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Backtesting | Online Course On Backtesting Algorithmic Trading Strategies

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 Vladislav Buchnev, Co Founder at Quantor

 Wednesday, July 5, 2017

This course focuses on the various practices and pitfalls of backtesting algorithmic trading strategies. We will study various common backtest performance metrics. Backtest performance can easily be made unrealistic and unpredictive of future returns due to a long list of pitfalls, which will be examined in this course. The choice of a software platform for backtesting is also important, and criteria for this choice will be discussed. Illustrative examples are drawn from a futures strategy and a stock portfolio trading strategy. Instructor: Ernest Chan 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. Please, learn more: https://quantor.co/courses/backtesting-complete-online-course/


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TRADING FUTURES AND OPTIONS INVOLVES SUBSTANTIAL RISK OF LOSS AND IS NOT SUITABLE FOR ALL INVESTORS
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