Quantitative Finance tools

Market Data & Derivatives Pricing Tutorial based on Jupyter notebooks

My answers to exercises in Stochastic Calculus for Finance by Steven E. Shreve.

Pricing weather futures using an ARIMA model and 8 years' worth of scraped weather data.

real-time predictive options model - mathematical modeling

Repositório com o código-fonte do Derivativos e Risco de Mercado

Part of the Neutryx Lab ecosystem for differentiable finance.

Financial Engineering in IRFX in C++

Note on financial mathematics

An implementation of the Longstaff-Schwartz algorithm, which we use to price a convertible bond.

A high performance pricing and calibration engine for Rough Volatility (rBergomi) models using a hybrid Python/C++ architecture with PyBind11.

Fullstack Bates (1996) Option Pricing Engine: A high-performance engine utilising Inverse Fourier Transforms for real-time calibration and Euler-Maruyama Monte Carlo for path projections. Optimised for 2026-2027 market volatility regimes and jump-diffusion dynamics.

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.

A hybrid classical-quantum proof-of-concept for pricing European Call Options using Black-Scholes, Monte Carlo, and Iterative Quantum Amplitude Estimation (IAE) via Qiskit. Demonstrates the theoretical quadratic speedup of quantum computing "O(√N) vs O(N)" - over classical Monte Carlo simulations.

Theoretical foundation of derivative pricing, covering financial markets, bonds, options and models like Black-Scholes.

Coursework, projects, and datasets from the MSc in Financial Engineering (MScFE) program at WorldQuant University.

A high-performance Monte Carlo pricer for Exotic Derivatives (Asian & Barrier Options) featuring a hybrid architecture (C++17, Python/Numba, and Pybind11).