OptionsSimulator for Research & Education

A forward-looking options market simulator built on the same stochastic models used in quantitative finance — for teaching derivatives, running bias-free trading experiments, and generating synthetic market data.

OptionsSimulator generates complete options markets that have never existed. Instead of replaying historical price series — which students and subjects can unconsciously read backwards — it simulates forward paths from well-specified stochastic processes, prices the full option chain against them in real time, and lets a trader act without knowing what happens next.

The result is a controlled, reproducible environment for studying decision-making under genuine uncertainty: no survivorship bias, no hindsight bias, no leaked ending. Every scenario is mathematically real and, crucially, unknown to the participant.

The underlying mathematics

Price paths are generated from seven peer-reviewed stochastic models spanning the standard curriculum of computational and mathematical finance:

  • Geometric Brownian Motion — the Black–Scholes framework (Black & Scholes, 1973).
  • Merton Jump-Diffusion — Poisson jumps for crashes and news shocks (Merton, 1976).
  • Heston — stochastic volatility with mean reversion (Heston, 1993).
  • Bates — Heston dynamics plus jumps (Bates, 1996).
  • SABR — stochastic-alpha-beta-rho volatility-smile modelling (Hagan et al., 2002).
  • GARCH — volatility clustering (Bollerslev, 1986).
  • Fractional Brownian Motion — long-memory / persistent dynamics via the Hurst exponent.

Options are priced with a Cox–Ross–Rubinstein binomial tree (1979), the Bjerksund–Stensland (2002) analytical American approximation, and Black–Scholes for European contracts. A vectorised Monte Carlo engine adds Longstaff–Schwartz American pricing, 95% confidence intervals, full Greeks (Delta, Gamma, Theta, Vega, Rho), and portfolio risk analytics (VaR / CVaR, probability of profit, P/L distributions).

These seven are the peer-reviewed stochastic processes at the core of the tool. The simulator also ships an eighth, experimental model — an AI-driven pattern generator that can be run in a deliberately chaotic market regime — offered for open-ended exploration rather than formal study; it is the eighth model referenced on the homepage.

Use in the classroom

Instructors use OptionsSimulator to make derivatives tangible without the cost and delay of live markets:

  • Show how a Call, Put, or spread behaves as it approaches expiration — in minutes, not weeks.
  • Let students feel the Greeks change across trending, ranging, calm, and volatile regimes.
  • Stress-test income strategies (Iron Condor, Covered Call, Cash-Secured Put) through a volatility spike.
  • Assign lab exercises on a shared setup: point a cohort at the same model, scenario, and ticker so everyone trades under matched conditions.

Use in research

For empirical and behavioural work, the simulator is a source of controlled market data and a platform for experiments:

  • Synthetic data generation — produce OHLC series and option chains with known, tunable dynamics for model-testing where real data is scarce, noisy, or confounded.
  • Behavioural finance — study cognitive biases (hindsight, disposition effect, overconfidence) in a setting where the future is provably unknown to the subject.
  • Strategy evaluation — compare strategies under matched, repeatable market conditions instead of a single realised history.
  • Data export — portfolio, trade history, and analysis reports can be exported to Excel (and CSV) for offline analysis in Python, R, or a spreadsheet.

Why forward simulation, not backtesting

Backtesting reports what a strategy would have done on a past series — but the past is readable, and both students and research subjects read it backwards even when they believe they do not. Strategies that look profitable in-sample fail live because the test already knew the ending.

Forward simulation removes that confound. Each path is drawn from a specified process and revealed one step at a time, so participants face the same information structure a live account imposes. That property is what makes the tool useful for pedagogy and for clean experimental design alike.

The Academic Licence — Fall 2026

For one course, one semester, on us: full Premium access for your entire class — regularly $30 per student per month — sponsored by Thetix Technologies as part of our academic programme.

  • One redemption code per course. Students self-register in the browser; no roster to send, nothing to install, nothing to invoice.
  • Seat-capped (up to 60 students) and semester-bound — the redemption code expires at term's end, and we remove the class's access at the same time.
  • The same market setup — model, scenario, and parameters — for shared lab exercises, and a fresh, unique market for every student on assessments that cannot be googled, shared, or replayed.
  • In return we ask only for 20 minutes of feedback at semester's end and permission to list your course among academic users.

Apply with five fields — name, institution, course, semester, and expected number of students. Approval is typically within 48 hours, after which we email your class code.

Apply for an Academic Licence →

Open the simulator →  ·  Read our research & education articles →

Who builds it

OptionsSimulator is built by Thetix Technologies Ltd (London, UK). It is an educational simulator; nothing on the platform is investment advice, and simulated performance does not represent real trading results.