatically shown for each trade based on ATR and market range
✅ Golden Entry Zones "Golden Entries" when the market offers the best possible opportunity
✅ Real-Time Trend Analysis Filter based on immediate trend changes
✅ Sound + Message Alerts For every signal
✅ Live Dashboard Shows real-time win rate
✅ Powerful Hidden Indicators QQE + RSI + EMA + ATR applied logically — without visual clutter
✅ Daily Updated Table Displays all today's signals in a clear table
LANZ Strategy 1.0 [Backtest]🔷 LANZ Strategy 1.0 — Time-Based Session Trading with Smart Reversal Logic and Risk-Controlled Limit Orders
This backtest version of LANZ Strategy 1.0 brings precision to session-based trading by using directional confirmation, pre-defined risk parameters, and limit orders that execute overnight. Designed for the 1-hour timeframe, it allows traders to evaluate the system with configurable SL, TP, and risk settings in a fully automated environment.
🧠 Core Strategy Logic:
1. Directional Confirmation at 18:00 NY:
At 18:00 NY, the system compares the 08:00 open vs the 18:00 close:
If the direction matches the previous day, the signal is reversed.
If the direction differs, the current day's trend is kept.
This logic is designed to avoid momentum exhaustion and capture corrective reversals.
2. Entry Level Definition:
Based on the confirmed direction:
For BUY, the Low of the day is used as Entry Point (EP).
For SELL, the High of the day becomes EP.
The system plots a Stop Loss and Take Profit based on user-defined pip inputs (default: SL = 18 pips, TP = 54 pips → RR 1:3).
3. Time-Limited Entry Execution (LIMIT Orders):
Orders are sent after 18:00 NY and can be triggered anytime between 18:00 and 08:00 NY.
If EP is not touched before 08:00, the order is automatically cancelled.
4. Manual Close Feature:
If the trade is still open at the configured hour (default 09:00 NY), the system closes all positions, simulating realistic intraday exit scenarios.
5. Lot Size Calculation Based on Risk:
Lot size is dynamically calculated using the account size, risk percentage, and SL distance.
This ensures consistent risk exposure regardless of market volatility.
⚙️ Step-by-Step Flow:
08:00 NY → Captures the open of the day.
18:00 NY → Confirms direction and defines EP, SL, and TP.
After 18:00 NY → If conditions are met, a LIMIT order is placed at EP.
Between 18:00–08:00 NY → If price touches EP, the trade is executed.
At 08:00 NY → If EP wasn’t touched, the order is cancelled.
At Configured Manual Close Time (default 09:00 NY) → All open positions are force-closed if still active.
🧪 Backtest Settings:
Timeframe: 1-hour only
Order Type: strategy.entry() with limit=
SL/TP Configurable: Yes, in pips
Risk Input: % of capital per trade
Manual Close Time: Fully adjustable (default 09:00 NY)
👨💻 Credits:
Developed by LANZ
Strategy logic and trading concept built with clarity and precision.
Code structure and documentation by Kairos, your AI trading assistant.
Designed for high-confidence execution and clean backtesting performance.
LANZ Strategy 1.0🔷 LANZ Strategy 1.0 — Session-Based Directional Logic with Visual Multi-Account Risk Management
LANZ Strategy 1.0 is a structured and disciplined trading strategy designed for the 1-hour timeframe, operating during the NY session and executing trades overnight. It uses the directional behavior between 08:00 and 18:00 New York time to define precise limit entries for the following night. Ideal for traders who prefer time-based execution, clear visuals, and professional risk management across multiple accounts.
🧠 Core Components:
1. Session Direction Confirmation:
At 18:00 NY, the system evaluates the market direction by comparing the open at 08:00 vs the close at 18:00:
If the direction matches the previous day, it is reversed.
If it differs, the current day’s direction is kept.
This logic is designed to avoid trend exhaustion and favor potential reversal opportunities.
2. EP Level & Risk Definition:
Once direction is defined:
For BUY, EP is set at the Low of the session.
For SELL, EP is set at the High of the session.
The system automatically plots:
SL fixed at 18 pips from EP
TP at 3.00× the risk → 54 pips from EP
All levels (EP, SL, TP) are shown with visual lines and price labels.
3. Time-Restricted Entry Execution:
The entry is only valid if price touches the EP between 19:00 and 08:00 NY.
If EP is not touched before 08:00 NY, the trade is automatically cancelled.
4. Multi-Account Lot Sizing:
Traders can configure up to five different accounts, each with its own capital and risk percentage.
The system calculates and displays the lot size per account, based on SL distance and pip value, in a dynamic floating label.
5. Outcome Tracking:
If TP is hit, a +3.00% profit label is displayed along with a congratulatory alert.
If SL is hit, a -1.00% label appears with a loss alert.
If the trade is still open by 09:00 NY, it is manually closed, and the result is shown as a percentage of the initial risk.
📊 Visual Features:
Custom-colored angle and guide lines.
Dynamic angle line starts at 08:00 NY and tracks price until 18:00.
Shaded backgrounds for key time zones (e.g., 08:00, 18:00, 19:00).
BUY/SELL signals shown at 19:00 based on match/divergence logic.
Label panel showing risk metrics and lot size for each active account.
⚙️ How It Works:
08:00 NY: Marks the session open and initiates a dynamic angle line.
18:00 NY: Evaluates the session direction and calculates EP/SL/TP based on outcome.
19:00 NY: Activates limit order monitoring.
During the night (until 08:00 NY): If EP is touched, the trade is triggered.
At 08:00 NY: If no touch occurred, trade is cancelled.
Overnight: TP/SL logic is enforced, showing percentage outcomes.
At 09:00 NY: If still open, trade is closed manually and result is labeled visually.
🔔 Alerts:
🚀 EP execution alert when touched
💢 Stop Loss hit alert
⚡ Take Profit hit alert
✅ Manual close at 09:00 NY with performance result
🔔 Daily reminder at 19:00 NY to configure and prepare the trade
📝 Notes:
Strategy is exclusive to the 1-hour timeframe.
Works best on assets with clean NY session movement.
Perfect for structured, semi-automated swing/overnight trading styles.
Fully visual, self-explanatory, and backtest-friendly.
👨💻 Credits:
Developed by LANZ
A strategy created with precision, discipline, and a vision for traders who value time-based entries, clean execution logic, and visual confidence on the chart.
Special thanks to Kairos — your AI assistant — for the detailed structure, scripting, and documentation of the strategy.
XAUUSD Smart AI Strategy v1.2spodfjkpsdogfjkpod
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Simple Pips GridOverview
This is a clean, simple, and highly practical indicator that draws horizontal grid lines at user-defined pip intervals.
Unlike other complex grid indicators, this script is designed to be lightweight and error-free. It eliminates automatic symbol detection and instead gives you full manual control, ensuring it works perfectly with any symbol you trade—FX, CFDs, Crypto, Stocks, Indices, and more.
Key Features
Universal Compatibility: Works with any trading pair by letting you manually define the pip value.
Fully Customizable: Easily set the pip interval for your grid (e.g., 10 pips, 50 pips, 100 pips).
Lightweight & Fast: Simple code ensures smooth performance without lagging your chart.
Visual Customization: Change the color, width, and style (solid, dashed, dotted) of the grid lines.
How to Use
It's incredibly simple to set up. You only need to configure two main settings:
Step 1: Set the "Pip Value"
This is the most important setting. You need to tell the indicator what "1 pip" means for the symbol you are currently viewing.
Go to the indicator settings and find the "Pip Value" input. Here are some common examples:
Symbol Pip Value (Input this number)
USD/JPY 0.01
EUR/USD 0.0001
GBP/USD 0.0001
XAU/USD (Gold) 0.1
JP225 (Nikkei 225) 10
US500 (S&P 500) 1
BTC/USD 0.1 or 1.0 (depending on your preference)
Step 2: Set the "Pip Interval"
Next, in the "Pip Interval" input, simply type how many pips you want between each line.
For a 10-pip grid, enter 10.
For a 50-pip grid, enter 50.
That's it! The grid will now be perfectly aligned to your specifications.
Additional Settings
Line Color, Width, Style: Customize the appearance of the lines to match your chart theme.
Number of Lines: Adjust how many lines are drawn above and below the current price to optimize performance and visibility.
This script was created with the assistance of Gemini (Google's AI) to be a simple and reliable tool for all traders. Feel free to use and modify it. Happy trading!
Timeframe Resistance Evaluation And Detection - CoffeeKillerTREAD - Timeframe Resistance Evaluation And Detection Guide
🔔 Important Technical Limitation 🔔
**This indicator does NOT fetch true higher timeframe data.** Instead, it simulates higher timeframe levels by aggregating data from your current chart timeframe. This means:
- Results will vary depending on what chart timeframe you're viewing
- Levels may not match actual higher timeframe candle highs/lows
- You might miss important wicks or gaps that occurred between chart timeframe bars
- **Always verify levels against actual higher timeframe charts before trading**
Welcome traders! This guide will walk you through the TREAD (Timeframe Resistance Evaluation And Detection) indicator, a multi-timeframe analysis tool developed by CoffeeKiller that identifies support and resistance confluence across different time periods.(I am 50+ year old trader and always thought I was bad a teaching and explaining so you get a AI guide. I personally use this on the 5 minute chart with the default settings, but to each there own and if you can improve the trend detection methods please DM me. I would like to see the code. Thanks)
Core Components
1. Dual Timeframe Level Tracking
- Short Timeframe Levels: Tracks opening price extremes within shorter periods
- Long Timeframe Levels: Tracks actual high/low extremes within longer periods
- Dynamic Reset Mechanism: Levels reset at the start of each new timeframe period
- Momentum Detection: Identifies when levels change mid-period, indicating active price movement
2. Visual Zone System
- High Zones: Areas between long timeframe highs and short timeframe highs
- Low Zones: Areas between long timeframe lows and short timeframe lows
- Fill Coloring: Dynamic colors based on whether levels are static or actively changing
- Momentum Highlighting: Special colors when levels break during active periods
3. Customizable Display Options
- Multiple Plot Styles: Line, circles, or cross markers
- Flexible Timeframe Selection: Wide range of short and long timeframe combinations
- Color Customization: Separate colors for each level type and momentum state
- Toggle Controls: Show/hide different elements based on trading preference
Main Features
Timeframe Settings
- Short Timeframe Options: 15m, 30m, 1h, 2h, 4h
- Long Timeframe Options: 1h, 2h, 4h, 8h, 12h, 1D, 1W
- Recommended Combinations:
- Scalping: 15m/1h or 30m/2h
- Day Trading: 30m/4h or 1h/4h
- Swing Trading: 4h/1D or 1D/1W
Display Configuration
- Level Visibility: Toggle short/long timeframe levels independently
- Fill Zone Control: Enable/disable colored zones between levels
- Momentum Fills: Special highlighting for actively changing levels
- Line Customization: Width, style, and color options for all elements
Color System
- Short TF High: Default red for resistance levels
- Short TF Low: Default green for support levels
- Long TF High: Transparent red for broader resistance context
- Long TF Low: Transparent green for broader support context
- Momentum Colors: Brighter colors when levels are actively changing
Technical Implementation Details
How Level Tracking Works
The indicator uses a custom tracking function that:
1. Detects Timeframe Periods: Uses `time()` function to identify when new periods begin
2. Tracks Extremes: Monitors highest/lowest values within each period
3. Resets on New Periods: Clears tracking when timeframe periods change
4. Updates Mid-Period: Continues tracking if new extremes are reached
The Timeframe Limitation Explained
`pinescript
// What the indicator does:
short_tf_start = ta.change(time(short_timeframe)) != 0 // Detects 30m period start
= track_highest(open, short_tf_start) // BUT uses chart TF opens!
