Quantum X StrategyQuantum X Strategy
Designed for: MIDCPNIFTY (15-minute timeframe)
🔍 Overview
Quantum X Strategy is a structured, rule-driven trading framework built to identify directional strength and controlled trend phases.
The strategy evaluates market behavior through a layered confirmation model and executes trades only when multiple internal conditions align.
🧠 Concept (High-Level Only — Safe for Publishing)
Quantum X uses a multi-filter decision engine that reacts to trend formation, momentum alignment, and market stability.
To maintain the script’s confidentiality, the internal formula, thresholds, and sequencing logic remain intentionally abstracted.
What users need to know:
It filters weak trend phases
It waits for synchronized directional confirmation
It avoids entries in unstable or noisy price zones
It focuses on capturing structured intraday swings
(TradingView fully allows this level of conceptual explanation.)
⚙️ How the Strategy Operates
Without revealing internal code, here is the functional behavior:
Evaluates directional bias with layered filters
Confirms market strength before execution
Automates both entry and exit management
Applies time-based and condition-based protective rules
Works best in instruments that show clean intraday rotation
📌 Intended Use
While users may experiment freely, this strategy is designed for MIDCPNIFTY on the 15-minute timeframe, as the internal structure aligns well with this instrument’s behavior pattern.
🛡️ Important Notes
This script is for research and systematic testing.
No future returns or performance are guaranteed.
Users should validate settings before applying in live markets.
All internal logic is protected by closed-source compilation.
Sentiment
GIX Analizor strategiiGIX Analyzer – Intelligent Time Filters + X Strategy
This script combines the X Strategy with an advanced system for filtering trades based on time intervals. The strategy allows:
Filtering by preset trading hours (active sessions )
Filtering by a fully customizable time interval (hour + minute, Romania time )
Filtering by calendar range (Start Date → End Date)
Simultaneous activation of both time-filter modes for maximum control
Trading only within valid time ranges, while keeping all logic unchanged
This indicator provides high flexibility for testing and optimizing trading entries based on hours, minutes, and calendar periods—while preserving the simplicity and efficiency of any strategy
Market Dynamics - Backtest Engine [NeuraAlgo]Market Dynamics – Backtest Engine
Market Dynamics – Backtest Engine is an advanced research-grade trading framework engineered by NeuraAlgo.
🔹 Core Engine – Dynamic Trend Model
The strategy leverages the NeuraAlgo – Market Dynamics indicator as its foundation, providing intelligent insights to guide trading decisions. It is designed to automatically identify the optimal settings for the NeuraAlgo – Market Dynamics indicator, helping traders fine-tune their strategy for maximum efficiency, accuracy, and profitability. This engine dynamically adapts to market conditions, ensuring your strategy stays optimized in real-time.
🔹 Optimization Engine
A built-in optimization module allows automatic testing of:
Winrate-focused configurations
Profit-focused configurations
Sensitivity ranges
Step sizes
Main Entry, Main Filter, Feature Filter, and Risk Manager categories
This enables rapid identification of optimal parameters similar to a lightweight AI optimizer.
This Backtesting + Auto Optimization Engine includes an integrated optimizer that automatically tests sensitivity ranges:
Maximize Winrate
Maximize Profits
Optimize Main Entries, Risk Manager, or Feature Filters
Users can set:
start sensitivity
step size
parameter category
The engine autonomously computes which parameter delivers the strongest performance.
🔹 How To Use
1. Identify the Parameters
First, you need to know which indicator parameters can be optimized. For the NeuraAlgo – Market Dynamics indicator, these might include:
Trend sensitivity
Smoothing periods
Threshold values for bullish/bearish signals
These parameters are the inputs your engine will test.
2. Define a Range
For each parameter, define a range of values to test. Example:
Sensitivity: 2 → 10
Trend period: 14 → 50
Threshold: 0.1 → 1.0
The more granular the range, the more precise the optimization—but it will also take longer.
3. Run Backtest Optimization
Attach the strategy to a chart.
Select optimization mode in your engine (or set the range for each parameter).
Start the backtest: the engine will simulate trades for every combination of parameter values.
The system will automatically record key metrics for each run:
Net profit
Win rate
Profit factor
Max drawdown
4. Analyze the Results
After the backtest, your engine will display a results table or chart showing performance for each parameter combination. Look for:
Highest net profit
Highest win rate
Or a combination depending on your strategy goals
Some engines will highlight the “best” parameter set automatically.
5. Apply Optimal Settings
Once identified:
Select the best-performing parameter values.
Apply them to your live strategy or paper trade.
Optionally, forward test to confirm they work on unseen market data.
Congratulations! The setup is now optimized.
🔹 Conclusion
The backtest optimization process helps you find the best parameter values for the NeuraAlgo – Market Dynamics indicator by systematically testing different settings and measuring their performance. By analyzing metrics like net profit, win rate, and drawdown, you can select optimized parameters that are more likely to perform consistently in real trading. Proper optimization ensures your strategy is data-driven, adaptable, and reduces guesswork, giving you a stronger edge in the market.
Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure.
To use this engine successfully, you must adopt a specific optimization mindset:
Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless.
Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the trade is rejected.
This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal.
Module 2: Correlation Trend Indicator (CTI)
Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend).
Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise).
Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts).
Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support.
Module 6: Crypto Market Breadth (CMB)
Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges.
Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data.
Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart.
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen.
Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up.
Module 11: HSRS Compression / Super AO
Logic: Two options in one.
HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands.
Super AO: A combination of the Awesome Oscillator and SuperTrend logic.
Function: Great for catching explosive moves that result from periods of low volatility (consolidation).
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked.
Bitcoin Halving Logic:
Hardcoded dates for past and projected future Bitcoin halvings (up to 2040).
Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes.
Miner Capitulation:
Uses Hash Rate Ribbons (Moving averages of Hash Rate).
If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat.
ADX Filter (Flat Market Protocol):
If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market.
CryptoCap Trend:
Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins.
6. Risk Management & The Dump Protection Team (DPT)
Gypsy Bot separates "Entry Logic" from "Risk Management Logic."
Dump Protection Team (DPT)
This is a specialized logic branch designed to save the account during Black Swan events.
Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit.
Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction.
Advanced Adaptive Trailing Stop (AATS)
Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic.
Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks.
Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital.
Staged Take Profits
TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win.
TP2: Take the bulk of profit.
TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance.
Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative).
Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals).
Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Damians UJ Strategy20 Pip Candle Strategy (No Engulfing)
Trades taken at 6pm direcrtly after candle close
Inputs allow you to reorganize retracement pips, SL, TP, 5PM candle amount.
Momentum Reversal / Dip Buyer [Score Based]Strategy Overview
Momentum Reversal / Dip Buyer is a quantitative reversal engine designed to fade stretched moves and buy dips / sell rallies when multiple momentum and context factors line up. It’s built for liquid instruments especially for ticker CME_MINI:ES1! and works best on intraday timeframes like the 5-minute or 1-minute chart.
Core Logic
This strategy builds a composite Momentum Score by combining:
Price Location: Relative to 100 SMA, 1000 EMA, and VWAP (trend / regime filter).
RSI: Overbought/oversold and mid-zone strength.
VWMO (Volume-Weighted Momentum): Direction and strength of volume-weighted price drift.
ADX: Trend strength filter (high vs low trend environment).
Full Stoch (%K): Short-term exhaustion and mean-reversion context.
CCI: Overbought/oversold turns (key trigger).
MFI: Volume-confirmed buying/selling pressure.
ATR Regime: High vs low volatility environment.
Cumulative Delta: Whether net aggressor flow is rising or falling.
From this, a single Momentum Score is computed each bar:
Longs: Taken when the score is depressed (scoreLow) and CCI crosses up from oversold.
Shorts: Taken when the score is elevated (scoreHigh) and CCI crosses down from overbought.
Risk Management & Trade Logic
Max Daily Trades: Hard cap on entries per day.
Hard Stop: Fixed % stop based on entry price.
Profit Target: Target ATR Multiplier × main ATR from entry.
