Thomas Chevrier was Head of State Street Associates for APAC from 2007 until 2013. In this capacity, he advised institutional investors on their portfolio management. Common themes included portfolio reallocation, manager selection, currency hedging, portfolio rebalancing, exposure management, alpha strategies, index replication, and risk management. He presented to the president of the GPIF of Japan on risk factors, to the board of an APAC sovereign wealth fund on risk parity during their strategy day, to the board of an Asian government body on alpha beta separation, and to several central banks on portfolio diversification, as well as at dozens of conferences.
Thomas initially earned an MBA from Essec Business School, and then an MS in Applied Mathematics from Universite Paris I and VII (Jussieu). His studies then took him to the University of Chicago where he earned an MA from the Department of Economics, and both an MBA and a PhD from the Booth School of Business.
While at Chicago Booth, as a graduate student, he was awarded with several teaching assistance excellence awards including twenty one awards for Exceptional Service to the Executive MBA Program presented annually by the students for outstanding teaching at the Chicago campus and five Outstanding Teaching Assistant Awards.
Thomas enjoys flying (certified FAA private pilot, both Sea and Land engines), diving (PADI Master Scuba Diver), Ironman racing and traveling, golfing, cooking, as well as learning languages.
2014 - 2015 Course Schedule
New: Using Economic Theory to Build Optimal Portfolios
Given expected returns and return covariances, portfolio weights are known in closed form in a mean-variance framework. The real difficulty is in estimating these parameters. Using recent advances in Bayesian techniques, we show how investors can incorporate any prior information for optimal portfolio selection. We apply our method to 27 domestic and international data sets. We find that our tangency portfolios have three essential and attractive features. i) They perform better in terms of out-