// What true multi-timeframe would be:
// short_tf_high = request.security(syminfo.tickerid, short_timeframe, high)
`
This means:
- On a 5m chart with 30m/4h settings: Tracks 5m bar opens during 30m and 4h windows
- On a 1m chart with same settings: Tracks 1m bar opens during 30m and 4h windows
- Results will be different between chart timeframes
- May miss important price action that occurred between your chart's bars
Visual Elements
1. Level Lines
- Short TF High: Upper resistance line from shorter timeframe analysis
- Short TF Low: Lower support line from shorter timeframe analysis
- Long TF High: Broader resistance context from longer timeframe
- Long TF Low: Broader support context from longer timeframe
2. Zone Fills
- High Zone: Area between long TF high and short TF high (potential resistance cluster)
- Low Zone: Area between long TF low and short TF low (potential support cluster)
- Regular Fill: Standard transparency when levels are static
- Momentum Fill: Enhanced visibility when levels are actively changing
3. Dynamic Coloring
- Static Periods: Normal colors when levels haven't changed recently
- Active Periods: Momentum colors when levels are being tested/broken
- Confluence Zones: Different intensities based on timeframe alignment
Trading Applications
1. Support/Resistance Trading
- Entry Points: Trade bounces from zone boundaries
- Confluence Areas: Focus on areas where short and long TF levels cluster
- Zone Breaks: Enter on confirmed breaks through entire zones
- Multiple Timeframe Confirmation: Stronger signals when both timeframes align
2. Range Trading
- Zone Boundaries: Use fill zones as range extremes
- Mean Reversion: Trade back toward opposite zone when price reaches extremes
- Breakout Preparation: Watch for momentum color changes indicating potential breakouts
- Risk Management: Place stops outside the opposite zone
3. Trend Following
- Direction Bias: Trade in direction of zone breaks
- Pullback Entries: Enter on pullbacks to broken zones (now support/resistance)
- Momentum Confirmation: Use momentum coloring to confirm trend strength
- Multiple Timeframe Alignment: Strongest trends when both timeframes agree
4. Scalping Applications
- Quick Bounces: Trade rapid moves between zone boundaries
- Momentum Signals: Enter when momentum colors appear
- Short-Term Targets: Use opposite zone as profit target
- Tight Stops: Place stops just outside current zone
Optimization Guide
1. Timeframe Selection
For Different Trading Styles:
- Scalping: 15m/1h - Quick levels, frequent updates
- Day Trading: 30m/4h - Balanced view, good for intraday moves
- Swing Trading: 4h/1D - Longer-term perspective, fewer false signals
- Position Trading: 1D/1W - Major structural levels
2. Chart Timeframe Considerations
**Important**: Your chart timeframe affects results
- Lower Chart TF: More granular level tracking, but may be noisy
- Higher Chart TF: Smoother levels, but may miss important price action
- Recommended: Use chart timeframe 2-4x smaller than short indicator timeframe
3. Display Settings
- Busy Charts: Disable fills, show only key levels
- Clean Analysis: Enable all fills and momentum coloring
- Multi-Monitor Setup: Use different color schemes for easy identification
- Mobile Trading: Increase line width for visibility
Best Practices
1. Level Verification
- Always Cross-Check: Verify levels against actual higher timeframe charts
- Multiple Timeframes: Check 2-3 different chart timeframes for consistency
- Price Action Confirmation: Wait for candlestick confirmation at levels
- Volume Analysis: Combine with volume for stronger confirmation
2. Risk Management
- Stop Placement: Use zones rather than exact prices for stops
- Position Sizing: Reduce size when zones are narrow (higher risk)
- Multiple Targets: Scale out at different zone boundaries
- False Break Protection: Allow for minor zone penetrations
3. Signal Quality Assessment
- Momentum Colors: Higher probability when momentum coloring appears
- Zone Width: Wider zones often provide stronger support/resistance
- Historical Testing: Backtest on your preferred timeframe combinations
- Market Conditions: Adjust sensitivity based on volatility
Advanced Features
1. Momentum Detection System
The indicator tracks when levels change mid-period:
`pinescript
short_high_changed = short_high != short_high and not short_tf_start
`
This identifies:
- Active level testing
- Potential breakout situations
- Increased market volatility
- Trend acceleration points
2. Dynamic Color System
Complex conditional logic determines fill colors:
- Static Zones: Regular transparency for stable levels
- Active Zones: Enhanced colors for changing levels
- Mixed States: Different combinations based on user preferences
- Custom Overrides: User can prioritize certain color schemes
3. Zone Interaction Analysis
- Convergence: When short and long TF levels approach each other
- Divergence: When timeframes show conflicting levels
- Alignment: When both timeframes agree on direction
- Transition: When one timeframe changes while other remains static
Common Issues and Solutions
1. Inconsistent Levels
Problem: Levels look different on various chart timeframes
Solution: Always verify against actual higher timeframe charts
2. Missing Price Action
Problem: Important wicks or gaps not reflected in levels
Solution: Use chart timeframe closer to indicator's short timeframe setting
3. Too Many Signals
Problem: Excessive level changes and momentum alerts
Solution: Increase timeframe settings or reduce chart timeframe granularity
4. Lagging Signals
Problem: Levels seem to update too slowly
Solution: Decrease chart timeframe or use more sensitive timeframe combinations
Recommended Setups
Conservative Approach
- Timeframes: 4h/1D
- Chart: 1h
- Display: Show fills only, no momentum coloring
- Use: Swing trading, position management
Aggressive Approach
- Timeframes: 15m/1h
- Chart: 5m
- Display: All features enabled, momentum highlighting
- Use: Scalping, quick reversal trades
Balanced Approach
- Timeframes: 30m/4h
- Chart: 15m
- Display: Selective fills, momentum on key levels
- Use: Day trading, multi-session analysis
Final Notes
**Remember**: This indicator provides a synthetic view of multi-timeframe levels, not true higher timeframe data. While useful for identifying potential confluence areas, always verify important levels by checking actual higher timeframe charts.
**Best Results When**:
- Combined with actual multi-timeframe analysis
- Used for confluence confirmation rather than primary signals
- Applied with proper risk management
- Verified against price action and volume
**DISCLAIMER**: This indicator and its signals are intended solely for educational and informational purposes. The timeframe limitation means results may not reflect true higher timeframe levels. Always conduct your own analysis and verify levels independently before making trading decisions. Trading involves significant risk of loss.
LiquidEdge Original1️⃣ Why Most Traders Miss Key Market Turning Points
Most traders (you) struggle to identify true market pivots THE REAL TOP and BOTTOMS where reversals begin.
❌ You enter too early or too late because price alone doesn’t give enough confirmation
❌ You follow price blindly, unaware of the volume pressure building underneath
❌ You get caught in sideways markets, not realizing they’re often accumulation or distribution zones
❌ You can’t tell if momentum is building or fading, which leads to low confidence and inconsistent results
👉 LiquidEdge helps solve this by tracking volume momentum through a modified MFI slope and scoring system. It highlights potential pivots with real context, so you can see where smart money might be entering or exiting before price makes it obvious.
2️⃣ What LiquidEdge Actually Does and How
LiquidEdge helps solve common trading problems by adding structure and clarity to volume analysis.
✅ It builds on the classic Money Flow Index (MFI), but instead of just showing overbought/oversold levels, it calculates the slope of MFI to track real-time changes in volume momentum
✅ Each setup is scored based on a combination of factors: divergence strength, trend alignment using EMA, and whether the signal occurs inside a liquidity zone
✅ Hidden accumulation or distribution is revealed when volume pressure increases or fades while price remains flat or moves slightly, a sign of smart money positioning
✅ Divergences are only flagged when they occur near pivot zones and align with overall trend conditions, helping reduce false signals
✅ Potential pivots are identified when multiple factors overlap such as a liquidity zone breach, volume slope shift, and valid divergence which often signals entry or exit points for institutional players
👉 The result is a structured interpretation of price and volume flow, helping traders read momentum shifts and potential reversals more clearly in both trending and ranging markets.
3️⃣ What Makes LiquidEdge Different
LiquidEdge is built on top of the classic Money Flow Index (MFI), but adds structure that transforms it from a basic momentum tool into a decision-support system.
Instead of simply showing highs and lows, it scores each potential setup based on:
✅ The steepness and direction of the MFI slope (used to measure volume pressure)
✅ Whether the setup aligns with the broader trend using an EMA filter (default: 200 EMA)
✅ Whether the signal appears inside predefined liquidity zones (MFI above 80 or below 20)
👉 This scoring system reduces noise and helps you focus only on high-probability setups.
👉 It also checks volume pressure across multiple timeframes using MFI slope on 5M, 15M, 1H, 4H, and Daily charts. This reveals whether short-term moves are backed by longer-term volume momentum.
Color changes in the line and histogram are not decorative they reflect real shifts in volume pressure. Every visual cue is linked to live market logic.
What Makes It Stand Out
👉 Setup Scoring That Makes Sense
Each setup is scored by combining:
Signal strength (MFI slope intensity and stability)
Trend direction (via customizable EMA)
Liquidity zone relevance (MFI range filtering)
This structured scoring means you spend less time second-guessing and more time reading clean signals.
👉 Flow That Follows Real Momentum
The slope of the MFI tracks whether volume pressure is rising or falling:
🟢 Green = increasing inflow (buying pressure)
🔴 Red = increasing outflow (selling pressure)
👉 Multi-Timeframe Volume Context
LiquidEdge calculates flow direction independently on each major timeframe. You’ll know if short-term setups are confirmed by higher timeframe volume or going against it.
👉 Smart Divergence Filtering
Unlike simple divergence tools that compare price highs/lows directly, LiquidEdge filters divergences based on:
Local pivot zones (defined by lookback periods)
Trend confirmation (to eliminate countertrend noise)
4️⃣ How LiquidEdge Works (Under the Hood)
LiquidEdge tracks directional momentum using the slope of the Money Flow Index (MFI) giving you a real-time read on buying and selling pressure.
When the slope rises, it means buyers are stepping in and volume is supporting the move.
When it falls, sellers are taking control and volume outflow is increasing.
This slope acts like a pressure gauge for the market, helping you spot when a trend has strength or when it's starting to fade.
💡 Quick Comparison
RSI = momentum from price
MFI = momentum from price + volume
LiquidEdge takes it one step further by calculating the rate of change (slope) in MFI. That’s where the pressure signal comes from not just value, but directional flow.
Core Calculations (Simplified)
Typical Price = (High + Low + Close) ÷ 3
Raw Money Flow = Typical Price × Volume
MFI = 100 −
MFI ranges from 0 to 100.
High = strong buying volume
Low = growing selling pressure
LiquidEdge then calculates the slope of this MFI over time to track volume momentum dynamically.
Divergence Engine
LiquidEdge detects divergence by comparing price pivots with the direction of MFI slope.
❌ If price makes a higher high but MFI slope turns down, it’s a bearish divergence
✅ If price makes a lower low but MFI slope rises, it’s a bullish divergence
Divergences are only confirmed when they occur:
Near local pivot zones (defined by configurable lookback windows)
And, optionally, in alignment with the broader trend using an EMA filter
This filtering helps reduce false positives and keeps you focused on clean setups.
Structured Confidence Scoring
Each signal is visually scored based on:
➡️ Whether a valid divergence is detected
➡️ Whether the signal occurs inside a liquidity zone (MFI > 80 or < 20)
➡️ Whether the setup aligns with the overall trend direction (EMA filter)
More confluence = higher confidence
The scoring system helps prioritize setups that meet multiple criteria, not just one.
Liquidity Zones
Above 80: Signals possible buying exhaustion 👉 risk of reversal
Below 20: Indicates potential selling exhaustion 👉 watch for a bounce
Zones are shaded directly on the chart to highlight pressure extremes in real time.
Price + Volume Fusion
LiquidEdge blends price action with volume pressure using MFI slope and histogram behavior. It doesn’t just show you where price is moving. it shows whether the move is backed by real volume.
This lets you see:
Whether volume is confirming or fading behind a move
If a reversal is building even before price confirms it
Visual Feedback That Speaks Clearly
🟢 Green slope = increasing buying pressure
🔴 Red slope = increasing selling pressure
5️⃣ When Price Is Flat but LiquidEdge Moves: Volume Tells the Truth
One of the most useful things LiquidEdge can do is reveal pressure shifts when price looks neutral.
If price is moving sideways but the MFI slope or histogram rises, it may suggest that buying pressure is quietly increasing possibly pointing to early accumulation.
If price stays flat while the volume slope or histogram drops, this could indicate distribution, where sellers are exiting without moving the market noticeably.
These changes don’t guarantee a breakout or breakdown, but they often precede key moves especially when combined with other confluences like trend alignment or liquidity zones.
👉 LiquidEdge helps spot these setups by measuring volume momentum shifts beneath price action.
It doesn’t predict the future, but it gives you additional context to evaluate what may be developing before it’s visible on price alone.
6️⃣ Multi-Timeframe Flow Table
LiquidEdge includes a real-time table that tracks volume pressure across multiple timeframes including 5-minute, 15-minute, 1-hour, 4-hour, and daily charts.
Each row reflects the direction of the MFI slope on that timeframe, indicating whether volume pressure is increasing (inflow) or decreasing (outflow).
🟢 A rising slope suggests that buying momentum is building
🔴 A falling slope suggests selling pressure may be increasing
👉 This lets traders quickly assess whether short-term setups are aligned with higher timeframe volume trends a useful layer of confirmation for both intraday and swing strategies.
Rather than flipping between charts, the table gives you a snapshot of flow strength across the board, helping you stay focused on opportunities that align with broader market pressure.
7️⃣ Timeframes & Assets
Where LiquidEdge Works Best:
✅ Crypto: Supports major coins and high-volume altcoins (BTC, ETH, Top 100)
✅ Stocks: Effective on large-cap and mid-cap equities with consistent volume
✅ Futures: Tested on instruments like NQ, MNQ, ES, and MES
✅ Any liquid market where volume data is reliable and stable
For best results, use LiquidEdge on assets with consistent trading volume. It’s not recommended for ultra-low volume crypto pairs or micro-cap stocks, where irregular volume can distort signals.
Recommended Timeframes:
👉 Intraday trading: Works well on 3-minute, 5-minute, 15-minute, and 1-hour charts
👉 Swing trading: Performs reliably on 4-hour, daily, and weekly charts
👉 Ultra short-term (1-minute or less): Not recommended due to high noise and low reliability
LiquidEdge adapts to various trading styles from scalping short-term momentum shifts to analyzing broader volume trends across swing and positional setups. The key is choosing assets and timeframes with reliable volume flow for the tool to work effectively.
8️⃣ Common Mistakes to Avoid When Using LiquidEdge
❌ Using It in Isolation
LiquidEdge offers valuable context, but it’s not designed to function as a standalone trading system. Always combine it with key tools such as trendlines, support/resistance zones, chart structure, or fundamental data. The more supporting evidence you have, the stronger your analysis becomes.
❌ Relying on a Single Indicator
No indicator, including LiquidEdge, can account for every market condition. It’s important to use it alongside other forms of confirmation to avoid making decisions based on limited data.
❌ Misinterpreting Divergences as Reversals
A divergence between price and volume pressure doesn't always signal the end of a trend. If the broader direction remains strong (based on EMAs or higher timeframe volume flow), a divergence could reflect temporary consolidation rather than reversal.
❌ Ignoring Trend Alignment and Confidence Scoring
LiquidEdge includes confidence scoring to help validate signals. Disregarding this structure can lead to reacting to weak or out-of-context divergences, especially in choppy or low-volume environments.
❌ Using It on Second-Based or Tick Charts
Very low timeframes introduce too much noise, which can distort volume slope and divergence signals. For intraday analysis, start with 3-minute charts or higher. For swing trading, use 4H and up for clearer, more reliable structure.
9️⃣ LiquidEdge Settings Overview
A quick breakdown of what you can customize in the indicator and how each option affects what you see:
➡️ LiquidEdge Length
Controls how sensitive the indicator is to changes in volume pressure (via MFI slope).
Shorter values = faster response, more frequent signals
Longer values = smoother output, less noise
👉 Default: 14
➡️ EMA Trend Filter
Determines overall trend direction based on EMA slope. Used to filter out signals that go against the broader move.
Helps reduce countertrend entries
Adjustable to suit your strategy
👉 Recommended: 200 EMA
➡️ Pivot Lookback (Left & Right)
Defines how many bars the system looks back and forward to identify swing highs/lows for divergence detection.
Narrow: more responsive but can be noisy
Wide: slower but more stable pivot zones
👉 Default: 5 left / 5 right
➡️ Histogram Toggle
Enables a visual histogram showing how volume pressure deviates from its recent average.
Useful for spotting shifts in flow intensity
👉 Optional for added visual detail
➡️ Liquidity Zones
Highlights potential exhaustion zones based on MFI value:
Above 80 = potential distribution (buying pressure peaking)
Below 20 = possible accumulation (selling pressure fading)
👉 Zones are fully customizable (color, opacity, background)
➡️ Custom Threshold Zones
Set your own upper/lower boundaries for liquidity extremes helpful when adapting to different markets or asset classes.
👉 Especially useful outside of crypto/forex
➡️ Show LiquidEdge Line
Toggle the main MFI slope line. When turned off, liquidity zones and levels also disappear.