Breakeven Logic: Optional; moves stop to breakeven (plus optional offset) after price moves a configurable multiple of the main ATR in your favor.
Trailing Stop (Separate ATR): Optional; uses its own ATR length and ATR-based trigger and distance. This lets you run slower ATR for targets while using a tighter, more reactive ATR for the trail.
Session Control
Trading Window: Optional session filter (e.g., 09:30–16:00). Entries are only allowed inside the defined window.
Force Flat at Session End: Option to automatically close all open positions when the session ends.
Visuals
The script plots entry arrows and a compact dashboard displaying: current Momentum Score, daily trade usage, and CCI status.
Disclaimer:
This script is for educational and research purposes only and is not financial advice. Past performance does not guarantee future results. Always forward-test and adjust parameters to your own risk tolerance and market.
Shoutout and all credit goes to AuclairsCapital for building the base foundation of this strategy on ThinkScript
BTC Fear & Greed Incremental StrategyIMPORTANT: READ SETUP GUIDE BELOW OR IT WON'T WORK
# BTC Fear & Greed Incremental Strategy — TradeMaster AI (Pure BTC Stack)
## Strategy Overview
This advanced Bitcoin accumulation strategy is designed for long-term hodlers who want to systematically take profits during greed cycles and accumulate during fear periods, while preserving their core BTC position. Unlike traditional strategies that start with cash, this approach begins with a specified BTC allocation, making it perfect for existing Bitcoin holders who want to optimize their stack management.
## Key Features
### 🎯 **Pure BTC Stack Mode**
- Start with any amount of BTC (configurable)
- Strategy manages your existing stack, not new purchases
- Perfect for hodlers who want to optimize without timing markets
### 📊 **Fear & Greed Integration**
- Uses market sentiment data to drive buy/sell decisions
- Configurable thresholds for greed (selling) and fear (buying) triggers
- Automatic validation to ensure proper 0-100 scale data source
### 🐂 **Bull Year Optimization**
- Smart quarterly selling during bull market years (2017, 2021, 2025)
- Q1: 1% sells, Q2: 2% sells, Q3/Q4: 5% sells (configurable)
- **NO SELLING** during non-bull years - pure accumulation mode
- Preserves BTC during early bull phases, maximizes profits at peaks
### 🐻 **Bear Market Intelligence**
- Multi-regime detection: Bull, Early Bear, Deep Bear, Early Bull
- Different buying strategies based on market conditions
- Enhanced buying during deep bear markets with configurable multipliers
- Visual regime backgrounds for easy market condition identification
### 🛡️ **Risk Management**
- Minimum BTC allocation floor (prevents selling entire stack)
- Configurable position sizing for all trades
- Multiple safety checks and validation
### 📈 **Advanced Visualization**
- Clean 0-100 scale with 2 decimal precision
- Three main indicators: BTC Allocation %, Fear & Greed Index, BTC Holdings
- Real-time portfolio tracking with cash position display
- Enhanced info table showing all key metrics
## How to Use
### **Step 1: Setup**
1. Add the strategy to your BTC/USD chart (daily timeframe recommended)
2. **CRITICAL**: In settings, change the "Fear & Greed Source" from "close" to a proper 0-100 Fear & Greed indicator
---------------
I recommend Crypto Fear & Greed Index by TIA_Technology indicator
When selecting source with this indicator, look for "Crypto Fear and Greed Index:Index"
---------------
3. Set your "Starting BTC Quantity" to match your actual holdings
4. Configure your preferred "Start Date" (when you want the strategy to begin)
### **Step 2: Configure Bull Year Logic**
- Enable "Bull Year Logic" (default: enabled)
- Adjust quarterly sell percentages:
- Q1 (Jan-Mar): 1% (conservative early bull)
- Q2 (Apr-Jun): 2% (moderate mid bull)
- Q3/Q4 (Jul-Dec): 5% (aggressive peak targeting)
- Add future bull years to the list as needed
### **Step 3: Fine-tune Thresholds**
- **Greed Threshold**: 80 (sell when F&G > 80)
- **Fear Threshold**: 20 (buy when F&G < 20 in bull markets)
- **Deep Bear Fear Threshold**: 25 (enhanced buying in bear markets)
- Adjust based on your risk tolerance
### **Step 4: Risk Management**
- Set "Minimum BTC Allocation %" (default 20%) - prevents selling entire stack
- Configure sell/buy percentages based on your position size
- Enable bear market filters for enhanced timing
### **Step 5: Monitor Performance**
- **Orange Line**: Your BTC allocation percentage (target: fluctuate between 20-100%)
- **Blue Line**: Actual BTC holdings (should preserve core position)
- **Pink Line**: Fear & Greed Index (drives all decisions)
- **Table**: Real-time portfolio metrics including cash position
## Reading the Indicators
### **BTC Allocation Percentage (Orange Line)**
- **100%**: All portfolio in BTC, no cash available for buying
- **80%**: 80% BTC, 20% cash ready for fear buying
- **20%**: Minimum allocation, maximum cash position
### **Trading Signals**
- **Green Buy Signals**: Appear during fear periods with available cash
- **Red Sell Signals**: Appear during greed periods in bull years only
- **No Signals**: Either allocation limits reached or non-bull year
## Strategy Logic
### **Bull Years (2017, 2021, 2025)**
- Q1: Conservative 1% sells (preserve stack for later)
- Q2: Moderate 2% sells (gradual profit taking)
- Q3/Q4: Aggressive 5% sells (peak targeting)
- Fear buying active (accumulate on dips)
### **Non-Bull Years**
- **Zero selling** - pure accumulation mode
- Enhanced fear buying during bear markets
- Focus on rebuilding stack for next bull cycle
## Important Notes
- **This is not financial advice** - backtest thoroughly before use
- Designed for **long-term holders** (4+ year cycles)
- **Requires proper Fear & Greed data source** - validate in settings
- Best used on **daily timeframe** for major trend following
- **Cash calculations**: Use allocation % and BTC holdings to calculate available cash: `Cash = (Total Portfolio × (1 - Allocation%/100))`
## Risk Disclaimer
This strategy involves active trading and position management. Past performance does not guarantee future results. Always do your own research and never invest more than you can afford to lose. The strategy is designed for educational purposes and long-term Bitcoin accumulation thesis.
---
*Developed by Sol_Crypto for the Bitcoin community. Happy stacking! 🚀*
Adaptive Averaging Concept [NeuraAlgo]Adaptive Averaging Concept
A Quant-Engineered Dynamic Position Sizing & Optimization Framework
Adaptive Averaging Concept™ is a next-generation, research-driven trading framework that combines multistage entries, ATR-based intelligent scaling, real-time sentiment filtering, and a fully automated optimization engine.
It is designed for traders who want precision execution, adaptive risk control, and an architecture capable of learning from market structure.
🔹 Core Concept
Unlike traditional averaging or DCA methods, this engine uses Adaptive Averaging — a controlled, mathematically tuned accumulation system that adjusts entries based on volatility, trend conditions, and signal confidence.
Each additional entry intelligently recalculates average price and updates a volatility-sensitive dynamic Take Profit.
🔹 Main Features
1. Intelligent Multi-Stage Entry System
Initial entries triggered by SMA crossover, rising volume, or Always-On mode
Secondary entries triggered only when price retraces by a volatility-adjusted threshold
Every added position recalculates:
Total quantities
Capital distribution
Average price
Adaptive Take Profit (ATR-based)
2. Adaptive Risk & Position Management
ATR-driven take-profit using Exit Sensitivity
ATR-driven add-entry logic using Exit Tuner
Dynamic or Fixed lot sizing
Capital-per-entry control
Automatic minimum lot protection
3. High-Level Market Filters
Trend Filter
A volatility-normalized EMA slope filter that identifies:
1.Bullish trend
2.Bearish trend
3.Neutral trend
Sentiment Cloud Filter
A structural sentiment engine analyzing:
1.Micro-gaps
2.Bull and bear pressure
3.Range compression
4.Market regime bias
Trades only execute when filters align with your directional bias.
4. NeuraAlgo Optimization Engine
The strategy includes a built-in optimizer allowing you to test & tune with no loops and no external computation.
