Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

Generate realizations of stochastic processes in python.

Monte Carlo option pricing algorithms for vanilla and exotic options

Quantitative finance and derivative pricing

Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods

Bayer, Friz, Gassiat, Martin, Stemper (2017). A regularity structure for finance.

Closed-form solutions and fast calibration & simulation for SABR-based models with mean-reverting stochastic volatility

A Python implementation of E. Robert Fernholz's Stochastic Portfolio Theory framework. This library provides tools for researchers, quantitative analysts, and portfolio managers to analyze, optimize, and simulate equity portfolios using the mathematical framework of Stochastic Portfolio Theory.

Code of numerical experiments in Master's thesis [TBD]

Code files containing research done around monte carlo stimulations, bayesian interference and stochastic volatility

An implementation of the Heston model, a stochastic volatility model for options pricing. We compute prices of European call and put options via Monte Carlo simulation, for a variety of strike prices and maturities. We also show that the Heston model captures volatility smiles/smirks/skews.