Matthew Dixon Quant of the Year 2022 & Gordon Ritter Quant of the Year 2019 (Deep Learning vs Reinforcement Learning vs Causality)
Professor Gordon Ritter and Professor Matthew Dixon discuss deep learning vs reinforcement learning vs causality in finance. 14.15 – panel discussion
Matthew Dixon is a British applied mathematician working in the field of algorithmic finance. His research focuses on applying computational and applied mathematics concepts to financial modeling, particularly in the area of algorithmic trading and derivatives. Matthew’s research is currently being funded by Intel Corporation to develop code for high performance architectures.
Matthew’s work in deep learning with Diego Klabjan (NWU) was widely recognized. He is also a frequent speaker at quantitative and fintech events around the world, and financial times When Bloomberg Markets.
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Gordon Ritter in Mathematical Physics from Harvard University in 2007. His publications during his Harvard years were on quantum field theory, differential geometry, quantum computation, and abstract algebra, including the well-known simplicity theorem for Kac-Moody groups and Euclid’s theory of Riemannian manifolds. of QFT. Prior to attending Harvard University, he received a BA in Mathematics with honors from the University of Chicago.
Dr. Ritter currently teaches at New York University-Columbia University, the University of Chicago, and the Baruch MFE Program. His academic research concerns portfolio optimization and statistical machine learning. His financial publications appear in journals such as Risk and the Journal of Portfolio Management. Journal of Financial Data Science, European Journal of Operations Research, etc.
He was named the 2019 Buy Side Quant of the Year.!
(Marcos López de Prado, Alex Lipton, Jean-Philippe Bouchot and other researchers who received the same honor in other years). In parallel with his teaching career, Dr. Ritter works full time in the industry. He founded Ritter Alpha LP in 2019. He is a Registered Investment Advisor who executes systematic absolute return trading strategies across multiple asset classes and geographies, based on the rigorous application of cutting-edge technology and statistics and the scientific approach to investment issues.
Prior to founding Ritter Alpha, he built a successful trading system from the ground up at GSA Capital, a four-time winner of the Eurohedge Awards for Equity Market Neutral and Quant Strategy. Prior to joining GSA, he was Vice President of Highbridge Capital Management (HCM) and a core member of the HCM Statistical Adjudication Group. In addition, it is a small team that shares complete discretion over a systematic trading model that has generated billions of dollars in profits for investors and directed trillions of dollars in trading across global stocks, futures and options. Several senior members of the HCM Statistical Arbitrage Group later joined Gordon at Ritter Alpha. Finally, Gordon enjoys his scuba diving in Hawaii in his spare time. Additionally, he is passionate about preserving Native Hawaiian culture and marine ecosystems.