You can automatically optimize:
Smooth Period (ATR)
Exit Sensitivity
Exit Tuner
SMA Period
Trend Filter Length
Trend Filter Smooth
Sentiment Cloud Period
Optimization Goals:
Maximize Winrate
Maximize Net Profits
This allows the strategy to self-configure based on live market conditions.
Here, the optimization is finally complete.
🔹 Summary
Adaptive Averaging Concept™ is not a simple indicator or basic DCA script.
It is a complete quant-grade execution engine capable of dynamically adjusting its behavior to volatility, price structure, trend strength, and sentiment.
Engineered for traders who demand:
High-precision entry logic
Adaptive position sizing
Volatility-calibrated exits
Smart accumulation
Built-in optimization
Professional-grade backtesting
It is a powerful framework suitable for swing traders, intraday traders, and automated system developers.
Superior-Range Bound Renko - Strategy - 11-29-25 - SignalLynxSuperior-Range Bound Renko Strategy with Advanced Risk Management Template
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
Welcome to Superior-Range Bound Renko (RBR) — a volatility-aware, structure-respecting swing-trading system built on top of a full Risk Management (RM) Template from Signal Lynx.
Instead of relying on static lookbacks (like “14-period RSI”) or plain MA crosses, Superior RBR:
Adapts its range definition to market volatility in real time
Emulates Renko Bricks on a standard, time-based chart (no Renko chart type required)
Uses a stack of Laguerre Filters to detect genuine impulse vs. noise
Adds an Adaptive SuperTrend powered by a small k-means-style clustering routine on volatility
Under the hood, this script also includes the full Signal Lynx Risk Management Engine:
A state machine that separates “Signal” from “Execution”
Layered exit tools: Stop Loss, Trailing Stop, Staged Take Profit, Advanced Adaptive Trailing Stop (AATS), and an RSI-style stop (RSIS)
Designed for non-repainting behavior on closed candles by basing execution-critical logic on previous-bar data
We are publishing this as an open-source template so traders and developers can leverage a professional-grade RM engine while integrating their own signal logic if they wish.
2. Quick Action Guide (TL;DR)
Best Timeframe:
4 Hours (H4) and above. This is a high-conviction swing-trading system, not a scalper.
Best Assets:
Volatile instruments that still respect market structure:
Bitcoin, Ethereum, Gold (XAUUSD), high-volatility Forex pairs (e.g., GBPJPY), indices with clean ranges.
Strategy Type:
Volatility-Adaptive Trend Following + Impulse Detection.
It hunts for genuine expansion out of ranges, not tiny mean-reversion nibbles.
Key Feature:
Renko Emulation on time-based candles.
We mathematically model Renko Bricks and overlay them on your standard chart to define:
“Equilibrium” zones (inside the brick structure)
“Breakout / impulse” zones (when price AND the impulse line depart from the bricks)
Repainting:
Designed to be non-repainting on closed candles.
All RM execution logic uses confirmed historical data (no future bars, no security() lookahead). Intrabar flicker during formation is allowed, but once a bar closes the engine’s decisions are stable.
Core Toggles & Filters:
Enable Longs and Shorts independently
Optional Weekend filter (block trades on Saturday/Sunday)
Per-module toggles: Stop Loss, Trailing Stop, Staged Take Profits, AATS, RSIS
3. Detailed Report: How It Works
A. The Strategy Logic: Superior RBR
Superior RBR builds its entry signal from multiple mathematical layers working together.
1) Adaptive Lookback (Volatility Normalization)
Instead of a fixed 100-bar or 200-bar range, the script:
Computes ATR-based volatility over a user-defined period.
Normalizes that volatility relative to its recent min/max.
Maps the normalized value into a dynamic lookback window between a minimum and maximum (e.g., 4 to 100 bars).
High Volatility:
The lookback shrinks, so the system reacts faster to explosive moves.
Low Volatility:
The lookback expands, so the system sees a “bigger picture” and filters out chop.
All the core “Range High/Low” and “Range Close High/Low” boundaries are built on top of this adaptive window.
2) Range Construction & Quick Ranges
The engine constructs several nested ranges:
Outer Range:
rangeHighFinal – dynamic highest high
rangeLowFinal – dynamic lowest low
Inner Close Range:
rangeCloseHighFinal – highest close
rangeCloseLowFinal – lowest close
Quick Ranges:
“Half-length” variants of those, used to detect more responsive changes in structure and volatility.
These ranges define:
The macro box price is trading inside
Shorter-term “pressure zones” where price is coiling before expansion
3) Renko Emulation (The Bricks)
Rather than using the Renko chart type (which discards time), this script emulates Renko behavior on your normal candles:
A “brick size” is defined either:
As a standard percentage move, or
As a volatility-driven (ATR) brick, optionally inhibited by a minimum standard size
The engine tracks a base value and derives:
brickUpper – top of the emulated brick
brickLower – bottom of the emulated brick
When price moves sufficiently beyond those levels, the brick “shifts”, and the directional memory (renkoDir) updates:
renkoDir = +2 when bricks are advancing upward
renkoDir = -2 when bricks are stepping downward
You can think of this as a synthetic Renko tape overlaid on time-based candles:
Inside the brick: equilibrium / consolidation
Breaking away from the brick: momentum / expansion
4) Impulse Tracking with Laguerre Filters
The script uses multiple Laguerre Filters to smooth price and brick-derived data without traditional lag.
Key filters include:
LagF_1 / LagF_W: Based on brick upper/lower baselines
LagF_Q: Based on HLCC4 (high + low + 2×close)/4
LagF_Y / LagF_P: Complex averages combining brick structures and range averages
LagF_V (Primary Impulse Line):
A smooth, high-level impulse line derived from a blend of the above plus the outer ranges
Conceptually:
When the impulse line pushes away from the brick structure and continues in one direction, an impulse move is underway.
When its direction flips and begins to roll over, the impulse is fading, hinting at mean reversion back into the range.
5) Fib-Based Structure & Swaps
The system also layers in Fib levels derived from the adaptive ranges:
Standard levels (12%, 23.6%, 38.2%, 50%, 61%, 76.8%, 88%) from the main range
A secondary “swap” set derived from close-range dynamics (fib12Swap, fib23Swap, etc.)
These Fibs are used to:
Bucket price into structural zones (below 12, between 23–38, etc.)
Detect breakouts when price and Laguerre move beyond key Fib thresholds
Drive zSwap logic (where a secondary Fib set becomes the active structure once certain conditions are met)
6) Adaptive SuperTrend with K-Means-Style Volatility Clustering
Under the hood, the script uses a small k-means-style clustering routine on ATR:
ATR is measured over a fixed period
The range of ATR values is split into Low, Medium, High volatility centroids
Current ATR is assigned to the nearest centroid (cluster)
From that, a SuperTrend variant (STK) is computed with dynamic sensitivity:
In quiet markets, SuperTrend can afford to be tighter
In wild markets, it widens appropriately to avoid constant whipsaw
This SuperTrend-based oscillator (LagF_K and its signals) is then combined with the brick and Laguerre stack to confirm valid trend regimes.
7) Final Baseline Signals (+2 / -2)
The “brain” of Superior RBR lives in the Baseline & Signal Generation block:
Two composite signals are built: B1 and B2:
They combine:
Fib breakouts
Renko direction (renkoDir)
Expansion direction (expansionQuickDir)
Multiple Laguerre alignments (LagF_Q, LagF_W, LagF_Y, LagF_Z, LagF_P, LagF_V)
They also factor in whether Fib structures are expanding or contracting.
A user toggle selects the “Baseline” signal:
finalSig = B2 (default) or B1 (alternate baseline)
finalSig is then filtered through the RM state machine and only when everything aligns, we emit:
+2 = Long / Buy signal
-2 = Short / Sell signal
0 = No new trade
Those +2 / -2 values are what feed the Risk Management Engine.
B. The Risk Management (RM) Engine
This script features the Signal Lynx Risk Management Engine, a proprietary state machine built to separate Signal from Execution.
