Volume 18, No. 2, 2020 Case Study – Collective Defined Contribution Plans Seoyoung Kim View PDF… Read more
2020
Book Review: Smart(er) Investing – How Academic Insights Propel the Savvy Investor
Volume 18, No. 2, 2020 Book Review: Smart(er) Investing – How Academic Insights Propel the Savvy Investor by Elisabetta Basilico and Tommi Johnsen (Reviewed by Zachary Simon) View PDF… Read more
Using Machine Learning to Predict Realized Variance
Volume 18, No. 2, 2020 Peter Carr, Liuren Wu and Zhibai Zhang Volatility index is a portfolio of options and represents market expectation of the underlying security’s future realized volatility/variance. Traditionally the index weighting is based on a variance swap pricing formula. In this paper we propose a new method for building volatility index by… Read more
Dynamic Goals-Based Wealth Management Using Reinforcement Learning
Volume 18, No. 2, 2020 Sanjiv R. Das and Subir Varma We present a reinforcement learning (RL) algorithm to solve for a dynamically optimal goal-based portfolio. The solution converges to that obtained from dynamic programming. Our approach is model-free and generates a solution that is based on forward simulation, whereas dynamic programming depends on backward… Read more
Can Machines “Learn” Finance?
Volume 18, No. 2, 2020 Ronen Israel, Bryan Kelly and Tobias Moskowitz Machine learning for asset management faces a unique set of challenges that differ markedly from other domains where machine learning has excelled. Understanding these differences is critical for developing impactful approaches and realistic expectations for machine learning in asset management. We discuss a… Read more
On the Stability of Machine Learning Models: Measuring Model and Outcome Variance
Volume 18, No. 2, 2020 Vasant Dhar and Haoyuan Yu How do you know how much you should trust a model that is learned from data? We propose that a central criterion in measuring trust is the decision-making variance of a model. We call this “model variance.” Conceptually, it refers to the inherent instability machine… Read more
Practitioner’s Digest
Volume 18, No. 1, 2020 View PDF… Read more
Book Review: Nonlinear Time Series Analysis by Ruey S. Tsay and Rong Chen (Reviewed by Alireza Yazdani)
Volume 18, No. 1, 2020 Ruey S. Tsay and Rong Chen (Reviewed by Alireza Yazdani) View PDF… Read more
Case Study: Fair and Responsible Drug Pricing: A Case Study of Radius Health and Abaloparatide
Volume 18, No. 1, 2020 Qingyang Xu and Andrew W. Lo View PDF… Read more
Time-Series Variation in Factor Premia: The Influence of the Business Cycle
Volume 18, No. 1, 2020 Christopher Polk, Mo Haghbin and Alessio de Longis Factor cyclicality can be understood in the context of factor sensitivity to aggregate cash-flow news. Factors exhibit different sensitivities to macroeconomic risk, and this heterogeneity can be exploited to motivate dynamic rotation strategies among established factors: size, value, quality, low volatility and momentum… Read more