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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/111326


    Title: 利用GARCH模型預測VIX ETN並建構避險策略
    VIX ETNs hedging strategies using GARCH models
    Authors: 吳培菱
    Contributors: 陳威光
    林靖庭
    Chen, Wei-Kuang
    Lin, Ching-Ting
    吳培菱
    Keywords: VIX指數
    GARCH模型
    ETN
    VIX Index
    GARCH models
    ETN
    Date: 2017
    Issue Date: 2017-07-24 12:04:29 (UTC+8)
    Abstract: 自從2008年金融危機爆發後，黑天鵝事件相繼出現，VIX成為投資人衡量股市波動度的重要指標。但是若投資人想使用VIX避險，僅能透過限專業投資人參與的VIX期貨。而在近年ETF產品盛行的背景下，投資標的更加多元的交易所交易債券（ETN）也應運而生，使一般投資人得以進入以往難以觸及或交易成本高昂的市場。本研究採用兩檔交易量較大之VIX ETN，分別追蹤VIX短期與中期期貨指數之VXX與VXZ，希望透過建構GARCH模型用以預測其隔日價格，並以此預測的價格近一步建構避險策略，目標係在預期空頭即將發生時，提供投資人除了VIX期貨和波動相對平穩的債券以外的避險替代工具。
    建構GARCH模型的部分，本研究主要參考Kambouroudis和McMillan（2013）的文獻，在變異數方程式中加入輔助變數，可以增加模型的預測能力，故本研究在VIX ETN之GARCH模型的變異數方程式中加入VIX、短期VIX指數及中期VIX指數。實證結果顯示，在VIX ETN的GARCH模型中同時加入VIX相關指數，確實能提高配適程度並增進預測能力，尤其當加入的輔助變數與VIX ETN追蹤標的的到期期限相符時，此改善模型的效果最為顯著。
    本研究接者參考Alexander和Korovilas（2012）的VIX ETN避險研究，文獻顯示，在S&P 500 ETF投資組合中加入VXX與VXZ避險可提高夏普比率。本研究在此基礎上，額外考量了不同的持有期間、進場條件、股債混合的投資組合，並分別比較兩種ETN的避險效果。本研究發現只在VIX大於20時才進場建構避險部位的策略，提前買入VIX ETN確實可以做為良好的避險工具。此外，在此策略下，VIX ETN亦則可達到比持有債券更佳的避險效果。而本研究所測試的兩種VIX ETN中，又以VXX 避險效果更佳，因VXX乃是追蹤VIX短期期貨指數，更能反映市場短期的變化，搭配滾動的避險比率，能更加精準的反應空頭時期劇烈的波動。
    Since the 2008 financial crisis, along with the black swan events, the volatility of global stock market has intensified, and VIX index becomes an important indicator for investors to measure the volatility of the stock market. However, if investors would like to use VIX index for hedge, they could only use VIX futures, which is only for professional investors to participate. In recent years, the prevalence and popularity of the various ETPs lead to the booming of VIX ETNs, which has become an alternative for regular investors to invest in VIX index. Therefore, this study hopes to build GARCH model for VIX ETN and predict their prices of the next day, and use the prediction to build hedging strategies.

    In this paper, this study mainly refers to the paper of Kambouroudis and McMillan (2013) to construct the VXX and VXZ prediction models. Because the two VIX ETNs track the S&P 500 VIX short-term and medium-term futures index respectively, the study add the VIX index, short-term VIX index and medium-term VIX index in the GARCH models. The empirical results show that the addition of VIX and other relevant VIX indices in the VIX ETN GARCH models can improve the forecasting ability. In particular, when the maturity of the VIX index is consistent with the maturity of the VIX ETN’s tracking target, it would improve the prediction power the most.

