DSpace CRIS
DSpace-CRIS consists of a data model describing objects of interest to Research and Development and a set of tools to manage the data. Standard DSpace is used to deal with publications and data sets, whereas DSpace-CRIS involves other CRIS entities: Researcher Pages, Projects, Organization Units and Second Level Dynamic Objects (single entities specialized by a profile, such as Journal, Prize, Event etc; because any profile can define its own set of properties and nested objects)
Learn More
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11455/97240| 標題: | VIX ETN與SPY投資組合的風險外溢與避險效果 Modeling Volatility Spillover and Hedging VIX ETN with SPY |
作者: | 駱冠霖 Guan-Lin Luo |
關鍵字: | 交易所買賣指數票據;VIX ENT;Co-Volatility Spillovers;SPY;最適避險比率;Diagonal BEKK;Exchange Traded Note;VIX ENT;Co-Volatility Spillovers;SPY;Optimal Hedge Ratio;Diagonal BEKK | 引用: | Aboura, S. and Chevallier, J. (2016), “Tail risk and the return-volatility relation”, Research in International Business and Finance, forthcoming. Aboura, S., and J. Chevallier (2015),“ A cross-volatility index for hedging the country risk,” Journal of International Financial Markets Institutions and Money, 38, 25-41. Andreasen, J., and B. Huge (2011) , “Volatility interpolation,” Risk Magazine, 3, 76–79. Baba, Y., R.F. Engle, D. Kraft and K.F. Kroner (1985), “Multivariate Simultaneous Generalized ARCH”, Unpublished manuscript, Department of Economics, University of California, San Diego, CA, USA. Bahaji, H., and Aberkane, S. (2016). “How rational could VIX investing be? ”Economic Modelling, 58, 556–568. Baltussen, G., S. V. Bekkum, and B. V. D. Grient (2014),” Unknown unknowns: uncertainty about risk and stock returns,” Journal of Financial and Quantitative Analysis (forthcoming). Białkowski, J., D. D. Huong, and X. Wei. (2016)“ Does the Tail Wag the Dog? Evidence from Fund Flow to VIX ETFs and ETNs,” The Journal of Derivatives 24(2),31-47. Black, F., Scholes M. (1973), “The Pricing of Options and Corporate Liabilities,” Journal of Political Economy,81(3),637–654. Bollerslev, T. (1990), “Modelling the Coherence in Short-Run Nominal Exchange Rate: A Multivariate Generalized ARCH Approach”, Review of Economics and Statistics, 72, 498-505. Bollerslev, T., R. Engle and J. Wooldridge (1988), “A Capital Asset Pricing Model with Time Varying Covariance”, Journal of Political Economy, 96, 116-131. Bordonado, C., Molnár, P., and Samdal, S. R. (2017). “VIX Exchange Traded Products: Price Discovery, Hedging, and Trading Strategy ” , Journal of Futures Markets, 37(2), 164-183. Carr, P. (2008), “Local Variance gamma, ” Bloomberg Quant Research Discussion Papers, New York. Chang, C. L., González-Serrano, L., & Jimenez-Martin, J. A. (2013), “Currency hedging strategies using dynamic multivariate GARCH, Mathematics and Computers in Simulation, 94, 164-182. Chang, C. L., McAleer, M., & Tansuchat, R. (2011), “Crude oil hedging strategies using dynamic multivariate GARCH.” , Energy Economics, 33(5), 912-923. Chang, C.-L., M. McAleer and Y.-A. Wang (2016), “Modelling volatility spillovers for bioethanol, sugarcane and corn”, Tinbergen Institute Discussion Papers,16-014/III, The Netherlands. Chang, C.-L., Y.