From the September 01, 2011 issue of Futures Magazine • Subscribe!

True cost of learning: Model implementation

Another lesson that traders can learn from the experience of FFF is that initiative and independence are necessary to research and find solutions. Again, see "To err is expensive." The green line shows the returns of the pool of money as if it were traded on a computer model. Unlike the student-run model, the computer model enters the position just after the actual cross of the 10- and 20-period EMAs.

Review the candlestick chart shown in "Lighting the way" (right). The actual cross of the EMAs was at approximately €1.42422 (triggering a short position). The computer model would set this position automatically. However, as an experiential learning tool, the student manually enters a position. The EMA cross occurred in the middle of a candlestick, but the student only trades at specific times. Thus, the student would have to wait and see if a cross had occurred and, if so, set the short position at the open of the next four-hour candlestick, which was approximately €1.4155. This is significant slippage of profitability. The team earned a simple return of 7.18% during the previous academic year; the computer model made more than 60% (hypothetically).

As for what can be done about this slippage, obviously some is because of the method employed to execute the trade. However, some is due to computer modeling.

Finally, there is the issue of research. If the object of any trading exercise is to increase profits, then a student might have questioned whether there was some way to better execute the trade entrance at the cross. How would a student be notified of the cross? In the case of FXCM, it can send an email notification of any strategy listed in its charting function. Being aware of such technology-powered advantages is vital to getting and staying ahead in today’s markets.

Lessons learned

There is a significant cost in learning to manage an algorithmic model when trading. Start-up costs, in terms of actual costs, and time are significant. The experiential learning potential is great; the frustrations on the senior professional management is greater. However, creating the foundation for a successful career or long-term success with a personal trading program is worth the price.

The Hanley Trading Center judges its performance partially in how it helps students develop skills to obtain relevant employment. In August 2010, 16 students started at the fund, trading real money. In January 2011, 11 junior traders entered the fund. Of the 27 students who began trading real money during the academic year, 22 students were placed for actual positions or summer internships, which is a placement rate of approximately 82%.

Despite challenges encountered, the second year out of the gate and the first year trading real money, fund performance is impressive. Overall, the professional placement statistics do illustrate the true success of the fund — and the mark of a good trader. From mistakes, lessons were learned.

Leslie K. McNew (lesmcnew@gmail.com) is a clinical professor of finance and visiting director of the Hanley Trading Center, University of Dayton School of Business Administration, and managing partner of the Flyer Forex Fund. Greg Trefz (gregtrefz@net-lp.com) is director of business development at NET and an advisor to the fund. John Rapp, Ph.D. (rapp@udayton.edu) is chair of the Department of Economics and Finance at Dayton, and an advisor to the fund. Todd Schneck, Masters of Financial Mathematics, University of Dayton, 2010 contributed to this article.

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