
Backtesting a Crypto Trading Bot: What Results Can and Cannot Tell You
Learn how to backtest a crypto trading bot while accounting for data leakage, overfitting, fees, slippage and the limits of historical results.
Trading, automation, digital-market and risk-management explainers.

Learn how to backtest a crypto trading bot while accounting for data leakage, overfitting, fees, slippage and the limits of historical results.

Learn what trading drawdown is, how maximum drawdown is calculated, and why recovery requires a larger percentage gain than the preceding loss.

Learn what risk per trade means in crypto, how position size relates to stop distance, and why a percentage rule cannot guarantee a safe outcome.

Use this 10-point checklist to compare automated trading platforms by custody, API permissions, fees, risk controls, monitoring and evidence.

Compare manual and automated trading across attention, speed, consistency, context, oversight and failure risk to understand where each approach fits.

Compare AI trading bots and rule-based bots by decision logic, data needs, explainability, adaptation, testing and operational risk controls.

Follow how automated crypto trading moves from market data and signals through eligibility, risk checks, order submission, fills and reconciliation.