Weighted Gaussian remainder bounds and validated transforms for arithmetic Asian valuation, with complete Heston projected Euler error accounting.
A Python library for options pricing and Greeks computation.
📈 Apply financial engineering techniques to option pricing using Monte Carlo simulations and the Black-Scholes model with clear, documented Python code.
Deep-learning option pricing and hedging: a neural surrogate for Asian options benchmarked against Monte Carlo, a rough Bergomi model for 0DTE, a CVaR deep hedging policy, live calibration, and an interactive dashboard.
Monte Carlo pricer and delta-hedging engine for basket, Asian and performance options on correlated shares (C++17 / PNL). Conditional re-pricing at every rebalancing date, finite-difference deltas on common random numbers, self-financing replication verified against Black-Scholes along a full hedged path and an independent replay to 1e-13.
Option Pricing with Monte Carlo Simulation — A Python library implementing Black–Scholes analytic pricing, Monte Carlo simulations (with variance reduction, quasi-MC), and advanced derivatives such as Asian, Barrier, and American options. Includes performance acceleration using Numba and comprehensive documentation with visualizations.
A quantitative finance project implementing stochastic volatility models (Heston, Bates) and interest rate diffusion models (CIR) to price Over-The-Counter (OTC) derivatives.
Monte Carlo pricer for arithmetic Asian options, with full path simulation and a three-panel convergence study.
Path-dependent option pricing engine in C++ using QuantLib. Implements Monte Carlo simulations for Discrete Arithmetic Average Strike Asian options, Lookback options, and European derivatives under a Constant Black-Scholes process with CI/CD integration.
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