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#backtesting
10 posts tagged backtesting.
10 posts
Regime-Aware Strategy Selection: Why One Rule Set Is Not Enough
Markets cycle through trends, ranges, and shocks. Learn how regime detection drives which strategy runs, and why a mixture of experts beats a single static rule.
How to Backtest a Trading Strategy (The Right Way)
Learn how to properly backtest trading strategies, avoid common pitfalls like overfitting, and use statistical credibility testing to validate your results.
Why Most Backtests Lie (And How Our 8-Layer Credibility Pipeline Fixes It)
How Alphactor's 8-layer credibility pipeline catches overfitting, data snooping, and curve-fitted strategies before they cost you money.
Survivorship Bias: The Invisible Flaw in Your Stock Screener
Survivorship bias silently inflates backtest returns and warps stock screener results. Here is how it works and what to do about it.
Walk-Forward Testing: The Only Backtest That Matters
Why walk-forward testing is the gold standard for strategy validation, how it works mechanically, and what the efficiency ratio tells you about real versus overfit edges.
The 7 Optimization Traps That Kill Backtested Strategies
Seven specific ways traders overfit their backtests, with examples, detection methods, and the statistical tools that separate real edges from noise.
Combining Multiple Signals Into One Strategy (Without Overfitting)
How to merge momentum, value, and quality signals into a single composite score that survives walk-forward testing, with practical rules to avoid the overfitting trap.
A Simple Mean Reversion Strategy That Survived Walk-Forward Testing
How a 2-period RSI mean reversion strategy on the S&P 500 held up across 15 years of walk-forward validation, and what the numbers actually look like.
Breakout Strategies: What 10 Years of Backtests Actually Show
A systematic look at breakout trading across 500 stocks over 10 years, with real numbers on win rates, expectancy, and the filters that separate signal from noise.
Your Trading Signals Have a Noise Problem (Here's How to Fix It)
Why most trading signals fire too often to be useful, and how to filter with multiple timeframes, volume confirmation, and market regime awareness.