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.

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

Note on financial mathematics

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

Financial Engineering in IRFX in C++

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

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.

Numerical methods for derivative pricing: analytical, Monte Carlo, PDE, and Heston stochastic volatility, cross-validated and tested in parallel Python/C++.

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

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