Quantitative investing blog

Code, mostly in R, for charts and analysis on our blog.

Old Matlab files

Notes and exercises exploring finance topics with Rstats

Schedule for Sunday lectures

A dynamic strategy that replicates the payoff of a derivative described as a stochastic process

Selected Questions and Answers for Quant Interviews

Udacity nanodegree: AI for Trading

Flask app using pandas to create custom indices and portfolios!

An asset-pricing model using historical prices. Volatility of the asset is modeled as the random variable that changes over time and each iteration. For modelling the future price behavior, Monte Carlo simulations were performed.

Portfolio Optimization Modules

The Quantitative Strategy Analysis project aims to provide analysts with tools to research, backtest, and analyze various trading strategies involving currency pairs and ETFs. With Python notebooks, historical datasets, and performance reporting tools, this project is designed to streamline quantitative research

This is where I originally designed my Monte Carlo simulation package (MCmarket) my Mcom financial econometrics course work at Stellenbosch University.

My portfolio website

FinanceCraft is a quantitative framework leveraging technical indicators and machine learning for stock market trend analysis and prediction. It employs yfinance for data acquisition and Pandas for preprocessing, laying the groundwork for feature engineering, model training, and the implementation of trading algorithms.

Este repositório contém o b3-scraping-project, uma ferramenta de web scraping projetada para extrair e processar dados da B3 (Bolsa de Valores do Brasil).