A Python library for evaluating option trading strategies.

Python implementation of the basic model described in Chan, Nicholas Tung, and Christian Shelton. "An electronic market-maker."

Portfolio optimization package in Python.

Application of the Bellman Ford (shortest-path) Algorithm to detect real time arbitrage opportunities in currency trading.

Monte Carlo Pricing Library in Python

Tool for building an options dataset written in Python for deployment on the Raspberry Pi.

Efficient financial risk estimation via computer experiment design (regression + variance-reduced sampling)

Code for extracting mean-reverting portfolios out of large data sets.

A simple algorithmic trading bot based on machine learning methods.

This report explores time series analysis, algorithmic trading, and portfolio optimization. It implements an ARIMA model for forecasting, compares pairs trading strategies on Tesco and Pershing Square Holdings, and derives an efficient portfolio using five stocks from the FTSE 100 index for comparison against a 1/n baseline portfolio.

Monte Carlo Simulation for Option Pricing Using MATLAB and Python

Computational Finance Projects

The algorithmic trading hypothesis relies on technical indicators to identify market trends and entry signals. Project of Group 3 - CS408 - APCS, HCMUS - 2025.

HedgeHog is an open-source, mid-to-long-term-focused stock portfolio manager. HedgeHog's investment model is based on fundamental analysis and market sentiment.

Uncharted is a pre-market analysis tool useful for intraday cash segment traders.

Pricing of a European call option under Monte Carlo & Black Scholes approach

⚡ Streamline option pricing with ML surrogate models, achieving 100-1000x speedup and <1% error for efficient real-time risk management.

A tool for combining historical financial data with user-provided forecasts to produce Kelly optimal investment portfolio allocations