Building a sensitivity-based portfolio selection models

Huiming Zhang*, Junzo Watada, Ye Li, You Li, Bo Wang

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Sensitivity Analysis is a method to evaluate the influence of each variable change. In portfolio selection model, it is essential to evaluate the sensitivity of each stock or security return rate in investment decision making. Investors look for selecting stable stocks or securities. For this purpose, sensitivity analysis should play a pivotal role. It is important for the decision-making to get both sensitivity and stability of each selection. This paper proposes a new portfolio-selection model (PSM) called the sensitivity-based portfolio selection models (SPSM). The SPSM model will focus on the sensitivity of the selected portfolio. In order to analyze the sensitivity of portfolio selection models, a sensitivity analysis will be introduced for calculating out insensitive stocks or securities with maximum return and minimum risk. Abstract environment.

    Original languageEnglish
    Title of host publicationSmart Innovation, Systems and Technologies
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages673-681
    Number of pages9
    Volume39
    ISBN (Print)9783319198569
    DOIs
    Publication statusPublished - 2015
    Event7th KES International Conference on Intelligent Decision Technologies, KES-IDT 2015 - Sorrento, Italy
    Duration: 2015 Jun 172015 Jun 19

    Publication series

    NameSmart Innovation, Systems and Technologies
    Volume39
    ISSN (Print)21903018
    ISSN (Electronic)21903026

    Other

    Other7th KES International Conference on Intelligent Decision Technologies, KES-IDT 2015
    Country/TerritoryItaly
    CitySorrento
    Period15/6/1715/6/19

    Keywords

    • Portfolio selection model
    • Sensitivity analysis
    • Value at risk (VaR)

    ASJC Scopus subject areas

    • Computer Science(all)
    • Decision Sciences(all)

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