•  English
    • Persian
    • English
  •   Login
  • Ferdowsi University of Mashhad
  • |
  • Information Center and Central Library
    • Persian
    • English
  • Home
  • Source Types
    • Journal Paper
    • Ebook
    • Conference Paper
    • Standard
    • Protocol
    • Thesis
  • Use Help
View Item 
  •   FUM Digital Library
  • Fum
  • Articles
  • Latin Articles
  • View Item
  •   FUM Digital Library
  • Fum
  • Articles
  • Latin Articles
  • View Item
  • All Fields
  • Title
  • Author
  • Year
  • Publisher
  • Subject
  • Publication Title
  • ISSN
  • DOI
  • ISBN
Advanced Search
JavaScript is disabled for your browser. Some features of this site may not work without it.

ENHANCEMENT OF THE APPLICABILITY OF MARKOWITZ\'S PORTFOLIO OPTIMIZATION BY UTILIZING RANDOM MATRIX THEORY

Author:
Zhidong Bai
,
Huixia Liu
,
Wing-Keung Wong
Year
: 2009
DOI: 10.1111/j.1467-9965.2009.00383.x
URI: https://libsearch.um.ac.ir:443/fum/handle/fum/2153570
Collections :
  • Latin Articles
  • Download: (455.2Kb)
  • Show Full MetaData Hide Full MetaData
  • Statistics

    ENHANCEMENT OF THE APPLICABILITY OF MARKOWITZ\'S PORTFOLIO OPTIMIZATION BY UTILIZING RANDOM MATRIX THEORY

Show full item record

contributor authorZhidong Bai
contributor authorHuixia Liu
contributor authorWing-Keung Wong
date accessioned2020-03-16T03:48:24Z
date available2020-03-16T03:48:24Z
date issued2009
identifier otherLerNhzOwX_iEK9DHCir8liB0LpoZlSkkKnIjYAzHOFXaaOJzw1.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/2153570
formatgeneral
languageEnglish
titleENHANCEMENT OF THE APPLICABILITY OF MARKOWITZ\'S PORTFOLIO OPTIMIZATION BY UTILIZING RANDOM MATRIX THEORY
typeJournal Paper
contenttypeFulltext
contenttypeFulltext
identifier padid14648560
identifier doi10.1111/j.1467-9965.2009.00383.x
coverageAcademic
pages639-667
journal volume19
journal issue4
filesize465978
citations0
  • About Us
نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
DSpace software copyright © 2019-2022  DuraSpace