Skip to main content

Main menu

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

The Journal of Wealth Management

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

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

Portfolio Optimization Strategy for Concentrated Portfolios: Models and Time Horizons

Sarah J. Campbell, James Chong, William P. Jennings and G. Michael Phillips
The Journal of Wealth Management Fall 2018, 21 (2) 39-54; DOI: https://doi.org/10.3905/jwm.2018.1.064
Sarah J. Campbell
is a senior software engineer and algorithm specialist at MacroRisk Analytics in Pasadena, CA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James Chong
is a professor at California State University, Northridge, in Los Angeles, CA, and a research economist at MacroRisk Analytics in Pasadena, CA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
William P. Jennings
is professor emeritus at California State University, Northridge, in Los Angeles, CA, and chief investment strategist at MacroRisk Analytics in Pasadena, CA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
G. Michael Phillips
is a professor at California State University, Northridge, in Los Angeles, CA, and chief scientist at MacroRisk Analytics in Pasadena, CA
  • 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

Recent academic literature has noted that high conviction, or concentrated, portfolios (i.e., those with approximately 15 or fewer assets) often outperform larger, theoretically better diversified, portfolios. Recent research has also suggested that some of the gains from traditional portfolio optimization are in fact from the selection of relatively lower volatility stocks through the optimization process. To help wealth managers navigate the new uncertainty in the academic literature, the authors conduct a large-scale test of four approaches to portfolio construction that could be applied to high conviction portfolios. This study found that the traditional mean–variance-optimization approach worked well with very small portfolios but that a minimum Black Swan risk portfolio worked better when more holdings were included in the portfolios. The authors discuss the results and possible implications for winning approaches for wealth management.

TOPICS: Portfolio construction, analysis of individual factors/risk premia, tail risks, performance measurement

  • © 2018 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 Wealth Management: 21 (2)
The Journal of Wealth Management
Vol. 21, Issue 2
Fall 2018
  • 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 Wealth 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.
Portfolio Optimization Strategy for Concentrated Portfolios: Models and Time Horizons
(Your Name) has sent you a message from The Journal of Wealth Management
(Your Name) thought you would like to see the The Journal of Wealth 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
Portfolio Optimization Strategy for Concentrated Portfolios: Models and Time Horizons
Sarah J. Campbell, James Chong, William P. Jennings, G. Michael Phillips
The Journal of Wealth Management Jul 2018, 21 (2) 39-54; DOI: 10.3905/jwm.2018.1.064

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
Portfolio Optimization Strategy for Concentrated Portfolios: Models and Time Horizons
Sarah J. Campbell, James Chong, William P. Jennings, G. Michael Phillips
The Journal of Wealth Management Jul 2018, 21 (2) 39-54; DOI: 10.3905/jwm.2018.1.064
del.icio.us logo Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Tweet Widget Facebook Like LinkedIn logo

Jump to section

  • Article
    • Abstract
    • LITERATURE REVIEW
    • METHODOLOGY
    • RESULTS
    • CONCLUSIONS AND DISCUSSIONS
    • APPENDIX A
    • APPENDIX B
    • APPENDIX C
    • 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
United Kingdom
+44 207 139 1600
 
NEW YORK
41 Madison Avenue, New York, NY 10010
USA
+1 646 931 9045
pm-research@pageantmedia.com
 

Stay Connected

  • LinkedIn
  • 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
  • Log In
  • Update your profile
  • Give us your feedback

© 2022 Pageant Media Ltd | All Rights Reserved | ISSN: 1534-7524 | E-ISSN: 2374-1368

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