Backtests
A backtest is where a strategy meets real quotes. You define a multi-leg options position, step it minute-by-minute over one symbol's intraday history, and read the equity curve, margin curve, and per-trade ledger it produces. This section takes that run apart one piece at a time.
Where a backtest sits in the pipeline
A backtest is the terminal stage of the research pipeline: Signal and EDA, then Model, then Backtest. The stages before it are optional. You can validate a signal or train a model on it first, but you do not have to. Every workflow ends in a backtest, because that is the only stage where a strategy is priced against historical quotes.
One run covers one symbol. For the symbol universe and how far each symbol's history reaches, see data coverage; that page is the single source for coverage, so no other page repeats it.
The engine and the interface
The backtest engine is the source of truth: the three fill modes, the five sizing modes, REG-T margin with auto-decomposition, the deficit and halt layer, the results frames, and streaming, resume, and extend. The three fill modes are the Backtest.ai fill model (calibrated, and the one that matches paper and live trading), mid (the optimistic bound), and bid_ask (the pessimistic bound). A run fixes one of them.
The visual Backtest tab carries the position designer, the condition builders for entry, exit, and adjustment logic, the capital form, and the results charts. The Signal language is the path underneath it: legs, entry and exit signals, adjustment triggers, and contract selection all have a code form.
Every run carries a benchmark it is read against, the S&P 500 total return by default.
The articles in this section
- Backtests on Backtest.ai: what a run is, what goes in, and what comes out.
- The backtest lifecycle: the per-minute phase order, session edges, streaming, resume, and halts.
- Designing the position: legs, strategy slugs, signed size, and lots.
- Selecting contracts: request-time contract selection, the selectors, and thresholds.
- Entry, exit, and timing: the signals that open and close a position and when they fire.
- Adjustments and triggers: the four adjustment actions and the level-based triggers that call them.
- Position sizing and capital: the five sizing modes, the premium-vs-margin basis, and starting capital.
- Margin and auto-decomposition: REG-T strategy-based margin, set-packing decomposition, and the TIMS portfolio-margin model.
- Reading backtest results: the equity curve, margin curve, per-trade ledger, and summary stats.
- Backtest assumptions and realism: the defaults behind every number, and what the engine does and does not model.
Related pages
- Signals inside a backtest documents the
book(),position(),leg(), andoption.contract()accessors that entry, exit, adjustment, and selection logic read. - The AI research assistant answers questions about the Signal language while you write a backtest slot.
- The metrics glossary and platform status in Reference give the per-metric lookup and the full status ledger.
- Portfolios, accounts, and live trading covers combining backtests into a portfolio and running it forward on paper or live.