政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/48957
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113648/144635 (79%)
Visitors : 51687936      Online Users : 527
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/48957


    Title: 隔夜恐慌情緒對日內台指現貨波動度與成交量之間的影響探討
    The effect of overnight emotion on the intraday relationship between TAIEX volatility and trading volume
    Authors: 袁明道
    Contributors: 杜化宇
    袁明道
    Keywords: 波動度
    成交量
    台指期貨
    VAR
    Date: 2009
    Issue Date: 2010-12-08 01:54:17 (UTC+8)
    Abstract: 本文主要針對隔夜情緒影響的不對稱性進行研究,本研究以今日開盤的波動率指數(VIX)與昨日收盤的VIX相減代表隔夜資訊,而波動率指數又稱為恐慌指數,就理論上而言,當市場出現恐慌時,波動率指數亦會上升,本文將以區分市場在恐慌普通與樂觀情緒下,波動度與成交量的關係是否有變化,其中成交量又細分為Total volume, Expected volume與Unexpected volume,此成交量分類的概念源自Illueca and Lafuente (2007),而波動度與交易量的關係則是參考Darrat et al.(2007)中VAR 的方法來探討。本文以台灣股價指數期貨與台灣股價指數作為研究標的。本文的實證結果顯示在不同的情況下,各種成交量與波動度的因果關係及影響方向均有變化,在隔夜有重要資訊發生時(恐慌或樂觀),開盤時的預期成交量與未預期成交量和波動度的因果關係會發生變化,若是普通情緒下,則各種成交量與波動度之間皆有雙向的因果關係,惟影響方向不同。開盤時段下,預期成交量除了在樂觀情緒下,會預期成交量使得波動度增加,恐慌與普通情緒下,預期成交量會使得波動度減少,類似提供流動性的角色,但極端情緒下,波動度卻無法對未預期成交量產生影響,代表在極端情緒下,波動度是由未預期成交量所導致,表示未預期成交量為波動的製造者,此與本研究推測未預期成交量帶有較大資訊含量相符。
    Reference: 陳榮逢(2008),「台股指數報酬波動性與異常交易量的關係」,國立政治大學國際經營與貿易研究所碩士論文。
    楊立吉(2008),「台北外匯市場交易量與波動性關係之實證分析」,國立政治大學國際經營與貿易研究所碩士論文。
    1. Andersen, T.G. and T. Bollerslev (1998), “Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts,” International Economic Review, 39, 885-905.
    2. Baker, Malcolm, and Jeremy Stein (2004), “Market liquidity as a sentiment indicator,” Journal of Financial Markets, 7, 271-299.
    3. Brown, Gregory W. and Michael T. Cliff (2004),”Investor Sentiment and the Near-term Stock Market,” Journal of Empirical Finance, 11, l-7.
    4. Carr, Peter P. and Wu, Liuren (2006), “A Tale of Two Indices,” The Journal of Derivatives, 13, 13-29
    5. Chen, N.F., R. Roll and S. Ross (1986), “Economic Forces and the Stock Market,” Journal of Business, Vol.59, 383-403.
    6. Clark, P.K. (1973), “A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices,” Econometrica, 41, 135-155.
    7. Conolly, R.A. (1989), “An Examination of the Robustness of the Weekend Effect,” Journal of Financial and Quantitative Analysis, 24, 133–169.
    8. Copeland, T.E. (1976), “A Model of Asset Trading under the Assumption of Sequential Information Arrival,” Journal of Finance, 31, 1149-1168.
    9. Conrad, J., A. Hameed and C. Niden, (1994), “Volume and Autocovariances in Short-horizon Individual Security Returns,” Journal of Finance, 49, 1305-1329.
    10. Darrat, A., Zhong, M. and Cheng, L. (2007) “Intraday Volume and Volatility Relations with and without Public News,” Journal of Banking and Finance, 31, 2711–2729.
    11. Epps, T. W. and Epps, M. L. (1976), “The Stochastic Dependence of Security Price Changes and Transaction Volumes Implications for the mixture-of-distribution Hypothesis,” Econometrica, Vol.44, 305-321.
    12. Etling, Cheri and Thomas W. Miller, Jr. (2000): “The Relationship Between Index Option Moneyness and Relative Liquidity,” Journal of Futures Markets, 20 (November), 971–987.
    13. Fama, Eugene F. and Kenneth R. French (1992), “The Cross-section of Expected Stock Returns,” Journal of Finance, 47, 427-465.
