Predicting Market Volatility

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

The goal of this research is to better understand the relationships between cryptocurrencies and stock indexes, including how cryptocurrencies are interconnected. Preliminary visualization revealed a trend of market movement across all cryptocurrencies, indicating a substantial correlation. Initial analysis focusses on finding the correlation be…

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

Stock Market Data - Correlations/Visualizations/Calculations

R project for bachelor's thesis in "International Economics and Financial Markets"

Python & Finance

Financial time series forecasting using R

Predicted Volatility: Applying Predicted Volatility to Determine Profitability of Cyclical and Defensive ETFs

Portfolio Performance Analysis

In this notebook, I've loaded historical Dollar-Yen exchange rate futures data. I've applied time series analysis and modeling to determine whether there is any predictable behavior.

Public repo of some of my options modeling projects

Fast black-scholes-merton option pricing model in Python

Curso diseñado para proporcionar una comprensión muy profunda del Trading Cuantitativo, fusionando los principios de Ingeniería Financiera con el poder de la Inteligencia Artificial, todo implementado en Python. Desarrollarás algoritmos y estrategias avanzadas que aprovechan datos financieros y técnicas de Inteligencia Artificial.

Java Spring Collaborative Project built by Erik van Erp, David Moore, & Coren Frankel

Model which predicts the volatility of a company's stock based on the shareholder meeting transcripts over the years for the Fortune 500 companies. This model is based on BERT and GPT-3 LLMs to summarize and predict the volatility.

Detailed implementation of various time series analysis models and concepts on real datasets.

Trying to set up a blog