Quantura – Quantitative Algorithm

Introduction
“Quantura – Quantitative Algorithm” is an algorithmic trading strategy written in Pine Script that combines technical indicators with fundamental market assessments. It was primarily developed for volatile crypto markets but can also be applied to Forex, equities, or indices with proper adjustments. The strategy works across multiple timeframes and generates automated buy and sell signals based on a wide range of market and sentiment data. Its goal is to produce robust trading signals through confluence across several analytical layers, without making unrealistic profit promises.

Originality & Value
Quantura stands out due to its unique combination of features: In addition to classic indicators, it incorporates customizable fundamental analysis and sentiment inputs that allow flexible adaptation to current market conditions. Unlike simpler strategies, the user can manually set the fundamental bias (bullish/bearish/neutral) and market sentiment, making the strategy more cautious or aggressive as needed.

Furthermore, Quantura combines multiple timeframes: a higher timeframe (HTF, e.g., daily) and a lower timeframe (LTF, e.g., intraday). This approach allows long-term trends to be aligned with short-term entry signals.

Key components include:

• [] Market Structure Analysis: Identifies higher highs and lower lows on the higher timeframe.
  [] Order Block Filter: Detects significant price levels (order blocks) with strong volume to filter out weak entries.
  [] Exponential Moving Averages (EMA): Adjustable HTF EMA filter for trend confirmation.
  [] Adaptive Premium/Discount Zones: Defines overvaluation (premium) and undervaluation (discount) areas based on HTF highs and lows.
  [] Candlestick Pattern Recognition: Optional detection of specific candle formations (Hammer, Shooting Star, Engulfing, Marubozu, etc.).
  [] Correlation Filter (optional): Cross-checks correlations between the main asset and a reference asset (e.g., SPY).
  

Functionality & Indicators
The strategy uses an RSI-based entry trigger as its primary signal: When the RSI (default: 10 periods) exits overbought/oversold zones, a potential long or short signal is created. However, an entry is only executed if all selected confluence filters align.

Quantura also integrates fundamental bias: The user-defined inputs for “Market Sentiment” and “Fundamental Analysis” add a bullish, bearish, or neutral weighting to the decision logic. An optional correlation filter compares price changes of the target asset with a reference symbol, confirming or rejecting trades based on correlation strength.

When all conditions are met, Quantura opens a position. Pyramiding is disabled (only one active trade at a time). Exits are managed primarily with ATR-based targets and stops, calculated dynamically from market volatility. Optional breakeven stops and session-end exits provide additional trade control.

Parameters & Customization
Quantura provides extensive input parameters for flexible configuration:

• [] Time & Session Settings: HTF and LTF selection, trade direction (Long/Short/Both), trading session hours, weekday filters.
  [] Filters: Enable or disable filters such as HTF structure, order blocks (with customizable volume multiplier), premium/discount zones, high-volume zones, HTF EMA filter, candlestick pattern filter, and ATR volatility filter.
  [] RSI Entry Settings: RSI length and thresholds for overbought/oversold.
  [] Fundamental Settings: Current market sentiment and fundamental analysis inputs (bullish/bearish/neutral).
  [] Correlation Settings: Reference asset and correlation strength (High/Low).
  [] Exit Rules: ATR-based TP/SL multipliers, optional breakeven logic, session-end exits, and opposite-signal exits.
  
• Visual Settings: Enable or disable buy/sell signals, trend candles, custom colors, and the built-in dashboard.
  

Backtesting & Performance
Backtests on BTCUSD (2 years) showed:

• [] 72 trades
  [] 46% win rate
  [] Profit factor: 1.6
  [] Maximum drawdown: 10%
  

These results demonstrate moderate profitability with controlled risk. However, with only 72 trades in two years, statistical reliability is limited. TradingView generally recommends over 100 trades for meaningful results.

Risk Management
Quantura includes several built-in risk management mechanisms:

• [] ATR-based TP/SL: Dynamic profit targets and stop-losses based on ATR multiples.
  [] Position sizing: Default is 100% equity (for backtests). In practice, smaller allocations (5–10%) are strongly recommended.
  [] Breakeven stop (optional): Moves SL to entry price after a predefined profit threshold.
  [] Opposite-signal exit: Closes and reverses trades when a contrary signal appears.
  
• Session-end exit: Automatically closes intraday positions at the end of a trading session.
  

Limitations & Market Conditions
Quantura is most effective in volatile, liquid markets like crypto. In low-volatility sideways markets, signals may be less reliable. Unexpected news events can also invalidate signals, regardless of technical/fundamental bias.

Backtest results are based on BTCUSD. For other markets (Forex, equities, indices), parameter adjustments are required. Users should conduct their own extended backtests before live usage.

Usage Guide

1. [] Add to chart: Apply “Quantura – Quantitative Algorithm” in strategy mode.
   [] Set timeframes: Choose HTF (e.g., 1D) and LTF (e.g., 5m). Define trade direction and sessions.
   [] Configure filters: Enable/disable confluence filters as needed.
   [] Set fundamentals: Enter current sentiment and fundamental bias.
   [] Define exits: Adjust ATR multipliers, breakeven rules, and session-end exits.
   [] Review signals: Check buy/sell markers, candle coloring, and the dashboard. Analyze in Strategy Tester.
   

Author & Access
The strategy was developed 100% by Quantura and is published as an Invite-Only script. Access is granted upon request. Instructions are available in the Author’s Instructions field (e.g., via the Quantura website).

Important: This description complies with TradingView’s official publishing rules. It avoids pricing or solicitation and provides a realistic, honest explanation of the strategy’s features and limitations.