政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/94758
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文笔数/总笔数 : 113318/144297 (79%)
造访人次 : 51072160      在线人数 : 958
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻
    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/94758


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/94758


    题名: 選擇權波動度交易策略之探討-以台指選擇權為例
    A study of volatility trading strategies: evidence from Taiwan index options
    作者: 賴星旅
    Lai, Hsing Lu
    贡献者: 陳威光
    江彌修
    賴星旅
    Lai, Hsing Lu
    关键词: 波動度交易
    選擇權交易策率
    隱含波動度指數
    時間序列模型
    市場情緒指標
    volatility trading
    option trading strategy
    VIX
    GARCH(1,1)
    Market Sentiment Indices
    日期: 2009
    上传时间: 2016-05-09 11:49:16 (UTC+8)
    摘要: 本文考量波動度不對稱效果(Volatility Asymmetric Effect)與均數回歸(Mean Reverting)兩個特性，並考量台股市場特性，嘗試建立一個適合台灣市場的波動度交易策略。利用GARCH(1,1)波動度與VIX指標建構第一個交易訊號，並建立當日沖銷部位。以賺取日內行情為出發點，利用時間序列模型捕捉波動度的高估或低估且搭配純跨式(Pure Straddle)策略或根據Delta調整後的跨式(Adjusted Straddle)策略。第二個交易訊號則是利用市場敏感指標，觀察外資與自營商在交易部位與未平倉部位的變化，找出對於波動度的影響。建立由選擇權與期貨組成的Delta-Hedged部位，藉由觀察市場上主力籌碼的變化，動態調整部位契約，尋找波段之間的獲利機會。
    實証部分以期交所公布的每日交易資料與VIX日資料，利用2007至2008兩年的歷史資料，估計參數與測試交易訊號。樣本外期間為2009年1月開始至3月結束共55個交易日。考量交易成本後，兩個不同型態的交易訊號，仍然能夠藉由本研究的策略，獲得正的報酬。本文認為台灣為一個淺碟市場，過度反應資訊的特性，讓波動度策略出現獲利的機會。藉由這個波動度交易系統的研究，除了讓資金豐沛的機構投資人使用外，也能夠讓一般投資大眾建立自己的波動度交易策略


    關鍵字:波動度交易，選擇權交易策略，GARCH(1,1)，VIX，市場情緒指標
    Trying to apply a preliminary study of volatility trading strategies in Taiwan derivative market is the topic of this dissertation. Capturing the market movement or even the dynamic of underlying asset is a Pandora’s Box for academic researchers and industry participants. Mean-reverting and asymmetrical effects are the two special characteristics of volatility for us to design our trading system according to the previous empirical studies.
    In our study, we use different type of volatility signal to capture the trading opportunities. Use the new released information form TAIFEX including VIX and Position Structure of Institutional Traders to design our signal. We apply the idea to use pure option position and delta-hedged position as our trading tools in this volatility trading system and look for the opportunities between realized volatility and implied volatility. An over-reaction may rises the uncertainty and also lead the market volatility change coherently. We use history data from 2007 to 2008 test our trading signal and parameters. The out sample period is from 2009 January to 2009 March which has 55 trading days to simulate our strategies. In the end, we see a positive result in both trading signals which earns positive return after considering the trading cost.



    Key words: Volatility Trading, Market Sentiment Indices, Option Strategies, VIX, GARCH(1,1)
    參考文獻: 5. References
    Alexander, C. ”Market Risk Analysis”, Volume Three, John Wiley & Sons, Inc., 2008
    Andersen T. G., Bollerslev T., Christoffersen P.F. and Diebold F.X., “Volatility
    Forecasting”, Working Paper, National Bureau of Economic Research, Cambridge, 2005
    Anil K. Bera, Matthew L. Higgins, “ ARCH Models: Properties, Estimation and Testing”, Journal of Economic Surveys, 1999
    Asger L. and P. R. Hansen., “A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?”, Working Papers 04, Brown University, Department of Economics, 2001
    Bartels, H.J and Jian, L.,”Volatility Forecasting and Delta-Neutral Volatility Trading for DTB Options on the DAX”, 1998
    Bollerslev, T., “Generalized Autoregressive Conditional Heteroskedasticity,” Journal of Econometrics, 1986
    Brown, G.W.,” Volatility, sentiment, and noise traders”, Financial Analysts Journal, pp. 82–90, 1999
    Carr, P. and D Madan.,” Towards a theory of volatility trading”. Handbooks in Mathematical Finance:Option Pricing, Interest Rates and Risk Management, eds. J. Cvitanic,E. Jouini and M. Musiela, Cambridge University Press, 458–476, 2001
    Carr, P., and Wu, L.,” A Tale of Two Indices. Journal of Derivatives”, 13-29. 2004
    Clive W.J. Granger, “The past and future of empirical finance: some personal comments”, Journal of Econometrics, Volume 129, Issues 1-2, 2005
    Corrado, C. J. T., and W. Miller,” The forecast quality of CBOE implied volatility indexes”, Journal of Futures Markets 25, 2005
    De Long, J.B., Shleifer, A., Summers, L. and Waldmann, R.,” Noise trader risk in financial markets”. Journal of Political Economy 98, pp. 703–738, 1990
    Dumas, B., J. Fleming and R. E. Whaley, “Implied Volatility Functions: Empirical Tests,” Journal of Finance, 53, 1998
    Engle, R.F., “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U.K. Inflation,” Econometrica, 1982
    Franses PH, van Dijk D.,” Forecasting stock market volatility using (non-linear) GARCH models”. Journal of Forecasting 15: 229-235, 1996
    Giot P., “Relationships between Implied Volatility Indexes and Stock Index Returns. Are implied volatility indexes leading indicators?”, Journal of Portfolio Management, pp. 92-100, 2005.
    Lee,W.Y C.X. Jiang and D.C. Indro, “Stock market volatility, excess returns, and the role of investor sentiment”, Journal of Banking and Finance, pp. 2277–2299, 2002
    Mark,B.,J., and Anthony,N.,” Option Prices, Implied Price Processes, and Stochastic Volatility”, The Journal of Finance, Vol. 55, No. 2, pp. 839-866, 2000
    Poon S.H. and Granger C.W.L., “Forecasting Volatility in Financial Markets: A
    Review.”, Journal of Economic Literature, Vol. XLI , pp.478-539, 2003
    Sato,A.-H., and H. Takayasu. “Derivation of ARCH(1) Process from Market Price Changes Based on Deterministic Microscopic Multi-Agent”, Empirical Science of Financial Fluctuations, Springer, 2002
    Simon D, and Wiggins R,”S&P Futures returns and contrary sentiment indicators”, Journal of Futures Mark, 21:447–462, 2001
    Sinclar E., “Volatility Trading”, John Wiley & Sons, Inc., 2008
    Solt, M.E. and M. Statman, “How useful is the sentiment index”, Financial Analysts Journal, pp. 45–55, 1988
    Whaley, R.E., ”The investor fear gauge”, Journal of Portfolio Management 26, 2000
    Yaw-Huei Wang, Y.H. and A. Keswani, Stephen J. Taylor,” The relationships between sentiment, returns and volatility”, International Journal of Forecasting, Volume 22, Pages 109-123, 2005
    描述: 碩士
    國立政治大學
    金融研究所
    94352014
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0094352014
    数据类型: thesis
    显示于类别:[金融學系] 學位論文

    文件中的档案:

    没有与此文件相关的档案.



    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