Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/32116
Title: Hedge Fund Performance, Classification with Machine Learning, and Managerial Implications
Authors: Platanakis, E
Stafylas, D
Sutcliffe, C
Zhang, W
Issue Date: 1-Sep-2025
Publisher: Wiley
Citation: Platanakis, E. et al. (2025) 'Hedge Fund Performance, Classification with Machine Learning, and Managerial Implications', British Journal of Management, 36 (4), pp. 1835 - 1858. doi: 10.1111/1467-8551.70011.
Abstract: Prior academic research on hedge funds focuses predominantly on fund strategies in relation to market timing, stock picking and performance persistence, among others. However, the hedge fund industry lacks a universal classification scheme for strategies, leading to potentially biased fund classifications and inaccurate expectations of hedge fund performance. This paper uses machine learning techniques to address this issue. First, it examines whether the reported fund strategies are consistent with their performance. Second, it examines the potential impact of hedge fund classification on managerial decision-making. Our results suggest that for most reported strategies there is no alignment with fund performance. Classification matters in terms of abnormal returns and risk exposures, although the market factor remains consistently the most important exposure for most clusters and strategies. An important policy implication of our study is that the classification of hedge funds affects asset and portfolio allocation decisions, and the construction of the benchmarks against which performance is judged.
Description: Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/full/10.1111/1467-8551.70011#support-information-section .
URI: https://bura.brunel.ac.uk/handle/2438/32116
DOI: https://doi.org/10.1111/1467-8551.70011
ISSN: 1045-3172
Other Identifiers: ORCiD: Charles Sutcliffe https://orcid.org/0009-0001-0138-6975
ORCiD: Wenke Zhang https://orcid.org/0009-0001-0138-6975
Appears in Collections:Dept of Economics and Finance Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdfCopyright © 2025 The Author(s). British Journal of Management published by John Wiley & Sons Ltd on behalf of British Academy of Management. This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.370.53 kBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons