Daily Close Breakout 20/10 + 200 (Signals)Daily Close Breakout 20/10 + 200 (Signals)
A simple “check once per day” breakout signal tool designed for the Daily (1D) chart.
Quickstart:
* Signals are confirmed at the daily candle close.
* If a triangle prints today, the earliest you act is the next day’s open (not the same candle).
* Green triangle = consider entering long.
* Red triangle = consider exiting.
* Long-only (no shorts).
How to use:
* Use on the Daily (1D) timeframe.
* Check the chart once per day after the daily candle closes.
* Do not act intraday on signals.
Rules (default settings 20 / 10 / 200):
* BUY: A green up triangle prints when the daily close is above the prior 20-day high and above the 200-day Simple Moving Average.
* SELL: A red down triangle prints when the daily close is below the prior 10-day low.
Lines and colors:
* Prior 20-day high (entry level): red
* Prior 10-day low (exit level): yellow
* 200-day Simple Moving Average: aqua
Notes:
* Best used on the Daily (1D) timeframe. Other timeframes may behave differently.
* This script plots signals and reference levels only. For performance metrics, use a matching strategy/backtest script.
* Educational use only. Not financial advice.
Following
Hash Ratings EngineHash Ratings Engine - Technical Consensus Strategy
A systematic trading strategy that harnesses TradingView's Technical Ratings to generate high-conviction entries with institutional-grade risk management.
What It Does
This strategy aggregates the consensus of 26+ technical indicators (RSI, MACD, Stochastics, multiple Moving Averages, etc.) into a single actionable signal. When enough indicators align bullish or bearish, the engine triggers an entry. Built-in trend filtering and ATR-based exits keep you on the right side of the market.
Key Features
Trend Filter - Only takes longs in uptrends, shorts in downtrends. This single filter typically improves results by 20-40% by avoiding counter-trend trades.
ATR-Based Risk Management - Stop loss and trailing stops adapt to current market volatility. Tight stops in calm markets, wider stops in volatile conditions.
Cooldown System - After a losing trade, the strategy waits before re-entering. This prevents the consecutive loss streaks that destroy accounts.
Clean Visuals - Fluorescent entry/exit signals with price level references. See exactly where you got in and out.
Settings Guide
Indicator Timeframe: Leave blank for current chart. Use higher timeframe for fewer, higher-quality signals.
Rating Source: "All" for balanced approach. "MAs" for trend-following. "Oscillators" for mean-reversion.
Entry Thresholds
Strong Signal Threshold: Higher = fewer trades but better conviction. Start at 0.5, test 0.4-0.6.
Risk Management
ATR Period: 12 is responsive, 14 is standard, 20+ is smoother.
Stop Loss: 2-3x ATR for tight stops, 3.5-4x for moderate, 5x+ for wide.
Trail Activation: How far price must move in profit before trailing begins.
Trail Offset: How closely the trail follows price.
Trend Filter
EMA Length: 150 works well on 4H charts. Use 100 for lower timeframes, 200 for daily.
Trade Timing
Cooldown: Keep enabled. 5 bars is a good starting point.
Best Practices
Start with default settings and backtest on your preferred instrument. Adjust the Strong Signal Threshold first - this has the biggest impact on trade frequency. Then tune the EMA length to match your timeframe. Finally, optimize the ATR multipliers for your risk tolerance.
Works on any liquid market - crypto, forex, stocks, futures. Higher timeframes (4H, Daily) tend to produce cleaner signals than lower timeframes.
Disclaimer
Past performance does not guarantee future results. Always backtest thoroughly and use proper position sizing. This strategy is for educational purposes - trade at your own risk.
Strategy: HMA 50 + Supertrend SniperHMA 50 + Supertrend Confluence Strategy (Trend Following with Noise Filtering)
Description:
Introduction and Concept This strategy is designed to solve a common problem in trend-following trading: Lag vs. False Signals. Standard Moving Averages often lag too much, while price action indicators can generate false signals during choppy markets. This script combines the speed of the Hull Moving Average (HMA) with the volatility-based filtering of the Supertrend indicator to create a robust "Confluence System."
The primary goal of this script is not just to overlay two indicators, but to enforce a strict rule where a trade is only taken when Momentum (HMA) and Volatility Direction (Supertrend) are in perfect agreement.
Why this combination? (The Logic Behind the Mashup)
Hull Moving Average (HMA 50): We use the HMA because it significantly reduces lag compared to SMA or EMA by using weighted calculations. It acts as our primary Trend Direction detector. However, HMA can be too sensitive and "whipsaw" during sideways markets.
Supertrend (ATR-based): We use the Supertrend (Factor 3.0, Period 10) as our Volatility Filter. It uses Average True Range (ATR) to determine the significant trend boundary.
How it Works (Methodology) The strategy uses a boolean logic system to filter out low-quality trades:
Bullish Confluence: The HMA must be rising (Slope > 0) AND the Close Price must be above the Supertrend line (Uptrend).
Bearish Confluence: The HMA must be falling (Slope < 0) AND the Close Price must be below the Supertrend line (Downtrend).
The "Choppy Zone" (Noise Filter): This is a unique feature of this script. If the HMA indicates one direction (e.g., Rising) but the Supertrend indicates the opposite (e.g., Downtrend), the market is considered "Choppy" or indecisive. In this state, the script paints the candles or HMA line Gray and exits all positions (optional setting) to preserve capital.
Visual Guide & Signals To make the script easy to interpret for traders who do not read Pine Script, I have implemented specific visual cues:
Green Cross (+): Indicates a LONG entry signal. Both HMA and Supertrend align bullishly.
Red Cross (X): Indicates a SHORT entry signal. Both HMA and Supertrend align bearishly.
Thick Line (HMA): The main line changes color based on the trend.
Green: Bullish Confluence.
Red: Bearish Confluence.
Gray: Divergence/Choppy (No Trade Zone).
Thin Step Line: This is the Supertrend line, serving as your dynamic Trailing Stop Loss.
Strategy Settings
HMA Length: Default is 50 (Mid-term trend).
ATR Factor/Period: Default is 3.0/10 (Standard for trend catching).
Exit on Choppy: A toggle switch allowing users to decide whether to hold through noise or exit immediately when indicators disagree.
Risk Warning This strategy performs best in trending markets (Forex, Crypto, Indices). Like all trend-following systems, it may experience drawdown during prolonged accumulation/distribution phases. Please backtest with your specific asset before using it with real capital.
XAU BUY/SELL Scalping Strategy M5 PROFX:XAUUSD
This XAU/USD Pro Scalping Strategy is tailored specifically for the M5 timeframe , designed to capture rapid Gold price movements. Instead of relying on lagging indicators, this system utilizes advanced Price Action and Market Structure analysis to identify high-probability entry zones.
The core strength of this strategy lies in its built-in Money Management engine and Multi-threaded Trailing Stop system, ensuring capital preservation and profit maximization.
🚀 Key Features:
1. Smart Price Action Recognition:
The algorithm scans for specific market scenarios to apply dynamic Risk:Reward ratios (ranging from 1:1 to 1:3).
Filters out noise and false breakouts using multi-candle analysis.
Auto Position Sizing:
Calculates trade quantity automatically based on your defined Risk % per Trade .
Ensures consistent risk management regardless of the Stop Loss distance.
Intelligent Trailing Stop:
Uses a dynamic trailing mechanism based on "R" multiples (Risk Units).
Automatically secures profits by moving SL based on the specific setup type ("Case") of each trade.
Safety Filters:
Min SL and Max SL inputs prevent trades during periods of extremely low volatility or excessive risk.
⚙️ Settings:
Risk % per Trade: The percentage of equity to risk per trade (Recommended: 1.0% - 2.0%).
Min/Max SL Points: Dynamic boundaries for Stop Loss to adapt to current market volatility.
💡 Recommendations:
Symbol: XAUUSD / Gold - FXCM.
Timeframe: M5.
Best performance during London and New York sessions.
Anchor SafeSwing Gold StrategyOverview:
The Anchor SafeSwing Gold Strategy is designed for users who prefer structured, rule-based swing trading on XAUUSD. It focuses on identifying high-quality trade setups rather than frequent entries.
This strategy analyzes the market using multiple technical indicators and methods—including trend analysis, multi-chart confirmation, and support/resistance evaluation—to identify potential swing points. It also incorporates a dynamic approach to risk management through adaptive stop-loss and take-profit logic.
How the Strategy Works
1. Multi-Chart & Trend Analysis:
The strategy evaluates trend direction using several indicators and multiple charts. This helps determine whether the trend favors long or short setups.
2. Buy/Sell Conditions:
a. Buy Conditions: When the broader trend is identified as bullish, the strategy waits for the formation of a strong support zone before considering a long position.
b. Sell Conditions: When the trend is bearish, it waits for a confirmed resistance zone before initiating short positions.
3. Dynamic Take-Profit Logic
The strategy uses adaptive take-profit behavior based on evolving market conditions. It monitors new support/resistance structures and various overbought/oversold signals to dynamically exit trades.
4. Dynamic and Configurable Stop-Loss:
A flexible stop-loss system adjusts according to volatility and market structure.
Users can modify the stop-loss threshold in the settings based on their own risk tolerance and account size.
Trading Frequency :
This strategy focuses on select, high-quality setups. As a result, trade frequency is relatively low and may vary depending on market conditions. Backtesting may show roughly several trades per month, but actual live performance can differ.
Important Notes
All trading involves risk, and users should evaluate the strategy and adjust settings according to their own risk management preferences.
Safe Supertrend Strategy (No Repaint)Overview
The Safe Supertrend is a repaint-free version of the popular Supertrend trend-following indicator.
Most Supertrend indicators appear perfect on historical charts because they flip intrabar and then repaint after the candle closes.
This version fixes that by using close-of-bar confirmation only, making every trend flip 100% stable, safe, and non-repainting.
Why This Supertrend Doesn’t Repaint
Most Supertrend indicators calculate their trend direction using the current bar’s data.
But during a live candle:
ATR expands and contracts
The upper/lower bands move
Price moves above/below the band temporarily
A false flip appears → then disappears when the candle closes
That is classic repainting.
