OptiNod Academy
Backtest Validation
Browse all 8 parts in the Backtest Validation series and start from the section you need.
Backtests vs. Live Trading: Five Reasons the Equity Curve Diverges
Backtest returns often fail to translate into expected live returns because the test assumes fills at the candle close. This article breaks down the delay between signal and execution into five practical sources of cost.
Slippage, Fees, and Liquidity: The Trading Costs Backtests Hide
Subtracting fees alone does not turn a backtest into a realistic live-trading estimate. Slippage and liquidity often take a much larger bite out of performance.
Look-Ahead Bias and Repainting: Why Perfect Chart Signals Didn’t Exist in Real Time
Why signals that look perfect on a chart often did not exist in real time, explained through `request.security` and bar-confirmation mechanics.
Overfitting: Only Settings With a Plateau Around the Peak Survive Live Trading
The parameter set with the best backtest return is often just a curve fitted to historical noise. In live trading, only plateau-shaped performance curves, where nearby settings also perform well, tend to hold up.
Walk-Forward Analysis: How to Validate the Optimization Process Itself
A score optimized over the full dataset is a score fitted with hindsight. Walk-forward analysis tests the process itself by selecting settings in-sample and evaluating them only on the next out-of-sample period.
The Three Robustness Scores — How to Decide Which of Two Equal-Return Settings to Trust
Between two parameter settings with the same return, three stability scores (neighborhood stability, Monte Carlo, top-N consistency) point to the one that survives live trading. Explained against OptiNod's actual implementation.
Profit Factor: The Sample Size and Distribution Hidden Inside One Number
A high PF can break down in live trading if it comes from too few trades or depends on one large winner. Look at the distribution and sample size behind the number.
Sharpe and Sortino: Performance Divided by Volatility, and the Problem With Penalizing Upside
Comparing strategies by return alone ignores how differently they may behave on the way to the same result. This article explains the limits of the Sharpe ratio and why the Sortino ratio is often closer to real trading conditions.