👉 Use if you prefer to focus only on histogram/divergences
➡️ Style Settings
Customize line colors, histogram appearance, and background shading
👉 Helps tailor visuals to your chart layout
➡️ Simplified Mode
Removes all colors and replaces visuals with a clean, grayscale output.
👉 Ideal for minimalist or distraction-free charting
➡️ Signal Score Label
Displays the confidence score of the current setup, based on:
Divergence presence
Liquidity zone positioning
Trend alignment (EMA)
👉 Tooltip explains how the score is calculated
➡️ Divergence Labels
Shows “Bullish” or “Bearish” labels at divergence points.
Optional Filters based on trend if EMA filter is active
➡️ Multi-Timeframe Flow Table
Shows directional flow (based on MFI slope) across: 5M, 15M, 1H, 4H, 1D
Color-coded (faded green/red) for clarity
👉 Table position is customizable on your chart
➡️ Alerts
Get notified when any of these conditions are met:
✅ Bullish or bearish divergence detected
✅ Price enters high/low liquidity zones
✅ Signal score reaches a defined value
➡️ Visibility Settings
Control which timeframes display the LiquidEdge indicator
👉 Best used on 3-minute and above
⚠️ Not recommended on ultra-low or second-based charts due to noise
🔟 Q&A – What Traders Usually Ask
➡️ Can this help reduce bad trades?
To a degree, yes. LiquidEdge is built to highlight areas where price may react, based on volume pressure, liquidity zones, and divergence patterns. It can offer clarity in sideways or messy markets, helping traders avoid impulsive or poorly timed entries.
That said, it’s not predictive or guaranteed. It works best when used with broader context including structure, support/resistance, trend, and volume-based confluence.
👉 Reminder: LiquidEdge is not a signal tool. It’s a decision-support framework designed to help you assess potential shifts, not replace judgment or trading rules.
➡️ Is this just another flashy signal tool?
No. LiquidEdge doesn’t give buy/sell alerts. Instead, it visualizes volume shifts using MFI slope, divergence filtering, and trend-based scoring. It’s built to help you understand why price action may be changing not just react to a one-dimensional signal.
You’re seeing how volume pressure evolves across timeframes, which gives added context to what’s unfolding in the market.
➡️ How do I know this isn’t just another overhyped tool?
LiquidEdge is based on real trading logic: volume pressure (via MFI slope), price behavior, and divergence within trend and liquidity zones. It was developed and tested by traders, not packaged by marketers.
No performance is guaranteed. It’s designed to support your decisions not promise results.
➡️ Will this work with my trading style?
If you trade any market with volume crypto, stocks, or futures LiquidEdge can add value.
✔️ Scalpers: Best from 3-minute and up
✔️ Swing traders: Works well on 4H, Daily, Weekly
✔️ Investors: Weekly charts show pressure buildup over time
⚠️ Avoid ultra-low timeframes (under 1M) or illiquid markets, as noise and irregular data can reduce reliability.
➡️ Can I trust the signals?
These are not buy/sell signals. LiquidEdge offers confidence-weighted insights based on:
✔️ Valid divergence
✔️ Zone positioning (above 80 / below 20)
✔️ Optional trend alignment (via EMA)
Each setup is scored visually to reflect how much confluence exists. You can combine that information with structure, price action, or your existing tools to evaluate opportunities.
👉 Think of LiquidEdge as a decision filter not a trigger.
It’s meant to slow down impulsive trades and help you make more context-aware decisions.
1️⃣1️⃣ Limitations – Know When It’s Less Effective
LiquidEdge performs best in stable, high-volume markets where volume data is consistent and structure is visible.
It’s not recommended for:
❌ Low-volume tokens
❌ Micro-cap or penny stocks
❌ Newly listed assets with limited trading history
These types of markets often show inconsistent or erratic volume behavior, making it difficult for LiquidEdge to accurately assess pressure or identify reliable divergences.
⚠️ During major news events or sudden volatility spikes, volume and price behavior can become disconnected or extreme. This may distort MFI slope calculations and reduce the accuracy of divergence or confidence scoring.
LiquidEdge is built to read structured volume flow. When market conditions become highly erratic or unpredictable, it's best to:
Wait for structure to return
Use it alongside other filters for additional confirmation
This isn't a flaw it's simply the nature of tools that rely on consistency in price and volume data.
1️⃣2️⃣ Real Chart Examples – See It in Action
Now that you’ve seen how LiquidEdge works, here are real-world chart examples from various asset classes
including:
✅ Crypto
✅ Stocks
✅ Futures
✅ Commodities
These examples demonstrate how LiquidEdge behaves under different conditions, and how both the line (MFI slope) and histogram (volume deviation) can be used to interpret market flow.
In each walkthrough, you’ll see:
How the histogram can highlight potential momentum shifts
When the slope line provides stronger directional clarity
Examples of possible hidden accumulation or distribution (before price responds)
What to watch out for such as weak volume, false divergences, or conflicting flow signals
👉 These are real examples based on live market data not theoretical setups. They’re meant to help you recognize how LiquidEdge reacts across multiple styles and timeframes.
Let’s walk through each one and break down the logic step by step, so you can understand how to evaluate setups using structure, volume behavior, and context-driven confluence.
Example: Microsoft (MSFT) – Possible Hidden Accumulation
In this setup, price was moving lower within a short-term downtrend. However, LiquidEdge began showing signs of increasing inflow pressure a common characteristic of accumulation, where volume rises even as price declines.
This divergence suggested that buying interest may have been increasing behind the scenes, despite weak price action on the surface.
Step-by-step breakdown:
👉 Trend context – Price was clearly trending down at the time
👉 Volume divergence – Price made lower lows, but LiquidEdge slope was rising = possible bullish divergence
👉 Accumulation clue – The rising slope, despite falling price, pointed to volume inflow often seen during quiet accumulation
👉 Histogram support – Volume pressure (via the histogram) also increased, confirming the flow shift
👉 Anticipating reaction – When liquidity pressure rises ahead of price, it can signal potential reversal interest
In this case, price later moved sharply higher. While not guaranteed, setups like this illustrate how divergence + volume flow may help highlight early accumulation zones before price confirms the shift.
Same Setup – Focusing on the Histogram Alone
Here, we’re revisiting the Microsoft setup but this time focusing only on the histogram, without the MFI slope line.
Even without the directional slope, the histogram showed rising volume pressure while price continued to drift lower. This visual pattern may indicate that buying interest was quietly increasing, despite weak price movement.
This is where the histogram adds value: it helps visualize the intensity of volume flow over time. When volume pressure builds during a flat or declining price phase, it can be consistent with accumulation where larger participants begin positioning before the market responds.
This example highlights how the histogram alone can provide early insight into underlying volume dynamics even before price shifts noticeably.
Filtering with EMA and why It Matters
Here, we revisit the Microsoft example this time applying the 200 EMA filter, which helps define the broader trend.
Once enabled, LiquidEdge automatically removed any bullish or bearish divergence signals that were against the prevailing trend. This helped reduce noise and focus only on setups aligned with market structure.
✅ The EMA acts as a contextual filter.
For example, if a bullish divergence occurs during a confirmed downtrend, LiquidEdge suppresses that signal helping you avoid setups that may carry more risk.
This filtering mechanism is especially useful in fast or choppy markets, where not all divergences are meaningful.
Want More Flexibility? Adjust the Filter
If you're a more aggressive trader or prefer shorter-term signals, you can reduce the EMA length (e.g., to 150, 50, or even 25). This increases the number of setups shown but also raises the importance of additional context and confirmation.
⚠️ Keep in mind:
❌ More signals doesn’t always mean better outcomes
✅ Focused, context-aware signals tend to be more consistent with broader market pressure
If you’re using this in combination with strategies like options trading, this filter can help refine your entry zones especially when paired with other structure or volatility tools.
Distribution Example and Bitcoin Setup Before a Major Drop
In this example, Bitcoin was trading in a relatively tight range while price continued to push upward. However, LiquidEdge began to show signs of volume outflow, which can suggest potential distribution.
Here’s what was observed:
🔴 Price was moving up inside a horizontal range
🔴 LiquidEdge’s slope indicated declining volume pressure
🔴 Several bearish divergence signals appeared during this consolidation phase
🔴 The histogram also showed weakening flow, even before price broke down
These overlapping signals pointed to a possible distribution phase, where buying momentum was fading despite price still holding up.
🧭 Signs to Watch for in Potential Distribution:
1️⃣ Price holding flat or rising slightly within a tight range
2️⃣ Volume pressure (line or histogram) sloping downward
3️⃣ Repeated bearish divergences forming at the highs
4️⃣ Lack of follow-through on bullish setups signaling hesitation in demand
While LiquidEdge can’t predict market outcomes, this scenario demonstrates how a combination of divergence, outflow, and failure to break out may serve as early warnings that momentum is shifting beneath the surface.
Failed Auction Example – Volume Shift Before a Breakdown
In this example, price attempted to break out above a recent high, creating the appearance of a bullish continuation. However, LiquidEdge began to signal volume outflow, despite the upward price move a potential sign of a failed auction.
Here’s what was observed:
👉 Price made a new high, appearing to break resistance
👉 LiquidEdge slope and histogram both showed declining liquidity
👉 The indicator formed lower lows, even as price pushed higher
👉 This divergence suggested that volume wasn’t supporting the breakout
Shortly after, price reversed and returned back inside the range which is a common characteristic of failed auction behavior.
🧭 Spotting a Potential Failed Auction with LiquidEdge:
1️⃣ Price breaks above a recent high
2️⃣ Volume flow (line + histogram) shows outflow, not inflow
3️⃣ Indicator forms lower lows while price makes higher highs (bearish divergence)
4️⃣ Market reverts back into the previous range without follow-through
While no tool can predict outcomes, this setup demonstrated how volume pressure and divergence can help identify moments where a breakout may lack real support offering context before price action confirms the shift.
Reading the Histogram - Spotting Pressure Fades
In this example, price was still rising but the LiquidEdge histogram showed falling volume pressure. This type of divergence between price and volume can serve as a potential early signal that momentum may be fading.
🔻 Histogram levels declined while price continued higher
🔻 This suggested that buying pressure was weakening, even though price hadn’t turned
🔻 Volume flow behavior didn’t support the continuation possibly indicating buyer exhaustion
Just before the peak, the histogram nearly reached its lower threshold, despite price still being near its highs.
💡 How to Read It:
When volume pressure (shown by the histogram) starts to fade while price is still rising, it can indicate that momentum is weakening. This may precede a pullback or reversal particularly if other factors like divergence or zone exhaustion are also present.
Conversely, rising histogram values during a price drop may suggest potential accumulation.
👉 Use the histogram as a volume intensity gauge, not a signal on its own especially when evaluating whether a move is supported by actual flow, or just price momentum.
The Table – Fast, Visual Multi-Timeframe Flow Insight
The multi-timeframe flow table in LiquidEdge provides a consolidated view of volume momentum across several key timeframes so you don’t need to switch between charts to compare flow strength.
👉 Instead of flipping from 5-minute to 15M, 1H, 4H, and Daily, the table displays flow direction on all of them at a glance.
Example layout:
🔼 Daily: Up
🔽 1H: Down
🔼 15M: Up
🔽 5M: Down
This setup gives you a quick read on whether volume momentum is aligned across multiple timeframes or diverging which can help frame your trade approach.
🧠 Why It’s Useful:
✅ Supports timeframe alignment
If higher timeframes show strong inflow while lower ones are mixed, you may interpret it as a swing-based opportunity. If short timeframes show pressure but higher frames are flat, it might suggest short-term setups with caution.
✅ Improves context awareness
Instead of interpreting a move in isolation, the table helps you assess whether short-term signals are part of a broader shift or going against higher timeframe flow.
💡 Pro Tip: Use the table as a starting point in your analysis. It’s a simple but effective snapshot of current liquidity pressure across the board helping you plan trades with broader context, rather than reacting chart-by-chart.
🔚 Final Thoughts
If you're focused on trading with better clarity and structure, LiquidEdge is designed to help you interpret what’s happening beneath the surface not just follow price movement.
While many tools highlight price alone, LiquidEdge combines volume pressure, divergence filtering, and trend-based context to help identify potential areas of accumulation, distribution, or momentum shifts even before they become obvious on a chart.
👉 This isn’t just another signal tool. It’s a framework to support smarter decision-making:
✔️ One that helps you filter out noise
✔️ One that scores setups using multiple layers of confirmation
✔️ One that brings volume context into every trade idea
Whether you're scalping on a 5-minute chart or managing a longer-term swing trade, LiquidEdge is built to help you stay aligned with volume-driven behavior not just react to price alone.
If you've struggled with late entries, unreliable setups, or second-guessing trades, this tool was designed to bring more structure to your process. It won’t remove all uncertainty but it can help you stay more selective, confident, and intentional.
✅ Trade with clarity
✅ Stay process-driven
✅ Focus on structure, not noise
LiquidEdge is not meant to replace your strategy. It’s here to enhance it.
In this chart, the 200 EMA filter was applied. As a result, only signals that aligned with the dominant trend direction were displayed helping to reduce distractions and focus on setups with stronger context.
💡 Using a higher EMA setting like 200 can reduce the number of signals shown, but may help you focus on higher-conviction opportunities.
That said, every trader is different:
Longer EMAs = fewer signals, but more trend-filtered setups
Shorter EMAs = more signals, faster entries but with potentially more noise
👉 Adjust the filter based on your trading style. Use a 200 EMA for swing trading, or reduce it to 50, 25, or even 5 if you're trading more aggressively or intraday.
LiquidEdge adapts to you not the other way around.
🔁 Adjusting EMA for Your Trading Style
Personal Tip: When trading more aggressively, I often use a 5 EMA filter especially when combining histogram strength with other tools. This increases signal responsiveness and may help highlight short-term flow shifts more quickly.
Below are visual examples that show how different EMA lengths impact the behavior of LiquidEdge:
50 EMA ON
25 EMA ON
5 EMA ON
Lower EMA Example – Gold with the 5 EMA
In this example, the 5 EMA filter was applied to Gold. As expected, more signals were plotted compared to higher EMA settings. The tool became more responsive to rapid shifts in volume momentum, making it more suitable for fast-paced trading environments.
This setting can help traders who prefer early entries but it also introduces more sensitivity, so context and additional confirmation become even more important.
Each setting affects signal frequency and filtering:
Higher EMA → fewer signals, more trend-confirmed setups
Lower EMA → more signals, quicker responses, but with more potential for noise
Choose what fits your approach:
Long-term swing → Stick with 200 EMA
Intraday or scalping → Consider shorter EMAs (50, 25, or 5)
💡 Reminder: EMA filtering is fully adjustable. LiquidEdge doesn’t lock you into one trading style it’s meant to adapt to your process, whether you’re swing trading or scalping short-term moves.
