Petter Kolm
Director of the Mathematics in Finance Master's program and a Clinical Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University; Partner at CorePoint.
Petter Kolm is Clinical Full Professor and Director of the M.S. in Mathematics in Finance Program at the Courant Institute of Mathematical Sciences, New York University, since 2007. He is Partner at CorePoint-Partners.com. Previously, Petter worked in the Quantitative Strategies group at Goldman Sachs Asset Management, developing proprietary investment strategies, portfolio and risk analytics in equities, fixed income and commodities. He was named "Quant of the Year’" in 2021 by Portfolio Management Research (PMR) for his contributions to the field of quantitative portfolio theory.
Petter is the co-author of numerous academic journal articles and several well-known finance books including, Financial Modeling of the Equity Market: From CAPM to Cointegration (Wiley, 2006); Trends in Quantitative Finance (CFA Research Institute, 2006); Robust Portfolio Management and Optimization (Wiley, 2007); and Quantitative Equity Investing: Techniques and Strategies (Wiley, 2010).
Petter is a frequent speaker, panelist and moderator at academic and industry conferences and events. He is a member of the editorial boards of the International Journal of Portfolio Analysis and Management (IJPAM), Journal of Financial Data Science (JFDS), Journal of Investment Strategies (JoIS), and Journal of Portfolio Management (JPM). Petter is an Advisory Board Member of Alternative Data Group (ADG), AISignals and Operations in Trading (Aisot), Betterment (one of the largest robo-advisors) and Volatility and Risk Institute at NYU Stern. He is also on the Board of Directors of the International Association for Quantitative Finance (IAQF) and Scientific Advisory Board Member of the Artificial Intelligence Finance Institute (AIFI).
As an advisory board member, consultant, and expert witness, Petter has provided services in areas including alternative data, data science, econometrics, forecasting models, high frequency trading, machine learning, portfolio optimization with transaction costs, quantitative and systematic trading, risk management, robo-advisory, smart beta strategies, trading strategies, transaction costs, and tax-aware investing.
He holds a Ph.D. in Mathematics from Yale University; an M.Phil. in Applied Mathematics from the Royal Institute of Technology, Stockholm, Sweden; and an M.S. in Mathematics from ETH Zurich, Switzerland.
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