The New Kings of Wall Street

Much like death and taxes, a cold and rainy September afternoon in Ithaca, NY is a certainty of life. Seeking refuge from the torrential downpour, students all across campus scrambled back to their respective homes. Yet, inside of the newly-opened eHub workspace in Kennedy Hall, just off Tower Road, a gathering of undergraduate and graduate students chatted, settling in and preparing to learn more about one of the hottest topics on campus: algorithmic trading.

 

Sparkstone Analytics Executive Director Ryan Kishore, alongside his fellow co-founder, Analytics Director Rishab Gupta, was giving a presentation to a sizeable group of students on how to develop their own algorithmic trading strategy. This presentation was part of their bi-annual Sparkstone Trading Challenge, a competition where participants are given access to the Sparkstone database and tasked with developing their own trading strategy over the course of a month. The competition, much like Sparkstone, is a new addition to the already large financial presence on Cornell’s campus. Last semester, over 100 students partook in the competition, seeking prizes including dinner with employees at Optiver, a high frequency trading firm that has experienced growing success over the past few years.

 

“As the first major organization on campus to embrace quantitative finance and consolidate interested people, we are thrilled as we serve this growing curiosity," says Kishore when asked about the growing presence of quantitative trading on the Cornell campus. “We also notice that not too many people understand that quantitative finance has a large range of roles that can exist within the field. I am looking forward to students discovering what the spectrum looks like, whether it is algorithm design, factor modeling, or even low latency hardware design.”

 

Sparkstone Analytics is a small group of students that represents the growing interest in quantitative trading sweeping the campus and, more broadly, the finance industry. Over the past few years, numerous clubs and projects have sprung up across campus to satiate demand among students seeking to learn more about automated trading. What explains the billions of dollars institutional investors have moved to this new technology-driven form of investment?

Quant funds allocate investor capital to securities relying heavily on advanced quantitative analysis. The strategies employed by the fund managers rely on heavy mathematical and computer-generated algorithmic models built on data gathered from the past several decades. Many of the traders employed by these firms come from traditional STEM-heavy backgrounds, with some holding doctorates in mathematics and physics and others having strong engineering backgrounds. Take Two Sigma, for example: in their Manhattan office they employ nearly 800 researchers. Roughly 130 of them holding doctorates, and 6 are former Math Olympiad winners. These funds’ consistent performance derives from using its algorithms and mathematical models to sift through mammoth amounts of data, attempting to find relationships and trends that a regular fund manager may not. They don’t trade based on “gut feelings” but rather precise reasoning.

 

It only takes a brief look at the performance of actively-managed hedge funds over the past several years to see what causes the mass exodus of investors from their firms. Since 2009, actively-managed funds have been up roughly 3 percent, posting returns lower than those of the S&P 500 and equity dividends of the index during that time. According to Bloomberg, hedge funds in 2016 delivered returns of 1.2 percent, well below the S&P 500’s 7.6 percent return. These funds saw a resounding $25.2 billion withdrawn last July alone, facing a $55.9 to $106 billion outflow in 2016 overall as investors sought out larger returns.

 

Much of the frustration that has catalyzed the demise of hedge funds has come from the traditional “2 and 20” fee. 2 percent of the value of the fund is paid to the manager, regardless of whether it performs well, with an additional 20 percent pocketed from any profits the fund earns. When these firms posted gargantuan returns, investors could easily turn a blind eye. But lately, funds’ poor performance has caused investors to lash out against managers. Renowned investor Warren Buffett has even voiced his concern about the absurd fees in an interview with CNBC, saying that “two and twenty… borders on obscene.” A few of the most notorious hedge fund managers like Bill Ackman and Paul Tudor Jones have had to answer for the lackluster performance of their funds over the past few years. They have since begun cutting their fees and reevaluating their investment strategies in hopes of stopping the financial bleeding.