This indicator avoids all of that by using:
close > upper
close < lower
This means:
Trend direction flips only based on the previous candle,
No intrabar calculations,
No flickering signals,
No “perfect but fake” historical performance.
Every signal you see on the chart is exactly what was available in real-time.
How It Works
Calculates ATR (Average True Range) and SMA centerline
Builds upper and lower volatility bands
Confirms trend flips only after the previous bar closes
Plots clear bull and bear reversal signals
Works on all markets (crypto, stocks, forex, indices)
No repainting, no recalc, no misleading flips.
Bullish Signal (Trend Up)
A bullish trend begins only when:
The previous candle closes above the upper ATR band,
And this flip is fully confirmed.
A green triangle marks the start of a new uptrend.
Bearish Signal (Trend Down)
A bearish trend begins only when:
The previous candle closes below the lower ATR band,
And the downtrend is confirmed.
A red triangle signals the start of a new downtrend.
Inputs
ATR Length - default 10
ATR Multiplier - default 3.0
Works on all timeframes and market
Simple, but powerful.
Why Use This Version Instead of a Regular Supertrend?
Most Supertrends:
Look great historically
But repaint continuously on live charts
Give false trend flips intrabar
Cannot be reliably used in strategies
This version:
Uses strict previous-bar logic
Never repaints trend direction
Works perfectly in live trading
Backtests accurately
Is ideal for algorithmic strategies
Ideal For:
Trend-following strategies
Breakout trading
Algo trading systems
Reversal detection
Filtering market noise
Swing trading & scalping
Final Note
This is a safer, more reliable Supertrend designed for real-world use — not perfect-looking repaint illusions.
If you use Supertrend in your trading system, this no-repaint version ensures your signals are trustworthy and consistent.
Safe Supertrend Strategy (No Repaint)Overview
The Safe Supertrend is a repaint-free version of the popular Supertrend trend-following indicator.
Most Supertrend indicators appear perfect on historical charts because they flip intrabar and then repaint after the candle closes.
This version fixes that by using close-of-bar confirmation only, making every trend flip 100% stable, safe, and non-repainting.
Why This Supertrend Doesn’t Repaint
Most Supertrend indicators calculate their trend direction using the current bar’s data.
But during a live candle:
ATR expands and contracts
The upper/lower bands move
Price moves above/below the band temporarily
A false flip appears → then disappears when the candle closes
That is classic repainting.
This indicator avoids all of that by using:
close > upper
close < lower
This means:
Trend direction flips only based on the previous candle,
No intrabar calculations,
No flickering signals,
No “perfect but fake” historical performance.
Every signal you see on the chart is exactly what was available in real-time.
How It Works
Calculates ATR (Average True Range) and SMA centerline
Builds upper and lower volatility bands
Confirms trend flips only after the previous bar closes
Plots clear bull and bear reversal signals
Works on all markets (crypto, stocks, forex, indices)
No repainting, no recalc, no misleading flips.
Bullish Signal (Trend Up)
A bullish trend begins only when:
The previous candle closes above the upper ATR band,
And this flip is fully confirmed.
A green triangle marks the start of a new uptrend.
Bearish Signal (Trend Down)
A bearish trend begins only when:
The previous candle closes below the lower ATR band,
And the downtrend is confirmed.
A red triangle signals the start of a new downtrend.
Inputs
ATR Length - default 10
ATR Multiplier - default 3.0
Works on all timeframes and market
Simple, but powerful.
Why Use This Version Instead of a Regular Supertrend?
Most Supertrends:
Look great historically
But repaint continuously on live charts
Give false trend flips intrabar
Cannot be reliably used in strategies
This version:
Uses strict previous-bar logic
Never repaints trend direction
Works perfectly in live trading
Backtests accurately
Is ideal for algorithmic strategies
Ideal For:
Trend-following strategies
Breakout trading
Algo trading systems
Reversal detection
Filtering market noise
Swing trading & scalping
Final Note
This is a safer, more reliable Supertrend designed for real-world use — not perfect-looking repaint illusions.
If you use Supertrend in your trading system, this no-repaint version ensures your signals are trustworthy and consistent.
ATR Trend + RSI Pullback Strategy [Profit-Focused]This strategy is designed to catch high-probability pullbacks during strong trends using a combination of ATR-based volatility filters, RSI exhaustion levels, and a trend-following entry model.
Strategy Logic
Rather than relying on lagging crossovers, this model waits for RSI to dip into oversold zones (below 40) while price remains above a long-term EMA (default: 200). This setup captures pullbacks in strong uptrends, allowing traders to enter early in a move while controlling risk dynamically.
To avoid entries during low-volatility conditions or sideways price action, it applies a minimum ATR filter. The ATR also defines both the stop-loss and take-profit levels, allowing the model to adapt to changing market conditions.
Exit logic includes:
A take-profit at 3× the ATR distance
A stop-loss at 1.5× the ATR distance
An optional early exit if RSI crosses above 70, signaling overbought conditions
Technical Details
Trend Filter: 200 EMA – must be rising and price must be above it
Entry Signal: RSI dips below 40 during an uptrend
Volatility Filter: ATR must be above a user-defined minimum threshold
Stop-Loss: 1.5× ATR below entry price
Take-Profit: 3.0× ATR above entry price
Exit on Overbought: RSI > 70 (optional early exit)
Backtest Settings
Initial Capital: $10,000
Position Sizing: 5% of equity per trade
Slippage: 1 tick
Commission: 0.075% per trade
Trade Direction: Long only
Timeframes Tested: 15m, 1H, and 30m on trending assets like BTCUSD, NAS100, ETHUSD
This model is tuned for positive P&L across trending environments and volatile markets.
Educational Use Only
This strategy is for educational purposes only and should not be considered financial advice. Past performance does not guarantee future results. Always validate performance on multiple markets and timeframes before using it in live trading.
Qullamagi EMA Breakout Autotrade (Crypto Futures L+S)Title: Qullamagi EMA Breakout – Crypto Autotrade
Overview
A crypto-focused, Qullamagi-style EMA breakout strategy built for autotrading on futures and perpetual swaps.
It combines a 5-MA trend stack (EMA 10/20, SMA 50/100/200), volatility contraction boxes, volume spikes and an optional higher-timeframe 200-MA filter. The script supports both long and short trades, partial take profit, trailing MA exits and percent-of-equity position sizing for automated crypto futures trading.
Key Features (Crypto)
Qullamagi MA Breakout Engine – trades only when price is aligned with a strong EMA/SMA trend and breaks out of a tight consolidation range. Longs use: Close > EMA10 > EMA20 > SMA50 > SMA100 > SMA200. Shorts are the mirror condition with all MAs sloping in the trend direction.
Strict vs Loose Modes – Strict (Daily) is designed for cleaner swing trades on 1H–4H (full MA stack, box+ATR and volume filters, optional HTF filter). Loose (Intraday) focuses on 10/20/50 alignment with relaxed filters for more frequent 15m–30m signals.
Volatility & Volume Filters for Crypto – ATR-based box height limit to detect volatility contraction, wide-candle filter to avoid chasing exhausted breakouts, and a volume spike condition requiring current volume to exceed an SMA of volume.
Higher-Timeframe Trend Filter (Optional) – uses a 200-period SMA on a higher timeframe (default: 1D). Longs only when HTF close is above the HTF 200-SMA, shorts only when it is below, helping avoid trading against dominant crypto trends.
Autotrade-Oriented Trade Management – position size as % of equity, initial stop anchored to a chosen MA (EMA10 / EMA20 / SMA50) with optional buffer, partial take profit at a configurable R-multiple, trailing MA exit for the remainder, and an optional cooldown after a full exit.
Markets & Timeframes
Best suited for BTC, ETH and major altcoin futures/perpetuals (Binance, Bybit, OKX, etc.).
Strict preset: 1H–4H charts for classic Qullamagi-style trend structure and fewer fake breakouts.
Loose preset: 15m–30m charts for higher trade frequency and more active intraday trading.
Always retune ATR length, box length, volume multiplier and position size for each symbol and exchange.
Strategy Logic (Quick Summary)
Long (Strict): MA stack in bullish alignment with all MAs sloping up → tight volatility box (ATR-based) → volume spike above SMA(volume) × multiplier → breakout above box high (close or intrabar) → optional HTF close above 200-SMA.
Short: Mirror logic: bearish MA stack, tight box, volume spike and breakdown below box low with optional HTF downtrend.
Best Practices for Crypto
Backtest on each symbol and timeframe you plan to autotrade, including commissions and slippage.
Start on higher timeframes (1H/4H) to learn the behavior, then move to 15m–30m if you want more signals.
Use the higher-timeframe filter when markets are strongly trending to reduce counter-trend trades.
Keep position-size percentage conservative until you fully understand the drawdowns.
Forward-test / paper trade before connecting to live futures accounts.
Webhook / Autotrade Integration
Designed to work with TradingView webhooks and external crypto trading bots.
Alert messages include structured fields such as: EVENT=ENTRY / SCALE_OUT / EXIT, SIDE=LONG / SHORT, STRATEGY=Qullamagi_MA.
Map each EVENT + SIDE combination to your bot logic (open long/short, partial close, full close, etc.) on your preferred exchange.
Important Notes & Disclaimer
Crypto markets are highly volatile and can change regime quickly. Backtest and forward-test thoroughly before using real capital. Higher timeframes generally produce cleaner MA structures and fewer fake breakouts.
This strategy is for educational and informational purposes only and does not constitute financial advice. Trading leveraged crypto products involves substantial risk of loss. Always do your own research, manage risk carefully, and never trade with money you cannot afford to lose.
EMA Cross + RSI + ADX - Autotrade Strategy V2Overview
A versatile trend-following strategy combining EMA 9/21 crossovers with RSI momentum filtering and optional ADX trend strength confirmation. Designed for both cryptocurrency and traditional futures/options markets with built-in stop loss management and automated position reversals.
