Machine learning automatic quantitative trading system

Simple metrics for Robinhood trading

A simple yet powerful way to visualize 4xdat trades.

My first experiments in quantitative finance

Quantitative Financial Risk Mangement

Copilation of Python Programming Codes

Algoritmos en R para las volatilidades propuestas en el Capitulo 9 del libro Paul Wilmott Introduces Quantitative Finance.

Computations of alpha and beta for tech stocks on the Australian Stock Exchange using the Capital Asset Pricing Model.

Algunos de los temas que me interesan / Subjects I'm interested

TeX and other sources from my PhD thesis

IME-published article on Long-term Real Dynamic Investment Planning. While we enhance predictability of the real returns of S&P500 Index, we derive optimal non-myopic investment strategy, and we compare its performance with near-optimal Dynamic and Constant Merton investment strategies.

The binomial tree model is a commonly used approach for pricing derivatives, such as options. The basic idea behind the model is to create a tree of possible stock prices over time, based on a set of input parameters

My portfolio website

Intraday trading Dataset from fyers API and code to fetch custom data.

My personal ML portfolio projects.

Public ✨ Feature and Bug 🐛 Tracker for the MesoSim project

Quantitative Investment Strategy for Traditional Chinese Medicine - Based on XGBoost Multi-Factor Stock Selection Model

A series of methods contained in classes to implement volatility based approaches to underlying data. For example, volatility timing strategies.

Jupyter notebook examples using QuantLib.