i want to use yourqueston to talk about signal systems in general, because i think it can inform signal research. When you look at the large basket of characteristics that you've compiled overtime, how many of those signals or characteristics do you think would fall under traditional or classifications? For example, gross profitability would be a profitability or quality factor, as an example. The brief answer is something like 50 % fall under typical factor classification. Those signals fall under familiar rubrics like value size, account in conservatism, investment conservatism, profitability, earnings ond revenue growth.
Vivek Viswanathan is the Head of Research at Rayliant Global, a quantitative asset manager focused on generating alpha from investing in China and other inefficient emerging markets.
Our conversation circles around three primary topics. The first is the features that make China a particularly attractive market for quantitative investing and some of the challenges that accompany it. The second is Vish’s transition from a factor-based perspective to an unconstrained, characteristic-driven one. Finally, the critical role that machine learning plays in managing a characteristic-driven portfolio.
And at the end of the conversation we are left with a full picture of what it takes to be a successful, quantitative investor in China.
I hope you enjoy my conversation with Vivek Viswanathan.