Tocaya Capital is a quantitative investment firm focused on event-driven investing powered by specialized AI and proprietary data. Our objective is to generate sustainable idiosyncratic alpha that is uncorrelated with other assets and strategies. We employ a systematic, market-neutral, U.S. equity strategy capitalizing on investor biases exposed by market-moving news. We find opportunities in corners of the market where institutional and behavioral biases persist. We believe inefficiencies will remain as long as humans make decisions in the market.

We study events that influence the fundamental outlook of companies and provide consistent sources of market moving information. By uncovering biased reactions to these events we are able to build strategies that provide unique return streams. Our strategies are powered by quantitative models that use artificial intelligence to make automated investment decisions. These models identify subtle, non-linear patterns from millions of disparate data points in order to detect mispricing caused by investor biases related to market-moving news. The combination of our systematic trading strategy, uncompromising data quality standards and understanding of market dynamics drives our ability to capture returns in short-lived investment opportunities.

To learn more about our investment approach, contact us or visit our research page where we write about investor biases, artificial intelligence and quantitative investing.

Alex is an event-prediction specialist and expert in quantitative investing methods. As the manager of Tocaya Capital, he maintains primary responsibility for the investment decisions and strategy. His quantitative expertise and market knowledge drive the development of Tocaya's unique event-driven investment approach.

Before founding Tocaya Capital, Alex was the global product manager for Markit's Transaction Cost Analysis business. At Markit, he managed a team of quantitative analysts and oversaw Transaction Cost Analysis research, development, client service, and sales. Prior to Markit, Alex was a senior quantitative analyst for Quantitative Services Group, where he developed novel transaction cost analysis metrics and worked closely with buy-side and sell-side trading desks to help traders reduce trading costs.

Alex graduated with Highest Honors from Washington University in St. Louis with degrees in Systems Science and Engineering and Finance with a minor in Mathematics.

Sina is a Portfolio Manager at Tocaya Capital and has 20 years of experience in financial markets. He joined Tocaya in 2022 where his responsibilities include research, portfolio construction, and business development.

Sina began his career as a trader at the CBOT and CME and went on to co-found a proprietary trading firm that specialized in interest rate derivatives. Prior to joining Tocaya, Sina co-founded a firm that specialized in developing quantitative trading signals on equities and options for institutional investors. He has additionally served as a management consultant to the largest market making firm and as a data strategy and data science advisor to multiple alternative data providers.

Sina graduated with Honors in Economics from Northwestern University.

Patrick is Director of Research at Tocaya Capital with 14 years of experience in both quantitative and fundamental investing. He joined Tocaya in 2024, where his responsibilities include research, data-driven strategy development, and portfolio management.

Before joining Tocaya, Patrick led data science efforts at Cederberg Capital, where he also served as a generalist fundamental analyst. Prior to that, he was Director of Quantitative Research at S&P Global (formerly IHS Markit), specializing in factor research, alternative data, and execution research.

Patrick graduated from Washington University in St. Louis with a Master of Science in Finance degree, and is a Charterholder of both CFA & CAIA designations.

We are always looking for exceptional talent to join our team. We value the following skills and experiences:

• Exceptional attention to detail, passionate curiosity and tenacious self-motivation
• Prior experience successfully applying quantitative methods to build investment strategies
• Proficiency in any programming language with experience in data manipulation and analysis