![]() In an industry facing heightened competition, dulled growth, volatility, and significant fee pressure, $50 billion Two Sigma differentiates itself among hedge funds by utilizing machine learning and the scientific method to quickly forecast market moves to enhance returns, control risk, and arbitrage information about stocks. This explosion of alternative data has created an arms race among hedge funds hiring data scientists to dive into pools of data and use machine learning algorithms to extract insights or predictive signals in a fraction of the time and with greater accuracy than the human brain. ![]() The IDC estimates that the amount of digital data the world produces will reach 44 zettabytes (trillions of gigabytes) by 2020, an amount so big that if it was all put in iPad Air tablets, the stack would reach from earth to the moon more than six times over. Having been a client of Two Sigma’s, I wonder how accurate Two Sigma’s predictive algorithms can be in an uncertain market backdrop and as unprecedented events occur that machines have never encountered. Since founding Two Sigma Investments in 2001, statistician and computer scientist co-founders John Overdeck and David Seigel have sought to reinvent the investment management industry through the use of machine learning, distributed computing, and other technologies to develop cutting-edge systematic hedge fund strategies that deliver superior risk-adjusted returns for its clients. ![]()
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