But There’s a Catch…
Using a lower EMA setting (like 5) opens up faster, more frequent signals but it also increases the need for precision and stronger trade management.
❗ More signals = More responsiveness
❗ Faster setups mean quicker decisions
❗ Risk control becomes even more important
💡 Lower Timeframes = More Detail, Less Margin for Error
A short EMA (like 5) can help you:
✅ Identify early momentum shifts
✅ Respond before traditional trend-followers
✅ Highlight short-term divergence and volume changes
But it also comes with tradeoffs:
❌ Greater signal noise
❌ Higher potential for misreads or fakeouts
❌ Requires clear structure and disciplined entries
🚩 Watch Out for Liquidity Grabs
In lower timeframes, a common trap is the liquidity grab where price pushes beyond recent highs or lows, triggers stops, then quickly reverses.
📌 These moves can look like breakouts, but often reverse quickly possibly reflecting institutional order placement or low-liquidity manipulation.
🧭 How to Approach It Smartly
✅ Use structure: Mark support and resistance to frame moves
✅ Confirm volume behavior: Is histogram strength rising or fading?
✅ Avoid chasing: Look for confluence, not just a single signal
✅ Be intentional with stops: Place them with structure in mind to avoid being swept out
NASDAQ Futures Example – Low Timeframe Setups with LiquidEdge
In this example, we look at how LiquidEdge was used to identify both short and long setups on the NASDAQ Futures (NQ) particularly on a low timeframe (5M), where quick decision-making and volume precision matter most.
⚠️ A Note on Futures and Volume
When trading futures, especially on intraday charts, it’s important to separate overnight volume from regular session activity.
🕒 Overnight Volume ≠ Real Volume Context
Overnight price action is informative, but the volume data itself may not reflect true market participation. In LiquidEdge, histogram and pressure calculations emphasize regular session flow helping avoid skewed signals that could come from low-volume overnight moves.
Using the Histogram to Spot Potential Shifts
One of the key cues I use is color transition in the histogram:
🔴 A flip from strong green to red can signal fading buying pressure, sometimes marking the beginning of a potential short setup.
🟢 A shift from red to green may indicate that buyers are returning, suggesting possible accumulation.
These shifts serve as early visual cues of changing pressure especially when confirmed by other tools or context.
🔁 Adding Context with the Line + Structure
After spotting a histogram shift, I look at:
1️⃣ Slope Line – Is it confirming the same directional pressure?
2️⃣ Support/Resistance – Are we near a meaningful zone?
3️⃣ Additional Tools – This includes trendlines, VWAP, EMAs, and overall price structure.
On lower timeframes like 5M, these pieces become even more important. LiquidEdge gives directional insight, but your full setup provides confirmation and execution logic.
⚠️ Disclaimer
LiquidEdge is not a signal tool. It’s a visual representation of market pressure and flow designed to help you make more informed trading and investing decisions. It shows you what’s happening beneath the price action but you are still responsible for your decisions.
Always combine LiquidEdge with your own strategy, research, and supporting tools. That includes trend analysis, support/resistance levels, chart patterns, and fundamentals (like P/E ratios, price-to-sales, debt ratios, etc.).
This tool should never be used alone or treated as financial advice.
Some content may include AI-powered enhancements for clarity or formatting.
Always do your own research. For personal financial guidance, speak with a licensed financial advisor.
Anomalous Holonomy Field Theory🌌 Anomalous Holonomy Field Theory (AHFT) - Revolutionary Quantum Market Analysis
Where Theoretical Physics Meets Trading Reality
A Groundbreaking Synthesis of Differential Geometry, Quantum Field Theory, and Market Dynamics
🔬 THEORETICAL FOUNDATION - THE MATHEMATICS OF MARKET REALITY
The Anomalous Holonomy Field Theory represents an unprecedented fusion of advanced mathematical physics with practical market analysis. This isn't merely another indicator repackaging old concepts - it's a fundamentally new lens through which to view and understand market structure .
1. HOLONOMY GROUPS (Differential Geometry)
In differential geometry, holonomy measures how vectors change when parallel transported around closed loops in curved space. Applied to markets:
Mathematical Formula:
H = P exp(∮_C A_μ dx^μ)
Where:
P = Path ordering operator
A_μ = Market connection (price-volume gauge field)
C = Closed price path
Market Implementation:
The holonomy calculation measures how price "remembers" its journey through market space. When price returns to a previous level, the holonomy captures what has changed in the market's internal geometry. This reveals:
Hidden curvature in the market manifold
Topological obstructions to arbitrage
Geometric phase accumulated during price cycles
2. ANOMALY DETECTION (Quantum Field Theory)
Drawing from the Adler-Bell-Jackiw anomaly in quantum field theory:
Mathematical Formula:
∂_μ j^μ = (e²/16π²)F_μν F̃^μν
Where:
j^μ = Market current (order flow)
F_μν = Field strength tensor (volatility structure)
F̃^μν = Dual field strength
Market Application:
Anomalies represent symmetry breaking in market structure - moments when normal patterns fail and extraordinary opportunities arise. The system detects:
Spontaneous symmetry breaking (trend reversals)
Vacuum fluctuations (volatility clusters)
Non-perturbative effects (market crashes/melt-ups)
3. GAUGE THEORY (Theoretical Physics)
Markets exhibit gauge invariance - the fundamental physics remains unchanged under certain transformations:
Mathematical Formula:
A'_μ = A_μ + ∂_μΛ
This ensures our signals are gauge-invariant observables , immune to arbitrary market "coordinate changes" like gaps or reference point shifts.
4. TOPOLOGICAL DATA ANALYSIS
Using persistent homology and Morse theory:
Mathematical Formula:
β_k = dim(H_k(X))
Where β_k are the Betti numbers describing topological features that persist across scales.
🎯 REVOLUTIONARY SIGNAL CONFIGURATION
Signal Sensitivity (0.5-12.0, default 2.5)
Controls the responsiveness of holonomy field calculations to market conditions. This parameter directly affects the threshold for detecting quantum phase transitions in price action.
Optimization by Timeframe:
Scalping (1-5min): 1.5-3.0 for rapid signal generation
Day Trading (15min-1H): 2.5-5.0 for balanced sensitivity
Swing Trading (4H-1D): 5.0-8.0 for high-quality signals only
Score Amplifier (10-200, default 50)
Scales the raw holonomy field strength to produce meaningful signal values. Higher values amplify weak signals in low-volatility environments.
Signal Confirmation Toggle
When enabled, enforces additional technical filters (EMA and RSI alignment) to reduce false positives. Essential for conservative strategies.
Minimum Bars Between Signals (1-20, default 5)
Prevents overtrading by enforcing quantum decoherence time between signals. Higher values reduce whipsaws in choppy markets.
👑 ELITE EXECUTION SYSTEM
Execution Modes:
Conservative Mode:
Stricter signal criteria
Higher quality thresholds
Ideal for stable market conditions
Adaptive Mode:
Self-adjusting parameters
Balances signal frequency with quality
Recommended for most traders
Aggressive Mode:
Maximum signal sensitivity
Captures rapid market moves
Best for experienced traders in volatile conditions
Dynamic Position Sizing:
When enabled, the system scales position size based on:
Holonomy field strength
Current volatility regime
Recent performance metrics
Advanced Exit Management:
Implements trailing stops based on ATR and signal strength, with mode-specific multipliers for optimal profit capture.
🧠 ADAPTIVE INTELLIGENCE ENGINE
Self-Learning System:
The strategy analyzes recent trade outcomes and adjusts:
Risk multipliers based on win/loss ratios
Signal weights according to performance
Market regime detection for environmental adaptation
Learning Speed (0.05-0.3):
Controls adaptation rate. Higher values = faster learning but potentially unstable. Lower values = stable but slower adaptation.
Performance Window (20-100 trades):
Number of recent trades analyzed for adaptation. Longer windows provide stability, shorter windows increase responsiveness.
🎨 REVOLUTIONARY VISUAL SYSTEM
1. Holonomy Field Visualization
What it shows: Multi-layer quantum field bands representing market resonance zones
How to interpret:
Blue/Purple bands = Primary holonomy field (strongest resonance)
Band width = Field strength and volatility
Price within bands = Normal quantum state
Price breaking bands = Quantum phase transition
Trading application: Trade reversals at band extremes, breakouts on band violations with strong signals.
2. Quantum Portals
What they show: Entry signals with recursive depth patterns indicating momentum strength
How to interpret:
Upward triangles with portals = Long entry signals
Downward triangles with portals = Short entry signals
Portal depth = Signal strength and expected momentum
Color intensity = Probability of success
Trading application: Enter on portal appearance, with size proportional to portal depth.
3. Field Resonance Bands
What they show: Fibonacci-based harmonic price zones where quantum resonance occurs
How to interpret:
Dotted circles = Minor resonance levels
Solid circles = Major resonance levels
Color coding = Resonance strength
Trading application: Use as dynamic support/resistance, expect reactions at resonance zones.
4. Anomaly Detection Grid
What it shows: Fractal-based support/resistance with anomaly strength calculations
How to interpret:
Triple-layer lines = Major fractal levels with high anomaly probability
Labels show: Period (H8-H55), Price, and Anomaly strength (φ)
⚡ symbol = Extreme anomaly detected
● symbol = Strong anomaly
○ symbol = Normal conditions
Trading application: Expect major moves when price approaches high anomaly levels. Use for precise entry/exit timing.
5. Phase Space Flow
What it shows: Background heatmap revealing market topology and energy
How to interpret:
Dark background = Low market energy, range-bound
Purple glow = Building energy, trend developing
Bright intensity = High energy, strong directional move
Trading application: Trade aggressively in bright phases, reduce activity in dark phases.
📊 PROFESSIONAL DASHBOARD METRICS
Holonomy Field Strength (-100 to +100)
What it measures: The Wilson loop integral around price paths
>70: Strong positive curvature (bullish vortex)
<-70: Strong negative curvature (bearish collapse)
Near 0: Flat connection (range-bound)
Anomaly Level (0-100%)
What it measures: Quantum vacuum expectation deviation
>70%: Major anomaly (phase transition imminent)
30-70%: Moderate anomaly (elevated volatility)
<30%: Normal quantum fluctuations
Quantum State (-1, 0, +1)
What it measures: Market wave function collapse
+1: Bullish eigenstate |↑⟩
0: Superposition (uncertain)
-1: Bearish eigenstate |↓⟩
Signal Quality Ratings
LEGENDARY: All quantum fields aligned, maximum probability
EXCEPTIONAL: Strong holonomy with anomaly confirmation
STRONG: Good field strength, moderate anomaly
MODERATE: Decent signals, some uncertainty
WEAK: Minimal edge, high quantum noise
Performance Metrics
Win Rate: Rolling performance with emoji indicators
Daily P&L: Real-time profit tracking
Adaptive Risk: Current risk multiplier status
Market Regime: Bull/Bear classification
🏆 WHY THIS CHANGES EVERYTHING
Traditional technical analysis operates on 100-year-old principles - moving averages, support/resistance, and pattern recognition. These work because many traders use them, creating self-fulfilling prophecies.
AHFT transcends this limitation by analyzing markets through the lens of fundamental physics:
Markets have geometry - The holonomy calculations reveal this hidden structure
Price has memory - The geometric phase captures path-dependent effects
Anomalies are predictable - Quantum field theory identifies symmetry breaking
Everything is connected - Gauge theory unifies disparate market phenomena
This isn't just a new indicator - it's a new way of thinking about markets . Just as Einstein's relativity revolutionized physics beyond Newton's mechanics, AHFT revolutionizes technical analysis beyond traditional methods.
🔧 OPTIMAL SETTINGS FOR MNQ 10-MINUTE
For the Micro E-mini Nasdaq-100 on 10-minute timeframe:
Signal Sensitivity: 2.5-3.5
Score Amplifier: 50-70
Execution Mode: Adaptive
Min Bars Between: 3-5
Theme: Quantum Nebula or Dark Matter
💭 THE JOURNEY - FROM IMPOSSIBLE THEORY TO TRADING REALITY
Creating AHFT was a mathematical odyssey that pushed the boundaries of what's possible in Pine Script. The journey began with a seemingly impossible question: Could the profound mathematical structures of theoretical physics be translated into practical trading tools?
The Theoretical Challenge:
Months were spent diving deep into differential geometry textbooks, studying the works of Chern, Simons, and Witten. The mathematics of holonomy groups and gauge theory had never been applied to financial markets. Translating abstract mathematical concepts like parallel transport and fiber bundles into discrete price calculations required novel approaches and countless failed attempts.
The Computational Nightmare:
Pine Script wasn't designed for quantum field theory calculations. Implementing the Wilson loop integral, managing complex array structures for anomaly detection, and maintaining computational efficiency while calculating geometric phases pushed the language to its limits. There were moments when the entire project seemed impossible - the script would timeout, produce nonsensical results, or simply refuse to compile.
The Breakthrough Moments:
After countless sleepless nights and thousands of lines of code, breakthrough came through elegant simplifications. The realization that market anomalies follow patterns similar to quantum vacuum fluctuations led to the revolutionary anomaly detection system. The discovery that price paths exhibit holonomic memory unlocked the geometric phase calculations.
The Visual Revolution:
Creating visualizations that could represent 4-dimensional quantum fields on a 2D chart required innovative approaches. The multi-layer holonomy field, recursive quantum portals, and phase space flow representations went through dozens of iterations before achieving the perfect balance of beauty and functionality.
The Balancing Act:
Perhaps the greatest challenge was maintaining mathematical rigor while ensuring practical trading utility. Every formula had to be both theoretically sound and computationally efficient. Every visual had to be both aesthetically pleasing and information-rich.
The result is more than a strategy - it's a synthesis of pure mathematics and market reality that reveals the hidden order within apparent chaos.
📚 INTEGRATED DOCUMENTATION
Once applied to your chart, AHFT includes comprehensive tooltips on every input parameter. The source code contains detailed explanations of the mathematical theory, practical applications, and optimization guidelines. This published description provides the overview - the indicator itself is a complete educational resource.
⚠️ RISK DISCLAIMER
While AHFT employs advanced mathematical models derived from theoretical physics, markets remain inherently unpredictable. No mathematical model, regardless of sophistication, can guarantee future results. This strategy uses realistic commission ($0.62 per contract) and slippage (1 tick) in all calculations. Past performance does not guarantee future results. Always use appropriate risk management and never risk more than you can afford to lose.