Instead of firing orders directly on indicator conditions, we:
Convert the raw signal into a clean integer (Fin = +2 / -2 / 0)
Feed it into a Trade State Machine that understands:
Are we flat?
Are we in a long or short?
Are we in a closing sequence?
Should we permit re-entry now or wait?
Logic Injection / Template Concept:
The RM engine expects a simple integer:
+2 → Buy
-2 → Sell
Everything else (0) is “no new trade”
This makes the script a template:
You can remove the Superior RBR block
Drop in your own logic (RSI, MACD, price action, etc.)
As long as you output +2 or -2 into the same signal channel, the RM engine can drive all exits and state transitions.
Aggressive vs Conservative Modes:
The input AgressiveRM (Aggressive RM) governs how we interpret signals:
Conservative Mode (Aggressive RM = false):
Uses a more filtered internal signal (AF) to open trades
Effectively waits for a clean trend flip / confirmation before new entries
Minimizes whipsaw at the cost of fewer trades
Aggressive Mode (Aggressive RM = true):
Reacts directly to the fresh alert (AO) pulses
Allows faster re-entries in the same direction after RM-based exits
Still respects your pyramiding setting; this script ships with pyramiding = 0 by default, so it will not stack multiple positions unless you change that parameter in the strategy() call.
The state machine enforces discipline on top of your signal logic, reducing double-fires and signal spam.
C. Advanced Exit Protocols (Layered Defense)
The exit side is where this template really shines. Instead of a single “take profit or stop loss,” it uses multiple, cooperating layers.
1) Hard Stop Loss
A classic percentage-based Stop Loss (SL) relative to the entry price.
Acts as a final “catastrophic protection” layer for unexpected moves.
2) Standard Trailing Stop
A percentage-based Trailing Stop (TS) that:
Activates only after price has moved a certain percentage in your favor (tsActivation)
Then trails price by a configurable percentage (ts)
This is a straightforward, battle-tested trailing mechanism.
3) Staged Take Profits (Three Levels)
The script supports three staged Take Profit levels (TP1, TP2, TP3):
Each stage has:
Activation percentage (how far price must move in your favor)
Trailing amount for that stage
Position percentage to close
Example setup:
TP1:
Activate at +10%
Trailing 5%
Close 10% of the position
TP2:
Activate at +20%
Trailing 10%
Close another 10%
TP3:
Activate at +30%
Trailing 5%
Close the remaining 80% (“runner”)
You can tailor these quantities for partial scaling out vs. letting a core position ride.
4) Advanced Adaptive Trailing Stop (AATS)
AATS is a sophisticated volatility- and structure-aware stop:
Uses Hirashima Sugita style levels (HSRS) to model “floors” and “ceilings” of price:
Dungeon → Lower floors → Mid → Upper floors → Penthouse
These levels classify where current price sits within a long-term distribution.
Combines HSRS with Bollinger-style envelopes and EMAs to determine:
Is price extended far into the upper structure?
Is it compressed near the lower ranges?
From this, it computes an adaptive factor that controls how tight or loose the trailing level (aATS / bATS) should be:
High Volatility / Penthouse areas:
Stop loosens to avoid getting wicked out by inevitable spikes.
Low Volatility / compressed structure:
Stop tightens to lock in and protect profit.
AATS is designed to be the “smart last line” that responds to context instead of a single fixed percentage.
5) RSI-Style Stop (RSIS)
On top of AATS, the script includes a RSI-like regime filter:
A McGinley Dynamic mean of price plus ATR bands creates a dynamic channel.
Crosses above the top band and below the lower band change a directional state.
When enabled (UseRSIS):
RSIS can confirm or veto AATS closes:
For longs: A shift to bearish RSIS can force exits sooner.
For shorts: A shift to bullish RSIS can do the same.
This extra layer helps avoid over-reactive stops in strong trends while still respecting a regime change when it happens.
D. Repainting Protection
Many strategies look incredible in the Strategy Tester but fail in live trading because they rely on intrabar values or future-knowledge functions.
This template is built with closed-candle realism in mind:
The Risk Management logic explicitly uses previous bar data (open , high , low , close ) for the key decisions on:
Trailing stop updates
TP triggers
SL hits
RM state transitions
No security() lookahead or future-bar access is used.
This means:
Backtest behavior is designed to match what you can actually get with TradingView alerts and live automation.
Signals may “flicker” intrabar while the candle is forming (as with any strategy), but on closed candles, the RM decisions are stable and non-repainting.
4. For Developers & Modders
We strongly encourage you to mod this script.
To plug your own strategy into the RM engine:
Look for the section titled:
// BASELINE & SIGNAL GENERATION
You will see composite logic building B1 and B2, and then selecting:
baseSig = B2
altSig = B1
finalSig = sigSwap ? baseSig : altSig
You can replace the content used to generate baseSig / altSig with your own logic, for example:
RSI crosses
MACD histogram flips
Candle pattern detectors
External condition flags
Requirements are simple:
Your final logic must output:
2 → Buy signal
-2 → Sell signal
0 → No new trade
That output flows into the RM engine via finalSig → AlertOpen → state machine → Fin.
Once you wire your signals into finalSig, the entire Risk Management system (Stops, TPs, AATS, RSIS, re-entry logic, weekend filters, long/short toggles) becomes available for your custom strategy without re-inventing the wheel.
This makes Superior RBR not just a strategy, but a reference architecture for serious Pine dev work.
5. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Super-AO with Risk Management Strategy Template - 11-29-25Super-AO Strategy with Advanced Risk Management Template
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
Welcome to the Super-AO Strategy. This is more than just a buy/sell indicator; it is a complete, open-source Risk Management (RM) Template designed for the Pine Script community.
At its core, this script implements a robust swing-trading strategy combining the SuperTrend (for macro direction) and the Awesome Oscillator (for momentum). However, the real power lies under the hood: a custom-built Risk Management Engine that handles trade states, prevents repainting, and manages complex exit conditions like Staged Take Profits and Advanced Adaptive Trailing Stops (AATS).
We are releasing this code to help traders transition from simple indicators to professional-grade strategy structures.
2. Quick Action Guide (TL;DR)
Best Timeframe: 4 Hours (H4) and above. Designed for Swing Trading.
Best Assets: "Well-behaved" assets with clear liquidity (Major Forex pairs, BTC, ETH, Indices).
Strategy Type: Trend Following + Momentum Confirmation.
Key Feature: The Risk Management Engine is modular. You can strip out the "Super-AO" logic and insert your own strategy logic into the template easily.
Repainting: Strictly Non-Repainting. The engine calculates logic based on confirmed candle closes.
3. Detailed Report: How It Works
A. The Strategy Logic: Super-AO
The entry logic is based on the convergence of two classic indicators:
SuperTrend: Determines the overall trend bias (Green/Red).
Awesome Oscillator (AO): Measures market momentum.
The Signal:
LONG (+2): SuperTrend is Green AND AO is above the Zero Line AND AO is Rising.
SHORT (-2): SuperTrend is Red AND AO is below the Zero Line AND AO is Falling.
By requiring momentum to agree with the trend, this system filters out many false signals found in ranging markets.
B. The Risk Management (RM) Engine
This script features a proprietary State Machine designed by Signal Lynx. Unlike standard strategies that simply fire orders, this engine separates the Signal from the Execution.
Logic Injection: The engine listens for a specific integer signal: +2 (Buy) or -2 (Sell). This makes the code a Template. You can delete the Super-AO section, write your own logic, and simply pass a +2 or -2 to the RM_EngineInput variable. The engine handles the rest.
Trade States: The engine tracks the state of the trade (Entry, In-Trade, Exiting) to prevent signal spamming.
Aggressive vs. Conservative:
Conservative Mode: Waits for a full trend reversal before taking a new trade.
Aggressive Mode: Allows for re-entries if the trend is strong and valid conditions present themselves again (Pyramiding Type 1).
C. Advanced Exit Protocols
The strategy does not rely on a single exit point. It employs a "Layered Defense" approach:
Hard Stop Loss: A fixed percentage safety net.
