Algorithmic game theory (AGT) and reinforcement learning (RL) research in finance and economics 2022 - Present

At the PhD program at CU Boulder, develops methods for using Markov Decision Processes (MDPs) and their variants (such as POMDPs). Works on practical solution to problems such as price prediction, risk management, portfolio management, market strength analysis, and trading sentiment.

"The Efficacy of a Regime-Switching Asset Pricing Model Conditioned on Market Volatility" DBA Dissertation, 2023

A proprietary statistical model that explains public equity returns in different market regimes, as defined by general return volatility.

Experiments with Systematic Fundamental Asset Pricing Models Dissertation exploration, 2020

Builds systematic (programmatic) asset pricing and portfolio management models from financial and fundamental data from firms in the US and abroad to determine the effect of firm management on stock returns, and the attributes of those returns. Have started incorporating machine learning methods into these models (GANs, SVMs, etc) to increase the explanatory power and potential predictive capability of these models which can be used in industry for active money managment or in academia to explain systemic factors of return premia. Guofu Zhou from the Finance Department of Washington University in St. Louis advises on some of these activies.

Determining Explanatory Power of Charateristics in Modern Asset Pricing Models Research assistantship, 2019

Working for David Rapach and Ilias Filippou in the Finance Department in the Olin Business School at Washington University in St. Louis by creating dynamic ETL programs in R to collect, clean, structure, and analyze numerous firm characteristics over the universe of stocks in the US - about 29,000 firms.

Dissecting the Specification Effectiveness of Ramsey's RESET Test Research assistantship, 2019

Working for Robert Parks in the Economics Department of Washington University in St. Louis by creating programs in R and EViews that test published results and suggest improved variants of the RESET test.

Bed, Bath, and Beyond: A Valuation Analysis Summer research paper, 2019

Abstract: Bed, Bath, and Beyond, Inc. (“BBBY”) is an omnichannel home décor retailer with 1,552 stores in the US, Canada, and Mexico. Over the last five years, they have been unsuccessful in growing top line revenue (5-year CAGR of 1.8%) while costs have continued to rise (five-year CAGR of 3.3%). While management has adroitly run the operating side of the business as evidenced by healthy financial ratios including higher than industry average ROE (27%), a low debt-equity-ratio (0.4x), and high EBIT interest coverage (18x), BBBY is projected to run out of debt-free cash flows in 2021 due to their evaporating net income. With this information, BBBY is evaluated at a SELL recommendation as its equity is valued at $429M on a DCF basis and $528M on a multiples basis; these are well below the $2.2B the company currently holds in market capitalization.

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“Does Financial Statement Analysis help pick winners from an OTC equity market?” Summer research paper, 2019

A research paper conceived and written in a seven-week period during the last semester of my MBA under advisor Francois Brochet, Associate Professor of Accounting at Boston University.

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