The current and future profitability category encompasses almost every signal in existence besides size and value. Even low volatility positively predicts, presumably because firms that have growing earnings are less likely to exhibit market volatility as they are further away from default. There's an entire other class of signals, which includes everything from high frequency trading signals to short turm reversal and co skewness. But critically, this is a tax on me for quants. It aids in organizin our research. And i'm not the first person who realizes mc lean, pontiff and engelberg wrote a paper in 20 18 called anomalies and noose,. They found that stock return anomalies were six times higher on earnings asom
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.