At the University of Dayton, within the Hanley Trading Center, the Flyer Forex Fund (FFF) has been coming together. FFF is a leveraged currency portfolio that is managed by a student-run proprietary trading group. It utilizes a non-discretionary algorithmic model that incorporates trend indicators including volatility, momentum and GIRTH (see "Learning to trade: It’s academic," October 2009, where the GIRTH model is defined).
FFF has two primary goals: 1) To educate student-members on finance by providing them with an in-depth experience trading real money in the spot currency market; and 2) to teach student-members the disciplines of money management to prepare them for financial management positions. For the academic year 2009-10, FFF was managed using simulation money. It was hoped that simulation trading would reduce human errors in execution.
By October 2010, a 15-member advisory board was formed to help guide the fund. The advisory board covers a wide range of areas: Corporate finance, energy trading, risk management, commodities, intellectual property, private wealth, hedge funds and interest rate strategies. That same month, the fund began to trade real money with a long position in the euro on Oct. 29 at 1 p.m.
In an effort to get the fund up and running quickly, FFF is solely owned by Prof. Leslie K. McNew. It is funded primarily by McNew with some student contributions in the form of non-refundable club dues. McNew manages the legal issues, tax consequences and intellectual property of the fund. The fund accepts no third-party money and holds a non-profit status.
The fund trades spot currency, specifically the EUR/USD, implementing the GIRTH model. Currently, positions are in €10,000, with a margin of $320 per position. Profit per pip is $1. At a spot of €1.4676 and a position size of €10,000, total leverage could be as much as 46:1. The fund has $2,500 in trading capital at FXCM. The FXCM system also was used during the simulation stage at the university in the academic environment. The fund holds $2,515.21 in reserve at Wells Fargo. As we prepare for a new school year, we report what we have learned operating FFF.
Analysis & execution
The GIRTH model, run on a spreadsheet, directs the student to implement a trade (long, short or exit) based on the open of the four-hour candlestick and analysis of the 10- and 20-period exponential moving averages (EMAs). Thus, the student must actively manage the model, watching the market at 1 a.m., 5 a.m., 9 a.m., 1 p.m., 5 p.m. and 9 p.m. To avoid the requirement that students monitor the markets 24 hours a day, they trade only at these times. This affects their entrance and exit of a trade. (It’s expected and accepted that the student-managed model will underperform an exact trade cross method because of the time situation.)
Because the spot forex market transacts 24 hours a day, from late Sunday afternoon to late Friday afternoon, students must be focused on the market and on team participation to manage and update the model, execute and inform others of decisions. FXCM is used to mark-to-market the book, running FXCM reports each time a position is closed (paper and digital). The fund also marks-to-market the book once a week, on Friday, to determine percentage returns.
The initial FFF team consisted of 20 traders, sophomores through graduate students. All students had to take a trading class either before entering the fund or simultaneously. The senior management of the simulation fund, consisting of students only, picked the 2010-11 academic year students to begin trading real money. Two students effectively left the fund in January 2011 to take full-time internships. Additionally, in May 2010, FFF "hired" junior traders to provide a pool to take on full-time trading positions in the fall of 2011. FFF is looking to provide continuity of knowledge and also to leverage the skill pool as students graduate. It is impractical and time consuming to teach the fund from ground zero every semester or every year.
FFF results are shown in "To err is expensive" (below) for Oct. 29 to May 5. These are actual trade results. FFF produced a simple return of 7.18% (including errors); this is the blue line. If the fund had no errors in execution, it would have made 18.59%; this is the orange line. Errors cost the fund approximately $285. Against an initial capital of $2,500, this error "loss" is approximately 11.5%.
Learning from mistakes
We knew that we would have student errors in running the money. Thus, Peter A. West, co-managing director of the fund, wrote a procedural draft document, spending more than 300 hours on this project, with more than 120 pages covering everything from training to execution. The document not only provides continuity of knowledge, but also establishes the culture of the fund.
It is the policy of FFF for team members who commit an error to write an error report. One report worth noting covers an error that occurred on Jan. 12, 2011, at 9 a.m.
That month, McNew took 10 members of the FFF team to Houston on a networking and informational trip. This trip left only seven students managing the position for more than a week in Dayton. There, it seemed most other students shirked their responsibilities, leaving one to cover for the entire fund.
To quote from his error report: "After trading for the third time, at 5 a.m. on Jan. 12, 2011, to cover for the other trading team, I became frustrated and sent out an email and a text message to remind them of their duties to the Flyer Forex Fund. Afterward, in a fit of rage, I threw my phone (which is also my alarm clock) and went to bed."
Unfortunately, the phone broke and the student missed the 9 a.m. trading slot, executing the trade 27 minutes late. While any manager would expect greater dedication from an employee than a student, this highlights the importance of making sure you have proper staffing and back-up.
Generation Y, being educated now, will have specific ramifications in the workforce, as has become evident in the running of FFF. Also known as Millennials, these kids are part of the "trophy generation," a term that reflects the trend in competitive sports, as well as many other aspects of life, where mere participation is frequently enough for a reward. It seems that many of the students that join FFF feel that this — the joining — is enough. No extra work is needed.
While the student with the error held the team together and worked through the problem, the remaining students simply didn’t feel that they were accountable.
The purpose here is not simply to critique society’s shaping of tomorrow’s workforce. It is relevant to traders in the sense that there are no entitlements in trading. Indeed, many students believe that everything is owed them — that the long hours and the out-of-pocket costs borne by the professional mentors and advisory board are a right and not a privilege. They argue that an error of $27 is not much. But in this case it represents about 1% of money under management and it is extremely significant.
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.