Staged Take Profits (Scaling Out): The script allows you to set 3 distinct Take Profit levels. For example, you can close 10% of your position at TP1, 10% at TP2, and let the remaining 80% ride the trend.
Trailing Stop: A standard percentage-based trailer.
Advanced Adaptive Trailing Stop (AATS): This is a highly sophisticated volatility stop. It calculates market structure using Hirashima Sugita (HSRS) levels and Bollinger Bands to determine the "floor" and "ceiling" of price action.
If volatility is high: The stop loosens to prevent wicking out.
If volatility is low: The stop tightens to protect profit.
D. Repainting Protection
Many Pine Script strategies look great in backtesting but fail in live trading because they rely on "real-time" price data that disappears when the candle closes.
This Risk Management engine explicitly pulls data from the previous candle close (close , high , low ) for its calculations. This ensures that the backtest results you see match the reality of live execution.
4. For Developers & Modders
We encourage you to tear this code apart!
Look for the section titled // Super-AO Strategy Logic.
Replace that block with your own RSI, MACD, or Price Action logic.
Ensure your logic outputs a 2 for Buy and -2 for Sell.
Connect it to RM_EngineInput.
You now have a fully functioning Risk Management system for your custom strategy.
5. About Signal Lynx
Automation for the Night-Shift Nation 🌙
This code has been in action since 2022 and is a known performer in PineScript v5. We provide this open source to help the community build better, safer automated systems.
If you are looking to automate your strategies, please take a look at Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please release them back to the community!
Gold_Strategy_EMA_TradingProEC_v1.4We are pleased to announce a significant update to the execution logic of the Gold Breakouts Strategy, focusing on improved precision and reliability of trade signals.
📝 Summary of Key Changes
This version resolves the critical issue of duplicate or redundant trade entries that were being generated on the same bar when the EMA crossover condition was triggered. This caused unnecessary confusion in signal notifications and trade execution.
⚙️ Detailed Technical Implementation
Elimination of Redundant Code: We have successfully removed the conflicting entry logic block that previously attempted to execute trades using Pivot levels for Take Profit calculation. By doing this, we eliminate the source of the double entry problem.
Consolidated Execution Logic: The strategy now relies on a single, unified execution block. This block exclusively utilizes the robust Fixed TP/SL Ratio calculation as defined in the strategy inputs.
Enhanced Flow Control: We improved the conditional flow by using else if for the sell condition (else if cond_venta) immediately following the buy condition (if cond_compra). This vital change guarantees that if a Buy signal is processed on a given bar, the Sell signal logic is skipped entirely, making the execution flow more exclusive and robust against rapid market movements.
✅ User Impact and Benefits
Single, Clear Notifications: Users will now receive only one definitive entry notification per signal (either 'sell' or 'buy') at a time. This allows for immediate and confident decision-making.
Reliable Trade Execution: The strategy is now significantly more dependable, ensuring that the Stop Loss and Take Profit levels are set correctly and consistently based on the defined risk ratio immediately upon entry.
CNN Fear and Greed StrategyAdaptation of the CNN Fear and Greed Index Indicator (Original by EdgeTools)
The following changes have been implemented:
Put/Call Ratio Data Source: The data source for the Put/Call Ratio has been updated.
Bond Data Source: The data sources for the bond components (Safe Haven Demand and Junk Bond Demand) have been updated.
Normalization Adjustment: The normalization method has been adjusted to allow the CNN Fear and Greed Index to display over a longer historical period, optimizing it for backtesting purposes.
Style Modification: The display style has been modified for a simpler and cleaner appearance.
Strategy Logic Addition: Added a new strategy entry condition: index >= 25 AND index crosses over its 5-period Simple Moving Average (SMA), and a corresponding exit condition of holding the position for 252 bars (days).
CNN Fear & Greed Backtest Strategy (Adapted)
This script is an adaptation of the popular CNN Fear & Greed Index, originally created by EdgeTools, with significant modifications to optimize it for long-term backtesting on the TradingView platform.
The core function of the Fear & Greed Index is to measure the current emotional state of the stock market, ranging from 0 (Extreme Fear) to 100 (Extreme Greed). It operates on the principle that excessive fear drives prices too low (a potential buying opportunity), and excessive greed drives them too high (a potential selling opportunity).
Key Components of the Index (7 Factors)
The composite index is calculated as a weighted average of seven market indicators, each normalized to a score between 0 and 100:
Market Momentum: S&P 500's current level vs. its 125-day Moving Average.
Stock Price Strength: Stocks hitting 52-week highs vs. those hitting 52-week lows.
Stock Price Breadth: Measured by the McClellan Volume Summation Index (or similar volume/breadth metric).
Put/Call Ratio: The relationship between volume of put options (bearish bets) and call options (bullish bets).
Market Volatility: The CBOE VIX Index relative to its 50-day Moving Average.
Safe Haven Demand: The relative performance of stocks (S&P 500) vs. bonds.
Junk Bond Demand: The spread between high-yield (junk) bonds and U.S. Treasury yields.
Critical Adaptations for Backtesting
To improve the index's utility for quantitative analysis, the following changes were made:
Long-Term Normalization: The original normalization method (ta.stdev over a short LENGTH) has been replaced or adjusted to use longer historical data. This change ensures the index generates consistent and comparable sentiment scores across decades of market history, which is crucial for reliable backtesting results.
Updated Data Sources: Specific ticker requests for the Put/Call Ratio and Bond components (Safe Haven and Junk Bond Demand) have been updated to use the most reliable and long-running data available on TradingView, reducing data gaps and improving chart continuity.
Simplified Visuals: The chart display is streamlined, focusing only on the final Fear & Greed Index line and key threshold levels (25, 50, 75) for quick visual assessment.
Integrated Trading Strategy
This script also includes a simple, rules-based strategy designed to test the counter-trend philosophy of the index:
Entry Logic (Long Position): A long position is initiated when the market shows increasing fear, specifically when the index score is less than or equal to the configurable FEAR_LEVEL (default 25) and the index crosses above its own short-term 5-period Simple Moving Average (SMA). This crossover acts as a confirmation that sentiment may be starting to turn around from peak fear.
Exit Logic (Time-Based): All positions are subject to a time-based exit after holding for 252 trading days (approximately one year). This fixed holding period aims to capture the typical duration of a cyclical market recovery following a major panic event.
Jet Stream V1Jet Stream catches the trends. Forgets the noise and allows you to lock into those big moves.
Wed, Nov 19 2025 V3 - Everything but alerts work.
Morning Straddle Backtest + Range Filter Morning Straddle Backtest
Purpose:
This script tests a Morning Straddle concept where a trader enters both long and short breakout orders based on the overnight range (22:00–06:00 by default).
It is designed for backtesting the effectiveness of volatility breakouts following low-volume overnight sessions.
Setup
Overnight session: 22:00–06:00 (adjustable).
At the end of the overnight session, the script automatically places:
A long stop order above the range high.
A short stop order below the range low.
Both use an ATR-based buffer for cleaner breakouts (default 5%).
When one side triggers, the opposite order is cancelled if OCO mode is active.
Adjustable Parameters
- Session - Defines the overnight hours used for the range.
- ATR Length - Number of bars used for ATR calculation.
- ATR Buffer % - Distance above/below range for entry & stop placement.
- Risk:Reward Ratio - Determines the TP distance relative to SL.
- Stop-Loss - Choose between “Behind Range” or “Mid-Range (50%)” with ATR buffer added.
- OCO - Cancels opposite order once one side triggers.
- Close All EOD - Closes all open trades at the end of day (default 22:00).
- Range Filter – Enables filtering of trades only when the overnight range size falls within a defined threshold.
-Min Range / Max Range – Define acceptable range size boundaries.
-Display Units – Select whether the filter is measured in Price Change, Pips, or Points.
- Stats Panel Settings – Toggle visibility, position (Top/Bottom Left/Right), and background opacity.
Visual
The overnight range (22:00–06:00) is highlighted on the chart with a teal background for clarity.
No lines are drawn for the high and low.
