Reflections – Quant Panel

-Nicholas Torres

On March 15th , 2018, the Wharton Hedge Fund Club hosted a Quant Panel in which representatives from Citadel, AQR, and Steven’s Capital Management discussed some of their quantitative strategies for the markets. The panel discussion began with the basic tasks that each of the members did on a daily basis being a “Quant”. A Quant’s main goal is to create an algorithm to achieve Alpha. In other words, they aim to use coding languages (Python, C++, etc.) to get a computer to trade based on a set of statistical predictions in order to beat the market return. One of the amazing things that algorithms are capable of is that they are able to take a certain strategy that a manager might create, and statistically tell the manager what the probability of return would be when used in a certain market given certain conditions. A manager is also able to create a strategy, and then run the algorithm on a simulator in any year all the way back to the 1940’s. This allows the manager to see how the algorithm would perform historically given certain conditions.

There are many different strategies that someone can utilize when they are creating algorithms. The main strategy that the panelists used was a market-neutral strategy. “A market-neutral strategy” is a type of investment strategy undertaken by an investor or an investment manager that seeks to profit from both increasing and decreasing prices in one or more markets, while attempting to completely avoid some specific form of market risk. This essentially means that the manager may buy shares of a particular stock, while also buying a put option on it at the same time. This way, no matter which way the share price moves, the manager is guaranteed to profit on one of his trades. Another prime example would be a difference in the price of the same stock on two different markets. If a manager sees that a certain company is selling at $100 on a certain exchange in a market while also selling at $98 on a different exchange in a different market, they will simply buy the stock for $98 in that market and sell it for $100 in the other market. This guarantees a profit and contains no risk.

The panelists described the obstacles they run into on a daily basis. First of all, most of the time they create an algorithm that performs exceptionally, it is usually discovered by another company and that drags down the return of that algorithm strategy. As a result, the managers have to constantly update and tailor their algorithms to make sure they are differentiating themselves in the market. Another obstacle they encounter is the amount of policies implemented by different countries on a daily basis. One of the panelists from AQR says that at least three times a week, a country in which her company has exposure in implements a new regulation which requires her to rewrite the algorithms to make sure they adhere to these new rules. When asked what students can do to stand out from the enormous wave of applicants for this sought-after sector, the panelists said to make sure to be efficient in coding language. Many of the panelists came from absolutely no financial background. Each one had a PhD in either Physics, Computer Science, or Mathematics. Being proficient in these areas will allow you to be recruited by certain quant funds. The financial knowledge can be obtained on the job or at home through books. The competition to get hired by one of these quant hedge funds has become extremely difficult; however, obtaining coding skills and being proficient in math will allow you to at least compete in this cut throat industry.