Winner

Arbitrage Opportunities in Exchange-Traded Funds

2018
Research Category: Computer and Information Sciences
Presenter: Nathan Kotler
Additional Authors: Brian Phillips
PI: Nathan Kotler
Faculty Advisor: David Massey
Award: Entrepreneurship

Despite the onset of high-frequency trading and the increasingly quantitative nature of investing, inefficiencies still exist in the global financial markets. Our research utilizes large data sets, advanced machine learning, and human insight to uncover such inefficiencies, with an emphasis on highly leveraged exchange-traded funds (ETFs). We then exploit these inefficiencies by using a net-zero market exposure arbitrage strategy on our proprietary algorithmic trading platform to execute short-term, consistently profitable trades.

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