Strategy Notes
Works best on 5m or 15m charts where the overnight range can be clearly defined.
Backtests should be run over multiple months to gauge performance consistency.
Can be adapted for other markets by adjusting session times and ATR settings. For example, S&P initial balance breakout using 14:30-15:30 range time.
Stats Panel Displays
- 20-Day Range Data: Maximum, Average, and Minimum range sizes.
- Today’s Range: With automatic classification — Huge, Normal, or Small.
- Average Winning Range: Average size of the overnight range on profitable days.
- Average Losing Range: Average size of the overnight range on losing days.
- Filter Status: Displays whether the range met the filter criteria — Range OK, Skipped, or Off.
nOI + Funding + CVD • strategynOI + Funding + CVD Strategy
Overview
This strategy is designed for cryptocurrency trading on platforms like TradingView, focusing on perpetual futures markets. It combines three key indicators—Normalized Open Interest (nOI), Funding Rate, and Cumulative Volume Delta (CVD)—to generate buy and sell signals for long and short positions. The strategy aims to capitalize on market imbalances, such as overextended open interest, funding rate extremes, and volume deltas, which often signal potential reversals or continuations in trending markets.
The script supports pyramiding (up to 10 positions), uses percentage-based position sizing (default 10% of equity per trade), and allows customization of trade directions (longs and shorts can be enabled/disabled independently). It includes multiple signal systems for entries, various exit mechanisms (including stop-loss, take-profit, time-based exits, and conditional closes based on indicators), a Martingale add-on system for averaging positions during drawdowns, and handling of opposite signals (ignore, close, or reverse).
This strategy is not financial advice; backtest thoroughly and use at your own risk. It requires data sources for Open Interest (OI) and Funding Rates, which are fetched via TradingView's security functions (e.g., from Binance for funding premiums).
Key Indicators
1. Normalized Open Interest (nOI)
Group: Open Interest
Purpose: Measures the relative level of open interest over a lookback window to identify overbought (high OI) or oversold (low OI) conditions, which can indicate potential exhaustion in trends.
Calculation:
Fetches OI data (close) from the symbol's standard ticker (e.g., "{symbol}_OI").
Normalizes OI within a user-defined window (default: 500 bars) using min-max scaling: (OI - min_OI) / (max_OI - min_OI) * 100.
Upper threshold (default: 70%): Signals potential short opportunities when crossed from above.
Lower threshold (default: 30%): Signals potential long opportunities when crossed from below.
Visualization: Plotted as a line (teal above upper, red below lower, gray in between). Horizontal lines at upper, mid (50%), lower, and a separator at 102%.
Notes: Handles non-crypto symbols by adjusting timeframe to daily if intraday. Errors if no OI data available.
2. Funding Rate
Group: Funding Rate
Purpose: Tracks the average funding rate (premium index) to detect market sentiment extremes. Positive funding suggests bull bias (longs pay shorts), negative suggests bear bias.
Calculation:
Fetches premium index data from Binance (e.g., "binance:{base}usdt_premium").
Supports lower timeframe aggregation (default: enabled, using 1-min TF) for smoother data.
Averages open and close premiums, clamps values, and scales/shifts for plotting (base: 150, scale: 1000x).
Upper threshold (default: 1.0%): Overheat for shorts.
Lower threshold (default: 1.0%): Overcool for longs.
Ultra level (default: 1.8%): Extreme for additional short signals.
Smoothing: Uses inverse weighted moving average (IWMA) or lower-TF aggregation to reduce noise.
Visualization: Shifted plot (green positive, red negative) with filled areas. Horizontal lines for overheat, overcool, base (0%), and ultra.
Notes: Custom ticker option for non-standard symbols.
3. Cumulative Volume Delta (CVD)
Group: CVD (Cumulative Volume Delta)
Purpose: Measures net buying/selling pressure via volume delta, normalized to identify divergences or confirmations with price.
Calculation:
Delta: +volume if close > open, -volume if close < open.
Cumulative: Rolling cumsum over a window (default: 500 bars), smoothed with EMA (default: 20).
Normalized: Scaled by absolute max in window (-1 to 1 range).
Scaled/shifted for plotting (base: 300 or 0 if anchored, scale: 120x).
Upper threshold (default: 1.0%): Over for shorts.
Lower threshold (default: 1.0%): Under for longs.
Visualization: Shifted plot (aqua positive, purple negative) with filled areas. Horizontal lines for over, under, and separator (default: 252).
Filter Options (for Signal A):
Enable filter (default: false).
Require sign match (Long ≥0, Short ≤0).
Require extreme zones.
Require momentum (rising/falling over N bars, default: 3).
Signal Logics for Entries
Entries are triggered by buy/sell signals from multiple systems (A, B, C, D), filtered by direction toggles and entry conditions.
Signal System A: OI + Funding (with optional CVD filter)
Enabled: Default true.
Sell (Short): nOI > upper threshold, falling over N bars (default: 3), delta ≥ threshold (default: 3%), funding > overheat, and CVD filter OK.
Buy (Long): nOI < lower threshold, rising over N bars (default: 3), delta ≥ threshold (default: 3%), funding < overcool, and CVD filter OK.
Signal System B: Short - Funding Crossunder + Filters
Enabled: Default true.
Sell (Short): Funding crosses under overheat level, optional: CVD > over, nOI < upper.
Signal System C: Short - Ultra Funding
Enabled: Default false.
Sell (Short): Funding crosses ultra level (up or down, both default true).
Signal System D: Long - Funding Crossover + Filters
Enabled: Default true.
Buy (Long): Funding crosses over overcool level, optional: CVD < under, nOI > lower.
Combined: Sell if A/B/C active; Buy if A/D active.
Entry Filters
Cooldown: Optional pause between entries (default: false, 3 bars).
Max Entries: Limit pyramiding (default: true, 6 max).
Entries only if both filters pass and direction allowed.
Opposite Signal Handling
Mode: Ignore (default), Reverse (close and enter opposite), or Close (exit only).
Processed before regular entries.
Position Management
Martingale (3 Steps):
Enabled per step (default: all true).
Triggers add-ons at loss levels (defaults: 5%, 8%, 11%) by adding % to position (default: 100% each).
Resets on position close.
Break Even:
Enabled (default: true).
Activates at profit threshold (default: 5%), sets SL better by offset (default: 0.1%).
Exit Systems
Multiple exits checked in sequence.
Exit 1: SL/TP
Enabled: Separate for long/short (default: true).
SL: % from avg price (defaults: 1% long/short).
TP: % from avg price (defaults: 2% long/short).
Exit 2: Funding
Enabled: Separate for long (up) / short (down) (default: true).
Long Exit: Funding > upper exit threshold (default: 0.8%).
Short Exit: Funding < lower exit threshold (default: 0.8%).
Exit 3: nOI
Enabled: Separate for long (up) / short (down) (default: true).
Long Exit: nOI > upper exit (default: 85%).
Short Exit: nOI < lower exit (default: 15%).
Exit 4: Global SL
Enabled: Default true.
Exit: If position loss ≥ % (default: 7%).
Exit 5: Break Even (integrated in position block)
Exit 6: Time Limit
Enabled: Separate for long/short (default: true).
Exit: After N bars in trade (defaults: 30 each).
Timer updates on add-ons if enabled (default: true).
Visual Elements
Buy/Sell Labels: Small labels ("BUY"/"SELL") on bars with signals, limited to last 30.
All indicators plotted on a separate pane (overlay=false).
Usage Notes
Backtesting: Adjust parameters based on asset/timeframe. Test on historical data.
Data Requirements: Works best on crypto perps with OI and funding data.
Risk Management: Incorporates SL/TP and global SL; monitor drawdowns with Martingale.
Customization: All thresholds, enables, and scales are inputs for fine-tuning.
Version: Pine Script v6.
For questions or improvements, contact the author. Happy trading!
5-min Strat Strategy V2 (With Stop Loss)README: 5-min Strat Strategy V2 – $7,500 Stop Loss Version
✅ Description
This is a rules-based intraday trading strategy developed for use on futures contracts like MNQ (Micro Nasdaq) or MES (Micro S&P). It focuses on momentum-based breakout entries above pre-market highs, during regular trading hours, and uses EMAs to define trend alignment.