Key Features
Multi-Market Compatibility: Works on both crypto futures (Bitcoin, Ethereum) and traditional markets (NIFTY, Bank NIFTY, S&P 500 futures, equity options)
Triple Confirmation System: EMA crossover + RSI filter + ADX strength (optional)
Automated Risk Management: 2% stop loss with wick-touch detection
Position Auto-Reversal: Opposite signals automatically close and reverse positions
Webhook Ready: Six distinct alert messages for automation (Entry Buy/Sell, Close Long/Short, SL Hit Long/Short)
Performance Metrics
NIFTY Futures (15min): 50%+ win rate with ADX filter OFF
Crypto Markets: Requires extensive backtesting before live deployment
Optimal Timeframes: 15-minute to 1-hour charts (patience required for higher timeframes)
Strategy Logic
Entry Signals:
LONG: EMA 9 crosses above EMA 21 + RSI > 55 + ADX > 20 (if enabled)
SHORT: EMA 9 crosses below EMA 21 + RSI < 45 + ADX > 20 (if enabled)
Exit Signals:
Opposite EMA crossover (auto-closes current position)
Stop loss hit at 2% from entry price (tracks candle wicks)
Technical Indicators:
Fast EMA: 9-period (short-term trend)
Slow EMA: 21-period (primary trend)
RSI: 14-period with 55/45 thresholds (momentum confirmation)
ADX: 14-period with 20 threshold (trend strength filter - optional)
Market-Specific Settings
Traditional Markets (NIFTY, Bank NIFTY, S&P Futures, Options)
Recommended Settings:
ADX Filter: Turn OFF (less choppy, cleaner trends)
Timeframe: 15-minute chart
Win Rate: 50%+ on NIFTY Futures
Why No ADX: Traditional markets have more institutional participation and smoother price action, making ADX unnecessary
Cryptocurrency Markets (BTC, ETH, Altcoins)
Recommended Settings:
ADX Filter: Turn ON (ADX > 20)
Timeframe: 15-minute to 1-hour
Extensive backtesting required before live trading
Why ADX: Crypto markets are highly volatile and prone to false breakouts; ADX filters low-quality chop
Best Practices
✅ Backtest thoroughly on your specific instrument and timeframe
✅ Use larger timeframes (1H, 4H) for higher quality signals and better risk/reward
✅ Adjust RSI thresholds based on market volatility (try 52/48 for more signals, 60/40 for fewer but stronger)
✅ Monitor ADX effectiveness - disable for traditional markets, enable for crypto
✅ Proper position sizing - adjust default_qty_value based on your capital and instrument price
✅ Paper trade first - test for 2-4 weeks before risking real capital
Risk Management
Fixed 2% stop loss per trade (adjustable)
Stop loss tracks candle wicks for accurate execution
Positions auto-reverse on opposite signals (no manual intervention needed)
0.075% commission built into backtest (adjust for your broker)
Customization Options
All parameters are adjustable via inputs:
EMA periods (default: 9/21)
RSI length and thresholds (default: 14-period, 55/45 levels)
ADX length and threshold (default: 14-period, 20 threshold)
Stop loss percentage (default: 2%)
Webhook Automation
This strategy includes six distinct alert messages for automated trading:
"Entry Buy" - Long position opened
"Entry Sell" - Short position opened
"Close Long" - Long position closed on opposite crossover
"Close Short" - Short position closed on opposite crossover
"SL Hit Long" - Long stop loss triggered
"SL Hit Short" - Short stop loss triggered
Compatible with Delta Exchange, Binance Futures, 3Commas, Alertatron, and other webhook platforms.
Important Notes
⚠️ Crypto markets require extensive backtesting - volatility patterns differ significantly from traditional markets
⚠️ Higher timeframes = better results - 15min works but 1H/4H provide cleaner signals
⚠️ ADX toggle is critical - OFF for traditional markets, ON for crypto
⚠️ Not financial advice - always conduct your own research and use proper risk management
⚠️ Past performance ≠ future results - backtest results may not reflect live trading conditions
Disclaimer
This strategy is for educational and informational purposes only. Trading futures and options involves substantial risk of loss. Always backtest thoroughly, start with paper trading, and never risk more than you can afford to lose. The author assumes no responsibility for any trading losses incurred using this strategy.
EMA + RSI Autotrade Webhook - VarunOverview
The EMA + RSI Autotrade Webhook is a powerful trend-following indicator designed for automated crypto futures trading. This indicator combines the reliability of Exponential Moving Average (EMA) crossovers with RSI momentum filtering to generate high-probability buy and sell signals optimized for webhook integration with crypto exchanges like Delta Exchange, Binance Futures, and Bybit.Key Features
Simple & Effective: Uses proven EMA 9/21 crossover strategy
RSI Momentum Filter: Eliminates low-probability trades in ranging markets
Webhook Ready: Two clean alerts (LONG Entry, SHORT Entry) for seamless automation
Exchange Compatible: Works with Delta Exchange, 3Commas, Alertatron, and other webhook platforms
Zero Lag Signals: Real-time alerts on crossover confirmation
Visual Clarity: Clean chart markers for easy signal identification
How It Works
Entry Signals:
LONG Entry: Triggers when EMA 9 crosses above EMA 21 AND RSI is above 52 (bullish momentum confirmed)
SHORT Entry: Triggers when EMA 9 crosses under EMA 21 AND RSI is below 48 (bearish momentum confirmed)
Technical Components:
Fast EMA: 9-period (tracks short-term price action)
Slow EMA: 21-period (identifies primary trend)
RSI: 14-period (confirms momentum strength)
RSI Long Threshold: 52 (filters weak bullish signals)
RSI Short Threshold: 48 (filters weak bearish signals)
Best Use Cases
Crypto Futures Trading: Bitcoin, Ethereum, Altcoin perpetual contracts
Automated Trading Bots: Integration with Delta Exchange webhooks, TradingView alerts
Timeframes: Optimized for 15-minute charts (works on 5min-1H)
Markets: Trending crypto markets with clear directional moves
Risk Management: Best used with 1-2% stop loss per trade (managed externally)
Webhook Automation Setup
Add indicator to your TradingView chart
Create alerts for "LONG Entry" and "SHORT Entry"
Configure webhook URL from your exchange (Delta Exchange, Binance, etc.)
Use alert message: Entry LONG {{ticker}} @ {{close}} or Entry SHORT {{ticker}} @ {{close}}
Exchange automatically reverses positions on opposite signals
Advantages
✅ No manual trading required - fully automated
✅ Eliminates emotional trading decisions
✅ Catches trending moves early with EMA crossovers
✅ RSI filter reduces whipsaws in choppy markets
✅ Works 24/7 without monitoring
✅ Simple two-alert system (easy to manage)
✅ Compatible with multiple exchanges via webhooksStrategy Philosophy
This indicator follows a trend-following with momentum confirmation approach. By waiting for both EMA crossover AND RSI confirmation, it ensures you're entering trades with genuine momentum behind them, not just random price noise. The tight RSI thresholds (52/48) keep you aligned with the prevailing trend.Recommended Settings
Timeframe: 15-minute (primary), 5-minute (scalping), 1-hour (swing)
Markets: BTC/USDT, ETH/USDT, high-liquidity altcoin perpetuals
Position Sizing: 100% capital per signal (exchange manages reversals)
Stop Loss: 2% (managed via exchange or external bot)
Leverage: 1-2x for conservative approach, up to 5x for aggressive
Important Notes
⚠️ This indicator generates entry signals only - position reversals are handled automatically by your exchange
⚠️ Always backtest on historical data before live trading
⚠️ Use proper risk management and position sizing
⚠️ Best performance in trending markets; may generate false signals in tight ranges
⚠️ Requires TradingView Premium or higher for webhook functionalityTags
cryptocurrency futures automated-trading ema-crossover rsi webhook delta-exchange tradingview-alerts trend-following momentum bitcoin ethereum crypto-bot algo-trading 15-minute-strategy
Normalized WMA Oscillator | OquantNormalized WMA Oscillator | Oquant
The Normalized WMA Oscillator is a trend-momentum indicator designed to help traders visualize the relative position of a Weighted Moving Average (WMA) within its recent price range.
What is a WMA and How It Works:
A Weighted Moving Average (WMA) is a type of moving average that gives more weight to recent price data, making it more responsive to price changes compared to a simple moving average. Each price point in the lookback period is multiplied by a weighting factor, with the most recent prices having the highest weights. The WMA helps traders identify potential trends more quickly.
This indicator applies min-max normalization to the standard WMA, scaling its values between 0 and 1 over a configurable lookback period. This allows traders to see whether the WMA is near its recent highs, lows, or midpoint, regardless of the absolute price level.
Key Features:
WMA Source Input: Choose price source for wma calculation.
Customizable WMA Length: Adjust the sensitivity of the WMA.
Min-Max Normalization Length: Smooth the scaling of WMA values between 0 and 1.
Signal Thresholds: Configurable upper and lower thresholds to indicate potential entries.
Visual Alerts: Color-coded oscillator and candles plot for bullish (green) and bearish (purple) signals.
Alerts Ready: Built-in alert conditions for crossovers and crossunders of the oscillator.
How It Works:
Calculate the WMA on the selected source.
Normalize its value using the minimum and maximum WMA values over the specified lookback period.
Generate long signals when the normalized WMA moves above the upper threshold, and short signals when it moves below the lower threshold.
Plot the oscillator and candles in green for bullish signals and purple for bearish signals.
Inputs:
Source: Data used for WMA calculation.
WMA Length: Period for Weighted Moving Average.
Min-Max Length: Lookback period for min-max scaling.
Upper Threshold: Level above which a long signal is considered.
Lower Threshold: Level below which a short signal is considered.
⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Bayesian Trend Navigator [QuantAlgo]🟢 Overview
The Bayesian Trend Navigator uses Bayesian statistics to continuously update trend probabilities by combining long-term expectations (prior beliefs) and short-term observations (likelihood evidence), rather than relying solely on recent price data like many conventional indicators. This mathematical framework produces robust directional signals that naturally balance responsiveness with stability, making it suitable for traders and investors seeking statistically-grounded trend identification across diverse market environments and asset types.
🟢 How It Works
The indicator operates on Bayesian inference principles, a statistical method for updating beliefs when new evidence emerges. The system begins by establishing a prior belief - a long-term trend expectation calculated from historical price behavior. This represents the "baseline hypothesis" about market direction before considering recent developments.
