Systematic and Discretionary Hedge Funds: Classification and Performance Comparison

31 Pages Posted: 27 Sep 2021 Last revised: 4 Jan 2022

See all articles by Hui-Ching Chuang

Hui-Ching Chuang

Yuan Ze University - College of Management

Chung‐Ming Kuan

National Taiwan University

Date Written: March 25, 2021

Abstract

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 the subjective judgment 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 excess returns than their discretionary counterparts. After controlling for the false discovery rate, we find that systematic funds are preferred to their discretionary ones because a higher portion of positive alpha (skilled) funds are systematic funds. The skilled funds' alpha average is larger for systematic funds than for discretionary funds across all categories and variant observable and unobservable factor models we considered.

Keywords: False discovery rate, Random forest, Statistical learning, Textual analysis

JEL Classification: C63, G11, G14, G23

Suggested Citation

Chuang, Hui-Ching and Kuan, Chung‐Ming, Systematic and Discretionary Hedge Funds: Classification and Performance Comparison (March 25, 2021). Available at SSRN: https://ssrn.com/abstract=3912348 or http://dx.doi.org/10.2139/ssrn.3912348

Hui-Ching Chuang (Contact Author)

Yuan Ze University - College of Management ( email )

135, Yuan-Tung Rd.
Taoyuan, 320
Taiwan
886-972-735-021 (Phone)

Chung‐Ming Kuan

National Taiwan University ( email )

1 Sec. 4, Roosevelt Road
Taipei 106, 106
Taiwan

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
42
Abstract Views
319
PlumX Metrics