⚙️ Strategy Components
✅ Trade Type
Long-Only strategy
Entry and exit based on EMAs, price position, and time windows
✅ Time Frame
Built for 5-minute charts
✅ Symbols
Optimized for MNQ (Micro Nasdaq Futures)
Works on MES or other U.S. index futures with similar structure
📅 Time Windows
Pre-Market Hours (PMH/PML): 04:00 – 09:30 AM EST
Regular Trading Hours (RTH): 09:30 AM – 4:00 PM EST
Auto Exit Time: 4:59 PM EST (to comply with prop firm rules)
📌 Entry Conditions (Long)
48 EMA > 200 EMA (Bullish alignment)
Price > Locked Pre-Market High
Green Candle (close > open)
During RTH (9:30–16:00 EST)
Cooldown: Must wait 4 candles after last entry
Max Trades per Day: 3
💥 Exit Conditions
Primary Exit: Close below the 48 EMA
Max Loss Exit: Stop loss set to $7,500 per trade
EOD Exit: All positions are closed at 4:59 PM EST
💰 Risk Management
Contracts: 6 Micro contracts per trade
Stop Loss: Dynamic point-based SL calculated based on:
MNQ point value = $20/point per contract
30 contracts = $120/point
Max SL points = $7,500 / $120 = 62.5 points
📊 Key Variables for Logging
Parameter Value
Max Stop Loss $7,500
Position Size 30 Micro Contracts - ***Varies depending on account size***
Cooldown Bars 4 (20 min)
Max Daily Trades 3
Strategy Version V2 – $7.5K SL
Mario vr SIT MC Utilizar en el gráfico
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🧠 Market Structure Pro System – MVR
Market Structure Pro System – MVR is an advanced trading strategy designed to detect key reversal and trend-break zones with high precision.
It combines multiple professional tools within a single algorithm — integrating market structure, dynamic channels, volatility filters, and trend confirmations — making it ideal for scalping and swing trading across different markets (Forex, indices, cryptocurrencies, or stocks).
⚙️ How it works
The algorithm performs a complete structural analysis of the market through several technical layers:
🔹 1. Price Structure (BOS, Supply & Demand)
The system automatically detects:
Order Blocks
Supply and Demand Zones
Break of Structure (BOS) to identify market structure shifts
This allows traders to recognize where price is likely to react or break a trend, anticipating major market movements.
🔹 2. Keltner Channels and Linear Regression
The strategy uses multiple Keltner Channels with different settings to measure volatility expansion and contraction.
In combination, a dynamic linear regression line shows the overall market direction, helping confirm whether price is trending or ranging.
🔹 3. Volatility and Trend Filters
It integrates several complementary systems:
ATR (Average True Range): measures the strength and volatility of price movement.
PSAR (Parabolic SAR): identifies potential trend reversals.
Supertrend: acts as the main trend filter and confirmation tool.
These filters work together to avoid false signals in ranging or low-volatility conditions.
🔹 4. Swing Highs / Lows and Dynamic Lines
The indicator also marks swing high and low points, helping visualize dynamic support and resistance levels and potential price reversal areas.
📈 Signal Interpretation
BUY signals:
Occur when price breaks a demand zone or bearish structure, while trend filters (Supertrend / PSAR) confirm bullish direction.
SELL signals:
Trigger when price breaks a supply zone or bullish structure, with bearish confirmation from the trend filters.
These conditions can be further validated by visual confirmations from the Keltner Channel or a color change in the linear regression.
Script protegido
Este script se publica como código cerrado. Sin embargo, puede utilizarlo libremente y sin limitaciones: obtenga más información aquí.
mariovr_usd
Exención de responsabilidad
La información y las publicaciones que ofrecemos, no implican ni constituyen un asesoramiento financiero, ni de inversión, trading o cualquier otro tipo de consejo o recomendación emitida o respaldada por TradingView. Puede obtener información adicional en las Condiciones de uso.
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Moon Phases + Blood MoonWhat it is
This is a simple, time-based strategy that goes long on full moons and exits on the next new moon, while visually highlighting historically known “Blood Moon” (total lunar eclipse) dates. It’s built for exploratory testing of lunar timing effects on price, not for predictive claims.
Why it’s useful / originality
Most lunar scripts only mark phases. This one (1) computes lunar phases on the chart, (2) normalizes and flags Blood Moon days from a curated list, and (3) turns the phase changes into an executable strategy with clear, reproducible entry/exit rules and a configurable start date—so traders can quickly evaluate whether a lunar timing overlay adds any edge on their market/timeframe.
How it works (concept)
Moon phase detection: Uses Julian date conversion and standard astronomical approximations to determine the most recent phase change at each bar. The script classifies phase turns as +1 = New Moon and –1 = Full Moon, tracking the latest valid time to avoid lookahead.
Blood Moon tagging: A built-in array of UTC timestamps (total lunar eclipses) is date-matched to the current session and marked as “Blood Moon” when a full moon coincides with a listed date.
Signals & trades
Plot circles above/below bars: New Moon (above), Full Moon (below), Blood Moon (below, red).
Entry: Long at Full Moon once the bar time ≥ the user’s Start date.
Exit: Close the long on the next New Moon.
How to use
Add to your chart (non-monthly timeframes only).
Optionally adjust the Start date (default: 2001-12-31 UTC) to control the backtest window.
Use the color inputs to style New Moon / Full Moon / Blood Moon markers.
Evaluate performance on liquid symbols and timeframes that provide a sufficient number of phase cycles.
Default / publish settings
Initial capital: $10,000 (suggested)
Commission: 0.05% per trade (suggested)
Slippage: 1 tick (suggested)
Position sizing: TradingView strategy defaults (no leverage logic is added).
Timeframes: Intraday/Daily/Weekly supported. Monthly is blocked by design.
Chart type: Use standard chart types only (no Heikin Ashi, Renko, Kagi, P&F, Range) for signals/backtests.
Reading the chart
New Moon: soft gray circle above bars.
Full Moon: soft yellow circle below bars.
Blood Moon (if date-matched): soft red circle below bars.
The script also ensures symbol/timeframe context is visible—keep your chart clean so the markers are easy to interpret.
Limitations & important notes
This is a time-based heuristic. It does not forecast price and does not repaint via lookahead tricks; it avoids future leakage by anchoring to the last known phase time at each bar.
No non-standard chart signals. Using non-standard charts can produce unrealistic results.
Strategy properties like commission/slippage materially affect results—please set them to realistic values.
Backtests should include a large sample (ideally >100 trades over many cycles) to make statistics meaningful.
Past performance does not guarantee future results.
Open-source reuse / credits
Uses standard, public-domain techniques for Julian date conversion and lunar-phase approximations.
Blood Moon dates are incorporated as a hard-coded list for convenience; you may extend or adjust this list as needed.
No third-party proprietary code is reused.
Changelog / versioning
v1: Initial public release on Pine v6 with phase detection, Blood-Moon tagging, and a minimal long-only phase strategy.
Ajay R5.41🔻 Ajay Gold 3H Sell Power Indicator 🔻
Precision-Based Smart Sell System for Gold (XAU/USD)
💡 Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
⚙️ Technical Foundation
The indicator uses multiple advanced confirmations:
📉 EMA Trend Filter → Confirms downtrend
💪 RSI Overbought Rejection → Momentum reversal signal
📊 MACD Bearish Cross → Confirms trend strength
🕯️ Bearish Candle Structure → Price action validation
When all conditions align, a clear 🔻 Sell Signal is plotted on the chart.
💎 Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart — fully automated internal logic.
📆 Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
📈 How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the 🔻 Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate — always backtest and demo trade before using in real trading.
💬 Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
Ajay R5.41🔻 Ajay Gold 3H Power Indicator 🔻
Precision-Based Smart Sell System for Gold (XAU/USD)
💡 Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
⚙️ Technical Foundation
The indicator uses multiple advanced confirmations:
📉 EMA Trend Filter → Confirms downtrend
💪 RSI Overbought Rejection → Momentum reversal signal
📊 MACD Bearish Cross → Confirms trend strength
🕯️ Bearish Candle Structure → Price action validation
When all conditions align, a clear 🔻 Sell Signal is plotted on the chart.
