This sponsored story was produced in association with WorldQuant, LLC, not by MIT Technology Review editorial staff.
WorldQuant is a quantitative investment firm with a global perspective, so it makes sense that the Connecticut-based company would draw on talent both near and far.
In fact, talent development has been the backbone of WorldQuant since its founding in 2007. The company’s team of researchers, portfolio managers, and technologists now includes more than 450 professionals in 18 offices worldwide, reflecting its core belief that talent is global.
As WorldQuant grows, the company is retaining that global emphasis—both in its search for talent and in its support of philanthropic and academic endeavors. “We saw a great need to provide an accessible international simulation platform,” says Jeffrey Scott, director of WorldQuant’s Virtual Research Center. “Tremendous things can happen when you open the door to people from all backgrounds and locations.”
To that end, WorldQuant has created a proprietary modeling platform for those who want to pursue their interest in the area of financial trading models. Anyone interested in exploring this field can take part in the WorldQuant Challenge, an ongoing, worldwide competition for building “alphas”—mathematical models. Participants try to create high-performing algorithms for stock-price movement prediction and then vie for incentives such as an invitation to join WorldQuant’s Research Consultant program. The program provides a part-time, “learn and earn” consulting opportunity to qualified individuals and has appealed to numerous university students.
Some 30,000 people worldwide have taken part in the WorldQuant Challenge during the past three years. Although algorithmic work hinges on an understanding of mathematics, there’s no definitive academic background for a quantitative researcher, or “quant,” Scott says. “If I were to poll a dozen Research Consultants, I might find a dozen different majors reflected. And they encompass every STEM major—including all engineering disciplines, all math disciplines, the various sciences, technology including computer science, along with finance, economics, and business. So it’s a very wide net that’s cast.”
The year-round WorldQuant Challenge spawned a spinoff for American students: the Solve-a-thon at MIT, hosted by the MIT-based Solve program and MIT Technology Review over a two-month period, culminating in January 2016. Sponsored by WorldQuant, the Solve-a-thon at MIT attracted more than 700 contestants from 140-plus universities and colleges, who took part in training sessions to learn about finance and alphas, and then sought to build predictive models. Using WorldQuant’s WebSim platform, a Web-based financial market simulation tool, participants created their own alphas to try to predict future movements in the stock market. Throughout the competition, they amassed points for generating high-performing alphas, and the highest scorers earned cash prizes from MIT.
The overall winner was Song Wang, a financial engineering student at Baruch College in New York City. He scored more than 100,000 points, almost double the number of his closest competitor, by working “hard and smart,” says Scott. “He was creative in building unique ideas, and tried to build on previous success as well as looking into new areas of opportunity and new data elements. He was persistent and very creative with his ideas”—all qualities that are important in the world of quantitative finance.
WorldQuant plans to sponsor a second Solve-a-thon at MIT in September 2016. In addition, highly competitive global competitions with potential financial incentives also take place throughout the year, including seasonal “Alphathons.” Meanwhile, to learn more about creating alphas and training for a career as a “quant,” sign up any time at www.WorldQuantChallenge.com to take the WorldQuant Challenge.