Trading API Backtest

Runs one specific, reproducible historical backtest from a date range and a strategy concept, making every assumption visible and producing auditable artifacts.

For research and education only. This is a hypothetical historical simulation, not investment advice; backtested results do not guarantee future performance, and you execute any real trades yourself through your own broker.

When to use

You want a single, well-documented historical backtest rather than a broad parameter sweep.
You need reproducible artifacts (config, per-trade rows, equity curve, metrics) you can re-run.
You want assumptions (fills, fees, slippage, calendar) stated explicitly before results.

What to provide

Start date, end date, and the strategy concept or explicit rules.
Asset class, symbols or universe, and the timeframe (e.g. daily, hourly).
Initial cash, position sizing, and a benchmark to compare against.
Historical price data, or a market-data source you will pull it from yourself.

How to work through it

Gather the required inputs, then infer and confirm the rest: sizing, execution assumptions, and benchmark.
Translate the idea into precise rules — data field, trigger, bounds, indicator variants and parameters, warmup, sizing, order type, and fill model — and confirm before running.
Resolve run considerations: fill timing, dividends and splits, fees, slippage, market hours, calendar handling, and look-ahead/survivorship/overfitting risks.
Keep signal timing separate from fill timing (e.g. signal on a bar's close, fill on the next open) and document the chosen fill model.
Simulate over the range, then record per-trade fills, an equity curve, and a benchmark equity curve.
Compute metrics: total and annualized return, max drawdown, Sharpe, win rate, profit factor, and fees paid; note if no trades occurred and why.
Save reproducible artifacts (assumptions notes, strategy spec, config, per-trade rows, equity, metrics) so the run can be repeated.

Presenting results

Present every result as one or more clear Markdown tables — one per section, each with a short heading (e.g. trades, per-parameter results, P&L, metrics).
Keep prose minimal; put the substance in the tables.
Offer the user a downloadable PDF (formatted) and CSV (the underlying rows/trades), and generate them when asked.
Never invent figures or fills. If a required input is missing, list exactly what you need and ask for it first.