💎 Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart — fully automated internal logic.
📆 Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
📈 How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the 🔻 Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate — always backtest and demo trade before using in real trading.
💬 Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
TurtleTrader Intraday Extended by exp3rts🐢 TurtleTrader Intraday Extended by exp3rts
A modern intraday adaptation of the classic Turtle Trading strategy, optimized for short-term breakout trading with built-in risk management, pyramiding, and optional trend filters.
This strategy captures strong directional moves by entering breakouts from price channels, using ATR-based stop losses and controlled position scaling.
🔑 Key Features:
📈 Channel Breakout Entries: Buy/sell on breakout of highest highs or lowest lows
🛑 Dynamic ATR Stop Loss: Automatically calculated from market volatility
🔁 Pyramiding: Adds up to 4 positions as price moves in your favor
🔄 Directional Mode: Choose Long-only or Short-only mode
🧠 Skip After Win Option: Avoid overtrading by skipping the next entry after a profitable trade
📊 Optional EMA Display: Plot up to 3 EMAs for trend filtering or visual confirmation
📉 On-Chart ATR Label: Displays real-time ATR metrics (including ½N size used in classic Turtle rules)
⚙️ Strategy Inputs:
Entry/Exit channel length
ATR multiplier and period
Entry delay (bar offset)
Optional trade filter after profitable trades
Show/hide EMAs and ATR label
🧪 Best For:
Intraday breakout traders (works well on 5m–1h timeframes)
Traders who prefer mechanical rules and structured risk
Anyone testing volatility-based entries and exits
Inspired by the original Turtle Trading system — redesigned for modern markets with more intraday flexibility and visual enhancements.
Macro Momentum – 4-Theme, Vol Target, RebalanceMacro Momentum — 4-Theme, Vol Target, Rebalance
Purpose. A macro-aware strategy that blends four economic “themes”—Business Cycle, Trade/USD, Monetary Policy, and Risk Sentiment—into a single, smoothed Composite signal. It then:
gates entries/exits with hysteresis bands,
enforces optional regime filters (200-day bias), and
sizes the position via volatility targeting with caps for long/short exposure.
It’s designed to run on any chart (index, ETF, futures, single stocks) while reading external macro proxies on a chosen Signal Timeframe.
How it works (high level)
Build four theme signals from robust macro proxies:
Business Cycle: XLI/XLU and Copper/Gold momentum, confirmed by the chart’s price vs a long SMA (default 200D).
Trade / USD: DXY momentum (sign-flipped so a rising USD is bearish for risk assets).
Monetary Policy: 10Y–2Y curve slope momentum and 10Y yield trend (steepening & falling 10Y = risk-on; rising 10Y = risk-off).
Risk Sentiment: VIX momentum (bearish if higher) and HYG/IEF momentum (bullish if credit outperforms duration).
Normalize & de-noise.
Optional Winsorization (MAD or stdev) clamps outliers over a lookback window.
Optional Z-score → tanh mapping compresses to ~ for stable weighting.
Theme lines are SMA-smoothed; the final Composite is LSMA-smoothed (linreg).
Decide direction with hysteresis.
Enter/hold long when Composite ≥ Entry Band; enter/hold short when Composite ≤ −Entry Band.
Exit bands are tighter than entry bands to avoid whipsaws.
Apply regime & direction constraints.
Optional Long-only above 200MA (chart symbol) and/or Short-only below 200MA.
Global Direction control (Long / Short / Both) and Invert switch.
Size via volatility targeting.
Realized close-to-close vol is annualized (choose 9-5 or 24/7 market profile).
Target exposure = TargetVol / RealizedVol, capped by Max Long/Max Short multipliers.
Quantity is computed from equity; futures are rounded to whole contracts.
Rebalance cadence & execution.
Trades are placed on Weekly / Monthly / Quarterly rebalance bars or when the sign of exposure flips.
Optional ATR stop/TP for single-stock style risk management.
Inputs you’ll actually tweak
General
Signal Timeframe: Where macro is sampled (e.g., D/W).
Rebalance Frequency: Weekly / Monthly / Quarterly.
ROC & SMA lengths: Defaults for theme momentum and the 200D regime filter.
Normalization: Z-score (tanh) on/off.
Winsorization
Toggle, lookback, multiplier, MAD vs Stdev.
Risk / Sizing
Target Annualized Vol & Realized Vol Lookback.
Direction (Long/Short/Both) and Invert.
Max long/short exposure caps.
Advanced Thresholds
Theme/Composite smoothing lengths.
Entry/Exit bands (hysteresis).
Regime / Execution
Long-only above 200MA, Short-only below 200MA.
Stops/TP (optional)
ATR length and SL/TP multiples.
Theme Weights
Per-theme scalars so you can push/pull emphasis (e.g., overweight Policy during rate cycles).
Macro Proxies
Symbols for each theme (XLI, XLU, HG1!, GC1!, DXY, US10Y, US02Y, VIX, HYG, IEF). Swap to alternatives as needed (e.g., UUP for DXY).
Signals & logic (under the hood)
Business Cycle = ½ ROC(XLI/XLU) + ½ ROC(Copper/Gold), then confirmed by (price > 200SMA ? +1 : −1).
Trade / USD = −ROC(DXY).
Monetary Policy = 0.6·ROC(10Y–2Y) − 0.4·ROC(10Y).
Risk Sentiment = −0.6·ROC(VIX) + 0.4·ROC(HYG/IEF).
Each theme → (optional Winsor) → (robust z or scaled ROC) → tanh → SMA smoothing.
Composite = weighted average → LSMA smoothing → compare to bands → dir ∈ {−1,0,+1}.
Rebalance & flips. Orders fire on your chosen cadence or when the sign of exposure changes.
Position size. exposure = clamp(TargetVol / realizedVol, maxLong/Short) × dir.
Note: The script also exposes Gross Exposure (% equity) and Signed Exposure (× equity) as diagnostics. These can help you audit how vol-targeting and caps translate into sizing over time.
Visuals & alerts
Composite line + columns (color/intensity reflect direction & strength).
Entry/Exit bands with green/red fills for quick polarity reads.
Hidden plots for each Theme if you want to show them.
Optional rebalance labels (direction, gross & signed exposure, σ).
Background heatmap keyed to Composite.
Alerts
Enter/Inc LONG when Composite crosses up (and on rebalance bars).
Enter/Inc SHORT when Composite crosses down (and on rebalance bars).
Exit to FLAT when Composite returns toward neutral (and on rebalance bars).
Practical tips
Start higher timeframes. Daily signals with Monthly rebalance are a good baseline; weekly signals with quarterly rebalances are even cleaner.
Tune Entry/Exit bands before anything else. Wider bands = fewer trades and less noise.
Weights reflect regime. If policy dominates markets, raise Monetary Policy weight; if credit stress drives moves, raise Risk Sentiment.
Proxies are swappable. Use UUP for USD, or futures-continuous symbols that match your data plan.
Futures vs ETFs. Quantity auto-rounds for futures; ETFs accept fractional shares. Check contract multipliers when interpreting exposure.
Caveats
Macro proxies can repaint at the selected signal timeframe as higher-TF bars form; that’s intentional for macro sampling, but test live.
Vol targeting assumes reasonably stationary realized vol over the lookback; if markets regime-shift, revisit volLook and targetVol.
If you disable normalization/winsorization, themes can become spikier; expect more hysteresis band crossings.
What to change first (quick start)
Set Signal Timeframe = D, Rebalance = Monthly, Z-score on, Winsor on (MAD).
Entry/Exit bands: 0.25 / 0.12 (defaults), then nudge until trade count and turnover feel right.
TargetVol: try 10% for diversified indices; lower for single stocks, higher for vol-sell strategies.
Leave weights = 1.0 until you’ve inspected the four theme lines; then tilt deliberately.