Simultaneously, the algorithm collects recent market evidence through short-term trend analysis, representing the likelihood component. This captures what current price action suggests about directional momentum independent of historical context.
The core Bayesian engine then combines these elements using conjugate normal distributions and precision weighting. It calculates prior precision (inverse variance) and likelihood precision, combining them to determine a posterior precision. The resulting posterior mean represents the mathematically optimal trend estimate given both historical patterns and current reality. This posterior calculation includes intervals derived from the posterior variance, providing probabilistic confidence bounds around the trend estimate.
Finally, volatility-based standard deviation bands create adaptive boundaries around the Bayesian estimate. The trend line adjusts within these constraints, generating color transitions between bullish (green) and bearish (red) states when the posterior calculation crosses these probabilistic thresholds.
🟢 How to Use
Green/Bullish Trend Line: Posterior probability favoring upward momentum, indicating statistically favorable conditions for long positions (buy)
Red/Bearish Trend Line: Posterior probability favoring downward momentum, signaling mathematically supported timing for short positions (sell)
Rising Green Line: Strengthening bullish posterior as new evidence reinforces upward beliefs, showing increasing probabilistic confidence in trend continuation with favorable long entry conditions
Declining Red Line: Intensifying bearish posterior with accumulating downside evidence, indicating growing statistical certainty in downtrend persistence and optimal short positioning opportunities
Flattening Trends: Diminishing posterior confidence regardless of color suggests equilibrium between prior beliefs and contradictory evidence, potentially signaling consolidation or insufficient statistical clarity for high-conviction trades
🟢 Pro Tips for Trading and Investing
→ Preset Configuration Strategy: Deploy presets based on your trading horizon - Scalping preset maximizes evidence weight (0.8) for rapid Bayesian updates on 1-15 minute charts, Default preset balances prior and likelihood for general applications, while Swing Trading preset equalizes weights (0.5/0.5) for stable inference on hourly and daily timeframes.
→ Prior Weight Adjustment: Calibrate prior weight according to market regime - increase values (0.5-0.7) in stable trending markets where historical patterns remain predictive, decrease values (0.2-0.3) during regime changes or news-driven volatility when recent evidence should dominate the posterior calculation.
→ Evidence Period Tuning: Modify the evidence period based on information flow velocity. Use shorter periods (5-8 bars) for assets with continuous price discovery like cryptocurrencies, medium periods (10-15) for liquid stocks, and longer periods (15-20) for slower-moving markets to ensure adequate likelihood sample size.
→ Likelihood Weight Optimization: Adjust likelihood weight inversely to market noise levels. Higher values (0.7-0.8) work well in clean trending conditions where recent data is reliable, while lower values (0.4-0.6) help during choppy periods by maintaining stronger reliance on established prior beliefs.
→ Multi-Timeframe Bayesian Confluence: Apply the indicator across multiple timeframes, using higher timeframes (Daily/Weekly) to establish prior belief direction and lower timeframes (Hourly/15-minute) for likelihood-driven entry timing, ensuring posterior probabilities align across temporal scales for maximum statistical confidence.
→ Standard Deviation Multiplier Management: Adapt the multiplier to match current uncertainty levels. Use tighter multipliers (1.0-1.5) during low-volatility consolidations to capture early trend emergence, and wider multipliers (2.0-2.5) during high-volatility events to avoid premature signals caused by statistical noise rather than genuine posterior shifts.
→ Variance-Based Position Sizing: Monitor the implicit posterior variance through trend line stability - smooth consistent movements indicate low uncertainty warranting larger positions, while erratic fluctuations suggest high statistical uncertainty calling for reduced exposure until clearer probabilistic convergence emerges.
→ Alert-Based Probabilistic Execution: Utilize trend change alerts to capture every statistically significant posterior shift from bullish to bearish states or vice versa without constantly monitoring the charts.
Bollinger Adaptive Trend Navigator [QuantAlgo]🟢 Overview
The Bollinger Adaptive Trend Navigator synthesizes volatility channel analysis with variable smoothing mechanics to generate trend identification signals. It uses price positioning within Bollinger Band structures to modify moving average responsiveness, while incorporating ATR calculations to establish trend line boundaries that constrain movement during volatile periods. The adaptive nature makes this indicator particularly valuable for traders and investors working across various asset classes including stocks, forex, commodities, and cryptocurrencies, with effectiveness spanning multiple timeframes from intraday scalping to longer-term position analysis.
🟢 How It Works
The core mechanism calculates price position within Bollinger Bands and uses this positioning to create an adaptive smoothing factor:
bbPosition = bbUpper != bbLower ? (source - bbLower) / (bbUpper - bbLower) : 0.5
adaptiveFactor = (bbPosition - 0.5) * 2 * adaptiveMultiplier * bandWidthRatio
alpha = math.max(0.01, math.min(0.5, 2.0 / (bbPeriod + 1) * (1 + math.abs(adaptiveFactor))))
This adaptive coefficient drives an exponential moving average that responds more aggressively when price approaches Bollinger Band extremes:
var float adaptiveTrend = source
adaptiveTrend := alpha * source + (1 - alpha) * nz(adaptiveTrend , source)
finalTrend = 0.7 * adaptiveTrend + 0.3 * smoothedCenter
ATR-based volatility boundaries constrain the final trend line to prevent excessive movement during volatile periods:
volatility = ta.atr(volatilityPeriod)
upperBound = bollingerTrendValue + (volatility * volatilityMultiplier)
lowerBound = bollingerTrendValue - (volatility * volatilityMultiplier)
The trend line direction determines bullish or bearish states through simple slope comparison, with the final output displaying color-coded signals based on the synthesis of Bollinger positioning, adaptive smoothing, and volatility constraints (green = long/buy, red = short/sell).
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward direction based on Bollinger positioning and adaptive smoothing = Potential long/buy opportunity
Falling Trend Line (Red): Indicates downward direction based on Bollinger positioning and adaptive smoothing = Potential short/sell opportunity
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant development without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency
Configuration Presets: Three parameter sets available - Default (standard settings), Scalping (faster response), and Swing Trading (slower response)
Sine Weighted Trend Navigator [QuantAlgo]🟢 Overview
The Sine Weighted Trend Navigator utilizes trigonometric mathematics to create a trend-following system that adapts to various market volatility. Unlike traditional moving averages that apply uniform weights, this indicator employs sine wave calculations to distribute weights across historical price data, creating a more responsive yet smooth trend measurement. Combined with volatility-adjusted boundaries, it produces actionable directional signals for traders and investors across various market conditions and asset classes.
🟢 How It Works
At its core, the indicator applies sine wave mathematics to weight historical prices. The system generates angular values across the lookback period and transforms them through sine calculations, creating a weight distribution pattern that naturally emphasizes recent price action while preserving smoothness. The phase shift feature allows rotation of this weighting pattern, enabling adjustment of the indicator's responsiveness to different market conditions.
Surrounding this sine-weighted calculation, the system establishes volatility-responsive boundaries through market volatility analysis. These boundaries expand and contract based on current market conditions, creating a dynamic framework that helps distinguish meaningful trend movements from random price fluctuations.
The trend determination logic compares the sine-weighted value against these adaptive boundaries. When the weighted value exceeds the upper boundary, it signals upward momentum. When it drops below the lower boundary, it indicates downward pressure. This comparison drives the color transitions of the main trend line, shifting between bullish (green) and bearish (red) states to provide clear directional guidance on price charts.
🟢 How to Use
Green/Bullish Trend Line: Rising momentum indicating optimal conditions for long positions (buy)
Red/Bearish Trend Line: Declining momentum signaling favorable timing for short positions (sell)
Steepening Green Line: Accelerating bullish momentum with increasing sine-weighted values indicating strengthening upward pressure and high-probability trend continuation
Steepening Red Line: Intensifying bearish momentum with declining sine-weighted calculations suggesting persistent downward pressure and optimal shorting opportunities
Flattening Trend Lines: Gradual reduction in directional momentum regardless of color may indicate approaching consolidation or trend exhaustion requiring position management review
🟢 Pro Tips for Trading and Investing
→ Preset Strategy Selection: Utilize the built-in presets strategically - Scalping preset for ultra-responsive 1-15 minute charts, Default preset for balanced general trading, and Swing Trading preset for 1-4 hour charts and multi-day positions.
→ Phase Shift Optimization: Fine-tune the phase shift parameter based on market bias - use positive values (0.1-0.5) in trending bull markets to enhance uptrend sensitivity, negative values (-0.1 to -0.5) in bear markets for improved downtrend detection, and zero for balanced neutral market conditions.
→ Multiplier Calibration: Adjust the multiplier according to market volatility and trading style. Use lower values (0.5-1.0) for tight, responsive signals in stable markets, higher values (2.0-3.0) during earnings seasons or high-volatility periods to filter noise and reduce whipsaws.
→ Sine Period Adaptation: Customize the sine weighted period based on your trading timeframe and market conditions. Use 5-14 for day trading to capture short-term momentum shifts, 14-25 for swing trading to balance responsiveness with reliability, and 25-50 for position trading to maintain long-term trend clarity.
→ Multi-Timeframe Sine Validation: Apply the indicator across multiple timeframes simultaneously, using higher timeframes (4H/Daily) for overall trend bias and lower timeframes (15m/1H) for entry timing, ensuring sine-weighted calculations align across different time horizons.
→ Alert-Driven Systematic Execution: Leverage the built-in trend change alerts to eliminate emotional decision-making and capture every mathematically-confirmed trend transition, particularly valuable for traders managing multiple instruments or those unable to monitor charts continuously.
→ Risk Management: Increase position sizes during strong directional sine-weighted momentum while reducing exposure during frequent color changes that indicate mathematical uncertainty or ranging market conditions lacking clear directional bias.
RSI Trend Navigator [QuantAlgo]🟢 Overview
The RSI Trend Navigator integrates RSI momentum calculations with adaptive exponential moving averages and ATR-based volatility bands to generate trend-following signals. The indicator applies variable smoothing coefficients based on RSI readings and incorporates normalized momentum adjustments to position a trend line that responds to both price action and underlying momentum conditions.
