{aligned} $$ we can write down its analytical solution with the help of Ito formula, as $$ \mathbf{X}(t)=\mathbf{X}_0\exp\left((\mu-\frac{1}{2}\sigma^2)t+\sigma\mathbf{W}(t)\right) $$ But here, we want to study the numerical solution of geometric Brownian motion, and ...
Option pricing based on Black-Scholes processes, Monte-Carlo simulations with Geometric Brownian Motion, historical volatility, implied volatility, Greeks hedging - boyac/pyOptionPricing
Mark brownian motion test as xfail Feb 3, 2025 .codecov.yml Bump Python 3.13 Feb 4, 2025 .deepsource.toml Rm dependecy files Dec 18, 2021 .gitattributes Ignore notebooks as a language Nov 30, 2024 .gitignore Remove install from notebook and update dependencies ...