Stress Testing — Monte Carlo

One backtest is one path — the sequence of days that happened to occur. The Monte Carlo simulation, the second tab of the Portfolio workspace, resamples your portfolio's historical daily P/L with replacement into thousands of alternative paths, so you can see the distribution: the median outcome, the tails, and above all the drawdowns you'd need to sit through.

Why this matters for 0DTE portfolios

Credit-spread portfolios have a characteristic shape: many small winning days, occasional sharp losing days. Whether a given sequence of those days feels survivable depends heavily on their order — the same set of trading days rearranged can produce a gentle year or a brutal quarter. That's sequence risk, and it's invisible in a single backtest. Resampling makes it visible: across thousands of orderings you see the realistic range of drawdowns, not just the one that history happened to produce.

What the simulation does, in one paragraph

Each simulation draws N random days from your portfolio's daily-P/L pool (N = horizon ÷ 12 × 252 trading days) and accumulates them onto your initial capital — one equity path. Across all paths, the app takes the 5th/50th/95th percentiles at each step for the band chart, every path's terminal value for the return scenarios, and every path's max drawdown for the drawdown scenarios. Optionally, it injects worst-case events into every path — either your portfolio's real worst day, or a theoretical simultaneous max loss.

The pages in this section

• Running a simulation — every setting: simulations, horizon, initial capital, and the stress injection with its two worst-case modes.
• Reading the results — the key metrics, the return and drawdown scenario cards, the equity-path band chart and the distributions.
• Limitations & caveats — what resampling can and cannot tell you. Read this one; it's short and it's the honest part.