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    Title: 個股選擇權之隱含波動度不對稱效果決定因素之探討—以Panel Data模型分析
    Authors: 周弘敏
    Contributors: 杜化宇
    周弘敏
    Keywords: 隱含波動度不對稱
    槓桿效果
    Panel Data
    Date: 2002
    Issue Date: 2009-09-18 19:17:14 (UTC+8)
    Abstract: 隱含波動度不對稱效果對選擇權市場參與者是很重要的，因為隱含波動度變大可增加選擇權買方的報酬相對的會減少選擇權賣方的報酬，並且對選擇權避險者來說是一種額外的風險。過去許多文獻皆已證實股票報酬波動度具有不對稱效果，所謂不對稱效果一般是指負向衝擊對報酬波動度增加的影響較正向衝擊大。然而多數研究是以條件變異數作為波動度的衡量，本研究則打算以選擇權之隱含波動度作為波動度的衡量。研究對象為歐洲期貨交易所交易之二十四家德國公司個股選擇權，利用EGARCH模型探討股票價格變動對個股選擇權之隱含波動度不對稱效果，研究期間從2000年2月14日至2001年12月31日。在不對稱效果成立之下，進而探討公司財務槓桿及公司規模對隱含波動度不對稱程度之影響。除以最小平方法模型分析並與Koutmos and Saidi(1995)對照外，更進一步以Panel Data模型加入公司效果或時間效果作為本研究最終目的的分析依據，研究期間從2000年至2001年。
    本研究實證結果如下：
    1.大多數公司股票選擇權之隱含波動度具有不對稱效果，也就是負向價格變動對隱含波動度增加的影響較正向價格變動大，只有兩家公司例外。
    2.以最小平方法模型分析公司財務槓桿對隱含波動度不對稱程度的影響，實證結果與Koutmos and Saidi(1995)不一致，且不能支持Black（1976）所提出槓桿效果能用以解釋隱含波動度不對稱效果之假說，產生遺漏變數偏誤。
    3.以Panel Data模型加入公司效果或時間效果之考量，分析公司財務槓桿對隱含波動不對稱程度的影響。實證發現隱含波動度不對稱效果可歸因於財務槓桿假說，此外證實存在時間效果但不存在公司效果。
    4.公司規模會影響隱含波動度不對稱程度，兩者呈現正向關係。也就是說規模較大的公司對負向衝擊的反應較規模較小的公司敏感，實證結果與Koutmos and Saidi(1995)一致。
    Reference: 一、中文部分(依作者姓名排序)
    王甡，”報酬衝擊對條件波動所造成之不對稱效果—台灣股票市場之實證分析”，證券市場發展季刊，民國八十四年一月，第七券第一期，125-160頁。
    林楚雄、劉維琪與吳欽杉，”台灣股票店頭市場股價報酬波動行為的研究”，企業管理學報，民國八十八年三月，第四十四期，165-192頁。
    林楚雄、劉維琪與吳欽杉，”不對稱GARCH模型的研究”，管理學報，民國八十八年九月，第十六券第三期，479-515頁。
    麥朝成，2002全球經濟展望—從不景氣中再現繁榮，民國九十一年，中央經濟研究院。
    二、英文部分(依作者姓氏字母排列)
    Bessembinder, H. and P. J. Swguin, (1993), ”Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets”, Journal of Financial and Quantitative Analysis, Vol. 28, P21-39.
    Black, F. (1976), “Studies of Stock, Price Volatility Changes”, Proceedings of the 1976 Meetings of the Business and Economics Statistics Section, American Statistical Association, P177-181.
    Blair, B., S. H. Poon, and S. J. Taylor, (2002) “Asymmetric and Crash Effects in Stock Volatility for the S&P 100 Index and Its Constituents”, Applied Financial Economics, Vol. 12, P319-329.
    Bollerslev, T. (1986), “Generalized Autoregressive Conditional Heteroscedasticity”, Journal of Econometrics, Vol. 31, P307-327.
    Breusch, T., and A. Pagan. (1980), “The LM Test and Its Applications to Model Specification in Econometrics”, Review of Economic Studies, Vol. 47, P239-254.
    Campbell, J. Y. and L. Hentschel, (1992), “No News is Good News：An Asymmetric Model of Changing Volatility in Stock Returns”, Journal of Financial Economics, Vol. 31, P281-318.
