Quantitative Research & Trading

Quantitative Research & Trading

​Quants is profoundly transforming the investment industry. The grizzled Wall Street traders of public perception are being deposed by young, brilliant mathematical minds. As financial securities have become increasingly complex, demand has grown rapidly for people who can use mathematical models to prices these securities, generate profits and reduce risk – enter the quant.

Quant analysts apply mathematical and statistical models in the sell-side for derivatives pricing and risk management, as well as the buy-side for statistical arbitrage, algorithmic trading and quantitative investment trading. Harnessing the power of computer science and vast data-sets to make investment decisions is no mean feat. In the words of Jim Simons, Renaissance Technologies founder and leader of the quant revolution,  The system is always leaking, and we keep having to add water to keep it ahead of the game.” The ‘quant king’ is no stranger to success. Since 1988, Renaissance Technologies has generated over $100bn in trading profits – more than any other hedge fund in history.

For decades, investors imagined a day when data-driven traders would dominate financial markets. That time has come – the quant hedge fund sector is experiencing significant growth. “Over the past decade the results of systematic quantitative investing have been undeniable,” says Philippe Jordan, president of CFM, an international quant hedge fund. The growth of Two Sigma, one of the leaders of the quant hedge fund industry, is also emblematic of the shift away from traditional hedge fund strategies. The New York-based firm’s assets have swelled from about $6bn in 2011 to more than $50bn in 2017, putting it roughly on par with the established quant powerhouses such as Renaissance Technologies and DE Shaw. Barclays analysts last summer estimated that quant hedge funds, or quant strategies within bigger hedge fund groups, managed about $500bn.

During unpredictable times, quants apply mathematical and statistical models to the most obscure financial and risk management problems. In 2018, the algorithms behind trend-following quants struggled to react fast enough to market volatility caused by President Trump’s tweets and US-China trade tensions, alongside other political maelstroms such as Brexit. In response, analysts at JP Morgan have created and coined the Volfefe Index to predict how “a broad swaths of assets from single-name stocks to macro products have their price dynamics beholden to a handful of tweets”.

As innovation and new technology move the financial services industry forward, there is an increasing technical demand on quants that will make it harder for firms to find the right talent. Selby Jennings has partnered with QuantMinds Americas to explore these talent challenges and discuss how firms can secure top quant talent in a competitive market. Looking at the future of quants talent, its clear they need to have a high level of quantitative skill, alongside computer science ability, topped off with true business understanding and soft skills to work with the trading desk to implement their solutions. This year Selby Jennings was named by HFM Global as the Best Hedge Fund Recruiter, emphasizing our commitment to help our clients secure top quant talent. The future looks bright for the quantitative hedge fund industry, with $1tn of assets under management this year, it's a great time to be a quant.

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