-Y. Li and M. McAleer (2015), “Volatility spillovers between energy and agricultural markets: A critical appraisal of theory and practice”, Tinbergen Institute Discussion Papers, 15-077/III, The Netherlands. Chang, C-L, T-L Hsieh and M. McAleer (2016), 'How are VIX and Stock Index ETF related?,' Tinbergen Institute Discussion Papers, 16-010/III Chen, T.-F., S.-L. Chung, and J.-C. Lin (2014), “Volatility-of-Volatility Risks and Asset Prices,” Discussion Papers series, University of Taiwan Cheung, W., Fung, S., and Tsai, S. C. (2010), “Global capital market interdependence and spillover effect of credit risk: evidence from the 2007–2009 global financial crisis. ”, Applied Financial Economics, 20(1-2), 85-103. Clowers, R. P., and Jones, T. L. (2016). “Is a VIX ETP an investment in the VIX,” Financial Services Review, 25(1), 73–85. Deng, G., McCann, C., & Wang, O. (2012). Are VIX futures ETPs effective hedges?. The Journal of Index Investing, 3(3), 35-48. Ederington, L. (1979), “The Hedging Performance of the New Futures Markets”, Journal of Finance, 34(1), 55-60 Engle, R. (2002), “Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Hereoskedasticity Models”, Journal of Business and Economic Statistics, 20, 339-350. Engle, R.F. (1982), “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation”, Econometrica, 50, 987-1007. Engle, R.F. and K.F. Kroner (1995), “Multivariate Simultaneous Generalized ARCH”, Econometric Theory, 11(1), 122-150. Eraker, B., & Wu, Y. (2017), “Explaining the negative returns to volatility claims: An equilibrium approach.” Journal of Financial Economics, 125(1), 72–98 Figlewski, S. (1984). “Hedging performance and basis risk in stock index futures”, The Journal of Finance, 39(3), 657-669. Ghulam, S. (2012), “Is VIX an investor fear gauge in BRIC equity markets? ”, Journal of Multinational Financial Management, 22, 55–65 Hafner, C. M., & McAleer, M. (2014). “A one line derivation of DCC: Application of a vector random coefficient moving average process.” Harris, R. D. F. and J. Shen (2003), “Robust Estimation of the Optimal Hedge Ratio,” The Journal of Futures Markets, 23(8),99-816. Huang, D. and I. Shaliastovich (2014), “Volatility-of-Volatility Risk,” Discussion Papers, University of Pennsylvania Jeantheau, T. (1998), “Strong Consistency of Estimators for Multivariate ARCH Models”, Econometric Theory, 14, 70-86. Johnson, L. L. (1960), “The theory of hedging and speculation in commodity futures. “, The Review of Economic Studies, 27(3), 139-151. Jung, Y. C. (2016),“ A portfolio insurance strategy for volatility index (VIX) futures”,The Quarterly Review of Economics and Finance, 60, 189-200 Ling, S. and M. McAleer (2003), “Asymptotic Theory for a Vector ARMA-GARCH Model”, Econometric Theory, 19, 278-308. McAleer, M. (2005), “Automated inference and learning in modeling financial volatility”, Econometric Theory, 21(1), 232-261. McAleer, M., F. Chan, S. Hoti and O. Lieberman (2008), “Generalized autoregressive conditional correlation”, Econometric Theory, 24(6), 1554-1583. McAleer, M., S. Hoti and F. Chan (2009), “Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility”, Econometric Reviews, 28, 422-440. Park, Y. (2013), “Volatility of volatility and tail risk premiums”, FED Washington, Finance and Economics Discussion Series, 2013–54. Poon, S.