臺灣博碩士論文加值系統

本文採用台灣期貨交易所金融指數期貨與金融類股票期貨，以比較Naïve避險、OLS估計式、時變MA估計式、時變EWMA(λ=0.94)、時變EWMA(λ=0.96)以及時變的雙變量GARCH模型等六種避險比率之避險績效。本文也比較｢金融指數期貨對金融類股票期貨避險績效之差異｣。
本文實證發現由於金融指數現貨與期貨以及金融類股票現貨與期貨之報酬率分配都具有高狹峰分配以及非常態分配之特性，因此雙變量GARCH模型都有最佳避險績效。其次，不管是時變或非時變避險比率估計式，運用股票期貨進行避險之績效優於運用金融指數期貨進行避險之績效。

This thesis uses the TWIFEX (Taiwan Futures Exchange) finance sector index futures and single stock futures to compare the hedge performance of the naïve hedge, the ordinary least square (OLS), 「the equally weighted moving average (MA), the exponentially weighted moving average (EWMA, λ=0.94), the EWMA (λ=0.96), and the bivariate GARCH model」. Additionally, this thesis also compares the difference in hedge performance between the financial sector index futures and single stock futures.
The empirical findings of this thesis are as follows：Since the return rates of the TWIFEX finance sector index futures and single stock futures have the leptokurtic distribution and non-normal distribution characteristics, the bivariate GARCH model has the best hedge performance. Additionally, regardless of the time-varying or non-time-varying hedge ratio estimators, the hedge performance of using financial sector stock futures is better than that of using financial sector index futures.

摘 要------------------------------------------------------------------------i
ABSTRACT--------------------------------------------------------------------ii
誌 謝--------------------------------------------------------------------iii
目錄------------------------------------------------------------------------iv
表 目 錄---------------------------------------------------------------------v
壹、緒論---------------------------------------------------------------------1
一、研究動機------------------------------------------------------------------1
二、研究目的------------------------------------------------------------------2
貳、文獻探討------------------------------------------------------------------3
一、金融指數期貨契約與股票期貨契約規格------------------------------------------3
二、「最小變異數避險比率(Minimum Variance Hedge Ratio)」-----------------------6
三、避險績效實證文獻-----------------------------------------------------------8
參、研究方法-----------------------------------------------------------------10
一、最小變異數避險比率之估計式------------------------------------------------10
二、避險績效之衡量-----------------------------------------------------------13
三、資料來源與說明-----------------------------------------------------------13
肆、實證結果分析-------------------------------------------------------------15
一、實證資料之基本統計量------------------------------------------------------15
二、各種避險比率估計式避險績效比較---------------------------------------------18
三、金融指數期貨對股票期貨避險績效比較-----------------------------------------25
四、近月期貨對遠月期貨避險績效比較---------------------------------------------26
伍、結論與建議---------------------------------------------------------------27
一、結論--------------------------------------------------------------------27
二、建議--------------------------------------------------------------------27
陸、參考文獻-----------------------------------------------------------------29

一、中文部份

1.王健聰，2006，「台股指數期貨避險―存續期間效果、到期效果與穩定性之研究」，經濟研究， 第42卷第2期pp.209-244。
2.王健聰，「2011，「考慮匯率風險與高狹峰分配之最小變異數避險比率估計-新加坡摩根台股指數期貨之驗證」，證券市場發展季刊，第23卷第4期」pp.111-142。
3.吳方聖，「2003，運用條件Power EWMA估計式衡量風險值之績效研究，東吳大學商學院企業管理所未出版碩士論文」。
4.張焯然，2001，「台股指數期貨動態避險效果之探討」，台灣管理學刊，第1卷第1期，pp.151-164。

二、英文部份

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3.「Baillie, R. and Myers, R. J., 1991, “Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge,” Journal of Applied Econometrics 6, 109-124.」
4.Bollerslev, T., 1986, “Generalized Autoregressive Conditional Heteroskedasticity,” Journal of Econometrics 31, 307-327.
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6.「Bollerslev, T., 1990, “Modeling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized ARCH Approach,” Review of Economics and Statistics 72, 498-505.」
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14.Ghosh, A. and Keong, C. I., 1994, “Hedging Effectiveness of U.S. Dollar Index Futures: An Error Correction Model,” The Journal of Futures Markets 4(1), 69-78.
15.「Harris, R. D. F. and Shen, J., 2003, “Robust Estimation of the Optimal Hedge Ratio,” The Journal of Futures Markets 23, 799-816.」
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17.Huber, P., 「1981, Robust Statistics, New York: Wiley.」
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21.Kroner, K. F. and Sultan, J., 1993, “Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures,” Journal of Financial and Quantitative Analysis 28, 535-551.
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23.Morgan, J. P., 1996, RiskMetrics Technical Document (4th ed.), New York: J. P. Morgan.
24.「Nelson, D. and Foster, D., 1996, “Asymptotic Filtering Theory for Multivariate ARCH Models,” Econometrica 62, 1-41.」
25.Park, T. H. and Switzer, L. N., 1995, “Time-Varying Distributions and the Optimal Hedge Ratios for Stock Index Futures,” Applied Financial Economics 5, 131-137.
26.Peters, E., 1986, “Hedged Equity Portfolios: Components of Risk and Return,” Advances in Futures and Options Research 1B, 75-91.
27.Wang, C. and Low, S. S., 2003, “Hedging with Foreign Currency Denominated Stock Index Futures: Evidence from the MSCI Taiwan Index Futures Market,” Journal of Multinational Financial Management 13, 1-17.
28.Yang, J. and Awokuse, T. O., 2003, “Asset Storability and Hedging Effectiveness in Commodity Futures Markets,” Applied Economics Letters 10, 487-491.