Systematic and Discretionary Hedge Funds: Classification and Performance Comparison
26 Pages Posted: 29 Dec 2018
Date Written: December 2, 2018
In this paper we introduce an approach to building classifiers that bifurcate hedge funds into systematic and discretionary funds and evaluate their performance. This approach makes use of textual analysis and statistical learning methods that are free from subjective judgement of investment strategies. In our empirical study, we find that a random forest classifier yields the highest accuracy ratio, and that the funds classified as systematic, on average, result in higher raw returns, Sharpe ratios, and factor-adjusted returns than their discretionary counterparts. A bootstrap analysis also shows that the standardized alphas of a large portion of systematic and discretionary funds are statistically significantly different from zero, suggesting such performance is due to fund managers’ authentic investment skills, rather than their luck. Nonetheless, we find that systematic Equity Hedge funds are to be preferred to their discretionary counterparts because the standardized alphas of the former stochastically dominate those of the latter.
Keywords: Bootstrap Analysis, Random Forest, Statistical Learning, Textual Analysis
JEL Classification: G11, G14, G23, C38
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