🟢 How It Works
The indicator begins by calculating and smoothing the RSI to reduce short-term fluctuations while preserving momentum information:
rsiValue = ta.rsi(source, rsiPeriod)
smoothedRSI = ta.ema(rsiValue, rsiSmoothing)
normalizedRSI = (smoothedRSI - 50) / 50
It then creates an adaptive smoothing coefficient that varies based on RSI positioning relative to the midpoint:
adaptiveAlpha = smoothedRSI > 50 ? 2.0 / (trendPeriod * 0.5 + 1) : 2.0 / (trendPeriod * 1.5 + 1)
This coefficient drives an adaptive trend calculation that responds more quickly when RSI indicates bullish momentum and more slowly during bearish conditions:
var float adaptiveTrend = source
adaptiveTrend := adaptiveAlpha * source + (1 - adaptiveAlpha) * nz(adaptiveTrend , source)
The normalized RSI values are converted into price-based adjustments using ATR for volatility scaling:
rsiAdjustment = normalizedRSI * ta.atr(14) * sensitivity
rsiTrendValue = adaptiveTrend + rsiAdjustment
ATR-based bands are constructed around this RSI-adjusted trend value to create dynamic boundaries that constrain trend line positioning:
atr = ta.atr(atrPeriod)
deviation = atr * atrMultiplier
upperBound = rsiTrendValue + deviation
lowerBound = rsiTrendValue - deviation
The trend line positioning uses these band constraints to determine its final value:
if upperBound < trendLine
trendLine := upperBound
if lowerBound > trendLine
trendLine := lowerBound
Signal generation occurs through directional comparison of the trend line against its previous value to establish bullish and bearish states:
trendUp = trendLine > trendLine
trendDown = trendLine < trendLine
if trendUp
isBullish := true
isBearish := false
else if trendDown
isBullish := false
isBearish := true
The final output colors the trend line green during bullish states and red during bearish states, creating visual buy/long and sell/short opportunity signals based on the combined RSI momentum and volatility-adjusted trend positioning.
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward momentum where RSI influence and adaptive smoothing favor continued price advancement = Potential buy/long positions
Declining Trend Line (Red): Indicates downward momentum where RSI influence and adaptive smoothing favor continued price decline = Potential sell/short positions
Flattening Trend Lines: Occur when momentum weakens and the trend line slope approaches neutral, suggesting potential consolidation before the next move
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, sending "RSI Trend Bullish Signal" or "RSI Trend Bearish Signal" messages for timely entry/exit
Color Bar Candles Option: Optional candle coloring feature that applies the same green/red trend colors to price bars, providing additional visual confirmation of the current trend direction
Linear Regression Trend Navigator [QuantAlgo]🟢 Overview
The Linear Regression Trend Navigator is a trend-following indicator that combines statistical regression analysis with adaptive volatility bands to identify and track dominant market trends. It employs linear regression mathematics to establish the underlying trend direction, while dynamically adjusting trend boundaries based on standard deviation calculations to filter market noise and maintain trend continuity. The result is a straightforward visual system where green indicates bullish conditions favoring buy/long positions, and red signals bearish conditions supporting sell/short trades.
🟢 How It Works
The indicator operates through a three-phase computational process that transforms raw price data into adaptive trend signals. In the first phase, it calculates a linear regression line over the specified period, establishing the mathematical best-fit line through recent price action to determine the underlying directional bias. This regression line serves as the foundation for trend analysis by smoothing out short-term price variations while preserving the essential directional characteristics.
The second phase constructs dynamic volatility boundaries by calculating the standard deviation of price movements over the defined period and applying a user-adjustable multiplier. These upper and lower bounds create a volatility-adjusted channel around the regression line, with wider bands during volatile periods and tighter bands during stable conditions. This adaptive boundary system operates entirely behind the scenes, ensuring the trend signal remains relevant across different market volatility regimes without cluttering the visual display.
In the final phase, the system generates a simple trend line that dynamically positions itself within the volatility boundaries. When price action pushes the regression line above the upper bound, the trend line adjusts to the upper boundary level. Conversely, when the regression line falls below the lower bound, the trend line moves to the lower boundary. The result is a single colored line that transitions between green (rising trend line = buy/long) and red (declining trend line = sell/short).
🟢 How to Use
Green Trend Line: Upward momentum indicating favorable conditions for long positions, buy signals, and bullish strategies
Red Trend Line: Downward momentum signaling optimal timing for short positions, sell signals, and bearish approaches
Rising Green Line: Accelerating bullish momentum with steepening angles indicating strengthening upward pressure and potential for trend continuation
Declining Red Line: Intensifying bearish momentum with increasing negative slopes suggesting persistent downward pressure and shorting opportunities
Flattening Trend Lines: Gradual reduction in slope regardless of color may indicate approaching consolidation or momentum exhaustion requiring position review
🟢 Pro Tips for Trading and Investing
→ Entry/Exit Timing: Trade exclusively on band color transitions rather than price patterns, as each color change represents a statistically-confirmed shift that has passed through volatility filtering, providing higher probability setups than traditional technical analysis.
→ Parameter Optimization for Asset Classes: Customize the linear regression period based on your trading style. For example, use 5-10 bars for day trading to capture short-term statistical shifts, 14-20 for swing trading to balance responsiveness with stability, and 25-50 for position trading to filter out medium-term noise.
→ Volatility Calibration Strategy: Adjust the standard deviation multiplier according to market volatility. For instance, increase to 2.0+ during high-volatility periods like earnings or news events to reduce false signals, decrease to 1.0-1.5 during stable market conditions to maintain sensitivity to genuine trends.
→ Cross-Timeframe Statistical Validation: Apply the indicator across multiple timeframes simultaneously, using higher timeframes for directional bias and lower timeframes for entry timing.
→ Alert-Based Systematic Trading: Use built-in alerts to eliminate discretionary decision-making and ensure you capture every statistically-significant trend change, particularly effective for traders who cannot monitor charts continuously.
→ Risk Allocation Based on Signal Strength: Increase position sizes during periods of strong directional movement while reducing exposure during frequent band color changes that indicate statistical uncertainty or ranging conditions.
Smart Structure Breaks & Order BlocksOverview (What it does)
The indicator “Smart Structure Breaks & Order Blocks” detects market structure using swing highs and lows, identifies Break of Structure (BOS) events, and automatically draws order blocks (OBs) from the origin candle. These zones extend to the right and change color/outline when mitigated or invalidated. By formalizing and automating part of discretionary analysis, it provides consistent zone recognition.
Main Components
Swing Detection: ta.pivothigh/ta.pivotlow identify confirmed swing points.
BOS Detection: Determines if the recent swing high/low is broken by close (strict mode) or crossover.
OB Creation: After a BOS, the opposite candle (bearish for bullish BOS, bullish for bearish BOS) is used to generate an order block zone.
Zone Management: Limits the number of zones, extends them to the right, and tracks tagged (mitigated) or invalidated states.
Input Parameters
Left/Right Pivot (default 6/6): Number of bars required on each side to confirm a swing. Higher values = smoother swings.
Max Zones (default 4): Maximum zones stored per direction (bull/bear). Oldest zones are overwritten.
Zone Confirmation Lookback (default 3): Ensures OB origin candle validity by checking recent highs/lows.
Show Swing Points (default ON): Displays triangles on swing highs/lows.
Require close for BOS? (default ON): Strict BOS (close required) vs loose BOS (line crossover).
Use candle body for zones (default OFF): Zones drawn from candle body (ON) or wick (OFF).
Signal Definition & Logic
Swing Updates: Latest confirmed pivots update lastHighLevel / lastLowLevel.
BOS (Break of Structure):
Bullish – close breaks last swing high.
Bearish – close breaks last swing low.
Only one valid BOS per swing (avoids duplicates).
OB Detection:
Bullish BOS → previous bearish candle with lowest low forms the OB.
Bearish BOS → previous bullish candle with highest high forms the OB.
Zones: Bull = green, Bear = red, semi-transparent, extended to the right.
Zone States:
Mitigated: Price touches the zone → border highlighted.
Invalidated:
Bull zone → close below → turns red.
Bear zone → close above → turns green.
Chart Appearance
Swing High: red triangle above bar
Swing Low: green triangle below bar
Bull OB: green zone (border highlighted on touch)
Bear OB: red zone (border highlighted on touch)
Invalid Zones: Bull zones turn reddish, Bear zones turn greenish
Practical Use (Trading Assistance)
Trend Following Entries: Buy pullbacks into green OBs in uptrends, sell rallies into red OBs in downtrends.
Focus on First Touch: First mitigation after BOS often has higher reaction probability.
Confluence: Combine with higher timeframe trend, volume, session levels, key price levels (previous highs/lows, VWAP, etc.).
Stops/Targets:
Bull – stop below zone, partial take profit at swing high or resistance.
Bear – stop above zone, partial take profit at swing low or support.
Parameter Tuning (per market/timeframe)
Pivot (6/6 → 4/4/8/8): Lower for scalping (3–5), medium for day trading (5–8), higher for swing trading (8–14). Increase to reduce noise.
Strict Break: ON to reduce false breaks in ranging markets; OFF for earlier signals.
Body Zones: ON for assets with long wicks, OFF for cleaner OBs in liquid instruments.
Zone Confirmation (default 3): Increase for stricter OB origin, fewer zones.
Max Zones (default 4 → 6–10): Increase for higher volatility, decrease to avoid clutter.
Strengths
Standardizes BOS and OB detection that is usually subjective.
Tracks mitigation and invalidation automatically.
Adaptable: allows body/wick zone switching for different instruments.
Limitations
Pivot-based: Signals appear only after pivots confirm (slight lag).
Zones reflect past balance: Can fail after new events (news, earnings, macro data).
Range-heavy markets: More false BOS; consider stricter settings.
Backtesting: This script is for drawing/visual aid; trading rules must be defined separately.
Workflow Example
Identify higher timeframe trend (4H/Daily).
On lower TF (15–60m), wait for BOS and new OB.
