backtesting
Paper Trading vs Backtesting: What Each One Can and Cannot Prove
Both look like validation. Neither is sufficient alone. Here's exactly what each test can and cannot prove — and why confusing them costs traders real money.
risk management
risk management
Drawdown Recovery Percentage: The Math That Makes Big Losses Almost Impossible to Escape
A 50% drawdown doesn't need a 50% gain to recover — it needs 100%. The math is asymmetric, it compounds against you, and most traders never look at it clearly until it's too late.
metrics
Sharpe Ratio vs Sortino Ratio vs Calmar Ratio: Which Risk-Adjusted Metric Should You Actually Optimize For?
Three metrics, three different definitions of risk — and optimizing for the wrong one can make a losing strategy look brilliant. Here's which one actually matters for your strategy.
Backtest Validity
Slippage Is Quietly Killing Your Backtest's Edge: How to Model It Honestly
Your backtest looks great — until you actually trade it. Slippage is the silent tax that turns winning strategies into losers, and most backtests ignore it almost entirely.
Monte Carlo
Monte Carlo Simulation for Trading Strategies: What It Can and Cannot Tell You
Your backtest shows one equity curve. Reality will hand you thousands of possible ones. Monte Carlo simulation maps that entire landscape — but most traders misread the map.
Win Rate
A 90% Win Rate That Loses Money: The Win-Rate Trap
Win rate is the most cited and most misleading number in trading. Here's how a strategy that wins 90% of the time can still bleed you dry — and what to track instead.
prop firms
Will Your Trading Strategy Pass an FTMO Challenge? The Statistics Prop Firms Don't Tell You
A high Sharpe ratio and a smooth equity curve aren't enough to pass an FTMO challenge. Here's how to map your backtest statistics to prop-firm rules before you risk the fee.