There are 3 repositories under geometric-brownian-motion topic.
Python-based portfolio / stock widget which sources data from Yahoo Finance and calculates different types of Value-at-Risk (VaR) metrics and many other (ex-post) risk/return characteristics both on an individual stock and portfolio-basis, stand-alone and vs. a benchmark of choice (constructed with wxPython)
Predicting stock prices using Geometric Brownian Motion and the Monte Carlo method
Python code of commonly used stochastic models for Monte-Carlo simulations
Pricing and Analysis of Financial Derivative by Credit Suisse using Monte Carlo, Geometric Brownian Motion, Heston Model, CIR model, estimating greeks such as delta, gamma etc, Local volatility model incorporated with variance reduction.(For MH4518 Project)
A virtual stock market and trading platform. Includes a fully simulated stock market, with dynamic price changes and news events. Simulation models a real calendar with time sped up
A dashboard for helping beginners identify trading opportunities through technical analysis, fundamental analysis, and possible future projections.
In this repository, a buy-and-hold investment is studied using Python and a Monte Carlo approach.
Using Finite Element and Finite Difference Methods to Price European Options
A collection of numerical implementations for the simulation of well-known stochastic processes on MATLAB.
Monte Carlo generator of geometric brownian motion sample paths for .Net.
Generating a stock's geometric Brownian motion using C# and plot the result.
Quantitative Financial Risk Mangement
Applying Geometric Brownian Motion (GBM) - Financial Modeling
Variational quantum simulations of stochastic differential equations
CERN ROOT codes used to develop the images and graphs in the article on my blog: http://muonray.blogspot.com/2014/09/particle-physics-software-and-financial.html
Generative Models in Commodity Trading
Option Price Forecaster
Determining performance of forecasting financial asset prices with geometric brownian motion
This project focuses on drift parameter optimization for out-of-the-money options within a geometric Brownian motion framework, with extensions to jump diffusion models.
Monte Carlo simulation toolkit for equity trading, utilizing GBM and Pareto distributions to model price movements and trading volumes
PROJECT MIGRATED TO CODEBERG - Reinforcement Learning in Multiplicative Domains
This is a project conducted on the NSE20 stock price that makes predictions on the July - August stock price by Applying Geometric-Brownian-Motion model.
This is a project conducted on the NSE20 stock price that makes predictions on the July - August stock price by Applying Geometric-Brownian-Motion model.
Stock Price Simulation with Geometric Brownian Motion and Efficient Frontier