Enter on first mitigation with confirmation candle.
Stop beyond zone; targets based on R multiples and swing points.
FAQ
Q: Why are zones invalidated quickly?
A: Flow reversal after BOS. Adjust pivots higher, enable Strict mode, or switch to Body zones to reduce noise.
Q: What does “tagged” mean?
A: Price touched the zone once = mitigated. Implies some orders in that zone may have been filled.
Q: Body or Wick zones?
A: Wick zones are fine in clean markets. For volatile pairs with long wicks, body zones provide more realistic areas.
Customization Tips (Code perspective)
Zone storage: Currently ring buffer ((idx+1) % zoneLimit). Could prioritize keeping unmitigated zones.
Automated testing: Add strategy.entry/exit for rule-based backtests.
Multi-timeframe: Use request.security() for higher timeframe swings/BOS.
Visualization: Add labels for BOS bars, tag zones with IDs, count touches.
Summary
This indicator formalizes the cycle Swing → BOS → OB creation → Mitigation/Invalidation, providing consistent structure analysis and zone tracking. By tuning sensitivity and strictness, and combining with higher timeframe context, it enhances pullback/continuation trading setups. Always combine with proper risk management.
Fundur - Trend LinesFundur - Trend Lines: Complete Trading Indicator Guide
Indicator Overview
The Fundur - Trend Lines is an advanced multi-layered trend analysis system that combines adaptive trend line technology, momentum analysis, and intelligent signal generation into one comprehensive trading tool. This indicator goes beyond traditional moving averages by utilizing volatility-adjusted trend lines that dynamically adapt to market conditions, providing traders with precise trend strength measurements and actionable trading signals.
What Makes Trend Lines Unique?
The Trend Lines indicator introduces Adaptive Trend Line Technology - a sophisticated methodology that uses Average True Range (ATR) calculations to create trend lines that respond intelligently to market volatility. Unlike static indicators, Trend Lines provides dynamic analysis that adapts its sensitivity based on current market conditions, offering more accurate trend identification and strength assessment.
Core Methodology
The indicator operates on the principle that trend strength can be quantified by analyzing the relationship between multiple adaptive trend lines, momentum indicators, and market structure. By combining Alignment Analysis , Distance Measurements , Momentum Confirmation , and Volatility Expansion Potential , the system generates a comprehensive trend strength score from 0-100% with corresponding trading signals.
Key Features
🎯 Adaptive Trend Line System Slow Trend Line : Primary trend direction with lower sensitivity for major trend identification Fast Trend Line : Higher sensitivity trend line for early trend change detection Volatility Adaptation : Both lines automatically adjust to market volatility using ATR calculations Cloud Visualization : Colored areas between trend lines show trend strength and direction
📊 Comprehensive Trend Strength Analysis Quantified Strength (0-100%) : Precise trend strength measurement combining multiple factors Alignment Score : Measures agreement between multiple trend line systems Distance Analysis : Evaluates price proximity to trend lines using ATR normalization Momentum Integration : Incorporates Awesome Oscillator for momentum confirmation Squeeze Factor : Identifies volatility expansion potential for breakout opportunities
🧠 Intelligent Signal Generation Position Signals : Clear ADD LONG, ADD SHORT, REDUCE, HOLD recommendations Risk Zone Classification : STRONG, MEDIUM, WEAK trend categorization Trend Direction : Bullish, Bearish, or Neutral trend identification Dynamic Updates : Real-time signal adjustments based on changing conditions
⚡ Enhanced Momentum Analysis Smoothed Momentum : Configurable momentum smoothing to reduce noise Acceleration Detection : Identifies momentum acceleration and deceleration Divergence Alerts : Detects price-momentum divergences for reversal warnings Directional Bias : Momentum confirmation for trend direction validation
🔍 Advanced Market Structure Detection Momentum Squeeze : Identifies low-volatility periods preceding major moves Volatility Expansion : Detects when markets break out of consolidation phases Trend Weakness Detection : Early warning system for deteriorating trends Structure Transition : Identifies when trends change character or direction
🎨 Professional Visual Interface Comprehensive Analysis Table : All key metrics displayed in organized format Visual Strength Bar : Graphical representation of trend strength Color-Coded Components : Intuitive color scheme for quick analysis Customizable Display : Flexible positioning and sizing options
Setup Guide
Step 1: Adding the Indicator
Open TradingView and navigate to your desired chart Click the "Indicators" button or press "/" key Search for "Fundur - Trend Lines" Add the indicator to your chart
Step 2: Basic Configuration
Main Features Settings ✅ Show Trend Analysis Table : ON (Essential for comprehensive analysis) ✅ Enable Trend Strength Analysis : ON (Core functionality) ✅ Generate Trading Signals : ON (For position management guidance)
Trend Lines Display ✅ Show Slow Trend Line : ON (Primary trend identification) ✅ Show Fast Trend Line : ON (Early signal detection) Trend Cloud Transparency : 89% (Default recommended, adjust for visibility)
Table Positioning Table Position : Top Right (recommended for most setups) Table Size : Normal (adjust based on screen size)
Step 3: Advanced Analysis Configuration
Enhanced Features (Optional) ✅ Enhanced Momentum Analysis : ON (for more accurate signals) ✅ Divergence Detection : ON (for reversal warnings) ⚠️ Momentum Squeeze Analysis : OFF initially (can add visual complexity)
Sensitivity Settings Divergence Sensitivity : 5 (Default - lower = more sensitive) Momentum Smoothing : 3 (Default - higher = smoother signals)
Step 4: Alert Configuration
Essential Alerts (Recommended) Trading Signal Alerts : Enable for position changes Trend Strength Change Alerts : Enable for trend monitoring Strength Change Threshold : 15% (Default recommended)
Advanced Alerts (Optional) Divergence Alerts : Enable for reversal warnings Early Weakness Alerts : Enable for risk management Momentum Squeeze Alerts : Enable for breakout opportunities Trend Line Cross Alerts : Enable for level-based signals
Basic Trading Guide
Understanding Trend Strength
The indicator's foundation is the Trend Strength Score - a quantified measurement (0-100%) that combines four key factors:
Strong Trends (75%+ Strength) 🟢 Characteristics : High alignment, close price-to-trend proximity, strong momentum Signals : ADD LONG (bullish) or ADD SHORT (bearish) Strategy : Aggressive position building, trend continuation trades Risk : Lower risk due to strong trend confirmation
Medium Trends (35-75% Strength) 🟡 Characteristics : Mixed signals, moderate alignment, transitional phases Signals : HOLD current positions Strategy : Conservative approach, wait for clearer signals Risk : Medium risk, requires careful monitoring
Weak Trends (Below 35% Strength) 🔴 Characteristics : Poor alignment, distant from trend lines, weak momentum Signals : REDUCE positions or CLOSE Strategy : Risk reduction, position unwinding Risk : High risk, trend likely changing or failing
Entry Strategies
Primary Strategy: Trend Continuation Entries Setup : Strong trend strength (75%+) with clear directional bias Entry Trigger : ADD LONG or ADD SHORT signal confirmation Direction : Follow the trend direction (Bullish ⬆ or Bearish ⬇) Timing : Enter on signal generation or price pullback to trend lines
Stop Loss Placement Conservative Method : Beyond the opposite trend line Aggressive Method : Below/above recent swing points For Long Positions : Below the Slow Trend Line For Short Positions : Above the Slow Trend Line Dynamic Adjustment : Move stops with trend line progression
Profit Taking Strategy
For Long Positions (Bullish Trend): Take 50% profits when trend strength begins declining from peak Take another 25% when trend strength drops below 60% Close remaining position when REDUCE signal appears Trail stops using Fast Trend Line for remaining position
For Short Positions (Bearish Trend): Take 50% profits when trend strength begins declining from peak Take another 25% when trend strength drops below 60% Close remaining position when REDUCE signal appears Trail stops using Fast Trend Line for remaining position
Alternative Strategy: Divergence-Based Reversal Entries Setup : Bullish or bearish divergence detected with weakening trend strength Entry : On trend direction change confirmation Risk Management : Tight stops due to counter-trend nature Targets : Opposite trend line or previous swing levels
Risk Management Framework
Position Sizing Based on Trend Strength Strong Trends (75%+) : Full position size (within risk tolerance) Medium Trends (35-75%) : Reduced position size (50-75% of normal) Weak Trends (Below 35%) : Minimal or no new positions Transitional Periods : Smallest position sizes due to uncertainty
Dynamic Risk Adjustment Increasing Strength : Can add to positions gradually Decreasing Strength : Begin profit-taking and position reduction Rapid Strength Loss : Quick position reduction or exit Divergence Warning : Tighten stops and prepare for reversal
Analysis Setups
Setup 1: Scalping Configuration (1-5 minute charts)
Settings Optimization: Momentum Smoothing: 2 (more responsive) Divergence Sensitivity: 3 (higher sensitivity) Enhanced Momentum Analysis: ON All alerts: ON for rapid signal updates
Visual Settings: Table Size: Small (less screen space) Table Position: Top Right Trend Cloud Transparency: 85% (subtle background)
Trading Approach: Focus on quick ADD signals in strong trends Use Fast Trend Line for entry timing Quick profit-taking at first sign of strength decline Very tight risk management due to lower timeframe noise
Setup 2: Day Trading Configuration (5-15 minute charts)
Settings Optimization: All default settings work well Enable Momentum Squeeze Analysis for breakout identification Divergence Detection: ON for reversal warnings Trend Strength Change Threshold: 12% (more sensitive)
Visual Settings: Table Size: Normal Show all trend analysis components Trend Cloud Transparency: 89% (default)
Trading Approach: Wait for clear trend strength above 65% before entering Use momentum squeeze breakouts for early entries Hold positions through medium strength phases Exit on REDUCE signals or strength below 40%
