This episode is all about performance. Our hosts discuss “what have you done for me lately?” through the lens of alternative investment, in particular - private equity, the j-curve, capital calls, and capital returns. Listen in.

Developing reliable and intuitive interpretation is essential for the application of machine learning to investing. This presentation discussed a framework for decomposing any machine learning model into linear, nonlinear, and interaction effects that drive both prediction and performance. With a case study of predicting US large cap stock returns, this presentation showed how the "Model Fingerprint" tool enables practitioners to summarize key characteristics, similarities and differences among different models, thereby enhancing their understanding of the market.

In this revealing episode, hosts Bill Kelly, CAIA CEO and Steven Novakovic, Managing Director, CAIA Curriculum discuss the evolution of allocating alternative investments as a science or art — or both?! Listen in!

Asset managers have struggled to apply machine learning to generate trading signals successfully. Instead, applying machine learning to determine the probability of profit of existing trading signals is very fruitful - this is Corrective AI. Taking this one step further, we developed Conditional Portfolio Optimization, a portfolio optimization technique that adapts to market regimes via machine learning. Applications on portfolios in vastly different markets suggest that CPO can outperform traditional optimization methods under varying market regimes.

Hosts Bill Kelly, CAIA CEO and Steven Novakovic, Managing Director, CAIA Curriculum, discuss ways in which the CAIA curriculum relates to the real world of an industry practitioner. Listen in!