Strategy Validation Methodology
Understanding how we validate and backtest trading strategies with rigorous academic standards and transparent reporting.
Backtesting Framework
- Historical Period: 2010-2024 (14 years of data)
- Universe: S&P 500 constituents with high liquidity
- Data Quality: OHLC (Open, High, Low, Close) daily bars
- Commissions: 0.05%-0.15% (realistic execution costs)
- Slippage: Conservative estimates included
Risk Reporting
- Maximum Drawdown: Peak-to-trough loss percentage
- Win Rate: % of profitable trades
- Sharpe Ratio: Risk-adjusted return metric
- Avg Return: Expected annual return (compound)
- Full Transparency: All parameters disclosed
Understanding Performance Metrics
Win Rate (%)
The percentage of trades that result in a profit. A 60% win rate means 6 out of 10 trades are profitable.
Higher win rates reduce psychological stress but don't guarantee profitability if winning trades are smaller than losing trades.
Average Return (%)
The annualized percentage return generated by the strategy over the backtest period, including all gains and losses.
Returns are gross of slippage and commissions already factored into performance. Past performance ≠ future results.
Sharpe Ratio
Measures risk-adjusted returns. Calculated as (return - risk-free rate) / volatility. Higher is better.
A Sharpe ratio above 1.0 is good, above 2.0 is excellent. Compares risk taken per unit of return.
Maximum Drawdown (%)
The largest peak-to-trough decline during the backtest period. Shows the worst-case scenario you would have experienced.
A 20% drawdown means if you invested $10,000, it could have dropped to $8,000 at the worst point.
Academic Foundation
All strategies are based on published academic research and are validated using peer-reviewed methodologies:
- Strategies cited in research papers from top universities (Stanford, MIT, Yale)
- Backtesting follows rigorous standards from Pring, Kaufman, and CFA Institute
- Each strategy includes reference to original research paper
- Forward-testing results available for recent periods (compare to historical backtests)
Important Risk Disclosures
- •Past performance does not guarantee future results. Market conditions, correlations, and volatility change over time.
- •Backtesting can be subject to bias. Overfitting, data snooping, and survivorship bias can all inflate reported returns.
- •Real-world execution is harder. Slippage, market impact, and psychological factors are greater than in simulation.
- •All strategies can lose money. Use proper position sizing, risk management, and diversification.
- •Not financial advice. Consult a financial advisor before trading with real money.