-H. and Granger, C. W. J. (2003), “Forecasting volatility in financial markets: A review,” Journal of Economic Literature, 41, 478-539 Baillie, R. T., & Myers, R. J. (1991). Bivariate GARCH estimation of the optimal commodity futures hedge. Journal of Applied Econometrics, 6(2), 109-124. Smales, L. A. (2016), “Risk-On/Risk-Off: Financial market response to investor fear,” Finance Research Letters, 17, 125–134 Tsay, R.S. (1987), “Conditional Heteroscedastic Time Series Models”, Journal of the American Statistical Association, 82, 590-604. Wang Z. and Daigler R. T. (2016), “The Option SKEW Index, VIX of VIX, and Market Tail Risk”, Review of Futures Markets, 22(4), 1-28 Zhou, J. (2016). Hedging performance of REIT index futures: A comparison of alternative hedge ratio estimation methods. Economic Modelling, 52, 690-698. | 摘要: | 近年來，由於黑天鵝事件頻傳使得投資者對於風險管理的重視，也促使了避險性資產多元化的發展，其中又以連結波動度風險因子的VIX ETPs最受歡迎。根據過往的研究發現到不同類型VIX ETPs存在著許多的特性，但鮮少有研究是以不同類型VIX ETN與 SPY配置而成的投資組合之避險效果。 本研究主要的研究目的乃是探討VIX ETN與SPY投資組合的風險外溢與避險效果。在Diagonal BEKK模型下，先利用Partial co-volatility spillovers來分析VIX ETN是否為SPY的動態避險工具，接著在使用SPY與對沖型ETN(VXX)、反向型ETN(ZIV)、槓桿型ETN(TVIX) 配置了三種不同類型的資產組合。最後在利用平均最適避險比率來分析第一類的投資組合(SPY、ZIV、TVIX)、第二類的投資組合(SPY、VXX、TVIX)，第三類的投資組合(SPY、VXX、ZIV)之避險效果。從實證結果可以發現，(1) VXX 、TVIX及ZIV皆可做為SPY的避險工具。(2) 在SPY、ZIV and TVIX資產配置的模組中，槓桿型TVIX為避險工具來規避被避性資產SPY的效果是最佳。(3) 在SPY、VXX and TVIX資產配置的模組中，槓桿型TVIX為避險工具來規避被避性資產SPY的效果是最佳。(4) 在SPY、VXX and ZIV資產配置的模組中，沖銷型VXX為避險工具來規避被避性資產SPY的效果是最佳。 In recent years, the increasing frequency of Black Swan Events has made investors attach more importance to risk management, and also facilitated diverse development of assets for hedging, among which VIX ETPs linked to volatility risk is the most popular. According to the past researches we could find that there are many characteristics in different types of VIX ETPs; however, few studies focused on the hedging effect of portfolios of different types of VIX ETN and SPY. This paper mainly focuses on the risk spillover and hedging effect of the portfolios of VIX ETN and SPY. Under Diagonal BEKK model, first we analyze if VIX ETN is the dynamic hedging instrument of SPY through Partial co-volatility spillovers. Secondly, make three different portfolios using SPY with direct ETN (VXX), inverse ETN (ZIV), or leveraged ETN (TVIX). These three portfolios are (1) SPY, ZIV and TVIX, (2) SPY, VXX and TVIX, (3) SPY, VXX and ZIV. Finally, analyze the hedging effect of the three portfolios with optimal hedge ratio. The results show as the following: (1) VXX, TVIX, and ZIV can all be the hedging instrument of SPY. (2) Leveraged ETN TVIX can best avoid assets for hedged, SPY, as a hedging instrument among the portfolios of SPY, ZIV, and TVIX. (3) Leveraged ETN TVIX can best avoid assets for hedged, SPY, as a hedging instrument among the portfolios of SPY, VXX, and TVIX. (4) Direct ETN VXX can best avoid assets for hedged, SPY, as a hedging instrument to among the portfolios of SPY, VXX and ZIV. |
URI: | http://hdl.handle.net/11455/97240 | Rights: | 同意授權瀏覽/列印電子全文服務，2017-09-07起公開。 |
| Appears in Collections: | 應用經濟學系 |
Files in This Item:
| File | Size | Format | Existing users please Login |
|---|---|---|---|
| nchu-106-7104034011-1.pdf | 1.2 MB | Adobe PDF | This file is only available in the university internal network |
TAIR Related Article
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.