My Projects
A deep dive into my work at the intersection of quantitative finance and artificial intelligence.
Based on Raj Chetty's Opportunity Atlas, this tool helps parents assess demographics and opportunities in their zipcodes, exploring local community and school options.
A comprehensive analysis of Bitcoin (BTC) and Ethereum (ETH) price movements, implementing various time series analysis techniques, machine learning models, and deep learning architectures. The project goes beyond traditional ARIMA modeling to incorporate advanced neural network architectures, feature engineering with external data sources, and pairs trading strategies.
This project focuses on predicting the movements of stocks over time based on various financial and economic indicators. The goal is to determine the most important financial indicators affecting stock prices and develop an accurate predictive model. The analysis includes feature importance analysis, model training with various machine learning algorithms, and performance evaluation across different market conditions.
This study dives into how specific metrics influence success in baseball, analyzing hitting, pitching, and fielding metrics to understand team performance. The project combines statistical rigor with domain knowledge to provide insights that can influence roster-building decisions, tactical approaches, and broadcasting narratives. The findings bridge the gap between traditional baseball insights and modern predictive techniques.
Modeling when coaches should go for two-point attempts versus extra points based on game situations and analytics.
Estimating player value and team performance using Monte Carlo simulations with high school baseball statistics.
Provides methods for assessing company similarity using specified sub-sections of 10-K filings. Uses cosine similarity of BERT embeddings for similarity.
A model of firm behavior under a duopoly using classical microecnonimic multivariate maximization and game theory.
An explanation of how ChatGPT works from the ground up. Topics include basic neural networks, recurrent neural networks, and long short-term memory networks.
A tract-level correlational analysis of economic growth factors, such as education and employment rate, on income, separated by gender and race.
An explanation of basic computer graphics. Includes discussions on transformations in 2D and 3D space, quaternions, perspective projections, and shadow mapping.