Setup 3: Swing Trading Configuration (1-4 hour charts)
Settings Optimization: Momentum Smoothing: 4 (smoother for higher timeframe) Divergence Sensitivity: 7 (less sensitive, higher quality signals) Enhanced Momentum Analysis: ON Early Weakness Alerts: ON (important for swing trades)
Visual Settings: Table Size: Normal or Large Focus on trend strength and direction components Enable all visual features for comprehensive analysis
Trading Approach: Require trend strength above 70% for new positions Hold through temporary strength dips if above 50% Use divergence signals for early exit warnings Focus on major trend changes for position adjustments
Setup 4: Position Trading Configuration (4H-Daily charts)
Settings Optimization: Momentum Smoothing: 5 (maximum smoothing) Divergence Sensitivity: 10 (only high-quality divergences) Strength Change Threshold: 20% (major changes only) Focus on trend direction and strength alerts
Visual Settings: Table Size: Large (detailed analysis) Clean visual setup focusing on major components Minimal clutter for long-term perspective
Trading Approach: Only enter on very strong trends (80%+ strength) Hold through significant strength fluctuations Focus on major trend direction changes Use weekly/monthly trend alignment for confirmation
Setup 5: Multi-Asset Analysis Configuration
For Forex Pairs: Standard settings work well due to 24-hour markets Pay attention to session-based strength changes Use momentum squeeze for breakout trading Enable all alert types for continuous monitoring
For Cryptocurrency: Reduce momentum smoothing (2-3) due to high volatility Increase divergence sensitivity (3-4) for early warnings Focus on strength changes above 20% threshold Use squeeze analysis for breakout opportunities
For Stock Indices: Standard settings appropriate for most indices Enable early weakness alerts for risk management Consider market hours for signal validity Use higher timeframes for better signal quality
Visual Components
Trend Analysis Table Trend Strength : Percentage with visual strength bar Trend Signal : Current position recommendation Risk Zone : STRONG/MEDIUM/WEAK classification Alignment : Trend line agreement analysis Distance : Price proximity to trend lines Momentum : Current momentum direction and strength
Trend Lines and Clouds Colored Clouds : Green for bullish trends, red for bearish trends Cloud Intensity : Opacity reflects trend strength Dynamic Colors : Automatically adjust based on trend direction
Momentum Squeeze Visualization Yellow Highlights : Above and below price during squeeze periods Squeeze Indication : Identifies low-volatility consolidation Breakout Preparation : Visual cue for potential explosive moves
Alert System
Trading Signal Alerts ADD LONG : Strong bullish trend confirmed ADD SHORT : Strong bearish trend confirmed REDUCE : Trend weakness detected, position reduction recommended HOLD : Maintain current positions, no change needed
Trend Analysis Alerts Strength Increase : Trend gaining momentum Strength Decrease : Trend losing momentum Early Weakness : Warning of potential trend deterioration Trend Direction Change : Major trend shift detected
Technical Alerts Bullish Divergence : Price falling but momentum rising Bearish Divergence : Price rising but momentum falling Momentum Squeeze Start : Volatility contraction beginning Momentum Squeeze End : Breakout from low volatility period Trend Line Cross : Price crossing above/below trend lines
Setting Up Alerts Enable desired alert types in indicator settings Create TradingView alerts using "Fundur - Trend Lines" as source Configure notification methods (email, SMS, app notifications) Test alerts with paper trading before live implementation Adjust alert frequency settings to avoid spam
Best Practices
Trend Strength Interpretation Above 75% : High confidence trades, full position sizes 50-75% : Moderate confidence, reduced positions Below 50% : Low confidence, minimal or no positions Rapid Changes : Pay attention to sudden strength shifts
Signal Management Don't Chase : Wait for clear signals rather than predicting Confirm with Price Action : Use chart patterns for additional confirmation Respect Risk Zones : Adjust position sizes based on trend classification Monitor Alignment : Strong alignment increases signal reliability
Multi-Timeframe Integration Higher Timeframe Bias : Use daily/weekly for overall trend direction Lower Timeframe Entries : Use hourly/15min for precise entry timing Confirmation Requirement : Ensure alignment between timeframes Conflict Resolution : Higher timeframe takes precedence
Common Mistakes to Avoid
Signal Misinterpretation Ignoring Trend Strength : Don't trade weak signals (below 60%) Fighting the Trend : Don't go against strong trend directions Overreliance on Single Component : Consider all analysis factors Impatience : Wait for clear STRONG trend classification
Risk Management Errors Fixed Position Sizes : Adjust sizes based on trend strength Ignoring REDUCE Signals : Take profits when indicator suggests No Stop Losses : Always use stops beyond trend lines Overleveraging Weak Signals : Use smaller positions in MEDIUM zones
Technical Analysis Errors Ignoring Divergences : Pay attention to momentum warnings Missing Squeeze Opportunities : Watch for breakout setups Poor Timeframe Selection : Match timeframe to trading style Alert Fatigue : Don't enable too many alerts simultaneously
Advanced Techniques
Divergence Trading Early Reversal Detection : Use divergences to anticipate trend changes Confirmation Required : Wait for trend strength decline confirmation Tight Risk Management : Use smaller positions for counter-trend trades Quick Exits : Take profits rapidly on divergence trades
Momentum Squeeze Strategies Breakout Preparation : Position before squeeze resolution Direction Bias : Use trend direction for breakout direction Volume Confirmation : Combine with volume analysis when possible False Breakout Protection : Use tight stops for failed breakouts
Multi-Component Analysis Alignment Priority : Perfect alignment (100%) provides highest confidence Distance Consideration : Closer to trend lines = higher probability Momentum Confirmation : Rising momentum supports trend direction Squeeze Integration : High squeeze factor increases breakout potential
Dynamic Position Management Scaling In : Add to positions as trend strength increases Scaling Out : Reduce positions as trend strength decreases Stop Trailing : Move stops with Fast Trend Line progression Profit Optimization : Use strength peaks for profit-taking timing
Conclusion
The Fundur - Trend Lines indicator represents a sophisticated approach to trend analysis, combining adaptive trend line technology with comprehensive strength measurement and intelligent signal generation. By quantifying trend strength through multiple analytical components, this indicator provides traders with objective, data-driven insights for making informed trading decisions.
The indicator's strength lies in its ability to adapt to changing market conditions while providing clear, actionable signals. The comprehensive trend strength analysis removes guesswork from trend trading, allowing traders to size positions appropriately and manage risk effectively based on quantified market conditions.
Success with the Trend Lines indicator comes from understanding that trend strength is dynamic and requires continuous monitoring. The 0-100% strength scale provides an objective framework for position management, while the multi-component analysis ensures robust signal generation across different market conditions.
Remember that this indicator works best when combined with proper risk management, position sizing, and market context awareness. Start with conservative settings and smaller position sizes while learning the indicator's behavior in different market environments. The comprehensive alert system helps maintain awareness of changing conditions, but successful trading still requires discipline and adherence to your trading plan.
For optimal results, practice with the indicator across different timeframes and market conditions, always prioritizing risk management over profit potential, and maintaining realistic expectations about market behavior and indicator performance.
Multi-Timeframe Resonance v2.0📌 Multi-Timeframe Resonance System — Identify trend, range, and turning points at a glance
✨ Core Advantages:
🔹 Multi-timeframe resonance analysis: Detects trend direction and range across timeframes. Helps identify M tops, W bottoms, consolidation turning points, and trend switches.
🔹 Clear phase visualization: Highlights trend momentum (green) and consolidation zones (red).
🔹 Universally compatible: Works on stocks/ETFs, futures/commodities, forex, gold, crypto — parameter tuning is the only requirement.
🎯 Target Users:
✅ Traders needing fast structure analysis
✅ Trend-followers, swing traders, or range-arbitrageurs
✅ Multi-timeframe analysts & volume researchers
✅ Quant teams seeking stable signal output
📈 Market Structure Evolution Sequence:
**Same-Bear → Small Box Bull → Medium Box Bull → Large Box Bull → Same-Bull → Small Box Bear → Medium Box Bear → Large Box Bear → Same-Bear**
- “Same-Bear”/“Same-Bull”: full agreement among timeframes，strongest trend stages.
- “Small/Medium/Large Box”: represent increasing-level consolidations indicating trend emergence or turn.
🔍 By identifying the current structure phase, traders can determine if:
- The market is in the **early trend stage** (Same-Bull/Same-Bear)
- Or in a **trend shift period** (Bear→Bull or Bull→Bear)
- Or still **oscillating** (structures switching)
⚠️ **Practical Note:**
Although structure usually follows the sequence above, in strong or volatile moves it may:
- **Skip steps** (e.g., Same-Bear → Large Box Bull)
- **Switch rapidly** within a few candles
Traders should use volume, candle patterns, and higher-timeframe trends to confirm valid structure changes or avoid false breakouts.
📌 Execution Logic:
This indicator applies **multi-timeframe resonance** to capture **trend pullbacks**:
- Identifies trend direction via higher timeframes
- Uses pullback in shorter timeframe to signal entry
- Executes trend-following trades at pullback points
- Protects with structured stop-loss based on higher timeframe structure
🔒 This is a protected script. For access details, please see the Author’s Instructions.
