臺灣博碩士論文加值系統

本文研究目的旨在探討台股指數期貨在不同避險模型下樣本內外避險績效。採用的模型包括簡單避險模型、傳統迴歸(OLS)避險模型、誤差修正模型(ECM)、單變量GARCH(1,1)模型、單變量E-GARCH(1,1)模型、單變量GJR-GARCH(1,1)模型、雙變量GARCH(1,1)、雙變量E-GARCH(1,1)與雙變量GJR-GARCH(1,1)等避險模型。研究期間為1998年7月21日至2003年4月21日，資料型態為日資料。依據上述避險模型針對台灣股價指數期貨加以實證，避險績效衡量標準為報酬變異數降低程度。實證結果如下：
1.指數期貨與現貨之時間序列資料均非為穩定序列與呈現非常態分配，經一階差分後之時間數列則為穩定序列。
2.股價指數期貨與現貨間存在共整合關係，表示期貨與現貨之間存在長期均衡關係。故應將誤差修正項納入模型中，才會使變數的短期動態關係不至於偏離長期均衡。此項長期均衡關係即能確保期貨與現貨價格的互動與因果關係的存在。
3.現貨與期貨數列皆具有波動群聚與不對稱現象，顯示探討期貨與現貨相關性，宜納入波動的群聚與波動不對稱效果。
4.基本上，運用傳統迴歸模型、誤差修正模型及GARCH模型所估算出避險比率皆小於1，其避險成本較簡單避險模型低。
5.樣本內外實證發現：傳統迴歸避險模型在避險效益上表現最佳，誤差修正模型次之。動態GARCH避險模型不如預期比傳統迴歸避險模型佳，雖然投資人計算避險比率時以簡單傳統迴歸模型進行即可獲得較佳的避險效果，不過要考慮風險波動的群聚現象與好壞消息對期貨現貨市場的影響，最適避險比率應以本文所設定之不對稱GARCH模型作為評估之依據。
6.一般而言，不論採用何種避險模型進行現貨部位避險，皆能大幅降低持有現貨之風險，實證顯示股價指數期貨契約為一良好的避險工具。

The purpose of this study is to examines the predictable models to generate optimal hedge ratios. The traditional model and time-varying model have been compared in this thesis. Naïve model, OLS model, ECM Model and GARCH Models are involved to. The empirical data including TAIFEX Taiwan stock index futures. Information used in this study which covered daily from Jul. 21 1998 to Apr. 21 2003. The hedging performance also has been measured by the decreasing degree of portfolio variance. The major empirical results are as follows:
1.By using unit roots testing for price series of stock index futures, it found the significance of unit roots and thus the nonstationarity of the price series. Hence, price series should be differenced to induce stationarity.
2.The result of cointegration test has shown that there is a long-run equilibrium relationship between spot and futures prices. Consequently, a cointegration measure should be taken into account in the hedge model.
3.The evidences for the effect of the volatility clustering and volatility asymmetry have been displayed in the price series. We should discuss the volatility clustering and volatility asymmetry when we discuss the relationships between futures prices and spot prices.
4.The hedge ratios estimated by the OLS model, ECM model and GARCH models to estimate value are all less 1. The hedge cost is less than the Naïve model.
5.In detecting the effects of in-of and out-of sample periods, the OLS model outperforms all other hedging models for stock index futures, and the ECM model is the second best. The results also has indicated that hedge performance from those more complicate model is not superior to those obtained from the traditional method. Although, investors calculate the hedge ratio, they can get the better hedging performance by the OLS model, but investors should think about the effest of volatility clustering and volatility asymmetry. The evaluation of optimal hedgin ratio should think about the asymmetry GARCH model.
6.In general, the findings of this study indicate that if investors can add index futures to their investment portfolio, they can effectively reduce their risk of investment portfolio.

第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究方法與步驟 4
第四節 研究對象與資料來源 5
第五節 論文架構 7
第二章 理論基礎與文獻回顧 8
第一節 理論基礎 8
第二節 文獻回顧 18
第三節 本章綜論 27
第三章 相關計量方法與實證引用模型之建立 28
第一節 定態序列與單根檢定 28
第二節 共整合、誤差修正模型與因果關係檢定模型 36
第三節 GARCH模型之估計與檢定方法 45
第四節 避險模型之建立 56
第五節 避險績效之衡量 66
第四章 實證結果與分析 68
第一節 資料描述 68
第二節 實證結果分析 76
第三節 本章小結 101
第五章 結論與建議 103
第一節 結論 103
第二節 建議與未來研究方向 105
參考文獻 105

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