Skip to main content

Main menu

  • Home
  • Current Issue
  • Past Issues
  • Videos
  • Submit an article
  • More
    • About JFDS
    • Editorial Board
    • Published Ahead of Print (PAP)
  • IPR logos x
  • 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 Financial Data Science
  • IPR logos x
  • About Us
  • Journals
  • Publish
  • Advertise
  • Videos
  • Webinars
  • More
    • Awards
    • Article Licensing
    • Academic Use
  • Sample our Content
  • Request a Demo
  • Log in
The Journal of Financial Data Science

The Journal of Financial Data Science

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

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

Introducing Objective Benchmark-Based Attribution in Private Equity

Sidney C. Porter and Sheridan Porter
The Journal of Financial Data Science Winter 2019, 1 (1) 130-140; DOI: https://doi.org/10.3905/jfds.2019.1.1.130
Sidney C. Porter
is the chief data scientist at FEV Analytics Corp in Kirkland, WA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sheridan Porter
is the chief product officer at FEV Analytics Corp in Kirkland, WA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Info & Metrics
  • PDF (Subscribers Only)
Loading

Click to login and read the full article.

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

Abstract

Private-equity asset owners seeking to reduce downside risk and increase upside probability would logically benefit from indexing prospective asset managers by their skill. However, theoretical deficiencies and a lack of rigorous market calibration prevent the metrics and techniques commonly used in private equity from isolating manager skill. In this article, the authors introduce a new conceptual framework for a repeatable decomposition of private equity returns that disambiguates the quantification of manager skill. Modern proxy benchmarks are a key component of the framework for their definition of systemic returns specific to the target asset. They satisfy the fundamental properties of an index (systematic, transparent, and investable) suggested by Andrew Lo and the CFA Institute’s SAMURAI criteria for a valid benchmark. However, the authors propose that the integrity of the decomposition requires that the benchmark’s similarity (to target) and its stability be systematically derived, measured quantities. The authors discuss these two new properties in conjunction with the technology that enables the construction of modern proxy benchmarks and their active management over time. With systemic returns thus defined, excess returns against the modern proxy benchmark are attributed to dynamic elements under the control of the manager, which the authors define as manager alpha. Systemic returns in excess of a broad/policy benchmark are deemed static elements. Static elements measure the portion of returns attributable to size and sector selection, in which a manager tends to specialize and which are known to the limited partner investor prior to investment. Although both static and dynamic elements contribute active returns to the investment, it is the dynamic elements-alpha-that should merit attention (and high fees) from limited partners.

  • © 2019 Pageant Media Ltd
View Full Text

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 Financial Data Science: 1 (1)
The Journal of Financial Data Science
Vol. 1, Issue 1
Winter 2019
  • Table of Contents
  • Index by author
  • Complete Issue (PDF)
Print
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 Financial Data Science.

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.
Introducing Objective Benchmark-Based Attribution in Private Equity
(Your Name) has sent you a message from The Journal of Financial Data Science
(Your Name) thought you would like to see the The Journal of Financial Data Science web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Introducing Objective Benchmark-Based Attribution in Private Equity
Sidney C. Porter, Sheridan Porter
The Journal of Financial Data Science Jan 2019, 1 (1) 130-140; DOI: 10.3905/jfds.2019.1.1.130

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
Introducing Objective Benchmark-Based Attribution in Private Equity
Sidney C. Porter, Sheridan Porter
The Journal of Financial Data Science Jan 2019, 1 (1) 130-140; DOI: 10.3905/jfds.2019.1.1.130
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo LinkedIn logo Mendeley logo
Tweet Widget Facebook Like LinkedIn logo

Jump to section

  • Article
    • Abstract
    • PROPERTIES OF MODERN PROXY BENCHMARKS
    • BENCHMARKING TECHNOLOGY
    • APPROACH
    • FRAMEWORK FOR DECOMPOSITION OF RETURNS
    • APPLICATION OF MODERN BENCHMARK-BASED ATTRIBUTION TO MANAGER EVALUATION
    • BENCHMARK-BASED ATTRIBUTION WITHIN AN OBJECTIVE MEASUREMENT FRAMEWORK
    • CONCLUSION
    • ENDNOTES
    • REFERENCES
  • 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
0207 139 1600
 
NEW YORK
41 Madison Avenue, 20th Floor, New York, NY 10010
646 931 9045
pm-research@pageantmedia.com

Stay Connected

  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

MORE FROM PMR

  • Home
  • 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

© 2021 Pageant Media Ltd | All Rights Reserved | ISSN: 2640-3943 | E-ISSN: 2640-3951

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