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Before running a backtest, configure the simulation parameters to match your intended trading conditions. Accurate configuration leads to results that better reflect what you’d actually experience in a real account.

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Opening backtest configuration

After defining your strategy in chat, click Run Backtest. The configuration panel opens before the simulation begins.

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Configuration parameters

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Starting capital

The simulated portfolio balance at the start of the backtest. Default is $10,000. Set this to the amount you intend to deploy in a real or paper account. Position sizing rules in your strategy (e.g. “use 10% of portfolio per trade”) are calculated as a percentage of this value.

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Date range

The historical period the backtest covers. Recommended ranges by strategy type:
Include at least one full market cycle (a bull and bear phase) to see how your strategy behaves in different conditions.

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Commission

A flat dollar amount charged per trade, applied at both entry and exit. Default is $0. Most retail brokers (Robinhood, Schwab, Fidelity) charge $0 commissions on US equity trades. Set to $0 unless your broker charges commissions.

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Slippage

An additional percentage cost applied per trade to simulate the difference between the expected price and the actual fill price. Default is 0.01% per trade. For liquid large-cap stocks and ETFs, 0.01%–0.05% is realistic. Increase for small-cap stocks or low-volume assets.

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Execution frequency

How often the bot evaluates signals during backtesting. This must match the bar frequency of your strategy’s indicators.
High-frequency backtests (1 min, 5 min) over long date ranges can take longer to run and are limited to shorter historical windows. See the Backtesting concepts page for max window limits by frequency.

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Running the backtest

Click Run Backtest after configuring parameters. Mobius fetches historical data, calculates all indicators, and runs the AI decision loop bar by bar. Results appear in the artifact panel within a few seconds for daily strategies, or up to 30 seconds for high-frequency intraday backtests.

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Interpreting results

After the backtest completes, the results panel shows:
  • Equity curve — portfolio value over time
  • Total return % — overall gain or loss
  • Annualized return — return normalized to one year
  • Sharpe ratio — risk-adjusted return (> 1.0 is generally good)
  • Max drawdown — largest peak-to-trough decline
  • Win rate — percentage of trades that closed in profit
  • Trade count — total completed buy/sell pairs
  • Trade log — every trade with entry date, exit date, price, and P&L

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Running multiple backtests

You can run as many backtests as your plan allows per day. Each run uses one backtest credit. Refine your strategy in chat or the visual editor between runs to compare results. Version history is preserved so you can see how performance changed across iterations.