Tomorrow’s trading all-stars need to acquire a plethora of skills to compete, but there is nothing like getting your hands dirty in an actual trading environment. MMspire is an enhanced algorithmic trading firm run by interns from back to front office. Interns are expected to cross train and manage several aspects of trading dynamically, including risk management, banking, compliance and marketing. Students don’t learn just to trade, they learn the business of trading.
The program began in January 2016 with interns from Benedictine University outside Chicago, and has added students from DePaul, Kalamazoo College, Loyola University and SUNY Binghamton.
Since a systematic approach is quite mechanical, interns are taught ways to enhance a core algorithmic spot currency model with discretionary elements.
Through trial and error this summer, our interns learned ways to speculate on market moves as well as systematic trading methods, which together help them build the necessary skills to be productive in many trading disciplines. The program is all about experiential learning.
The speculation framework includes updating algorithmic models daily and reporting positions and pending positions. By requiring interns to watch the models, they learn to look out over the trading time horizon. They also obtain an understanding of how volatility drives the market by building a historical volatility model.
They also learn applied economics. If the economy produces a set of data, what happens to the dollar and the other currencies in our book? The interns study a weekly trading calendar and are expected to anticipate market movement during the week based on economic data. Interns are shown how to trade (or not trade) the data announcement.
Part of this is developing correlation models to learn how markets react to each other. They also develop basic trading plans using “If, then, unless” logic. They learn how to trade with the trend and what signs indicate a trend is becoming exhausted.
Interns also learn to create and maintain a trading diary to be updated daily with analysis of the day’s trading activity. Every trade is analyzed for profit/loss, account leverage and return on risk capital. The diary includes a checklist of critical technical and fundamental information for the trading day ahead.
The trader also learns to accept compliance results if he or she violates the trading plan. Mistakes were many. Failure to exit a trade at the trend cross, trading the wrong currency, initiating trades prior to a confirmed cross and fat fingered mistakes were just a few. Compliance reports are issued daily.
Finally, traders had to report results each afternoon and learn to live with them.
This summer there were three simulation traders, two compliance analysts, one web master and one overall summer manager. Following are the simulation speculation parameters for the traders:
Currencies: EUR, GBP, CAD
Size: 20,000 maximum
Daily stop ($): $75
Time frame: 8 to 11:30 a.m. (CDT), Monday – Thursday
Trend trade: With trend only, as per individual trading plans
No trader has produced 12 consecutive positive days within their plan, which is required to graduate to real money. However, it can help one learn to trade during a hugely volatile summer, including Brexit, and one also can learn how to discuss their books with other traders, such as former students from Geneva Trading, Uniper Global Commodities and the Gelber Group in Chicago. “Performance report” (below) shows the returns by a single trader as well as the entire team.
MMspire functions as a mentorship program with help from professional traders, risk managers, web designers and compliance directors from our partner network.
There are 34 members of our advisory board active in helping the internship team directly and through job placement. The interns must become student members of the Chartered Financial Analyst (CFA) designation and use the CFA for additional learning and networking opportunities.
MMspire’s models take the trend from a short harmonic exponential moving average (EMA) pair and enter trades when an EMA cross occurs. These models are intended to be executed by inexperienced students, so delayed entries are employed. We execute only once a day at the optimal time to execute based on backtested results.
Entering and exiting the trade is not only trend dependent, it is volatility dependent. All models use volatility triggers. For example, it doesn’t trade below a certain volatility level. It also uses volatility to determine exits; the model uses a limit and stop loss at one volatility level, but exits only at trend reversals at another level (see “Volatility’s role,” Right).
“Euro trades” (below) shows how the winter model executed in the euro with a short EMA pair (two- and four-period).
Using this type of short EMA pair model was distracting for the interns. Almost every day, there was a model data update, a text message to write and an e-mail to send. The interns spent so much time accomplishing these tasks that it was difficult to attempt enhanced returns. This provided enough logistical nightmares to simulate a real environment. This short EMA pair model was too demanding on the intern so we changed it.
The goal is for the interns to become proficient in managing money based on the model and confident they can improve on the model when presented with key fundamental and technical data.
Interns began trading the short-term EMA models in February. These models were backtested by several of the author’s former DePaul students. As expected, historical model results were more impressive than actual trading results (see “Model improvements,” below).
The program has provided vital insights into how best to motivate students, encouraging self-directed learning and inspiring the kind of passion for trading that is essential to long-term success. Allowing a discretionary trading plan rather than just simple model execution inspired a fascination with the markets.
Demanding adherence to a trading plan and detailed daily analysis of strategy instilled discipline and demonstrated that becoming a good trader requires not only an understanding of the mechanics of the market, but psychological mastery over the inevitable forces of fear and greed. Daily P/L reporting on our website along with audits of trading logs forced brutal honesty about individual failures and an acceptance of personal responsibility for mistakes. It also satisfied the ubiquitous millennial obsession with constant feedback from management. All told, the experience has given us a roadmap for the future of MMspire and created a new set of students who have learned to be inquisitive about the world’s financial markets.