My Workshops

I currently offer the online course “Quantitative Momentum Strategies” to a select number of traders and portfolio managers. This is an online workshop conducted in real-time through Adobe Connect. This workshop focuses on the theories and practical implementation of mean reversion strategies using MATLAB. Free MATLAB trial licenses will be arranged for extensive in-class exercises. No prior knowledge of MATLAB is needed, but some experience with programming is necessary. The math requirement assumed is basic college-level statistics.

  • Maximum number of attendees: 6.
  • Total hours: 12.
  • Fee: $1,890.
  • Suggested dates and times: December 2,3,4, 5:30-9:30 pm ET. (Final dates and times by collective agreement.).
  • Registration: ernest@epchan.com.

Course outline is available for download here.

___________

The pre-recorded online course “Backtesting” is now available. This consists of recorded Adobe Connect sessions and a live Q&A session. The focus is on discovering and avoiding various pitfalls during the backtesting process that may degrade performance forecasting. Illustrative exercises are drawn from a futures strategy and a stock portfolio trading strategy using MATLAB. Free MATLAB trial licenses will be arranged for extensive in-class exercises. No prior knowledge of MATLAB is needed, but some experience with programming is necessary. The math requirement is basic college-level statistics.

  • Total hours: 7 hours of recorded session .
  • Fee: $800.
  • Registration: ernest@epchan.com.

Course outline is available for download here.

___________

I also conduct 3 different hands-on in-person workshops in London and Singapore: Momentum StrategiesStatistical Arbitrage, and Millisecond Frequency Trading. The statistical arbitrage course is mainly about mean-reverting strategies.These workshops are organized either by the Technical Analyst magazine or the Nanyang Technological University. Please click on the links above to see course outlines and registration details.

Comments are closed.