🌟 CONCLUSION
The Anomalous Holonomy Field Theory represents a quantum leap in technical analysis - literally. By applying the profound insights of differential geometry, quantum field theory, and gauge theory to market analysis, AHFT reveals structure and opportunities invisible to traditional methods.
From the holonomy calculations that capture market memory to the anomaly detection that identifies phase transitions, from the adaptive intelligence that learns and evolves to the stunning visualizations that make the invisible visible, every component works in mathematical harmony.
This is more than a trading strategy. It's a new lens through which to view market reality.
Trade with the precision of physics. Trade with the power of mathematics. Trade with AHFT.
I hope this serves as a good replacement for Quantum Edge Pro - Adaptive AI until I'm able to fix it.
— Dskyz, Trade with insight. Trade with anticipation.
Technical Strength Index (TSI)📘 TSI with Dynamic Bands – Technical Strength Index
The TSI with Dynamic Bands is a multi-factor indicator designed to measure the statistical strength and structure of a trend. It combines several quantitative metrics into a single, normalized score between 0 and 1, allowing traders to assess the technical quality of market moves and detect overbought/oversold conditions with adaptive precision.
🧠 Core Components
This indicator draws from the StatMetrics library, blending:
📈 Trend Persistence: via the Hurst exponent, indicating whether price action is mean-reverting or trending.
📉 Risk-Adjusted Volatility: via the inverted , rewarding smoother, less erratic price movement.
🚀 Momentum Strength: using a combination of directional momentum and Z-score–normalized returns.
These components are normalized and averaged into the TSI line.
🎯 Features
TSI Line: Composite score of trend quality (0 = weak/noise, 1 = strong/structured).
Dynamic Bands: Mean ± 1 standard deviation envelopes provide adaptive context.
Overbought/Oversold Detection: Based on a rolling quantile (e.g. 90th/10th percentile of TSI history).
Signal Strength Bar (optional): Measures how statistically extreme the current TSI value is, helping validate confidence in trade setups.
Dynamic Color Cues: Background and bar gradients help visually identify statistically significant zones.
📈 How to Use
Look for overbought (red background) or oversold (green background) conditions as potential reversal zones.
Confirm trend strength with the optional signal strength bar — stronger values suggest higher signal confidence.
Use the TSI line and context bands to filter out noisy ranges and focus on structured price moves.
⚙️ Inputs
Lookback Period: Controls the smoothing and window size for statistical calculations.
Overbought/Oversold Quantiles: Adjust the thresholds for signal zones.
Plot Signal Strength: Enable or disable the signal confidence bar.
Overlay Signal Strength: Show signal strength in the same panel (compact) or not (cleaner TSI-only view).
🛠 Example Use Cases
Mean reversion traders identifying reversal zones with statistical backing
Momentum/Trend traders confirming structure before entries
Quantitative dashboards or multi-asset screening tools
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any financial instrument.
This AI is not a financial advisor; please consult your financial advisor for personalized advice.
Linear Regression Channel Pro# Linear Regression Channel Pro - Script Description
## English Description
### What it does
The **Linear Regression Channel Pro** is a technical analysis indicator that creates a statistical channel around price movements using linear regression mathematics. The script calculates the best-fit line through a specified number of price bars and then adds parallel boundaries based on standard deviation calculations.
### Key Features
- **Main Regression Line**: Shows the statistical trend direction of the price over the selected period
- **Channel Boundaries**: Upper and lower bands that contain most price movements (typically 95% when using 2.0 multiplier)
- **Inner Boundaries**: Additional reference lines for more precise analysis
- **Future Projection**: Extends all lines into the future to show potential price paths
- **Customizable Parameters**: Adjustable period length, deviation multipliers, and projection distance
### How it works
1. **Data Collection**: Gathers price data over the specified regression length (default 400 bars)
2. **Linear Regression**: Calculates the mathematical best-fit line through the price data
3. **Standard Deviation**: Measures how much prices deviate from the regression line
4. **Channel Creation**: Creates parallel lines above and below the regression line
5. **Future Projection**: Extends the channel into the future using the same slope
### Statistical Foundation and Band Settings
**The 68-95-99.7 Rule**
The indicator is based on the statistical principle that in a normal distribution:
- **1 Standard Deviation (σ)**: Contains approximately **68%** of price movements
- **2 Standard Deviations (σ)**: Contains approximately **95%** of price movements
- **3 Standard Deviations (σ)**: Contains approximately **99.7%** of price movements
**Outer Bands (Default 2.0 Multiplier)**
- **Coverage**: Approximately **95%** of price movements
- **Meaning**: Only 5% of price action should exceed these bands
- **Usage**: Identification of extreme overbought/oversold conditions
- **Signal**: Touching outer bands often indicates potential reversal points
**Inner Bands (Default 1.0 Multiplier)**
- **Coverage**: Approximately **68%** of price movements
- **Meaning**: 32% of movements can normally exceed these bands
- **Usage**: Identification of significant but not extreme price moves
- **Signal**: Breaking inner bands suggests meaningful directional movement
### Recommended Settings by Market Type
**Standard Configuration**
```
- Outer Bands: 2.0 (95% coverage)
- Inner Bands: 1.0 (68% coverage)
```
**High Volatility Markets (Crypto, Emerging Markets)**
```
- Outer Bands: 2.5-3.0 (99%+ coverage)
- Inner Bands: 1.5 (85% coverage)
```
**Low Volatility Markets (Major Forex, Blue Chip Stocks)**
```
- Outer Bands: 1.5 (86% coverage)
- Inner Bands: 0.5 (38% coverage)
```
### Trading Applications
**Trend Analysis**
- The slope of the regression line indicates the overall trend direction
- Steep slopes suggest strong trends, flat slopes suggest consolidation
- Price above center line = bullish bias, below = bearish bias
**Support and Resistance Levels**
- **Inner bands**: Act as first level support/resistance (68% probability)
- **Outer bands**: Act as strong support/resistance (95% probability)
- **Dynamic levels**: Bands adjust automatically to market conditions
**Entry and Exit Strategies**
*Using Inner Bands (1.0σ):*
- **Breakout signals**: Price breaking through inner bands with volume confirms direction
- **Pullback entries**: Price returning to inner band after breakout offers entry opportunity
- **Range trading**: Price oscillating between inner bands suggests consolidation
*Using Outer Bands (2.0σ):*
- **Reversal signals**: Price touching outer bands often indicates exhaustion
- **Extreme conditions**: Only 5% of movements reach these levels
- **Profit taking**: Consider closing positions when price reaches outer bands
**Risk Management Applications**
- **Stop Loss Placement**: Use opposite band as stop level (high probability of not being hit randomly)
- **Position Sizing**: Wider channels = higher volatility = smaller position sizes
- **Risk/Reward**: Measure potential moves using band distances
**Future Planning with Projections**
- **Target Setting**: Orange projection lines show potential future support/resistance
- **Trade Duration**: Plan holding periods based on projected channel direction
- **Market Timing**: Anticipate when price might reach significant levels
### Practical Trading Examples
**Bullish Trend Scenario**
1. Price consistently above center line (trend confirmed)
2. Bounces from inner lower band = re-entry opportunity
3. Reaching outer upper band = consider profit taking
4. Break above outer upper band = potential trend acceleration
**Range-Bound Market**
1. Price oscillates between inner bands = range trading mode
2. Sell near inner upper band, buy near inner lower band
3. Breakout from outer bands = range breakout signal
**Bearish Trend Scenario**
1. Price consistently below center line (downtrend confirmed)
2. Bounces from inner upper band = short entry opportunity
3. Reaching outer lower band = potential oversold bounce
4. Break below outer lower band = trend continuation likely
### Best Practices and Tips
- **Timeframe Selection**: Use higher timeframes (4H, Daily) for more reliable statistical significance
- **Confirmation**: Combine with volume analysis and other indicators
- **Market Adaptation**: Adjust multipliers based on asset volatility characteristics
- **Regression Length**: Shorter periods (100-200) for reactive signals, longer (400-800) for stable trends
- **False Breakouts**: Wait for close beyond bands rather than just touching
- **Volume Confirmation**: Higher volume on band breakouts increases signal reliability
---
## Descrizione Italiana
### Cosa fa
Il **Linear Regression Channel Pro** è un indicatore di analisi tecnica che crea un canale statistico intorno ai movimenti di prezzo utilizzando la matematica della regressione lineare. Lo script calcola la linea di miglior adattamento attraverso un numero specificato di barre di prezzo e aggiunge quindi confini paralleli basati sui calcoli della deviazione standard.
### Caratteristiche Principali
- **Linea di Regressione Principale**: Mostra la direzione statistica del trend del prezzo nel periodo selezionato
- **Confini del Canale**: Bande superiori e inferiori che contengono la maggior parte dei movimenti di prezzo (tipicamente il 95% usando il moltiplicatore 2.0)
- **Confini Interni**: Linee di riferimento aggiuntive per un'analisi più precisa
- **Proiezione Futura**: Estende tutte le linee nel futuro per mostrare potenziali percorsi di prezzo
- **Parametri Personalizzabili**: Lunghezza del periodo, moltiplicatori di deviazione e distanza di proiezione regolabili
### Come Funziona
1. **Raccolta Dati**: Raccoglie i dati di prezzo per la lunghezza di regressione specificata (default 400 barre)
2. **Regressione Lineare**: Calcola matematicamente la linea di miglior adattamento attraverso i dati di prezzo
3. **Deviazione Standard**: Misura quanto i prezzi si discostano dalla linea di regressione
4. **Creazione del Canale**: Crea linee parallele sopra e sotto la linea di regressione
5. **Proiezione Futura**: Estende il canale nel futuro usando la stessa pendenza
### Fondamenti Statistici e Impostazione delle Bande
**La Regola 68-95-99.7**
L'indicatore si basa sul principio statistico che in una distribuzione normale:
- **1 Deviazione Standard (σ)**: Contiene circa il **68%** dei movimenti di prezzo
- **2 Deviazioni Standard (σ)**: Contiene circa il **95%** dei movimenti di prezzo
- **3 Deviazioni Standard (σ)**: Contiene circa il **99.7%** dei movimenti di prezzo
**Bande Esterne (Moltiplicatore Default 2.0)**
- **Copertura**: Circa il **95%** dei movimenti di prezzo
- **Significato**: Solo il 5% dell'azione di prezzo dovrebbe superare queste bande
- **Utilizzo**: Identificazione di condizioni estreme di ipercomprato/ipervenduto
- **Segnale**: Il tocco delle bande esterne spesso indica potenziali punti di inversione
**Bande Interne (Moltiplicatore Default 1.0)**
- **Copertura**: Circa il **68%** dei movimenti di prezzo
- **Significato**: Il 32% dei movimenti può normalmente superare queste bande
- **Utilizzo**: Identificazione di movimenti di prezzo significativi ma non estremi
- **Segnale**: La rottura delle bande interne suggerisce un movimento direzionale significativo
### Impostazioni Raccomandate per Tipo di Mercato
**Configurazione Standard**
```
- Bande Esterne: 2.0 (copertura 95%)
- Bande Interne: 1.0 (copertura 68%)
```
**Mercati ad Alta Volatilità (Crypto, Mercati Emergenti)**
```
- Bande Esterne: 2.5-3.0 (copertura 99%+)
- Bande Interne: 1.5 (copertura 85%)
```
**Mercati a Bassa Volatilità (Forex Maggiori, Azioni Blue Chip)**
```
- Bande Esterne: 1.5 (copertura 86%)
- Bande Interne: 0.5 (copertura 38%)
```
### Applicazioni nel Trading
**Analisi del Trend**
- La pendenza della linea di regressione indica la direzione generale del trend
- Pendenze ripide suggeriscono trend forti, pendenze piatte suggeriscono consolidamento
- Prezzo sopra la linea centrale = bias rialzista, sotto = bias ribassista
**Livelli di Supporto e Resistenza**
- **Bande interne**: Agiscono come supporto/resistenza di primo livello (probabilità 68%)
- **Bande esterne**: Agiscono come supporto/resistenza forte (probabilità 95%)
- **Livelli dinamici**: Le bande si adattano automaticamente alle condizioni di mercato
**Strategie di Entrata e Uscita**
*Usando le Bande Interne (1.0σ):*
- **Segnali di breakout**: Il prezzo che rompe le bande interne con volume conferma la direzione
- **Entrate su pullback**: Il prezzo che ritorna alla banda interna dopo un breakout offre opportunità di entrata
- **Range trading**: Il prezzo che oscilla tra bande interne suggerisce consolidamento
*Usando le Bande Esterne (2.0σ):*
- **Segnali di inversione**: Il prezzo che tocca le bande esterne spesso indica esaurimento
- **Condizioni estreme**: Solo il 5% dei movimenti raggiunge questi livelli
- **Presa di profitto**: Considera di chiudere posizioni quando il prezzo raggiunge le bande esterne
**Applicazioni di Gestione del Rischio**
- **Posizionamento Stop Loss**: Usa la banda opposta come livello di stop (alta probabilità di non essere colpito casualmente)
- **Dimensionamento Posizioni**: Canali più larghi = volatilità maggiore = posizioni più piccole
- **Rischio/Rendimento**: Misura i movimenti potenziali usando le distanze delle bande
**Pianificazione Futura con Proiezioni**
- **Impostazione Target**: Le linee di proiezione arancioni mostrano potenziali supporti/resistenze futuri
- **Durata del Trade**: Pianifica i periodi di detenzione basandoti sulla direzione del canale proiettato
- **Timing di Mercato**: Anticipa quando il prezzo potrebbe raggiungere livelli significativi
### Esempi Pratici di Trading
**Scenario Trend Rialzista**
1. Prezzo costantemente sopra la linea centrale (trend confermato)
2. Rimbalzi dalla banda interna inferiore = opportunità di re-entrata
3. Raggiungimento banda esterna superiore = considera presa di profitto
4. Rottura sopra banda esterna superiore = potenziale accelerazione del trend
**Mercato in Range**
1. Prezzo oscilla tra bande interne = modalità range trading
2. Vendi vicino alla banda interna superiore, compra vicino a quella inferiore
3. Breakout dalle bande esterne = segnale di rottura del range
**Scenario Trend Ribassista**
1. Prezzo costantemente sotto la linea centrale (downtrend confermato)
2. Rimbalzi dalla banda interna superiore = opportunità di short
3. Raggiungimento banda esterna inferiore = potenziale rimbalzo da ipervenduto
4. Rottura sotto banda esterna inferiore = probabile continuazione del trend
### Migliori Pratiche e Consigli
- **Selezione Timeframe**: Usa timeframe più alti (4H, Giornaliero) per maggiore significatività statistica
- **Conferma**: Combina con analisi del volume e altri indicatori
- **Adattamento al Mercato**: Regola i moltiplicatori in base alle caratteristiche di volatilità dell'asset
- **Lunghezza Regressione**: Periodi più corti (100-200) per segnali reattivi, più lunghi (400-800) per trend stabili
- **Falsi Breakout**: Aspetta la chiusura oltre le bande piuttosto che solo il tocco
- **Conferma del Volume**: Volume più alto sui breakout delle bande aumenta l'affidabilità del segnale
Langlands-Operadic Möbius Vortex (LOMV)Langlands-Operadic Möbius Vortex (LOMV)
Where Pure Mathematics Meets Market Reality
A Revolutionary Synthesis of Number Theory, Category Theory, and Market Dynamics
🎓 THEORETICAL FOUNDATION
The Langlands-Operadic Möbius Vortex represents a groundbreaking fusion of three profound mathematical frameworks that have never before been combined for market analysis:
The Langlands Program: Harmonic Analysis in Markets
Developed by Robert Langlands (Fields Medal recipient), the Langlands Program creates bridges between number theory, algebraic geometry, and harmonic analysis. In our indicator:
L-Function Implementation:
- Utilizes the Möbius function μ(n) for weighted price analysis
- Applies Riemann zeta function convergence principles
- Calculates quantum harmonic resonance between -2 and +2
- Measures deep mathematical patterns invisible to traditional analysis
The L-Function core calculation employs:
L_sum = Σ(return_val × μ(n) × n^(-s))
Where s is the critical strip parameter (0.5-2.5), controlling mathematical precision and signal smoothness.
