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    政大機構典藏 > 商學院 > 財務管理學系 > 學位論文 >  Item 140.119/34084
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/34084


    Title: 企業財務槓桿效果之再探討:動態 Panel Data 方法之應用
    Authors: 林景民
    Contributors: 杜化宇
    林景民
    Keywords: 不對稱效果
    動態縱橫資料
    Date: 2004
    Issue Date: 2009-09-17 19:25:13 (UTC+8)
    Abstract: 本研究目的在於探討隱含波動度不對稱效果,並分析公司規模與財務槓桿比率對於波動度不對稱的影響。波動度不對稱效果是指負向報酬衝擊對波動度增加的影響較正向報酬衝擊大。由於過去的文獻多針對現貨與期貨價格行為上的研究,並以條件變異數衡量波動度,本研究則試著以選擇權之隱含波動度作為波動度不對稱效果的衡量基礎,希冀以隱含波動度代表未來波動度的不偏估計量,反應出投資者對於未來的預期。本研究選取29支英國的個股選擇權,並利用EGARCH(1,1)模型來探討在股票價格變動下,個股選擇權所反應出來的波動度不對稱效果,研究期間主要從2000年1月25日至2003年12月31日止。而在驗證波動度不對稱效果確實存在下,我們更進一步以Pooled OLS模型、靜態Panel Data 模型與動態Panel Data模型來探討公司規模與財務槓桿比率對隱含波動度不對稱效果之關係。
    本文之主要結論如下:
    1. 在29家英國樣本公司中,確實均存在隱含波動度不對稱之效果,即負向股票價格變動對隱含波動度的影響較正向股票價格變動為大。
    2. 在分析公司資產規模與公司財務槓桿影響波動度不對稱效果,若只以Pooled OLS模型分析,可能產生錯誤的推論,雖然公司規模為顯著性正相關,但財務槓桿則為不顯著之負相關,其實證結果與KS不一致,並且不能支持Black(1976)之槓桿效果。
    3. 為了避免使用 Pooled OLS模型產生錯誤的推論,本研究另以靜態Panel Data 模型來分析波動度不對稱程度與公司資產規模和財務槓桿之關係,對於公司資產規模因素而言,不管在公司效果(固定模式)與時間效果(隨機模式)均呈現顯著之正相關,而在同時考量公司效果及時間效果(隨機模式)下,則呈現不顯著之正相關,此結果與KS的推論一致。而對於財務槓桿而言,則只有在公司效果(固定模式)呈現顯著之正相關,在同時考量公司效果及時間效果則呈現不顯著之正相關,而若單只考慮時間效果,則係數為-0.000(不顯著),則與KS推論不符合,且不支持Black之槓桿效果假說。
    4. 為了較正確反應投資市場是有記憶性與調整性,我們另以動態Panel Data 模型來作實證,而這亦是一般較符合市場之模型,實證結果顯示不管在one-step 或 two-step 下,公司財務規模與財務槓桿確實與波動度不對稱性呈現顯著正相關,其結果與KS一致,且支持Black所提出之槓桿效果,而動態的延遲項則呈現不顯著(推測受限於樣本數過少)之負相關(係數為負,且值小於1),若以部分調整模型之經濟意義來解釋,即調整係數值均大於1,顯示出實際市場反應出來的波動度不對稱之結果,大於投資人對於波對度不對稱情形預期的調整,這可能是選擇權市場投資人之過度反應的行為所造成,故可能使得前期項對於後期項的影響為負,但會逐漸消失。
    The purpose of the research is to discuss the asymmetric effect of volatility, and analyze firm scale and debt ratio affect the asymmetric effect of volatility. Asymmetric effect of volatility is the influence of negative return is more than positive return. Most research focus on the futures and spot goods,and takes conditional variance as volatility. We want to use IV as unbiased estimator of volatility in the future, and reflect the investor’s expectation. We chose 29 call options in English, and use EGARCH (1,1) model to explore the asymmetric effect of volatility over 2000/1/25-2003/12/31 period. After confirming the asymmetric effect of volatility, we use Pooled OLS Model, Static Panel Data Model, and Dynamic Panel Data Model to discuss the relationship between firm scale, debt ratio, and asymmetric effect.
    The funding of the paper are:
    (a) There is certainly the existence of asymmetric effect in 29 sample firms.
