政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/76171

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/76171

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政大機構典藏 > 商學院 > 金融學系 > 學位論文 > Item 140.119/76171

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题名:	預測S&P500指數實現波動度與VIX－探討VIX、VIX選擇權與VVIX之資訊內涵 The S&P 500 Index Realized Volatility and VIX Forecasting - The Information Content of VIX, VIX Options and VVIX
作者:	黃之澔
贡献者:	陳威光林靖庭 Chen, Wei Kuang Lin, Ching Ting 黃之澔
关键词:	VIX 選擇權 VVIX 資訊內涵 S&P500指數實現波動度動態轉換模型風險中立動差 VIX Options VVIX Information Content S&P 500 Realized Volatility Regime Switching Model Risk Neutral Moments
日期:	2014
上传时间:	2015-07-01 14:45:06 (UTC+8)
摘要:	波動度對於金融市場影響甚多，同時為金融資產定價的重要參數以及市場穩定度的衡量指標，尤其在金融危機發生時，波動度指數的驟升反映資產價格震盪。本篇論文嘗試捕捉S&P500 指數實現波動度與VIX變動率未來之動態，並將VIX、 VIX 選擇權與VVIX 納入預測模型中，探討其資訊內涵。透過研究S&P500 指數實現波動度，能夠預測S&P500 指數未來之波動度與報酬，除了能夠觀察市場變動，亦能使未來選擇權定價更為準確；而藉由模型預測VIX，能夠藉由VIX 選擇權或VIX 期貨，提供避險或投資之依據。文章採用2006 年至2011 年之S&P500 指數、VIX、VIX 選擇權與VVIX 資料。在 S&P500 指數之實現波動度預測當中，本篇論文的模型改良自先前文獻，結合實現波動度、隱含波動度與S&P500 指數選擇權之風險中立偏態，所構成之異質自我回歸模型(HAR-RV-IV-SK model)。論文額外加入VIX 變動率以及VIX指數選擇權之風險中立偏態作為模型因子，預測未來S&P500 指數實現波動度。研究結果表示，加入VIX 變動率作為S&P500 指數實現波動度預測模型變數後，可增加S&P500 指數實現波動度預測模型之準確性。在 VIX 變動率預測模型之中，論文採用動態轉換模型，作為高低波動度之下，區分預測模型的方法。以VIX 過去的變動率、VIX 選擇權之風險中立動差以及VIX 之波動度指數(VVIX)作為變數，預測未來VIX 變動率。結果顯示動態轉換模型能夠提升VIX 預測模型的解釋能力，並且在動態轉換模型下，VVIX 與 VIX 選擇權之風險中立動差，對於VIX 預測具有相當之資訊隱涵於其中。 This paper tries to capture the future dynamic of S&P 500 index realized volatility and VIX. We add the VIX change rate and the risk neutral skewness of VIX options into the Heterogeneous Autoregressive model of Realized Volatility, Implied Volatility and Skewness (HAR-RV-IV-SK) model to forecast the S&P 500 realized volatility. Also, this paper uses the regime switching model and joins the VIX, risk neutral moments of VIX options and VVIX variables to raise the explanatory ability in the VIX forecasting. The result shows that the VIX change rate has additional information on the S&P 500 realized volatility. By using the regime switching model, the VVIX and the risk neutral moments of VIX options variables have information contents in VIX forecasting. These models can be used for hedging or investment purposes.
參考文獻:	Akaya O., Senyuzc Z., Yoldas E., 2013. Hedge fund contagion and risk-adjusted returns: a Markov-switching dynamic factor approach. Journal of Empirical Finance 22, 16–29. Bakshi, Kapadia, Madan, 2003. Stock return characteristics, skew laws, and the differential pricing of individual equity options. The Reviews of Financial Studies, Vol. 16, 101 - 143. Bauwensa L., Dufaysa A., Rombouts J.V.K., 2014. Marginal likelihood for Markov-switching and change-point GARCH models. Journal of Econometrics 178, 508–522. Bekaerta G., Hoerova M., 2014. The VIX, the variance premium and stock market volatility. Journal of Econometrics 183, 181–192. Byun S.J., Kim J.S., 2013. The information content of risk-neutral skewness for volatility forecasting. Journal of Empirical Finance 23, 142–161. Chalamandaris G., Rompolis L.S., 2012. Exploring the role of the realized return distribution in the formation of the implied volatility smile. Journal of Banking & Finance 36, 1028–1044. Chang B.Y, Christoffersen P., Jacobs K., 2013. Market skewness risk and the cross section of stock returns. Journal of Financial Economics 107, 46–68. Chuanga W.I., Huangb T.C., Lin B.H., 2013. Predicting volatility using the Markov- switching multifractal model: Evidence from S&P 100 index and equity options. North American Journal of Economics and Finance 25, 168– 187. Chung S.L., TsaiW.C., Wang Y.H., Weng P.S., 