I tweeted a few days ago that I had big news–huge news–gigantic news about the trading course, and I do. I have been very pleased with the reception the course has gotten, and I’ve heard from many traders that it has been a pivotal piece in their development. I decided that the time has come to widen the scope of the course, and I’ve invited some of the best and brightest in the industry to contribute on their topics of expertise–keeping true, of course, to the spirit of the course, which is that it would always be a free and accessible resource to the trading community.
Today, I am delighted to announce the next module of the course, Introduction to Algorithmic Trading, presented by Dr. Ernest Chan, Ph.D. Ernie needs very little introduction–he is simply the best. When I decided to ask for others to contribute to the course, the email to him was the very first I wrote. A great teacher and a great mind, and the course is much richer for his contribution.
Dr. Chan is the managing partner of QTS Quantitative Trading, LLC, writes a great blog that has long been on my short must-read list, Quantitative Trading, and also tweets as @chanep. You should be reading his blog, following him on Twitter, and you should already have read his books, Algorithmic Trading: Winning Strategies and their Rationale, and Quantitative Trading: How to Build Your Own Algorithmic Trading Business.
Ernie’s contribution to The Art and Science of Trading course includes the following modules:
- Introduction to backtesting
- How to tell if a strategy is worth backtesting (before you waste your time!)
- Choosing a backtesting platform, pros and cons. The module discusses MATLAB, but the concepts will apply easily to whatever platform and structure you work within.
- Performance measures and their relation to backtesting
- Transaction costs in backtests
- Choosing a historical database: issues with stocks, dividends, splits, futures rolls, intraday data, and more
Wherever you fall on the spectrum of discretionary to blended to fully systematic trading, there are insights and ideas for you in this module. Head on over to the course and check it out.
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Thank you and Appreciate your valuable contributions and insights Dr Chan
Thanks so much for this content! Simply amazing!
Great! Thank you