本文使用美式選擇權的觀點分析西德州中級原油(WTI)現貨與期貨價差的便利收益所表現的資訊內涵以及其與波動性的關係，對於文獻上對於商品期貨便利收益假設及看法做實證分析，並利用計算出的隱含便利收益配合時間序列模型做波動性風險管理計算風險值（VaR）及價差交易策略，分析其經濟價值。
    由於資產報酬率具有GARCH效果，本文利用Copula方法結合Duan(1995) GARCH選擇權定價模型，另外，為了計算美式選擇權有提早履約的權利，因此本文結合最小平方蒙地卡羅法，提出兩變量GARCH美式選擇權定價模型計算商品期貨便利收益。
    最後，由於波動性是影響買權價值的顯著因子，因此可以對於期貨使用多變量波動性模型進行波動性預測，計算期貨之間的價差預期值以及期貨之間的價差的風險值。因此隱含便利收益的確具有波動性的資訊內涵。

This article examines empirically the behavior and determinants of convenience yield over time for three month oil commodities futures. Contrary to previous approaches, convenience yields are treated as call options with identifiable exercise price, time to maturity and underlying asset. The empirical results derived from the analysis of oil three month commodities futures data covering the period 1995 to 2005, are in line with previous evidence that convenience yields are negatively related to inventory levels. Furthermore, it is demonstrated that observed convenience yields are valued as call options according to an extension of the Black-Scholes option pricing model.
   
    The pricing of commodity futures contracts is important both for professionals and academics. It is often argued that futures prices include a convenience yield, and this article uses a simple trading strategy and GARCH and Geometric Brownian motion to approximate the impact of convenience yields. The convenience yield approximation is both statistically and economically important in explaining variation between the futures price and the spot price after adjustment for interest rates.

中文摘要…………………………………………………………………………….. .I
英文摘要……………………………………………………………………………..III
目錄…………………………………………………………………………….. …...IV
圖目錄…………………………………………………………………………….. …V
表目錄…………………………………………………………………………..….. ..V

第一章    緒論	1
第一節  前言	1
第二節	研究動機	3
第三節	論文架構流程圖	6
第二章	便利收益模型文獻回顧	7
第一節　理論模型	7
2.1.1  Kaldor(1939)	7
2.1.2  Fischer (1978)	10
第二節  實證模型	13
2.2.1  Milonas and Thomadakis(1997)	13
2.2.2  Milonas and Henker (2001)	15
2.2.3  Heaney(2002)	17
第三章	美式選擇權定價模型	19
第一節　幾何布朗運動模型	19
3.1.1	Black-Scholes 歐式選擇權評價模型	20
3.1.2	二項樹過程	22
3.1.3	雙變量兩項樹過程	26
第二節  GARCH選擇權評價模型	30
3.2.1　GARCH 模型 (Duan（1995）)	31
3.2.2	蒙地卡羅模擬法	33
3.2.3	雙變量Copula GARCH 選擇權訂價模型
(Goorgergh , Genest and Werker(2005)	36
3.2.4	最小平方蒙地卡羅法（least squares Monte Carlo
        , LSMLongstaff and Schwartz(2001)）	41
第四章	研究方法	46
第一節	評估文獻便利收益模型	48
第二節	美式選擇權定價模型的應用	49
第五章	實證結果	56
第一節	模型配適度比較	56
第二節	美式選擇權定價法之風險管理應用	65
5.2.1  GARCH模型	66
5.2.2	CY-BEKK模型	68
第六章	結論與建議	71
參考文獻		72



圖目錄
[圖3.1] 單期二項樹過程.......................................................................................28
[圖3.2] 乘法雙變量兩項過程...............................................................................29
[圖3.3] 加法雙變量兩項過程...............................................................................29
[圖4.1] 兩期貨標準化後的每日殘差圖...............................................................51
[圖4.2] 報酬率的標準化殘差所計算的kendall tau 圖...................................51
[圖4.3] Kendall tau 配適度................................................................................52
[圖5.1] 原始TS 3m 模型殘差與配適能力...........................................................61
[圖5.2] 原始GBM 3m 模型殘差與配適能力.........................................................62
[圖5.3] 原始GARCH 3m 模型殘差與配適能力.....................................................62
[圖5.4] 一次差分後的TS 3m 模型殘差與配適能力...........................................63
[圖5.5] 一次差分後的GBM 3m 模型殘差與配適能力.........................................63
[圖5.6] 一次差分後的GARCH 3m 模型殘差與配適能力.....................................64
表目錄
[表4.1] 期貨合約的到期月份...............................................................................46
[表4.2] 單一參數Copula 族................................................................................54
[表4.3] Kendall tau.............................................................................................54
[表5.1] 敘述統計量與時間序列統計量...............................................................59
[表5.2] 經利率調整後基差使用Cochrane-Orcutt AR(1) 迴歸估計便利收益.60
[表5.3] 一階差分後的參數估計...........................................................................60
[表5.4] 分析期貨價格對於便利收益估計值的影響...........................................61

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