2011.The information content of the S&P 500 index and VIX options on the dynamics of the S&P 500 index. Journal of Futures Markets, Vol. 31, No. 12, 1170–1201. Conrad J., Dittmar R.F., Ghysels E., 2013. Ex Ante Skewness and Expected Stock Returns. Journal of Finance Vol. 68, No. 1. Cordisa S.A., Kirby C., 2014. Discrete stochastic autoregressive volatility. Journal of Banking & Finance 43, 160–178. Corsi, F, 2009.A simple approximate long-memory model of realized volatility, Journal of Financial Econometrics,Vol.7, Issue 2, 174-196 Dueker M., Neely C.J., 2007. Can Markov switching models predict excess foreign exchange returns? Journal of Banking & Finance 31, 279–296. Fernandesa M.,. Medeirosc M.C., Scharth M., 2014. Modeling and predicting the CBOE market volatility index. Journal of Banking & Finance 40, 1–10. Gatheral, 2008. Consistent Modeling of SPX and VIX options. Gray S.F, 1996. Modeling the conditional distribution of interest rates as a regime-switching process. Journal of Financial Economics 42, 27 - 62. Hamilton J.D., 1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica Vol. 57, No. 2, 357 - 384. Hamilton J.D., 1990.Analysis of time series subject to changes in regime. Journal of Econometrics 45, 39-70. Kanniainena J., Lina B., Yang H., 2014. Estimating and using GARCH models with VIX data for option valuation. Journal of Banking & Finance 43, 200–211. Khalifaa A.A.A, Hammoudehb S., Otranto E., 2014. Patterns of volatility transmissions within regime switching across GCC and global markets. International Review of Economics and Finance 29, 512–524. Kim C.J, 1994. Dynamic linear models with Markov-switching. Journal of Econometrics 60, l-22. Lin Y.N., 2013. VIX option pricing and CBOE VIX Term Structure: A new methodology for volatility derivatives valuation. Journal of Banking & Finance 37, 4432–4446. Liua X., Margaritisb D., Wang P., 2012. Stock market volatility and equity returns: Evidence from a two-state Markov-switching model with regressors. Journal of Empirical Finance 19, 483–496. Miaoa W.C., Wub C.C., Su Y.K., 2013. Regime-switching in volatility and correlation structure using range-based models with Markov-switching. Economic Modelling 31, 87–93. Neumanna M., Skiadopoulos G., 2013.Predictable dynamics in higher order risk-neutral moments:evidence from the S&P 500 options. Journal of Financial and Quantitative Analysis, Vol. 48, Issue 03, 947 - 977. Onan M., Salih A., Burze Yasar, 2014. Impact of macroeconomic announcements on implied volatility slope of SPX options and VIX. Finance Research Letters 11, 454–462. Pan Q., Li Y., 2013. Testing volatility persistence on Markov switching stochastic volatility models. Economic Modelling 35, 45–50. Patrick S., Stewart M., 2002. Risk-neutral skewness: evidence from stock options. Journal of Financial & Quantitative Analysis, Vol. 37, 471. Raggia D., Bordignon S., 2012. Long memory and nonlinearities in realized volatility: A Markov switching approach. Computational Statistics and Data Analysis 56, 3730–3742. Raggia, Bordignon, 2012. Long memory and nonlinearities in realized volatility: A Markov switching approach. Computational Statistics & Data Analysis,Vol. 56, Issue 11, Pages 3730–3742 Rossia A., Giampiero, 2006. Volatility estimation via hidden Markov models. Journal of Empirical Finance 13, 203– 230. Zhou Y., 2014. Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities. Journal of Banking & Finance 38, 216–228
描述:	碩士國立政治大學金融研究所 102352010 103
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0102352010
数据类型:	thesis
显示于类别:	[金融學系] 學位論文

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