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AlgoGators Investment Fund

Research

In addition to managing live capital, members conduct research on various topics within quant finance, including market analysis, machine learning, risk management, and strategy development.

Bayesian Alpha Estimation via Fama–French and Momentum Model

Industrial Metals and US Macro Indicators A Copper-Focused Analysis

Enhancing Futures Trading Signals with Kalman Filtering

Lock-Free Trade Engine Acceleration Through High-Efficiency Memory Pooling

Commodity Prices and Currency Movements Exploring the Link Between Commodities and Commodity-Linked Currencies

Physics-Informed Neural Networks for Futures Pricing and Signal-Generation Under Stochastic Volatility

Corporate Credit Spreads as Predictors of Equity Market Performance

Shannon Entropy as a Forward Indicator of Volatility Regime Shifts in Energy Futures

Hierarchical Hidden Markov Models for
Multi-Time-Scale Volatility Regime Detection

Reading Between the Lines: The Immediate
Stock Market Impact of Earnings Calls

Predicting US Market Returns Using Fundamental Indicators

Neural Networks Predicting Next-Day Stock Prices

Comparing the Beta Estimation Methods of Fixed-Time Periods, Rolling Windows, and Random Forests on Futures Contracts

Efficient Event Processing System

Using Temporal Fusion Transformers for Market Regime Detection

Impact of Corporate Changes on Market Volatility and Market Return

Survival of the Fittest Benchmarking Biological Dynamics and Neural ODEs for Volatility Forecasting

Mispriced Tail Risk and Optimal Exit Boundaries

Examining the Explanatory Power of Political Risk

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