📌 多周期共振识别系统 — 趋势、震荡与拐点，一目了然
✨ 核心优势：
🔹 多周期共振分析：同时检测多个周期的趋势方向与震荡结构，辅助识别 M 顶 / W 底 / 震荡拐点 / 趋势转换等关键信号。
🔹 趋势与震荡清晰可视：自动高亮趋势推进（绿色）与震荡盘整（红色）区域，一眼看清市场节奏。
🔹 全品种通用：适配股票 / ETF、期货 / 商品、外汇 / 黄金、加密货币等市场，仅需轻微参数微调。
🎯 适用人群：
✅ 需要快速识别图表结构的交易者
✅ 趋势跟随者、波段捕捉者、震荡套利者
✅ 热衷于多周期分析与量能行为研究的交易者
✅ 追求稳定信号输出的量化策略团队
📈 市场结构演变路径：
同空 → 小箱多 → 中箱多 → 大箱多 → 同多 → 小箱空 → 中箱空 → 大箱空 → 同空
“同空” / “同多”：表示多周期趋势完全一致，代表趋势最强阶段
“小箱 / 中箱 / 大箱”：代表不同级别的震荡结构，结构逐步递进，表示趋势正在酝酿或转向
🔍 通过识别当前所处的结构阶段，交易者可以判断：
当前是否处于趋势初期阶段（如同空 / 同多）
是否处于趋势转换区间（如由空转多或由多转空）
或仍处于震荡反复区间（结构频繁切换）
⚠️ 实战提醒：
虽然市场结构通常遵循上述顺序演化，但在强趋势或剧烈波动行情下，可能出现以下情况：
跳跃演化（如从“同空”直接进入“大箱多”阶段）
快速切换（几根K线内连续跳过多个结构）
因此，交易者应结合量能、K线形态及更高周期趋势，判断结构变化是否“有效”或为“假突破”。
📌 执行逻辑：
本指标通过多周期趋势共振确认，捕捉趋势中的回踩机会：
利用高阶周期判断趋势方向
在低阶周期的回踩位置作为进场信号
顺势交易，捕捉主趋势中的低吸 / 高抛机会
止损位置依据上位周期结构确认，明确清晰
🔒 本脚本为受控授权版本，如需获取使用权限，请参阅“作者说明”。
Directional Market Efficiency [QuantAlgo]🟢 Overview
The Directional Market Efficiency indicator is an advanced trend analysis tool that measures how efficiently price moves in a given direction relative to the total price movement over a specified period. Unlike traditional momentum oscillators that only measure price change magnitude, this indicator combines efficiency measurement with directional bias to provide a comprehensive view of market behavior ranging from -1 (perfectly efficient downward movement) to +1 (perfectly efficient upward movement).
The indicator transforms the classic Efficiency Ratio concept by incorporating directional bias, creating a normalized oscillator that simultaneously reveals trend strength, direction, and market regime (trending vs. ranging). This dual-purpose functionality helps traders and investors identify high-probability trend continuation opportunities while filtering out choppy, inefficient price movements that often lead to false signals and whipsaws.
🟢 How It Works
The indicator employs a sophisticated two-step calculation process that first measures pure efficiency, then applies directional weighting to create the final signal. The efficiency calculation compares the absolute net price change over a lookback period to the sum of all individual bar-to-bar price movements during that same period. This ratio reveals how much of the total price movement contributed to actual progress in a specific direction.
The directional component applies the mathematical sign of the net price change (positive for upward movement, negative for downward movement) to the efficiency ratio, creating values between -1 and +1. The resulting Directional Efficiency is then smoothed using an Exponential Moving Average to reduce noise while maintaining responsiveness. Additionally, the system incorporates a configurable threshold level that distinguishes between trending markets (high efficiency) and ranging markets (low efficiency), enabling regime-based analysis and strategy adaptation.
🟢 How to Use
1. Signal Interpretation and Market Regime Analysis
Positive Territory (Above Zero): Indicates efficient upward price movement with bullish directional bias and favorable conditions for long positions
Negative Territory (Below Zero): Signals efficient downward price movement with bearish directional bias and favorable conditions for short positions
High Absolute Values (±0.4 to ±1.0): Represent highly efficient trending conditions with strong directional conviction and reduced noise
Low Absolute Values (±0.1 to ±0.3): Suggest ranging or consolidating markets with inefficient price movement and increased whipsaw risk
Zero Line Crosses: Mark critical directional shifts and provide primary entry/exit signals for trend-following strategies
2. Threshold-Based Market Regime Classification
Above Threshold (Trending Markets): When efficiency exceeds the threshold level, markets are classified as trending, favoring momentum strategies
Below Threshold (Ranging Markets): When efficiency falls below the threshold, markets are classified as ranging, favoring mean reversion approaches
3. Preset Configurations for Different Trading Styles
Default
Universally applicable configuration optimized for medium-term analysis across multiple timeframes and asset classes, providing balanced sensitivity and noise filtering.
Scalping
Highly responsive setup for ultra-short-term trades with increased sensitivity to quick efficiency changes. Best suited for 1-15 minute charts and rapid-fire trading approaches.
Swing Trading
Designed for multi-day position holding with enhanced noise filtering and focus on sustained efficiency trends. Optimal for 1-4 hour and daily timeframe analysis.
🟢 Pro Tips for Trading and Investing
→ Trend Continuation Filter: Enter long positions when Directional Efficiency crosses above zero in trending markets (above threshold) and short positions when crossing below zero, ensuring alignment with efficient price movement.
→ Range Trading Optimization: In ranging markets (below threshold), take profits on extreme readings and enter mean reversion trades when efficiency approaches zero from either direction.
→ Multi-Timeframe Confluence: Combine higher timeframe trend direction with lower timeframe efficiency signals for optimal entry timing.
→ Risk Management Enhancement: Reduce position sizes or avoid new entries when efficiency readings are weak (near zero), as these conditions indicate higher probability of choppy, unpredictable price movement.
→ Signal Strength Assessment: Prioritize trades with high absolute efficiency values (±0.4 or higher) as these represent the most reliable directional moves with reduced likelihood of immediate reversal.
→ Regime Transition Trading: Watch for efficiency threshold breaks combined with directional changes as these often mark significant trend initiation or termination points requiring strategic position adjustments.
→ Alert Integration: Utilize the built-in alert system for real time notifications of zero-line crosses, threshold breaks, and regime changes to maintain constant market awareness without continuous chart monitoring.
Global Risk Matrix [QuantAlgo]🟢 Overview
The Global Risk Matrix is a comprehensive macro risk assessment tool that aggregates multiple global financial indicators into a unified risk sentiment framework. It transforms diverse economic data streams (from currency strength and liquidity measures to volatility indices and commodity prices) into standardized Z-Score readings to identify market regime shifts across risk-on and risk-off conditions.
The indicator displays both a risk oscillator showing weighted average sentiment and a dynamic 2D matrix visualization that plots signal strength against momentum to reveal current market phase and historical evolution. This helps traders and investors understand broad market conditions, identify regime transitions, and align their strategies with prevailing macro risk environments across all asset classes.
🟢 How It Works
The indicator employs Z-Score normalization across various global macro components, each representing distinct aspects of market liquidity, sentiment, and economic health. Raw data from sources like DXY, S&P 500, Fed liquidity, global M2 money supply, VIX, and commodities undergoes statistical standardization. Several components are inverted (USDT.D, DXY, VIX, credit spreads, treasury bonds, gold) to align with risk-on interpretation, where positive values indicate bullish conditions.
This unique system applies configurable weights to each component based on selected asset class presets (Crypto Investor/Trader, Stock Trader, Commodity Trader, Forex Trader, Risk Parity, or Custom), creating a weighted average Z-Score. It then analyzes both signal strength and momentum direction to classify market conditions into four distinct phases: Risk-On (positive signal, rising momentum), Risk-Off (negative signal, falling momentum), Recovery (negative signal, rising momentum), and Weakening (positive signal, falling momentum). The 2D matrix visualization plots these dimensions with historical trail tracking to show regime evolution over time.
🟢 How to Use
1. Risk Oscillator Interpretation and Phase Analysis
Positive Territory (Above Zero) : Indicates risk-on conditions with capital flowing toward growth assets and higher risk tolerance
Negative Territory (Below Zero) : Signals risk-off sentiment with capital seeking safety and defensive positioning
Extreme Levels (±2.0) : Represent statistically significant deviations that often precede regime reversals or trend exhaustion
Zero Line Crosses : Mark critical transitions between risk regimes, providing early signals for portfolio rebalancing
Phase Color Coding : Green (Risk-On), Red (Risk-Off), Blue (Recovery), Yellow (Weakening) for immediate regime identification
2. Risk Matrix Visualization and Trail Analysis
Current Position Marker (⌾) : Shows real-time location in the risk/momentum space for immediate situational awareness
Historical Trail : Connected path showing recent market evolution and regime transition patterns
Quadrant Analysis : Risk-On (upper right), Risk-Off (lower left), Recovery (lower right), Weakening (upper left)
Trail Patterns : Clockwise rotation typically indicates healthy regime cycles, while erratic movement suggests uncertainty
3. Pro Tips for Trading and Investing
→ Portfolio Allocation Filter : Use Risk-On phases to increase exposure to growth assets, small caps, and emerging markets while reducing defensive positions during confirmed green phases
→ Entry Timing Enhancement : Combine Recovery phase signals with your technical analysis for optimal long entry points when macro headwinds are clearing but prices haven't fully recovered
→ Risk Management Overlay : Treat Weakening phase transitions as early warning systems to tighten stop losses, reduce position sizes, or hedge existing positions before full Risk-Off conditions develop
→ Sector Rotation Strategy : During Risk-On periods, favor cyclical sectors (technology, consumer discretionary, financials) while Risk-Off phases favor defensive sectors (utilities, consumer staples, healthcare)
→ Multi-Timeframe Confluence : Use daily matrix readings for strategic positioning while applying your regular technical analysis on lower timeframes for precise entry and exit execution
→ Divergence Detection : Watch for situations where your asset shows bullish technical patterns while the matrix shows Risk-Off conditions—these often provide the highest probability short opportunities and vice versa
Gann Swing PointsIndicator Logic
This is a GANN-style swing indicator that classifies bars based on their high/low structure relative to the previous bar.
I strongly encourage you to replay bars on Tradingview using this indicator to get a sense of how it creates pivot (or swing) points
Bar Classification:
Up-Bar (direction: 'up'): Higher High and Higher Low (HH/HL)
Down-Bar (direction: 'down'): Lower High and Lower Low (LH/LL)
Outside-Bar (generates 2 directions):
Green: 'down' then 'up'
Red: 'up' then 'down'
Inside-Bar: No direction generated (HL/LH)
Swing Line Logic
The swing line continues in the current direction until n opposite directions are detected.
n is the "n-direction" parameter (commonly set to 2, so 2 consecutive opposite direction is needed to turn the swing)
When n opposing directions occur, the swing turns, creating a pivot point
Inside bar is ignored, so e.g up-bar -> inside-bar -> up-bar generates "up", "up" direction
A top pivot is formed when the swing turns down
A bottom pivot is formed when it turns up
Note: This swing logic is inherently lagging — it only confirms tops/bottoms after the fact
This swing structure gives the system a clear and noise-resistant way to identify pivot points (swing-points)
