Learn About Me
I'm a recent college graduate with degrees in Mathematics/Satistics, Computer Science, and Economics. Since financial markets are always evolving, I like to analyze data, build and test financial models and forecasts, using various algorithms to capture new opportunities.
MY CURRENT PROJECTS
Over the last two years, I’ve been working on multiple papers and projects. My research assistantship focused on multi-view embedding using multiple time series to come up with a predictor of chaotic time series. This article is currently being revised and has been resubmitted. I’m also working on a paper outlining Monte-Carlo simulations between standard forecasting models and trained neural network models on SPY data. My other projects are in applied research involving financial data, such as a grid-search based ARIMA model forecasting top weighted SPY stocks, or machine learning algorithm for housing prices in 2019.
News and Stock Sentiment
A Python based news sentiment analyzer used to match stock movements for comparison
LSTM Crude Oil
R and Python Binding based LSTM Neural Network to forecast crude oil prices
Grid-Search Based ARIMA
Python based forecasting model using ARIMA and the Grid-Search numerical method
Options Pricing Program
C++ based Options pricing program using Black-Scholes, Vasicek, and Hull-White configurations
K-Means Clustering News Headlines
News Sentiment Analysis using K-Means clustering in order to create a basis for stock forecasting
Sales Forecasting
Simple Forecasting model with Big Data and several time series models