Advanced Quantitative
Advanced quantitative and statistical strategies including mean reversion, pairs trading, regime detection, and multi-factor models.
6 Strategy Templates
Advanced Quantitative strategies apply statistical methods. Standard deviation, correlation, regression, Monte Carlo simulation. to trading, producing setups with explicit mathematical definitions rather than visual pattern recognition. These strategies require more data infrastructure than typical chart-based methodologies but in exchange offer rigorously testable rules with quantifiable edge expectations.
The strategies in this category span the most-cited quantitative approaches. Z-Score Mean Reversion (both Hurst-filtered and ADX-filtered variants) trades extreme deviations from a moving-average mean, requiring statistical confirmation that the underlying regime is actually mean-reverting rather than trending. Statistical Pairs Trade identifies cointegrated instrument pairs and trades their spread when it deviates beyond historical norms. Multi-Timeframe Confluence stacks structural signals across three timeframes, requiring alignment before entry. Mathematically filtering out low-probability setups. Connors RSI(2) ETF Reversion trades the canonical published quant strategy: buy oversold ETFs on 2-period RSI extremes, exit when mean-reverting. Turtle System Rule 1 implements the original Donchian-channel breakout system with full N-based position sizing and pyramiding rules. Across all these strategies, the core discipline is honoring the statistics. setups that backtest poorly don't become good because the current example looks compelling. Use Monte Carlo simulation on at least 100 backtested trades to understand the variance of outcomes before committing real capital.
When price deviates 2+ standard deviations from its mean, reversion is statistically likely. Use Z-Score to measure deviation and time entries.
Trade the spread between two correlated instruments. When correlation breaks, the spread is expected to revert, go long the underperformer, short the outperformer.
Align signals across three timeframes for maximum conviction. Higher TF sets bias, mid TF confirms structure, lower TF times the entry.
Calculate the Z-score of price relative to its 50-period moving average. Extreme Z-scores (±2 or ±2.5) indicate statistically significant deviation, fade these extremes expecting mean reversion to the...
In a long-term uptrend (above 200-day SMA), buy when 2-period RSI drops below 10 (severe short-term oversold) and exit when price closes above the 5-day SMA. Designed specifically for broad market ETF...
The original Turtle trading system rule: buy on breakouts above the 20-day high, sell below the 20-day low. Position size based on ATR (1 unit = 1% account risk per N, where N = 20-day ATR). Rigorous ...