English  |  正體中文  |  简体中文  |  Items with full text/Total items : 63276/95973 (66%)
Visitors : 4906062      Online Users : 400
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/51572

    Title: 臺灣加權股價指數避險績效比較:雙變量韋伯分配之應用
    Other Titles: Comparison on hedging performance with Taiwan weighted stock index: application for bivariate Weibull distribution
    Authors: 吳沛澄;Wu, Pei-chen
    Contributors: 淡江大學財務金融學系碩士班
    Keywords: 避險績效;避險比率;雙變量對數常態分配;雙變量韋伯分配;Hedging performance;Hedging ratio;Bivariate Weibull Distribution;Bivariate Longnormal Distribution
    Date: 2009
    Issue Date: 2010-09-23 15:25:53 (UTC+8)
    Abstract: 本研究應用雙變量韋伯分配右偏分配型態,以最大概似函數估計法估計台灣加權股價指數期貨價格與現貨價格在避險策略下之避險比率探討。文中進一步探討單變量韋伯與雙變量韋伯分配的性質。在研究中以(OLS)最小平方法、GARCH(1,1)常態分配模型、雙變量對數常態分配進行避險績效之比較,來驗證韋伯分配模型的穩健性。
    This study uses the bivariateWeibull distribution model of the distributed of right, using the maxima likelihood estimation to calculate the hedging ratio under the hedging strategies of Taiwan weighted stock index price, predicting better result of the hedging and hedging performance. Going more into the depths of the characteristics of the Weibull distribution method, this study also adds the (OLS) least square method and the GARCH(1,1) normal distribution model, bivariate lognormal distribution modelto the comparison of hedging performance, proving the toughness of the Weibull distribution model.
     The resources date from the 5th of January1999, to 31st of December 2009. The results show that using the Weibull distribution model and least square method leads to better results when calculating the hedging ratio and hedging performance, with the GARCH(1,1) normal distribution model and bivariate lognormal distribution model following behind. Therefore, when calculating the hedging ratio, considering the Weibull distribution model will produce a better hedging performance.
    Appears in Collections:[財務金融學系暨研究所] 學位論文

    Files in This Item:

    File SizeFormat

    All items in 機構典藏 are protected by copyright, with all rights reserved.

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