9 Mistakes Quants Make that Cause Backtests to Lie
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9 Mistakes Quants Make that
Cause Backtests to Lie

Tie Breaker
All too often strategies look great in simulation but fail to live up to their promise in live trading. There are a number of reasons for these failures, some of which are beyond the control of a quant developer. But other failures are caused by common, insidious mistakes. An over optimistic backtest can cause a lot of pain. Lucena CTO Tucker Balch, Ph.D. will help you avoid that pain by sharing 9 of the most common pitfalls that can result in overly optimistic backtest results.


Date: Friday, April 24, 2015
Time: 11:00 AM - 12:00 PM EDT.

Tucker Balch Tucker Balch, Ph.D. is a former F-15 pilot, professor at Georgia Tech, and co-founder and CTO of Lucena Research, an investment software startup. His research focuses on topics that range from the understanding social animal behavior to the challenges of applying Machine Learning to Finance. His online course, Computational Investing Part I, is the most popular online course offered by Georgia Tech and one of the most popular at coursera.com with over 175,000 students enrolled. Balch holds B.S. and Ph.D. degrees in Computer Science from Georgia Tech. Honors include the NSF CAREER Award, the Georgia Tech Outstanding Service Award and a distinguished graduate designation from the USAF in Undergraduate Pilot Training. Tucker has authored over 150 technical papers, journal articles and books, including the recent book What Hedge Funds Really Do with Philip Romero. His work has been reported in the popular press and TV including on CNN, in Institutional Investor, the New York Times and the New Scientist.


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9 Mistakes Quants Make that Cause Backtests to Lie
Friday, April 24, 2015
11:00 AM - 12:00 PM EDT.


Lucena Research
Lucena Research brings elite technology to hedge funds, investment professionals and wealth advisors. Our Artificial Intelligence decision support technology enables investment professionals to find market opportunities and to reduce risk in their portfolio.

We employ machine-learning technology to help our customers exploit market opportunities with precision and scientifically validate their investment strategies before risking capital.
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