Case study 02

Option Pricing Engine

Live Monte Carlo pricing with honest standard errors.

A browser-native TypeScript engine for vanilla, path-dependent, American, Heston, and two-asset contracts, with sampling error reported beside each estimate.

Evidence at a glance

Runtime
Worker-backed simulation with a main-thread fallback.
Reporting
Standard error and a 95% confidence interval accompany each estimate.
Scope
Vanilla, path-dependent, American, Heston, basket, and best-of contracts.

A price estimate needs an error bar.

The browser engine keeps the stochastic model, payoff, sampling method, and uncertainty report visible together. A number is not presented as exact when it came from simulation.

Numerical scope

The TypeScript engine covers vanilla and path-dependent contracts, Longstaff-Schwartz American puts, Heston QE, and correlated two-asset basket and best-of calls.

Runtime boundary

Pricing runs in a web worker when available. If worker startup or execution fails, the same engine has a main-thread fallback and reports an inline error if both paths fail.

Price a contract

Select a payoff and model, set the market inputs, then run a batch. The path canvas, estimate, standard error, confidence interval, and ledger update from the real engine result.

Live simulation · S 100 · K 100 · σ 20.0% · r 5.0% · q 0.00% · T 1yChecking worker

Run a batch to draw sample paths.

Latest estimateRun a batch to estimate price and sampling error
BatchPathsEstimateStd. error95% interval
No batches yet. Each run prices 12,000 paths with 52 steps in a worker.

No closed form for this contract here, so the engine reports sampling error instead.