 

While active funds spent much of the past year dealing with investor backlash and poor performances, quant funds flourished. Over the past several years, roughly $7.9 billion has poured into funds that employ consistently-performing quantitative strategies, pushing the total amount of assets under management for quant funds up to $908 billion. According to Forbes, quant funds hauled in $113 billion over the past several years, making up 25 percent of total net gains brought in by the top 20 hedge funds over the course of their existence. Firms like Two Sigma, Renaissance Technologies, D.E. Shaw, and PDT Technologies have all enjoyed robust returns. Renaissance’s Equity Fund rose 4.6 percent last June, 3.8 percent higher than hedge funds globally. Two Sigma’s fund rose 12.6 percent through last year, versus 2.2 percent for hedge funds across the board according to Bloomberg. D.E. Shaw, considered one of the pioneers of quantitative finance, has consistent double-digit returns net of fees over the past several years. Some quant fund managers have achieved near celebrity status; top Wall Street investors have forked up to $1000 just to spend an evening with the “quant fund master”, Peter Mueller, of PDT Partners. His fund has seen annualized returns of roughly 18.5 percent since its inception.

 

While quant funds already outperform their competitors, some investors believe they have a long way to go before being widely trusted. Big name quant funds such as Systematica saw losses of $3.8 billion, or a resounding 11 percent drop in their flagship fund, while Cantab Capital saw its main quant fund drop nearly 8 percent. BlackRock recently reported that its quantitative hedge fund strategies suffered losses for 2016. Much of the industry’s hesitation towards quant funds stems from the great quant meltdown of 2007. In August 2007, quantitative hedge funds across the board faced monumental losses seemingly out of the blue. As one fund began to unwind, others followed quickly behind resulting in a massive sell-off by numerous quant funds. The surprise crash still lacks a suitable explanation, leading some to fear similar implosions will happen again and feeding into concerns about placing money in the hands of computers.

 

Despite their past inconsistencies, the beauty of quant funds lies in their capacity for evolution. They constantly develop new strategies, each one more sophisticated and utilizing more data than the previous, in hopes of generating larger, more consistent returns. Sparkstone’s Kishore believes that the superiority of human investors is beginning to decay: “This is a critical question with implications for anyone considering work in the finance industry. Ultimately, alpha generated by humans will diminish as computational techniques improve and thought processes are systematized,” he says in an interview. It seems that more and more actively-traded hedge funds are beginning to adopt quantitative strategies to bring back investors. Paul Tudor Jones, who was a key investor in the opening Two Sigma Partners in 2001, has laid off 15 percent of the workforce at his Tudor Investment Corp. and is working towards implementing quant-driven strategies in order to post higher returns. The rest of Wall Street is also following this trend, hiring some of the top talent from Silicon Valley in hopes of making their firms more competitive and appealing to investors.

 

While the past few years have seen humans take the backseat in many industries, finance may be the only frontier in which computers will never gain total control. Hedge fund managers, despite the absurd fees, are able to command so much by harnessing their ability to see things that a computer-generated algorithm may not, honing in on potentially lucrative investments. “Yet, we will not see a complete overtaking as there are certain roles and pattern recognition abilities that humans will continue to excel in the foreseeable future," Kishore says. Hedge fund managers can still sift through current events and make the appropriate trades to ensure his investors are protected. But hedge fund managers should not take too much comfort in their edge. Quantitative hedge funds are beginning to implement better artificial intelligence into their strategies, allowing them to seek out patterns that could not be detected with a mathematical formula. Take traders at BlackRock, who use satellite images of China’s largest cities to draw conclusions on China’s real estate industry. There has become a much greater emphasis on artificial intelligence’s implementation in these already tech-heavy funds. As AI evolves, quant funds can turn to machines to sift through millions of news articles and test models that make trades based on hypothetical world events, further diminishing the need for human intervention. Paul Tudor Jones said it best in an address to the remaining employees of his firm: “No man is better than a machine. And no machine is better than a man with a machine.”