Skip to main content

Main menu

  • Home
  • Current Issue
  • Past Issues
  • Videos
  • Submit an article
  • More
    • About JPM
    • Awards
    • Editorial Board
    • Published Ahead of Print (PAP)
  • IPR Logo
  • About Us
  • Journals
  • Publish
  • Advertise
  • Videos
  • Webinars
  • More
    • Awards
    • Article Licensing
    • Academic Use
  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

User menu

  • Sample our Content
  • Request a Demo
  • Log in

Search

  • ADVANCED SEARCH: Discover more content by journal, author or time frame
The Journal of Portfolio Management
  • IPR Logo
  • About Us
  • Journals
  • Publish
  • Advertise
  • Videos
  • Webinars
  • More
    • Awards
    • Article Licensing
    • Academic Use
  • Sample our Content
  • Request a Demo
  • Log in
The Journal of Portfolio Management

The Journal of Portfolio Management

ADVANCED SEARCH: Discover more content by journal, author or time frame

  • Home
  • Current Issue
  • Past Issues
  • Videos
  • Submit an article
  • More
    • About JPM
    • Awards
    • Editorial Board
    • Published Ahead of Print (PAP)
  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

Detecting Performance Persistence in Fund Managers

Rajesh K. Aggarwal, Galin Georgiev and Jake Pinato
The Journal of Portfolio Management Winter 2007, 33 (2) 110-120; DOI: https://doi.org/10.3905/jpm.2007.674797
Rajesh K. Aggarwal
An associate professor of finance in the Carlson School of Management of the University of Minnesota, Minneapolis.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: raggarwal@csom.umn.edu
Galin Georgiev
A director at Pacific Alternative Asset Management Company in Irvine,CA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: ggeorgiev@paamco.com
Jake Pinato
An Associate at The Provident Group & Longship Capital in NewYork City.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: jpinato@provident-group.com
  • Article
  • Info & Metrics
  • PDF (Subscribers Only)
Loading

Abstract

A new approach for relative evaluation of fund managers within a portfolio (book) is based on the explicit positions of the funds and the positions of the overall portfolio. The approach decomposes each fund's return into beta and alpha components relative to the overall book. Tests of this book benchmark analysis on a portfolio of equity-based hedge funds during a 31-month period indicate its alphas are significantly more predictive than returns for short in-sample periods (six to nine months). This suggests that book benchmark alphas are a valuable quantitative tool for managing a portfolio of hedge funds with position-level transparency. While the analysis here is developed for a fund of hedge funds because of data considerations, the book benchmark concept is more general it can be used in any circumstances involving manager selection as long as there is position-level transparency.

TOPICS: Portfolio management/multi-asset allocation, manager selection, performance measurement

  • © 2007 Pageant Media Ltd

Don’t have access? Click here to request a demo

Alternatively, Call a member of the team to discuss membership options

US and Overseas: +1 646-931-9045

UK: 0207 139 1600

Log in using your username and password

Forgot your user name or password?
PreviousNext
Back to top

Explore our content to discover more relevant research

  • By topic
  • Across journals
  • From the experts
  • Monthly highlights
  • Special collections

In this issue

The Journal of Portfolio Management
Vol. 33, Issue 2
Winter 2007
  • Table of Contents
  • Index by author
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on The Journal of Portfolio Management.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Detecting Performance Persistence in Fund Managers
(Your Name) has sent you a message from The Journal of Portfolio Management
(Your Name) thought you would like to see the The Journal of Portfolio Management web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Detecting Performance Persistence in Fund Managers
Rajesh K. Aggarwal, Galin Georgiev, Jake Pinato
The Journal of Portfolio Management Jan 2007, 33 (2) 110-120; DOI: 10.3905/jpm.2007.674797

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Save To My Folders
Share
Detecting Performance Persistence in Fund Managers
Rajesh K. Aggarwal, Galin Georgiev, Jake Pinato
The Journal of Portfolio Management Jan 2007, 33 (2) 110-120; DOI: 10.3905/jpm.2007.674797
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Tweet Widget Facebook Like LinkedIn logo

Jump to section

  • Article
  • Info & Metrics
  • PDF (Subscribers Only)
  • PDF (Subscribers Only)

Similar Articles

Cited By...

  • No citing articles found.
  • Google Scholar
LONDON
One London Wall, London, EC2Y 5EA
United Kingdom
+44 207 139 1600
 
NEW YORK
41 Madison Avenue, New York, NY 10010
USA
+1 646 931 9045
reply@pm.research.com
 

Stay Connected

  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

MORE FROM PMR

  • News
  • Awards
  • Investment Guides
  • Videos
  • About PMR

INFORMATION FOR

  • Academics
  • Agents
  • Authors
  • Content Usage Terms

GET INVOLVED

  • Advertise
  • Publish
  • Article Licensing
  • Contact Us
  • Subscribe Now
  • Sign In
  • Update your profile
  • Give us your feedback

© 2023 With Intelligence Ltd | All Rights Reserved | ISSN: 0095-4918 | E-ISSN: 2168-8656

  • Site Map
  • Terms & Conditions
  • Privacy Policy
  • Cookies