Dr. Ernest P. Chan is the Managing Member of QTS Capital Management, LLC. His career since 1994 has been focusing on the development of statistical models and advanced computer algorithms to find patterns and trends in large quantities of data. He has applied his expertise in statistical pattern recognition to projects ranging from textual retrieval at IBM Research, mining customer relationship data at Morgan Stanley, and statistical arbitrage trading strategy research at Credit Suisse, Mapleridge Capital Management, and other hedge funds.
While at the Human Language Technologies group at IBM T. J. Watson Research Center (Yorktown Heights, NY), Dr. Chan spearheaded IBM’s research effort to develop a system for searching large text databases such as the World Wide Web, catapulting IBM’s reputation as a top player in the field. His system was placed seventh among some forty competitors in a competition sponsored by the National Institute of Science and Technology and the Department of Defense in 1996. At the Data Mining group in Morgan Stanley’s headquarter in New York, Ernie pioneered the application of some of these sophisticated statistical algorithms to the complex task of extracting customer relationships in the Morgan Stanley customer accounts database.
Ernie was invited to join a proprietary trading group at Credit Suisse in New York in 1998 to develop statistical models for equities and futures trading. He later joined Mapleridge Capital Management Corp. in 2002 as a Senior Quantitative Analyst working on futures trading strategies, and then Maple Financial in 2003 as a senior researcher and trader.
Ernie writes the Quantitative Trading blog and was quoted by the New York Times, Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program, Technical Analysis of Stocks and Commodities magazine, Securities Industry News, Automated Trader magazine, and the CFA Institute Magazine on topics related to quantitative trading. In recognition of his expertise in statistical data mining, he was invited to serve on the Program Committees of the International Conference of Knowledge Discovery and Data Mining in 1998. He was an invited speaker at the Automated Trading conference in London, UK, in October 2009, the Market Technicians Association Toronto Annual Conference in 2010, the Quant Invest Canada conference in 2012, and QuantCon in New York in 2015-17. He is the author of “Quantitative Trading: How to Build Your Own Algorithmic Trading Business” and “Algorithmic Trading: Winning Strategies and Their Rationale“, both published by John Wiley & Sons. His new book “Machine Trading: Deploying Computer Algorithms to Conquer the Markets” was published in 2017. Ernie conducts workshops on Statistical Arbitrage, Quantitative Momentum Strategies, and Artificial Intelligence for Traders in London. He was an Adjunct Associate Professor of Finance at Nanyang Technological University in Singapore, and an Industry Fellow of the NTU-SGX Centre for Financial Education, which is jointly set up by NTU and the Singapore Exchange. He is on the faculty of Northwestern University’s Master of Advanced Data Science program and supervises student theses there.
Ernie holds a Bachelor of Science degree from University of Toronto in 1988, a Master of Science (1991) and a Doctor of Philosophy (1994) degree in theoretical physics from Cornell University.