Operadic Composition Theory: Multi-Strategy Democracy
Category theory and operads provide the mathematical framework for composing multiple trading strategies into a unified signal. This isn't simple averaging - it's mathematical composition using:
Strategy Composition Arity (2-5 strategies):
- Momentum analysis via RSI transformation
- Mean reversion through Bollinger Band mathematics
- Order Flow Polarity Index (revolutionary T3-smoothed volume analysis)
- Trend detection using Directional Movement
- Higher timeframe momentum confirmation
Agreement Threshold System: Democratic voting where strategies must reach consensus before signal generation. This prevents false signals during market uncertainty.
Möbius Function: Number Theory in Action
The Möbius function μ(n) forms the mathematical backbone:
- μ(n) = 1 if n is a square-free positive integer with even number of prime factors
- μ(n) = -1 if n is a square-free positive integer with odd number of prime factors
- μ(n) = 0 if n has a squared prime factor
This creates oscillating weights that reveal hidden market periodicities and harmonic structures.
🔧 COMPREHENSIVE INPUT SYSTEM
Langlands Program Parameters
Modular Level N (5-50, default 30):
Primary lookback for quantum harmonic analysis. Optimized by timeframe:
- Scalping (1-5min): 15-25
- Day Trading (15min-1H): 25-35
- Swing Trading (4H-1D): 35-50
- Asset-specific: Crypto 15-25, Stocks 30-40, Forex 35-45
L-Function Critical Strip (0.5-2.5, default 1.5):
Controls Riemann zeta convergence precision:
- Higher values: More stable, smoother signals
- Lower values: More reactive, catches quick moves
- High frequency: 0.8-1.2, Medium: 1.3-1.7, Low: 1.8-2.3
Frobenius Trace Period (5-50, default 21):
Galois representation lookback for price-volume correlation:
- Measures harmonic relationships in market flows
- Scalping: 8-15, Day Trading: 18-25, Swing: 25-40
HTF Multi-Scale Analysis:
Higher timeframe context prevents trading against major trends:
- Provides market bias and filters signals
- Improves win rates by 15-25% through trend alignment
Operadic Composition Parameters
Strategy Composition Arity (2-5, default 4):
Number of algorithms composed for final signal:
- Conservative: 4-5 strategies (higher confidence)
- Moderate: 3-4 strategies (balanced approach)
- Aggressive: 2-3 strategies (more frequent signals)
Category Agreement Threshold (2-5, default 3):
Democratic voting minimum for signal generation:
- Higher agreement: Fewer but higher quality signals
- Lower agreement: More signals, potential false positives
Swiss-Cheese Mixing (0.1-0.5, default 0.382):
Golden ratio φ⁻¹ based blending of trend factors:
- 0.382 is φ⁻¹, optimal for natural market fractals
- Higher values: Stronger trend following
- Lower values: More contrarian signals
OFPI Configuration:
- OFPI Length (5-30, default 14): Order Flow calculation period
- T3 Smoothing (3-10, default 5): Advanced exponential smoothing
- T3 Volume Factor (0.5-1.0, default 0.7): Smoothing aggressiveness control
Unified Scoring System
Component Weights (sum ≈ 1.0):
- L-Function Weight (0.1-0.5, default 0.3): Mathematical harmony emphasis
- Galois Rank Weight (0.1-0.5, default 0.2): Market structure complexity
- Operadic Weight (0.1-0.5, default 0.3): Multi-strategy consensus
- Correspondence Weight (0.1-0.5, default 0.2): Theory-practice alignment
Signal Threshold (0.5-10.0, default 5.0):
Quality filter producing:
- 8.0+: EXCEPTIONAL signals only
- 6.0-7.9: STRONG signals
- 4.0-5.9: MODERATE signals
- 2.0-3.9: WEAK signals
🎨 ADVANCED VISUAL SYSTEM
Multi-Dimensional Quantum Aura Bands
Five-layer resonance field showing market energy:
- Colors: Theme-matched gradients (Quantum purple, Holographic cyan, etc.)
- Expansion: Dynamic based on score intensity and volatility
- Function: Multi-timeframe support/resistance zones
Morphism Flow Portals
Category theory visualization showing market topology:
- Green/Cyan Portals: Bullish mathematical flow
- Red/Orange Portals: Bearish mathematical flow
- Size/Intensity: Proportional to signal strength
- Recursion Depth (1-8): Nested patterns for flow evolution
Fractal Grid System
Dynamic support/resistance with projected L-Scores:
- Multiple Timeframes: 10, 20, 30, 40, 50-period highs/lows
- Smart Spacing: Prevents level overlap using ATR-based minimum distance
- Projections: Estimated signal scores when price reaches levels
- Usage: Precise entry/exit timing with mathematical confirmation
Wick Pressure Analysis
Rejection level prediction using candle mathematics:
- Upper Wicks: Selling pressure zones (purple/red lines)
- Lower Wicks: Buying pressure zones (purple/green lines)
- Glow Intensity (1-8): Visual emphasis and line reach
- Application: Confluence with fractal grid creates high-probability zones
Regime Intensity Heatmap
Background coloring showing market energy:
- Black/Dark: Low activity, range-bound markets
- Purple Glow: Building momentum and trend development
- Bright Purple: High activity, strong directional moves
- Calculation: Combines trend, momentum, volatility, and score intensity
Six Professional Themes
- Quantum: Purple/violet for general trading and mathematical focus
- Holographic: Cyan/magenta optimized for cryptocurrency markets
- Crystalline: Blue/turquoise for conservative, stability-focused trading
- Plasma: Gold/magenta for high-energy volatility trading
- Cosmic Neon: Bright neon colors for maximum visibility and aggressive trading
📊 INSTITUTIONAL-GRADE DASHBOARD
Unified AI Score Section
- Total Score (-10 to +10): Primary decision metric
- >5: Strong bullish signals
- <-5: Strong bearish signals
- Quality ratings: EXCEPTIONAL > STRONG > MODERATE > WEAK
- Component Analysis: Individual L-Function, Galois, Operadic, and Correspondence contributions
Order Flow Analysis
Revolutionary OFPI integration:
- OFPI Value (-100% to +100%): Real buying vs selling pressure
- Visual Gauge: Horizontal bar chart showing flow intensity
- Momentum Status: SHIFTING, ACCELERATING, STRONG, MODERATE, or WEAK
- Trading Application: Flow shifts often precede major moves
Signal Performance Tracking
- Win Rate Monitoring: Real-time success percentage with emoji indicators
- Signal Count: Total signals generated for frequency analysis
- Current Position: LONG, SHORT, or NONE with P&L tracking
- Volatility Regime: HIGH, MEDIUM, or LOW classification
Market Structure Analysis
- Möbius Field Strength: Mathematical field oscillation intensity
- CHAOTIC: High complexity, use wider stops
- STRONG: Active field, normal position sizing
- MODERATE: Balanced conditions
- WEAK: Low activity, consider smaller positions
- HTF Trend: Higher timeframe bias (BULL/BEAR/NEUTRAL)
- Strategy Agreement: Multi-algorithm consensus level
Position Management
When in trades, displays:
- Entry Price: Original signal price
- Current P&L: Real-time percentage with risk level assessment
- Duration: Bars in trade for timing analysis
- Risk Level: HIGH/MEDIUM/LOW based on current exposure
🚀 SIGNAL GENERATION LOGIC
Balanced Long/Short Architecture
The indicator generates signals through multiple convergent pathways:
Long Entry Conditions:
- Score threshold breach with algorithmic agreement
- Strong bullish order flow (OFPI > 0.15) with positive composite signal
- Bullish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bullish OFPI (>0.3) with any positive score
Short Entry Conditions:
- Score threshold breach with bearish agreement
- Strong bearish order flow (OFPI < -0.15) with negative composite signal
- Bearish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bearish OFPI (<-0.3) with any negative score
Exit Logic:
- Score deterioration below continuation threshold
- Signal quality degradation
- Opposing order flow acceleration
- 10-bar minimum between signals prevents overtrading
⚙️ OPTIMIZATION GUIDELINES
Asset-Specific Settings
Cryptocurrency Trading:
- Modular Level: 15-25 (capture volatility)
- L-Function Precision: 0.8-1.3 (reactive to price swings)
- OFPI Length: 10-20 (fast correlation shifts)
- Cascade Levels: 5-7, Theme: Holographic
Stock Index Trading:
- Modular Level: 25-35 (balanced trending)
- L-Function Precision: 1.5-1.8 (stable patterns)
- OFPI Length: 14-20 (standard correlation)
- Cascade Levels: 4-5, Theme: Quantum
Forex Trading:
- Modular Level: 35-45 (smooth trends)
- L-Function Precision: 1.6-2.1 (high smoothing)
- OFPI Length: 18-25 (disable volume amplification)
- Cascade Levels: 3-4, Theme: Crystalline
Timeframe Optimization
Scalping (1-5 minute charts):
- Reduce all lookback parameters by 30-40%
- Increase L-Function precision for noise reduction
- Enable all visual elements for maximum information
- Use Small dashboard to save screen space
Day Trading (15 minute - 1 hour):
- Use default parameters as starting point
- Adjust based on market volatility
- Normal dashboard provides optimal information density
- Focus on OFPI momentum shifts for entries
Swing Trading (4 hour - Daily):
- Increase lookback parameters by 30-50%
- Higher L-Function precision for stability
- Large dashboard for comprehensive analysis
- Emphasize HTF trend alignment
🏆 ADVANCED TRADING STRATEGIES
The Mathematical Confluence Method
1. Wait for Fractal Grid level approach
2. Confirm with projected L-Score > threshold
3. Verify OFPI alignment with direction
4. Enter on portal signal with quality ≥ STRONG
5. Exit on score deterioration or opposing flow
The Regime Trading System
1. Monitor Aether Flow background intensity
2. Trade aggressively during bright purple periods
3. Reduce position size during dark periods
4. Use Möbius Field strength for stop placement
5. Align with HTF trend for maximum probability
The OFPI Momentum Strategy
1. Watch for momentum shifting detection
2. Confirm with accelerating flow in direction
3. Enter on immediate portal signal
4. Scale out at Fibonacci levels
5. Exit on flow deceleration or reversal
⚠️ RISK MANAGEMENT INTEGRATION
Mathematical Position Sizing
- Use Galois Rank for volatility-adjusted sizing
- Möbius Field strength determines stop width
- Fractal Dimension guides maximum exposure
- OFPI momentum affects entry timing
Signal Quality Filtering
- Trade only STRONG or EXCEPTIONAL quality signals
- Increase position size with higher agreement levels
- Reduce risk during CHAOTIC Möbius field periods
- Respect HTF trend alignment for directional bias
🔬 DEVELOPMENT JOURNEY
Creating the LOMV was an extraordinary mathematical undertaking that pushed the boundaries of what's possible in technical analysis. This indicator almost didn't happen. The theoretical complexity nearly proved insurmountable.
The Mathematical Challenge
Implementing the Langlands Program required deep research into:
- Number theory and the Möbius function
- Riemann zeta function convergence properties
- L-function analytical continuation
- Galois representations in finite fields
The mathematical literature spans decades of pure mathematics research, requiring translation from abstract theory to practical market application.
The Computational Complexity
Operadic composition theory demanded:
- Category theory implementation in Pine Script
- Multi-dimensional array management for strategy composition
- Real-time democratic voting algorithms
- Performance optimization for complex calculations
The Integration Breakthrough
Bringing together three disparate mathematical frameworks required:
- Novel approaches to signal weighting and combination
- Revolutionary Order Flow Polarity Index development
- Advanced T3 smoothing implementation
- Balanced signal generation preventing directional bias
Months of intensive research culminated in breakthrough moments when the mathematics finally aligned with market reality. The result is an indicator that reveals market structure invisible to conventional analysis while maintaining practical trading utility.
🎯 PRACTICAL IMPLEMENTATION
Getting Started
1. Apply indicator with default settings
2. Select appropriate theme for your markets
3. Observe dashboard metrics during different market conditions
4. Practice signal identification without trading
5. Gradually adjust parameters based on observations
Signal Confirmation Process
- Never trade on score alone - verify quality rating
- Confirm OFPI alignment with intended direction
- Check fractal grid level proximity for timing
- Ensure Möbius field strength supports position size
- Validate against HTF trend for bias confirmation
Performance Monitoring
- Track win rate in dashboard for strategy assessment
- Monitor component contributions for optimization
- Adjust threshold based on desired signal frequency
- Document performance across different market regimes
🌟 UNIQUE INNOVATIONS
1. First Integration of Langlands Program mathematics with practical trading
2. Revolutionary OFPI with T3 smoothing and momentum detection
3. Operadic Composition using category theory for signal democracy
4. Dynamic Fractal Grid with projected L-Score calculations
5. Multi-Dimensional Visualization through morphism flow portals
6. Regime-Adaptive Background showing market energy intensity
7. Balanced Signal Generation preventing directional bias
8. Professional Dashboard with institutional-grade metrics
📚 EDUCATIONAL VALUE
The LOMV serves as both a practical trading tool and an educational gateway to advanced mathematics. Traders gain exposure to:
- Pure mathematics applications in markets
- Category theory and operadic composition
- Number theory through Möbius function implementation
- Harmonic analysis via L-function calculations
- Advanced signal processing through T3 smoothing
⚖️ RESPONSIBLE USAGE
This indicator represents advanced mathematical research applied to market analysis. While the underlying mathematics are rigorously implemented, markets remain inherently unpredictable.