    Based on the predicted VIX ETN prices, this study then constructs the hedging strategies, considering the different holding period, the entry condition and the stock and debt mixed portfolio, and also compares the hedging effect of VXX and VXZ respectively. This study found that under the strategy that only enter the VIX ETN market when VIX was greater than 20, VIX ETN can indeed be a good hedge tool and reduce the standard deviation of the portfolio. In addition, under this strategy, if investors use VIX ETN to hedge, investors can achieve a higher return and lower standard deviation than holding a bond to hedge. Finally, among the two VIX ETNs tested in this study, VXX is a better hedge tool against VXX. It is because VXX tracks the VIX short-term futures index which reflects the short-term changes in the market and hence could reflect the short-term volatility better.
    Reference: 1. Ahoniemi, K., (2008), “Modelling and Forecasting the VIX Index”, Unpublished working paper, Helsinki School of Economics and HECER.
    2. Ding, Z., Granger, C. W. J., and Engle, R. F., (1993), “A long memory property of stock market returns and a new model”, Journal of Empirical Finance, Vol. 1, pp. 83-106.
    3. Engle, R. F., (1982), “Autoregressive Conditional Heteroscedasticity with estimates of the variance of UK inflation”, Econometrica, Vol. 50, pp. 987-1008.
    4. Engle, R. F., and Bollerslev, T., (1986), “Modelling the persistence of conditional variances”, Econometric Reviews, Vol. 5, pp.1-50.
    5. Dimos S Kambouroudis and David G McMillan (2015), “Does VIX or volume improve GARCH volatility forecasts?”, Applied Economics, Vol. 48(13), pp. 1-19.
    6. Frennberg, P., and Hansson, B., (1996), “An Evaluation of Alternative Models for Predicting Stock Volatility: Evidence from a Small Stock Market”, Journal of International Financial Markets Institutions and Money, Vol. 5, pp.117-134.
    7. Fuertes, A., Izzeldin, M., and Kalotychou, E., (2009), “On forecasting daily stock volatility: The role of intraday information and market conditions”, International Journal of Forecasting, Vo. 25, pp. 259-281.
    8. Nelson, D. B., (1991), “Conditional heteroscedasticity in asset returns: a new approach”, Econometrica, Vol. 59 (2), pp. 347-370.
    9. Poon, S., and Granger, C. W. J., (2003), “Forecasting Volatility in Financial Markets: A Review”, Journal of Economic Literature, Vol. 41 (2), pp. 478-539
    10. Whaley, R. E., (2009), “Understanding VIX”, Journal of Portfolio Management, Vol. 35, pp. 98-105.
    11. Alexander, Carol and Dimiris Korovilas (2012), “Diversification of Equity with VIX Futures: Personal Views and Skewness Preference”, working paper.
    12. Alexander, Carol and Dimiris Korovilas (2012), “Understanding ETNs on VIX Futures”, working paper.
    13. Liang, Youguo, Chatrath, and McIntosh (1996), “Apartment REITs and Apartment Real Estate” Journal of Real Estate Research, Vol.11, Issue 3, 277-290.
    14. Figlewski, Stephen (1985), “Hedging with Stock Index Futures: Theory and Application in a New Market”, Journal of Futures Markets, Vol. 5, Issue. 2, 183-199.
    15. Chen, Chung, and Ho (2010), “The Diversification Effects of Volatility-related Assets”, Journal of Banking and Finance, Vol. 35, Issue 5, 1179-1189.
    16. Daigler, Robert T., and Laura Rossi (2006), “A Portfolio of Stocks and Volatility”, The Journal of Investing, Vol.15, No. 2, 99–106.
    17. Dash, Srikant, and Matthew T. Moran (2005), “VIX as a Companion for Hedge Fund Portfolios”, The Journal of Alternative Investments, Vol. 8, No. 3, 75–80.
    18. Hafner, Reinhold, and Wallmeier (2008), “Optimal Investments in Volatility,” Financial Markets and Portfolio Management, Vol. 22, No.2, 147–167.
    19. Husson, Tim and McCann (2011), “The VXX ETN and Volatility Exposure” PIABA Bar Journal, Vol 18, No. 24, 235-252.
    20. Warren, Geoffrey J. (2011), “Can Investing in Volatility Help Meet Your Portfolio Objectives?”, Journal of Portfolio Management, Vol. 38, No.2, 82-98.
    21. Zhu, Song-Ping and Lian (2012), “An Analytical Formula for VIX Futures and its Applications” Journal of Futures Markets, Vol.32, No.2, 166-190.
    Description: 碩士
    國立政治大學
    金融學系
    105352004
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0105352004
    Data Type: thesis
    Appears in Collections:[Department of Money and Banking] Theses

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