Neil Chriss

Before founding Hutchin Hill Capital in 2007, Neil was a Managing Director at SAC Capital Management (2003-2007), where he founded and ran the firm's quantitative trading business and was a member of SAC's operating committee.

Prior to SAC, Neil was founder and president of ICor Brokerage Inc. (2000-2003), a global electronic trading firm that Reuters Plc acquired in 2004. Previously, he had been a portfolio manager in the Quantitative Strategies group at Goldman Sachs Asset Management (1998-2000), in charge of volatility arbitrage strategies. Neil started his career on Wall Street as a member of the Quantitative Research group at Morgan Stanley (1996-1998), where he developed models for equity program trading, prime brokerage and stock loan.

Neil is a founding board member, and a member of the executive committee, of Math for America (2003-Present), a nonprofit organization that seeks to improve mathematics education in the United States; an executive director of the University of Chicago's Financial Mathematics Program, and a member of the governing board of the Mathematics in Finance Program at New York University's Courant Institute of Mathematical Sciences (2003-Present); and a member of the visiting committee of the University of Chicago's Physical Sciences Division (2007-Present).

Neil holds Ph.D. and B.S. degrees in mathematics from the University of Chicago and an MS in mathematics from the California Institute of Technology. He has held academic positions in the mathematics departments of Harvard University and the University of Toronto, and was a Member in the School of Mathematics at the Institute for Advanced Study in Princeton, NJ.

He has published numerous influential research articles on quantitative trading, trade execution, portfolio optimization and risk management, and is the author of several books, including the best-selling finance text Black-Scholes and Beyond: Modern Options Pricing (McGraw Hill, 1996). Neil's 1998 paper "Optimal Execution of Portfolio Transactions" is widely credited as the theoretical model driving many of the algorithmic trading strategies on Wall Street.