Key Principles:
- Use as part of comprehensive trading strategy
- Implement proper risk management at all times
- Backtest thoroughly before live implementation
- Understand that past performance does not guarantee future results
- Never risk more than you can afford to lose
The mathematics reveal deep market structure, but successful trading requires discipline, patience, and sound risk management beyond any indicator.
🔮 CONCLUSION
The Langlands-Operadic Möbius Vortex represents a quantum leap forward in technical analysis, bringing PhD-level pure mathematics to practical trading while maintaining visual elegance and usability.
From the harmonic analysis of the Langlands Program to the democratic composition of operadic theory, from the number-theoretic precision of the Möbius function to the revolutionary Order Flow Polarity Index, every component works in mathematical harmony to reveal the hidden order within market chaos.
This is more than an indicator - it's a mathematical lens that transforms how you see and understand market structure.
Trade with mathematical precision. Trade with the LOMV.
*"Mathematics is the language with which God has written the universe." - Galileo Galilei*
*In markets, as in nature, profound mathematical beauty underlies apparent chaos. The LOMV reveals this hidden order.*
— Dskyz, Trade with insight. Trade with anticipation.
DCA Investment Tracker Pro [tradeviZion]DCA Investment Tracker Pro: Educational DCA Analysis Tool
An educational indicator that helps analyze Dollar-Cost Averaging strategies by comparing actual performance with historical data calculations.
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💡 Why I Created This Indicator
As someone who practices Dollar-Cost Averaging, I was frustrated with constantly switching between spreadsheets, calculators, and charts just to understand how my investments were really performing. I wanted to see everything in one place - my actual performance, what I should expect based on historical data, and most importantly, visualize where my strategy could take me over the long term .
What really motivated me was watching friends and family underestimate the incredible power of consistent investing. When Napoleon Bonaparte first learned about compound interest, he reportedly exclaimed "I wonder it has not swallowed the world" - and he was right! Yet most people can't visualize how their $500 monthly contributions today could become substantial wealth decades later.
Traditional DCA tracking tools exist, but they share similar limitations:
Require manual data entry and complex spreadsheets
Use fixed assumptions that don't reflect real market behavior
Can't show future projections overlaid on actual price charts
Lose the visual context of what's happening in the market
Make compound growth feel abstract rather than tangible
I wanted to create something different - a tool that automatically analyzes real market history, detects volatility periods, and shows you both current performance AND educational projections based on historical patterns right on your TradingView charts. As Warren Buffett said: "Someone's sitting in the shade today because someone planted a tree a long time ago." This tool helps you visualize your financial tree growing over time.
This isn't just another calculator - it's a visualization tool that makes the magic of compound growth impossible to ignore.
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🎯 What This Indicator Does
This educational indicator provides DCA analysis tools. Users can input investment scenarios to study:
Theoretical Performance: Educational calculations based on historical return data
Comparative Analysis: Study differences between actual and theoretical scenarios
Historical Projections: Theoretical projections for educational analysis (not predictions)
Performance Metrics: CAGR, ROI, and other analytical metrics for study
Historical Analysis: Calculates historical return data for reference purposes
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🚀 Key Features
Volatility-Adjusted Historical Return Calculation
Analyzes 3-20 years of actual price data for any symbol
Automatically detects high-volatility stocks (meme stocks, growth stocks)
Uses median returns for volatile stocks, standard CAGR for stable stocks
Provides conservative estimates when extreme outlier years are detected
Smart fallback to manual percentages when data insufficient
Customizable Performance Dashboard
Educational DCA performance analysis with compound growth calculations
Customizable table sizing (Tiny to Huge text options)
9 positioning options (Top/Middle/Bottom + Left/Center/Right)
Theme-adaptive colors (automatically adjusts to dark/light mode)
Multiple display layout options
Future Projection System
Visual future growth projections
Timeframe-aware calculations (Daily/Weekly/Monthly charts)
1-30 year projection options
Shows projected portfolio value and total investment amounts
Investment Insights
Performance vs benchmark comparison
ROI from initial investment tracking
Monthly average return analysis
Investment milestone alerts (25%, 50%, 100% gains)
Contribution tracking and next milestone indicators
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📊 Step-by-Step Setup Guide
1. Investment Settings 💰
Initial Investment: Enter your starting lump sum (e.g., $60,000)
Monthly Contribution: Set your regular DCA amount (e.g., $500/month)
Return Calculation: Choose "Auto (Stock History)" for real data or "Manual" for fixed %
Historical Period: Select 3-20 years for auto calculations (default: 10 years)
Start Year: When you began investing (e.g., 2020)
Current Portfolio Value: Your actual portfolio worth today (e.g., $150,000)
2. Display Settings 📊
Table Sizes: Choose from Tiny, Small, Normal, Large, or Huge
Table Positions: 9 options - Top/Middle/Bottom + Left/Center/Right
Visibility Toggles: Show/hide Main Table and Stats Table independently
3. Future Projection 🔮
Enable Projections: Toggle on to see future growth visualization
Projection Years: Set 1-30 years ahead for analysis
Live Example - NASDAQ:META Analysis:
Settings shown: $60K initial + $500/month + Auto calculation + 10-year history + 2020 start + $150K current value
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🔬 Pine Script Code Examples
Core DCA Calculations:
// Calculate total invested over time
months_elapsed = (year - start_year) * 12 + month - 1
total_invested = initial_investment + (monthly_contribution * months_elapsed)
// Compound growth formula for initial investment
theoretical_initial_growth = initial_investment * math.pow(1 + annual_return, years_elapsed)
// Future Value of Annuity for monthly contributions
monthly_rate = annual_return / 12
fv_contributions = monthly_contribution * ((math.pow(1 + monthly_rate, months_elapsed) - 1) / monthly_rate)
// Total expected value
theoretical_total = theoretical_initial_growth + fv_contributions
Volatility Detection Logic:
// Detect extreme years for volatility adjustment
extreme_years = 0
for i = 1 to historical_years
yearly_return = ((price_current / price_i_years_ago) - 1) * 100
if yearly_return > 100 or yearly_return < -50
extreme_years += 1
// Use median approach for high volatility stocks
high_volatility = (extreme_years / historical_years) > 0.2
calculated_return = high_volatility ? median_of_returns : standard_cagr
Performance Metrics:
// Calculate key performance indicators
absolute_gain = actual_value - total_invested
total_return_pct = (absolute_gain / total_invested) * 100
roi_initial = ((actual_value - initial_investment) / initial_investment) * 100
cagr = (math.pow(actual_value / initial_investment, 1 / years_elapsed) - 1) * 100
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📊 Real-World Examples
See the indicator in action across different investment types:
Stable Index Investments:
AMEX:SPY (SPDR S&P 500) - Shows steady compound growth with standard CAGR calculations
Classic DCA success story: $60K initial + $500/month starting 2020. The indicator shows SPY's historical 10%+ returns, demonstrating how consistent broad market investing builds wealth over time. Notice the smooth theoretical growth line vs actual performance tracking.
MIL:VUAA (Vanguard S&P 500 UCITS) - Shows both data limitation and solution approaches
Data limitation example: VUAA shows "Manual (Auto Failed)" and "No Data" when default 10-year historical setting exceeds available data. The indicator gracefully falls back to manual percentage input while maintaining all DCA calculations and projections.
MIL:VUAA (Vanguard S&P 500 UCITS) - European ETF with successful 5-year auto calculation
Solution demonstration: By adjusting historical period to 5 years (matching available data), VUAA auto calculation works perfectly. Shows how users can optimize settings for newer assets. European market exposure with EUR denomination, demonstrating DCA effectiveness across different markets and currencies.
NYSE:BRK.B (Berkshire Hathaway) - Quality value investment with Warren Buffett's proven track record
Value investing approach: Berkshire Hathaway's legendary performance through DCA lens. The indicator demonstrates how quality companies compound wealth over decades. Lower volatility than tech stocks = standard CAGR calculations used.
High-Volatility Growth Stocks:
NASDAQ:NVDA (NVIDIA Corporation) - Demonstrates volatility-adjusted calculations for extreme price swings
High-volatility example: NVIDIA's explosive AI boom creates extreme years that trigger volatility detection. The indicator automatically switches to "Median (High Vol): 50%" calculations for conservative projections, protecting against unrealistic future estimates based on outlier performance periods.
NASDAQ:TSLA (Tesla) - Shows how 10-year analysis can stabilize volatile tech stocks
Stable long-term growth: Despite Tesla's reputation for volatility, the 10-year historical analysis (34.8% CAGR) shows consistent enough performance that volatility detection doesn't trigger. Demonstrates how longer timeframes can smooth out extreme periods for more reliable projections.
NASDAQ:META (Meta Platforms) - Shows stable tech stock analysis using standard CAGR calculations
Tech stock with stable growth: Despite being a tech stock and experiencing the 2022 crash, META's 10-year history shows consistent enough performance (23.98% CAGR) that volatility detection doesn't trigger. The indicator uses standard CAGR calculations, demonstrating how not all tech stocks require conservative median adjustments.
Notice how the indicator automatically detects high-volatility periods and switches to median-based calculations for more conservative projections, while stable investments use standard CAGR methods.
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📈 Performance Metrics Explained
Current Portfolio Value: Your actual investment worth today
Expected Value: What you should have based on historical returns (Auto) or your target return (Manual)
Total Invested: Your actual money invested (initial + all monthly contributions)
Total Gains/Loss: Absolute dollar difference between current value and total invested
Total Return %: Percentage gain/loss on your total invested amount
ROI from Initial Investment: How your starting lump sum has performed
CAGR: Compound Annual Growth Rate of your initial investment (Note: This shows initial investment performance, not full DCA strategy)
vs Benchmark: How you're performing compared to the expected returns
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⚠️ Important Notes & Limitations
Data Requirements: Auto mode requires sufficient historical data (minimum 3 years recommended)
CAGR Limitation: CAGR calculation is based on initial investment growth only, not the complete DCA strategy
Projection Accuracy: Future projections are theoretical and based on historical returns - actual results may vary
Timeframe Support: Works ONLY on Daily (1D), Weekly (1W), and Monthly (1M) charts - no other timeframes supported
Update Frequency: Update "Current Portfolio Value" regularly for accurate tracking
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📚 Educational Use & Disclaimer
This analysis tool can be applied to various stock and ETF charts for educational study of DCA mathematical concepts and historical performance patterns.
Study Examples: Can be used with symbols like AMEX:SPY , NASDAQ:QQQ , AMEX:VTI , NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:GOOGL , NASDAQ:AMZN , NASDAQ:TSLA , NASDAQ:NVDA for learning purposes.
EDUCATIONAL DISCLAIMER: This indicator is a study tool for analyzing Dollar-Cost Averaging strategies. It does not provide investment advice, trading signals, or guarantees. All calculations are theoretical examples for educational purposes only. Past performance does not predict future results. Users should conduct their own research and consult qualified financial professionals before making any investment decisions.
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© 2025 TradeVizion. All rights reserved.
RRC Sniper SetupRRC Sniper Setup, this looks at candles this way:
Go to Market Scanner
Create New Scan → "RRC Sniper Setup"
Add filters listed below with timeframe logic (e.g. 1m/5m)
Run scan on:
Your Watchlist
SPY 500
QQQ 100
AI/Momentum names
1. Reclaim Filter
Find price breaking back above a key level (VWAP or EMA113)
Last 1m Close > EMA 113 (1m)
OR
Last 5m Close > VWAP
2. Retrace Filter
Price pulls back into the zone and holds within a tight range
Current Price < VWAP * 1.0025
AND
Current Price > VWAP * 0.9975
AND
Volume (Current Candle) < Volume (Previous Candle)
✅ 3. Confirm Filter
Price begins moving back up with confirmation candle and volume
Last Candle Close > Last Candle Open
AND
Volume (Current Candle) > Volume (Previous Candle)
ML: Lorentzian Classification Premium█ OVERVIEW
Lorentzian Classification Premium represents the culmination of two years of collaborative development with over 1,000 beta testers from the TradingView community. Building upon the foundation of the open-source version, this premium edition introduces powerful enhancements that transform how machine-learning classification can be applied to market analysis.
The premium version maintains the core Lorentzian distance-based classification algorithm while expanding its capabilities through triple the feature dimensionality (up to 15 features), sophisticated mean-reversion detection, first-pullback identification, and a comprehensive signal taxonomy that goes far beyond simple buy/sell signals. Whether you're building automated trading systems, conducting deep market research, or integrating proprietary indicators into ML workflows, this tool provides the advanced edge needed for professional-grade analysis.
█ BACKGROUND
Lorentzian Classification analyzes market structures, especially those exhibiting non-linear distortions under stress, by employing advanced distance metrics like the Lorentzian metric, prominent in fields such as relativity theory. Where traditional indicators assume flat space, we embrace the curve. The heart of this approach is the Lorentzian distance metric—a sophisticated mathematical tool. This framework adeptly navigates the complex curves and distortions of market space, aiming to provide insights that traditional analysis might miss, especially during moments of extreme volatility. It analyzes historical data from a multi-dimensional feature space consisting of various technical indicators of your choosing. Where traditional approaches fail, Lorentzian space reveals the true geometry of market dynamics.
Neighborhoods in Different Geometries: In the above figure, the Lorentzian metric creates distinctive cross-patterns aligned with feature axes (RSI, CCI, ADX), capturing both local similarity and dimensional extremes. This unique geometry allows the algorithm to recognize similar market conditions that Euclidean spheres and Manhattan diamonds would miss entirely. In LC Premium, users can have up to 15 features -- you are not limited to 3-dimensions.
Among the thousands of distance metrics discovered by mathematicians, each perceives data through its own geometric lens. The Lorentzian metric stands apart with its unique ability to capture market behavior during volatile events.
