Practical Applications of Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance

Practical Applications Summary Quantitative investing, which deploys machine learning and other algorithms, now more or less dominates financial markets. In this environment, it9s useful to step back and compare the performance and risk exposures of discretionary and systematic hedge fund managers. Many allocators to hedge funds, large and small alike, avoid allocating to systematic funds, either partially or entirely, believing them to be difficult to understand, to offer less transparency, and to deliver worse performance due to the use of data from the past. These reasons seem to be consistent with “algorithm aversion”—a distrust of systems. In their article Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance, published in the Summer 2017 issue of The Journal of Portfolio Management , Campbell R. Harvey, Sandy Rattray, Andrew Sinclair, and Otto van Hemert compare the past performance of systematic funds with their discretionary counterparts. They show that, after adjusting for volatility and factor exposures, the lack of confidence in systematic funds is not justified.