Journal of Asset Management Impact Factor & Information

Publisher: Palgrave Macmillan

Journal description

Each issue of the Journal of Asset Management publishes detailed, authoritative briefings, analysis, research and reviews by leading experts in the field, to keep subscribers up to date with the latest developments and thinking in asset management.

Current impact factor: 0.00

Impact Factor Rankings

Additional details

5-year impact 0.00
Cited half-life 0.00
Immediacy index 0.00
Eigenfactor 0.00
Article influence 0.00
Website Journal of Asset Management website
ISSN 1479-179X
OCLC 225158833
Material type Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Palgrave Macmillan

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 18 months embargo
  • Conditions
    • Pre-print on personal and employers websites, a free public pre-print server
    • Pre-print must state where article has been submitted
    • Must change to accepted by if accepted
    • Once published must update acknowledgement with set statement (see policy)
    • Author's version only
    • Post-print on institutional repository or funding body's repository
    • Must be clearly identified as authors post-peer-review, pre-copy-edit version
    • Must link to publisher version
    • Publisher copyright must be acknowledged with set statement (see policy)
    • Please see link below for list of journals not covered by this policy
  • Classification
    ‚Äč yellow

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: We propose a robust portfolio optimization approach based on Value-at-Risk (VaR) adjusted Sharpe ratios. Traditional Sharpe ratio estimates based on limited historical return data are subject to estimation errors. Portfolio optimization based on traditional Sharpe ratios ignores this uncertainty in parameter estimation from historical data and is therefore not robust. In this paper, we propose a robust portfolio optimization framework that selects the portfolio with the largest worse-case-scenario Sharpe ratios. We show that this framework is equivalent to maximizing the Sharpe ratio reduced by the VaR of the Sharpe ratio and highlight the relationship between the VaR-adjusted Sharpe ratios and other modied Sharpe ratios proposed in the literature. In addition, we present both numerical and empirical results comparing optimal portfolios generated by the approach advocated here and those generated by alternative optimization approaches.
    Journal of Asset Management 11/2013; 14(5):293-305. DOI:10.2139/ssrn.2146219