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Style analysis for diversified US equity funds

Style analysis for diversified US equity funds
Style analysis for diversified US equity funds
In this study we consider two methods of returns based style analysis for classification of investment styles for a single asset class, US Diversified Equity Funds. We extend Sharpe’s (1992) style Returns Based Style Analysis (RBSA) by forming style groups using cluster analysis and RBSA factors. We also introduce a parsimonious Best Fit Index (BFI) of style classification which explicitly acknowledges the existence of market segmentation and practitioner benchmarking. The methods provide complementary information about mutual fund returns. Both methodologies explain a significant proportion of the cross section of out of sample returns, but the BFI method performs better out-of-sample is more transparent and more closely aligned to investment practice.
1470-8272
170-185
McGroarty, Frank
693a5396-8e01-4d68-8973-d74184c03072
Mason, Andrew
3af84441-6899-4e78-8a3a-95803da96c49
Thomas, Steve
effeb4ca-ca6b-4b21-b399-4f56cecc5d31
McGroarty, Frank
693a5396-8e01-4d68-8973-d74184c03072
Mason, Andrew
3af84441-6899-4e78-8a3a-95803da96c49
Thomas, Steve
effeb4ca-ca6b-4b21-b399-4f56cecc5d31

McGroarty, Frank, Mason, Andrew and Thomas, Steve (2012) Style analysis for diversified US equity funds. Journal of Asset Management, 13, 170-185.

Record type: Article

Abstract

In this study we consider two methods of returns based style analysis for classification of investment styles for a single asset class, US Diversified Equity Funds. We extend Sharpe’s (1992) style Returns Based Style Analysis (RBSA) by forming style groups using cluster analysis and RBSA factors. We also introduce a parsimonious Best Fit Index (BFI) of style classification which explicitly acknowledges the existence of market segmentation and practitioner benchmarking. The methods provide complementary information about mutual fund returns. Both methodologies explain a significant proportion of the cross section of out of sample returns, but the BFI method performs better out-of-sample is more transparent and more closely aligned to investment practice.

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More information

Published date: 1 May 2012
Organisations: Centre for Digital, Interactive & Data Driven Marketing

Identifiers

Local EPrints ID: 301108
URI: http://eprints.soton.ac.uk/id/eprint/301108
ISSN: 1470-8272
PURE UUID: c16efbf0-1187-4a48-9cff-6ae48791882c
ORCID for Frank McGroarty: ORCID iD orcid.org/0000-0003-2962-0927

Catalogue record

Date deposited: 02 Mar 2012 16:20
Last modified: 08 Jan 2022 02:58

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Contributors

Author: Frank McGroarty ORCID iD
Author: Andrew Mason
Author: Steve Thomas

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