Creation of stationary series from correlated asset portfolios with the goal of statistically arbitraging deviations. This project uses advanced techniques of time series analysis and cointegration to identify trading opportunities.
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Exploration of strategies and conceptual ideas for arbitrage — statistical, token-based, or latency-driven approaches. We develop algorithms that identify and exploit inefficiencies in financial markets.
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An interpretive language model designed to extract, summarize, and explain quantitative finance research papers. Uses artificial intelligence to make the most complex academic research accessible.
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Experimental projects related to data analysis, automation, and alternative financial modeling approaches. We explore new frontiers at the intersection of technology and finance.
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