    14. Fama, Eugene F., and Kenneth R. French (1993), “Common Risk Factors in Returns on Stocks and Bonds,” Journal of Financial Economics, 33, 3-56.
    15. Granger, C. W. J.(1969), “Investigating Causal Relations by Econometric Models and Cross-Spectral Methods,” Econometrica, 37, 424-438.
    16. Gervais, S., R. Kaniel and D.H. Mingelgrin (2001), “The High-volume Return Premium,” Journal of Finance, LVI, 877–919.
    17. Illueca M. and Lafuente J. A. (2007) “The Effect of Futures Trading Activity on the Distribution of Spot Market Returns,” Journal of Futures Markets, 27(9), 839–866.
    18. Jennings, R., L. Starks, and J. Fellingham (1981), “An Equilibrium Model of Asset Trading with Sequential Information Arrival,” Journal of Finance, 36, 143-161.
    19. Kahneman, D., and A. Tversky, (1979), “Prospect Theory: An Analysis of Decision under Risk,” Econometrica, 47(2), 263–292.
    20. Kaniel, Ron, Gideon Saar, and Sheridan Titman. (2008), “Individual Investor Trading and Stock Returns,” Journal of Finance, 63, 273-310.
    21. Karpoff, J. M. (1987), “The Relation between Price changes and Trading Volume: A Survey,” Journal of Financial and Quantitative Analysis, Vol. 22, 109-129.
    22. Lafuente-Luengo, Juan A..(2009) “Intraday Realized Volatility Relationships between the S&P 500 Spot and Futures Market,” Journal of Derivatives & Hedge Funds, Aug2009, Vol. 15 Issue 2, 116-121.
    23. Lintner, J. (1965), “The Valuation of Risk Assets and Selection of Risky Investments in Stock Portfolios and Capital Budgets,” Review of Economics and Statistics, Vol.47, 13-37.
    24. Llorente, G., R. Michaely, G. Saar, and J. Wang, (2002), “Dynamic Volume-return Relation of Individual Stocks,” Review of Financial Studies, 15, 1005-1048.
    25. Mossin, J. (1966), “Equilibrium in a Capital Market,” Econometrica, Vol.34, 768-783.
    26. Schwert, G.W. (1989), "Why Does Stock Market Volatility Change Over Time?," Journal of Finance, 44,1115-1153.
    27. Schwert, G. William (1990), "Stock Returns and Real Activity: A Century of Evidence," NBER Working Papers 3296, National Bureau of Economic Research, Inc.
    28. Sharpe, W. F. (1964), “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk,” Journal of Finance, Vol.19, 425-442.
    29. Tauchen, G. E., and M. Pitts. (1983), “The Price Variability-Volume Relationship on Speculative Markets,” Econometrica, 51, 485-505.
    30. Tsay, R.S. (1998). “Testing and Modeling Multivariate Threshold Models,” Journal of the American Statistical Association, 93, 1188-1202.
    31. Whaley, R., (2000), “The Investor Fear Gauge,” Journal of Portfolio Management, 26, 12-17.
    32. Xu, X.E., Chen, P. and Wu, C. (2005), "Time and Dynamic Volume-Volatility Relation," Journal of Banking and Finance, 30, 1535-1558.
    Description: 碩士
    國立政治大學
    財務管理研究所
    97357004
    98
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0097357004
    Data Type: thesis
    Appears in Collections:[Department of Finance] Theses

    Files in This Item:

    There are no files associated with this item.



    All items in 政大典藏 are protected by copyright, with all rights reserved.


    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 ©   - Feedback