Backtesting & Analytics

Validate your strategies with historical data before risking real capital. Learn backtesting best practices, metrics interpretation, and walk-forward analysis.

12Articles

139 min readTotal Reading Time

Beginner / AdvancedDifficulty

Backtesting DCA bots: reading the safety-order analytics

Backtesting & AnalyticsIntermediate

8 min read

Backtesting DCA bots: reading the safety-order analytics

Safety orders rescue losing trades, which inflates win rate and hides the real risk. Freya's backtest breaks out how your DCA ladder actually performed, so you can see whether averaging down is earning its danger.

Aug 18, 2026

Does your backtest beat buy and hold? Using the HODL benchmark

Backtesting & AnalyticsBeginner

7 min read

Does your backtest beat buy and hold? Using the HODL benchmark

Freya overlays your bot's equity against simply buying and holding the coin. If a strategy cannot beat HODL, the effort and risk are not paying you. Here is how to read the benchmark.

Aug 18, 2026

How Freya models slippage and fees in backtests

Backtesting & AnalyticsIntermediate

7 min read

How Freya models slippage and fees in backtests

A backtest that ignores slippage and fees is a fantasy. Here is exactly how Freya's engine applies slippage, fill buffers, and maker-taker commissions so your numbers reflect what live trading actually costs.

Aug 18, 2026

Monte Carlo simulation for trading bots: reading probability of ruin

Backtesting & AnalyticsAdvanced

11 min read

Monte Carlo simulation for trading bots: reading probability of ruin

Your backtest is one ordering of trades out of thousands. Monte Carlo reshuffles it 1000 times to reveal probability of ruin, confidence intervals, and the drawdown a single equity curve hides.

Aug 18, 2026

R-multiple and expectancy: sizing winners against your risk

Backtesting & AnalyticsIntermediate

8 min read

R-multiple and expectancy: sizing winners against your risk

R-multiple measures every trade in units of what you risked, and expectancy turns that into one number: your edge per trade. Read both from a Freya backtest and know if your strategy actually makes money.

Aug 18, 2026

Value at Risk, CVaR, and the Omega ratio explained

Backtesting & AnalyticsAdvanced

7 min read

Value at Risk, CVaR, and the Omega ratio explained

Beyond max drawdown: how to read the tail-risk metrics in a Freya backtest. VaR is the loss you should expect on a bad day, CVaR is how bad the worst days get, and Omega weighs every gain against every loss.

Aug 18, 2026

Volatility regimes: why your bot wins in chop but loses in trends

Backtesting & AnalyticsIntermediate

7 min read

Volatility regimes: why your bot wins in chop but loses in trends

The same bot can be a money machine in a calm market and a disaster in a volatile one. Freya's backtest classifies your trades by market volatility using ATR, so you can see the conditions your strategy actually needs.

Aug 18, 2026