Nicholas Polson is a British statistician who is a professor of econometrics and statistics at the University of Chicago Booth School of Business. His works are primarily in Financial Econometrics, Markov chain Monte Carlo, Particle learning, and Bayesian inference. Inspired by an interest in probability, Polson has developed many new algorithms and applied them to the fields of statistics and financial econometrics, including the Bayesian analysis of stochastic volatility models and sequential particle learning for statistical inference.
Polson’s article, “Bayesian Analysis of Stochastic Volatility Models,” was named one of the most influential articles in the 20th-anniversary issue of the Journal of Business and Economic Statistics. His recent work in Sports Analytics includes “The Implied Volatility of a Sports Game” and “The Market for EPL Odds.