• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • 1
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

台灣政府債券期貨避險效果之研究

謝作治 Unknown Date (has links)
本研究資料期間自2004年1月2日至2005年12月13日止,擷取政府債券期貨收盤價及10年期最具流動性之政府債券收盤價資料進行整理,2004年1月2日~2005年6月30日為樣本內期間,2005年7月1日~2005年12月13日為樣本外期間。以簡單避險法、最小平方法(價格)模型、最小平方法(報酬)模型及GARCH 模型之避險比率,應用於樣本外期間的避險。實證結果如下:避險績效方面,日資料無論何種模型均未降低其報酬率之波動度,週資料而言各模型均可降低原公債現貨之報酬波動度,其中以OLS(return)較佳,但避險成效不彰。日資料避險比率最小為OLS(報酬)模型,週資料避險比率最小為OLS(價格)模型。就報酬而言,無論日資料及週資料,各種避險模型所作之避險,均降低其報酬率,換言之,未作避險動作之報酬率最佳。 / The main purpose of this paper is to examine the hedging effectiveness of the Taiwan government bond futures under several hedging models. These models are Naive, OLS-reward, OLS-level and GARCH. The daily data is from January 2004 to December 2005. The in-sample data is from January 2, 2004 to June 30,2005. The out-of-sample one is from July 1, 2005 to December 13,2005. The hedging porformance is measured by the decreasing degree of portfolio variance.The empirical results show as follows:1. OLS(return)model has the better hedge performance from weekly data. 2.The smallest hedge ratio is OLS(reward)from daily data, and it’s OLS(level)from weekly data. 3.The reward is highest without hedge

Page generated in 0.0556 seconds