    (b) Pooled OLS Model may result wrong conclusions. There is a significantly positive relationship between firm scale and asymmetric effect. And there is a less significantly negative relationship between debt ratio and asymmetric effect. The result doesn’t consist with KS, and doesn’t support Black’s leverage effect.
    (c) To avoid the error from Pooled OLS Model, we use Static Panel Data Model to analyze the relationship with firm scale, debt ratio, and asymmetric effect. Asymmetric effect is significantly positively related to firm scale with single corporate effect (fixed effect) and single time effect (random effect). And asymmetric effect is less significantly positively impacted by firm scale if we chose corporate effect and time effect simultaneously. Asymmetric effect is significantly positively related to debt ratio with single corporate effect (fixed effect), and is less significantly positively related to debt ratio with corporate effect and time effect simultaneously. The coefficient is -0.000 (less significantly) of debt ratio with single time effect. The result doesn’t consist with KS, and doesn’t support Black’s leverage effect.
    (d) For showing capital market’s memory and adjustability, we use Dynamic Panel Data Model to analyze the problem. Asymmetric effect is significantly positively impacted by firm scale and debt ration in one-step model and two-step model. The result consists with KS, and supports Black’s leverage effect. The coefficient of lagged term is between 0 and -1 (less significantly) may be come from the real asymmetric effect is more than investor’s expectancy, and investors my have overreaction in capital market.
    Reference: 一、 中文部分(依作者姓氏排序)
    周弘敏, “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”,政治大學財務管理研究所未出版碩士論文,民國九十二年六月。
    黃淑娟, “影響台灣地區產險公司現金持有之決定因素:動態現金持有模型之實證研究”,真理大學管理科學研究所未出版碩士論文,民國九十二年六月。
    楊奕農,時間序列分析:經濟與財務上應用,民國九十二年,雙葉書廊。
    劉威漢,財金風險管理理論、應用與發展趨勢,民國九十三年,智勝文化事業。
    二、 英文部分(依作者姓氏排序)
    Arellano, M. and S. Bond, (1991), “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations”, The Review of Economic Studies, Vol. 58, P277-297.
    Arellano, M. and O. Bover, (1995), ”Another look at the instrumental variables estimation of error-component models”, Journal of Econometrics , Vol. 68, P29-51
    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.
    Braun, P. A, D.B. Nelson, and A. M. Sunier (1995), “Good News, Bad News, Volatility, and Betas”, Journal of Finance, Vol.50, P1575-1603.
    Cagan, P. (1956), “The Monetary dynamics of Hyperinflation,” in M. Friedman (ed.), Studies in the Quantity Theory of Money, Chicago: University Of Chicago Press, P25-117.
    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.
    Figlewski, S. and X. Wang (2000), “IS the “Leverage Effect“ a Leverage Effect?”, Working Paper, New York University, Stern School of Business.
    Flannery, M. J. (1981), “Market interest rates and commercial bank profitability:An empirical investigation”, Journal of Finance, Vol. 36, P1085-1101.
    Flannery, M. J. (1983), “Interest rates and banks profitability:Additional evidence”, Journal of Money,Credit and Banking, Vol. 15, P355-362.
    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.
    Hansen, L.P. (1982),“Large Sample Properties of Generalized Method of Moments Estimators”, Econometrica, Vol. 50, P1024-54.
    Johnston, J. and Dinardo, J. (1997), Econometric Methods, Fourth Edition.
    Jorion, Philippe, (1995), “Predicting Volatility in the Foreign Exchange Market”, Journal of Finance, Vol. 2, P507-528.
    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.
    Nam Kiseok, Chong Soo Pyun, and Stephen L. Avard, (2001),” Asymmetric reverting behavior of short-horizon stock returns: an evidence of stock market overreaction”, Journal of Banking & Finance Vol. 25, P807-824.
    Rabemananjara, R. and J. M. Zakoian, (1993), “Threshold ARCH Models and Asymmetries in Volatility”, Journal of Applied Econometrics, Vol. 8, P31-49.
    Sargan, J. D., (1958), “The Estimation of Economic Relationships Using Instrumental Variables”, Econometrica, Vol. 26, P393-415.
    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. (1994), “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
    923570011
    93
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0923570011
    Data Type: thesis
    Appears in Collections:[財務管理學系] 學位論文

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