#overfitting

If a model has seen the data it's being tested on, the result is not a test.

Out-of-sample testing separates a real trading edge from one that only memorised the past. Here's how it works and why it's the minimum bar for validation.

5/13/2026

The model with three rules and one parameter beats the one with thirty more often than most quants will admit.

Complex trading models look impressive in backtests and disappoint in live markets. Here's why simpler models survive longer — and how darwintIQ surfaces it.

5/11/2026

And What They Actually Tell You

Backtests can be misleading. Learn why trading strategies often fail despite strong backtest results — and how to evaluate models more realistically.

3/18/2026

Built to Adapt, Not Memorize

Avoid the trap of overfitting. Learn how we use a sliding time window to keep strategies aligned with current market conditions — not just historical data.

2/17/2026