█ COMMUNITY-DRIVEN EVOLUTION
It has been profoundly humbling over the past 2 years to witness this indicator's evolution through the collaborative efforts of our incredible community. This journey has been shaped by thousands of user suggestions and validated through real-world application.
A particularly amazing milestone was the development of a complete community-driven Python port, which meticulously matched even the most minute PineScript quirks. Building on this solid foundation, a new command-line interface (CLI) has opened up exciting possibilities for chart-specific parameter optimization:
Early insights from parameter optimization research: Through grid-search testing across thousands of parameter combinations, the analysis identifies which parameters have the biggest effects on performance and maps regions of stability across different market regimes. This reveals that optimal neighbor counts vary significantly based on market conditions—opening up incredible potential for timeframe-specific optimization.
This is just one of the insights gleaned so far from this ongoing investigation. The potential for chart-specific optimization for any given timeframe could transform how traders approach parameter selection.
Demand from power users for extra capabilities—while keeping the open-source version simple—sparked this Premium release. The open-source branch remains maintained, but the premium tier adds unique features for those who need an analytical edge and to leverage their own custom indicators as feature series for the algorithm.
█ KEY PREMIUM FEATURES
📈 First Pullback Detection System
Automatically identifies high-probability trend-continuation entries after initial momentum moves.
Detects when price retraces to optimal entry zones following breakouts or trend initiations.
Green/red triangle signals often fire before main classification arrows.
Dedicated alerts for both bullish and bearish pullback opportunities.
Based on veryfid's extensive research into pullback mechanics and market structure.
🔄 Dynamic Kernel Regression Envelope
Powerful, zero-setup confluence layer that immediately communicates trend shifts.
Dual-kernel system creates a visual envelope between trend estimates.
Color gradient dynamically represents prediction strength and market conviction.
Crossovers provide additional confirmation without cluttering your chart.
Professional visualization that rivals institutional-grade analysis tools.
✨ Massively Expanded Dimensionality: 10 Custom Sources, 5 Built-In Sources
Transform the indicator from 5 built-in standard to 15 total total features—triple the analytical power.
Integrate ANY TradingView indicator as a machine learning feature.
Built-in normalization ensures all indicators contribute equally regardless of scale.
Create theme-based systems: pure volume analysis, multi-timeframe momentum, or hybrid approaches.
📊 Tiered Mean Reversion Signals with Scalping Alerts
Regular (🔄) and Strong (⬇️/⬆️) mean reversion signals based on statistical extremes.
Opportunities often arise before candle close—perfect for scalping entries.
Visual markers appear at high-probability reversal zones.
Four specialized alert types: upward/downward for both regular and strong reversals.
Pre-optimized probability thresholds, no fine-tuning required.
📅 Daily Kernel Trend Filter
Instantly cleans up noisy intraday charts by aligning with higher timeframe trends.
Swing traders report immediate signal quality improvement.
Automatically deactivates on daily+ timeframes (intelligent context awareness).
Reduces counter-trend signals by up to 60% on lower timeframes.
Simple toggle—no complex multi-timeframe setup required.
📋 Professional Backtesting Stream (-6 to +6)
Multiple distinct signal types (including pullbacks, mean reversions, and kernel deviations) vs. basic binary (buy/sell) output for nuanced analysis.
Enables detailed walk-forward analysis and ML model training.
Compatible with external backtesting frameworks via numeric stream.
Rare precision for TradingView indicators—usually only found in institutional tools.
Perfect for quants building sophisticated strategy layers.
⚡ Performance Optimizations
Faster distance calculations through algorithmic improvements.
Reduced indicator load time (measured via Pine Profiler).
Handles 15 active features without timeouts—critical for multi-chart setups.
Optimized for live auto-trading bots requiring minimal latency.
🎨 Full Visual Customization & Accessibility
Complete color control for all visual elements.
Colorblind-safe default palette with customization options.
Dark mode optimization for extended trading sessions.
Professional appearance matching your trading workspace.
Accessibility features meeting modern UI standards.
🛠️ Advanced Training Modes
Downsampling mode for training on diverse market conditions; Down-sampling and remote-fractals for exotic pattern discovery.
Remote fractals option extends analysis to deep historical patterns.
Reset factor control for fine-tuning neighbor diversity; Reset-factor tuning to control neighbor diversity.
Appeals to systematic traders exploring exotic data approaches.
Prevents temporal clustering bias in model training.
█ HOW TO USE
Understanding the Approach (Core Concept):
Lorentzian Classification uses a k-Nearest Neighbors (k-NN) algorithm. It searches for historical price action "neighborhoods" similar to the current market state. Instead of a simple straight-line (Euclidean) distance, it primarily uses a Lorentzian distance metric, which can account for market "warping" or distortions often seen during high volatility or significant events. Each historical neighbor "votes" on what happened next in its context, and these votes aggregate into a classification score for the current bar.
Interpreting Bar Scores & Signals (Interpreting the Chart):
Bar Prediction Values: Numbers over each candle (e.g., ranging from -8 to +8 if Neighbors Count is 8) represent the aggregated vote from the nearest neighbors. Strong positive scores (e.g., +7, +8) indicate a strong bullish consensus among historical analogs. Strong negative scores (e.g., -7, -8) indicate a strong bearish consensus. Scores near zero suggest neutrality or conflicting signals from neighbors. The intensity of bar colors (if Use Confidence Gradient is on) often reflects these scores.
Main Arrows (Main Buy/Sell Labels): Large ▲/▼ labels are the primary entry signals generated when the overall classification (after filters) is bullish or bearish.
Pullback Triangles: Small green/red ▲/▼ identify potential trend continuation entries. These signals often appear after an initial price move and a subsequent minor retracement, suggesting the trend might resume. This is based on recognizing patterns where a brief counter-movement is followed by a continued advance in the initial trend direction.
Mean-Reversion Symbols: 🔄 (Regular Reversion) appears when price has crossed the average band of the Dynamic Kernel Regression Envelope. ⬇️/⬆️ (Strong Reversion) means price has crossed the far band of the envelope, indicating a more extreme deviation and potentially a stronger reversion opportunity.
Custom Mean Reversion Deviation Markers (Deviation Dots): If Enable Custom Mean Reversion Alerts is on, these dots appear when price deviates from the main kernel regression line by a user-defined ATR multiple, signaling a custom-defined reversion opportunity.
Kernel Regression Lines & Envelope: The Main Kernel Estimate (thicker line) is an adaptive moving average that smooths price and helps identify trend direction. Its color indicates the current trend bias. The Envelope (outer bands and a midline) creates a channel around price, and its interaction with price generates mean reversion signals.
Key Input Groups & Their Purpose:
🔧 GENERAL SETTINGS:
Reduce Price-Time Warping : Toggles the distance metric. When enabled, it reduces the characteristic "warping" effect of the default Lorentzian metric, making the distance calculation more Euclidean in nature. This may be suited for periods exhibiting less pronounced price-time distortions.
Source : Price data for calculations (default: close ).
Neighbors Count : The 'k' in k-NN – number of historical analogs considered.
Max Bars Back : How far back the indicator looks for historical patterns.
Show Exits / Use Dynamic Exits : Controls visibility and logic for exit signals.
Include Full History (Use Remote Fractals) : Allows model to pick "exotic" fractals from deep chart history.
Use Downsampling / Reset Factor : Advanced training parameters affecting neighbor selection.
Show Trade Stats / Use Worst Case Estimates : Displays a real-time performance table (for calibration only).
🎛️ DEFINE CUSTOM SOURCES (OPTIONAL):
Integrate up to 10 external data series (e.g., from other indicators) as features. Each can be optionally normalized. Load the external indicator on your chart first for it to appear in the dropdown.
🧠 FEATURE ENGINEERING:
Configure up to 15 features for the k-NN algorithm. Select type (RSI, WT, CCI, ADX, Custom Sources), parameters, and enable/disable. Start simple (3-5 features) and add complexity gradually. Normalize features with vastly different scales.
🖥️ DISPLAY SETTINGS:
Controls visibility of chart elements: bar colors, prediction values/labels, envelope, etc.
Align Signal with Current Bar : If true, pullback signals appear on the current bar (calculated on closed data). If false (default), they appear on the next bar.
Use ATR Offset : Positions bar prediction values using ATR for visibility.
🧮 FILTERS SETTINGS:
Refine raw classification signals: Volatility, Regime, ADX, EMA/SMA, and Daily Kernel filters.
🌀 KERNEL SETTINGS (Main Kernel):
Adjust parameters for the primary Nadaraya-Watson Kernel Regression line. Lookback Window , Relative Weighting , Regression Level , Lag control sensitivity and smoothness.
✉️ ENVELOPE SETTINGS (for Mean Reversion):
Configure the dynamic Kernel Regression Envelope. ATR Length , Near/Far ATR Factor define band width.
🎨 COLOR SETTINGS (Colors):
Customize colors for all visual elements; override every palette element.
General Approach to Using the Indicator (Suggested Workflow):
Load defaults and observe behavior: Familiarize yourself with the indicator's behavior.
Feature Engineering: Experiment with features, considering momentum, trend, and volatility. Add/replace features gradually.
Apply Filters: Refine signals according to your trading style.
Contextualize: Use kernels and envelope to understand broader trend and potential overbought/oversold areas.
Observe Signals: Pay attention to the interplay of main signals, pullbacks, and mean reversions. Watch interplay of main, pullback & mean-reversion signals.
Calibrate (Not Backtest): Use the "Trade Stats" table for real-time feedback on current settings. This is for calibration, *not a substitute for rigorous backtesting.*
Iterate & refine: Adjust settings, observe outcomes, and refine your approach.
█ ACKNOWLEDGMENTS
This premium version wouldn't exist without the invaluable contributions of:
veryfid for his groundbreaking ideas on unifying pullback detection with Lorentzian Classification, but most of all for always believing in and encouraging me and so many others. For being a mentor and, most importantly, a friend. We all miss you.
RikkiTavi for his help in creating the settings optimization framework and for other invaluable theoretical discussions.
The 1,000+ beta testers worldwide who provided continuous feedback over two years.
The Python porting team who created the foundation for advanced optimization; for the cross-language clone.
The broader TradingView community for making this one of the platform's most popular indicators.
█ FUTURE DEVELOPMENT
The Premium version will continue to evolve based on community feedback. Planned enhancements include:
Specialized exit model trained independently from entry signals (ML-based exit model).
Feature hub with pre-normalized, commonly requested indicators (Pre-normalized feature hub).
Better risk-management options (Enhanced risk-management options).
Fully automated settings optimization (Auto-settings optimization tool).
Enhanced Cycle IndicatorEnhanced Cycle Indicator Guide
DISCLAIMER
"This PineScript indicator evolved from a foundational algorithm designed to visualize cycle-based center average differentials. The original concept has been significantly enhanced and optimized through collaborative refinement with AI, resulting in improved functionality, performance, and visualization capabilities while maintaining the core mathematical principles of the original design"
Overview
The Enhanced Cycle Indicator is designed to identify market cycles with minimal lag while ensuring the cycle lows and highs correspond closely with actual price bottoms and tops. This indicator transforms price data into observable cycles that help you identify when a market is likely to change direction.
Core Principles
Cycle Detection: Identifies natural market rhythms using multiple timeframes
Dynamic Adaptation: Adjusts to changing market conditions for consistent performance
Precise Signals: Provides clear entry and exit points aligned with actual market turns
Reduced Lag: Uses advanced calculations to minimize delay in cycle identification
How To Use
1. Main Cycle Interpretation
Green Histogram Bars: Bullish cycle phase (upward momentum)
Red Histogram Bars: Bearish cycle phase (downward momentum)
Cycle Extremes: When the histogram reaches extreme values (+80/-80), the market is likely approaching a turning point
Zero Line: Crossovers often indicate a shift in the underlying market direction
2. Trading Signals
Green Triangle Up (bottom of chart): Strong bullish signal - ideal for entries or covering shorts
Red Triangle Down (top of chart): Strong bearish signal - ideal for exits or short entries
Diamond Shapes: Indicate divergence between price and cycle - early warning of potential reversals
Small Circles: Minor cycle turning points - useful for fine-tuning entries/exits
3. Optimal Signal Conditions
Bullish Signals Work Best When:
The cycle is deeply oversold (below -60)
RSI is below 40 or turning up
Price is near a significant low
Multiple confirmation bars have occurred
Bearish Signals Work Best When:
The cycle is heavily overbought (above +60)
RSI is above 60 or turning down
Price is near a significant high
Multiple confirmation bars have occurred
4. Parameter Adjustments
For Shorter Timeframes: Reduce cycle periods and smoothing factor for faster response
For Daily/Weekly Charts: Increase cycle periods and smoothing for smoother signals
For Volatile Markets: Reduce cycle responsiveness to filter noise
For Trending Markets: Increase signal confirmation requirement to avoid false signals
Recommended Settings
Default (All-Purpose)
Main Cycle: 50
Half Cycle: 25
Quarter Cycle: 12
Smoothing Factor: 0.5
RSI Filter: Enabled
Signal Confirmation: 2 bars
Faster Response (Day Trading)
Main Cycle: 30
Half Cycle: 15
Quarter Cycle: 8
Smoothing Factor: 0.3
Cycle Responsiveness: 1.2
Signal Confirmation: 1 bar
Smoother Signals (Swing Trading)
Main Cycle: 80
Half Cycle: 40
Quarter Cycle: 20
Smoothing Factor: 0.7
Cycle Responsiveness: 0.8
Signal Confirmation: 3 bars
Advanced Features
Adaptive Period
When enabled, the indicator automatically adjusts cycle periods based on recent price volatility. This is particularly useful in markets that alternate between trending and ranging behaviors.
Momentum Filter
Enhances cycle signals by incorporating price momentum, making signals more responsive during strong trends and less prone to whipsaws during consolidations.
RSI Filter
Adds an additional confirmation layer using RSI, helping to filter out lower-quality signals and improve overall accuracy.
Divergence Detection
Identifies situations where price makes a new high/low but the cycle doesn't confirm, often preceding significant market reversals.
Best Practices
Use the indicator in conjunction with support/resistance levels
Look for signal clusters across multiple timeframes
Reduce position size when signals appear far from cycle extremes
Pay special attention to signals that coincide with divergences
Customize cycle periods to match the natural rhythm of your traded instrument
Troubleshooting
Too Many Signals: Increase signal confirmation bars or reduce cycle responsiveness
Missing Major Turns: Decrease smoothing factor or increase cycle responsiveness
Signals Too Late: Decrease cycle periods and smoothing factor
False Signals: Enable RSI filter and increase signal confirmation requirement
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
