Major: Mathematics with minors in Computer Science, Actuarial Science, and Business
Mentor: Paul Wagoner
Can big data make big money?
Undergraduate researcher Reilley Luedde hopes to find out through math, data analysis, business acumen
The title of Reilley Luedde’s research project is “Relating Trade Conditions and Behavior of Currency Markets Using Technical Analysis,” which is another way of saying he’s using big data to try to make big money. Luedde is working to find a system or algorithm that produces profits over the long run in the currency market.
The currency market functions much like the stock market in that traders buy and sell currencies from around the world, trying to take advantage of shifting exchange rates to make a profit.
Luedde, who is majoring in Mathematics and minoring in Computer Science, Actuarial Science, and Business, initiated the project following his own academic interests. He presented his idea to a coding club, where he found research partners Anthony Simard and Chris Keefe. The trio then went to The W. A. Franke College of Business to find a professor willing to mentor them. There they teamed up with Assistant Professor of Practice Paul Wagner.
Their project includes gathering historical information about market activity and looking for patterns.
“We’re essentially building models that tell us when to buy and sell a certain asset,” Luedde said. “Right now, we have what are called indicators—basically recalculations of the price of the assets. So a moving average, for example, is one indicator. And that averages prices over a certain period, for example, over the last 20 days. And then when another day comes around, it takes the last 20 days, starting from the new day. So it’s like a constant window that is moving as the price changes.”
Luedde has been working to translate these indicators into the Python programming language in preparation for data analysis.
“I’ve also been doing a little bit of research to learn what is a profitable system, what isn’t a profitable system and what might be a red herring—something that seems very good on the outside, but actually isn’t.”
The work Luedde and the team are doing represents a financial trading discipline called technical analysis, which is essentially using patterns in price and indicators to predict future price.
“If you can predict future price with some sort of reliability, then that means you can extract some sort of profit,” Luedde explained.
It’s a field he wants to explore in graduate school.
“I want to get into a quantitative engineering or quantitative finance master’s program so I figured I should get some research experience before applying to grad school,” he said.
It’s too soon to say if the research partners have successfully mixed the secret data sauce for profit, but the experience alone has been worth the hard work, Luedde said.
“I’ve learned about how research is done,” he said. “I’m expanding my skill set and I’m learning new things.”
He aspires to be a quantitative trader on Wall Street, “which is somebody who does pretty much exactly what we’re doing, except with a lot more math.”
Luedde and his partners will be presenting the results of their research at the upcoming Undergraduate Symposium.
In the meantime, they’re discussing the ethics and legalities involved, should they find a successful formula, such as whether they should share the details or keep the information private.
“That’s something we’ve been thinking about. And that’s a bridge we’re going to cross if it happens.”