Despite having moved on from a more traditional factor base approach to investing, you actually hold still some pretty strong views. There's this ongoing debate about whether should take an integrated approach or a mixed approach. The advantage of the mixing approach is you get dynamic active weights based on how confident you are about various stocks. If two signals agree on a stock's active weight, its active weight will stay the same. But they disagree, the active weight will decline moreover if two signals want to more than zero out a stock. And by the way, bottom up expecto return models o behave like this too.
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.