English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62805/95882 (66%)
造访人次 : 3931104      在线人数 : 564
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109380


    题名: Market Collective Wisdom Discovery for Portfolio Investments
    作者: Juszczuk, Przemys law;Kaliszewski, Ignacy;Podkopaev, Dmitry;Shih, Hsu-Shih Shih
    关键词: Multiple criteria decision making;investment portfolio;knowledge discovery
    日期: 2016
    上传时间: 2017-01-17 11:15:58 (UTC+8)
    出版者: 淡江大學出版中心
    摘要: The goal of numerous investing strategies, as opposed to hedging strategies, is “to beat the market”, i.e. to secure returns higher than those guaranteed by tracking market indices. In order to achieve this goal, one needs to identify key factors which drive markets and cause security prices to fluctuate. We assume that distinctive key market factors exist, though it is not known how such factors correlate and aggregate, and eventually push a market from one quotation to another. In other words, we purport that at a given time there is the collective wisdom in a market
    which shapes the collective investment pattern for the future. We engage ourselves to reverse engineer that wisdom. Specifically, we attempt to reverse engineer it from market returns (which we interpret as collective market wisdom embodiment) with the use of the notions of vectors of concessions and compromise half lines, recently introduced into Multiple Criteria Decision Analysis. We illustrate our approach with preliminary calculations for selecting portfolios of international investment funds.
    關聯: International Journal of Information and Management Sciences 27 (2), pp.87-102
    DOI: 10.6186/IJIMS.2016.27.2.1
    显示于类别:[資訊與管理科學期刊] 第27卷第2期

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html全文連結0KbHTML620检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