    Cheung, Y. W. and Ng, L. K. (1992), “Stock Price Dynamics and Firm Size: An Empirical Investigation”, Journal of Finance, Vol. 48, P1985-1997.
    Christie, A. (1982), “The Stochastic Behavior of Common Stock Variance: Value, Leverage and Interest Rate Effects”, Journal of Financial Economics, Vol. 10, P407-432.
    Davidson, W. N., J. K. Kim, E. Ors, and A. Szakmary, (2001), “Using Implied Volatility on Options to Measure the Relation Between Asset Returns and Variability”, Journal of Banking & Finance, Vol. 25, P1245-1269.
    Duffee, G. R. (1995), “Stock Returns and Volatility: A Firm-Level Analysis”, Journal of Financial Economics, Vol. 37, P399-420.
    Engle, R. F. (1990), “Discussion: Stock Market Volatility and the Crash of ’87”, Review of Financial Studies, Vol. 3, P103-106.
    Engle, R. F. (1982), “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation”, Econometrica, Vol. 50, P987-1008.
    Engle, R. F. and V. K. Ng (1993), “Measuring and Testing the Impact of News on Volatility”, Journal of Finance, Vol. 48, P1749-1778.
    Fleming, J. (1998), “The Quality of Market Volatility Forecasts Implied by S&P 100 Index Option Prices”, Journal of Empirical Finance, Vol. 5, P317-345.
    Fleming, J., Ostdiek, B., and Whaley, R. E. (1995), “Predicting Stock Market Volatility: A New Measure”, Journal of Futures Markets, Vol. 15, P265-302.
    French, R. K., G. W. Schwert, and R. F. Stambaugh, (1987), “Expected Stock Returns and Volatility,” Journal of Financial Economics, Vol. 19, P3-29.
    Gallant, A. R., P. E. Rossi, and G. Tauchen, (1992), “Stock Prices and Volume”, The Review of Financial Studies, Vol. 5, P199-242.
    Glosten, L. R., R. Jagannathan, and D. E. Runkle, (1993), “On the Relation Between the Expected Value and Volatility of the Nominal Excess Return on Stocks”, Journal of Finance, Vol. 48, P1779-1801.
    Greene, W. H. (2000), Econometric Analysis, Fourth Edition.
    Johnston, J. and Dinardo, J. (1997), Econometric Methods, Fourth Edition.
    Koutmos, G. (1998), “Asymmetries in the Conditional Mean and the Conditional Variance: Evidence From Nine Stock Markets”, Journal of Economics and Business, Vol. 50, P277-290.
    Koutmos, G. and G.G. Booth, (2002), “Asymmetric Volatility Transmission in International Stock Markets”, Journal of International Money and Finance, Vol. 14, P747-762.
    Koutmos, G. and Saidi, R. (1995), “The Leverage Effect in Individual Stocks and the Debt to Equity Ratio”, Journal of Business Finance and Accounting, Vol. 22, P1063-1075.
    Longin, F. and Solnik, B. (1995), “Is the Correlation in International Equity Returns Constant: 1960-1990?”, Journal of International Money and Finance, Vol. 14, P3-26.
    Nelson, D. (1991), “Conditional Heteroskedasticity in Asset Returns: A New Approach,” Econometrica, Vol. 59, P347-370.
    Rabemananjara, R. and J. M. Zakoian, (1993), “Threshold ARCH Models and Asymmetries in Volatility”, Journal of Applied Econometrics, Vol. 8, P31-49.
    Schwert, G. W. (1989), “Why Does Stock Market Volatility Change Over Time?”, Journal of Finance, Vol. 44, P1115-1153.
    Schwert, G. W. (1990), “Stock Volatility and the Crash of ’87”, Review of Financial Studies, Vol. 3, P77-102.
    Simon, D. P. (1997), “Implied Volatility Asymmetries in Treasury Bond Futures Options”, Journal of Futures Markets, Vol. 17, P873-885.
    Zakoian, J.M. (1991), “Threshold Heteroskedastic Models”, Journal of Economic Dynamics and Control, Vol. 18, P931-955.
    Description: 碩士
    國立政治大學
    財務管理研究所
    90357024
    91
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0090357024
    Data Type: thesis
    Appears in Collections:[Department of Finance] Theses

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