政大機構典藏:Item 140.119/64607

政大機構典藏

Menu Search
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


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/64607


    题名: 通貨膨脹風險、學習機制與策略性資產配置
    其它题名: Inflation Risk, Learning Mechanism and Strategic Asset Allocation
    作者: 張士傑;蔡政憲;黃雅文
    Chang, Shih-Chieh;Tsai, Cheng-Hsien;Huang, Ya-Wen
    贡献者: 風管系
    关键词: Time horizon;expected utility;volatility;risk averse;improvement rate
    日期: 2011-06
    上传时间: 2014-03-12 16:03:54 (UTC+8)
    摘要: Campbell and Viceira (2001) were the first to incorporate inflation risk into the optimal portfolio problem and found that the investor decreased the holding weights of long term bonds in the absence of inflation-linked underlying assets. Xia (2001) found that opportunity cost was significantly substantial when investors ignored the learning mechanism of uncertainty parameters and used the learning method to predict the parameter of the dynamics of stock price. In this study, we not only show that the learning process increases the utility value of terminal wealth, but also analyze the effect of learning process on the expected utility value of terminal wealth. The results are as follows. 1. Investment horizon, instantaneous volatility of inflation rate and risk attitude positively affects the learning process on the terminal wealth and its expected utility. The effects are more significant when the investment horizon, volatility and risk-averse attitude increase. 2. When volatility of the consumer price index and the estimation error increase, the learning ability enhance the expected wealth and utility. However, the improvement rate of utility decrease since investors becomes hardly learn from the inflation rate.
    關聯: 財務金融學刊, 19(2), 73-109
    数据类型: article
    显示于类别:[風險管理與保險學系] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    index.html0KbHTML21519检视/开启


    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing
    DSpace Software Copyright © 2002-2004  MIT &  HP  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