English  |  正體中文  |  简体中文  |  Post-Print筆數 : 11 |  Items with full text/Total items : 88837/118541 (75%)
Visitors : 23547821      Online Users : 574
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: http://nccur.lib.nccu.edu.tw/handle/140.119/36584


    Title: Co-movement in Market Liquidity Measures
    市場流動性指標之共動性
    Authors: 劉鴻耀
    Liu, Hung-Yao
    Contributors: 郭維裕
    Kuo, Wei-Yu
    劉鴻耀
    Liu, Hung-Yao
    Keywords: 共動性
    流動性
    時間序列分解
    Co-movement
    Liquidity
    Time-Series Decomposition
    State-Space Models
    Date: 2002
    Issue Date: 2009-09-18 18:54:42 (UTC+8)
    Abstract: Abstract

    Undoubtedly, liquidity is one of the most popular topics of research among the academia for decades. However intuitively-clear it is, scholars and experts have always found it not only hard but vague to define and measure. Moreover, researches or methods concerning commonality in liquidity are proposed one after another. Most of these works attempt to document what lies beneath the commonality by offering industry-wide or market-wide explanations. Nevertheless, this paper adopts an exact multivariate model-based structural decomposition methodology developed by Casals, Jerez and Sotoca (2002) to analyze the co-movement in market liquidity measures in a totally different manner. Except for decomposing three well-known market liquidity measures, share volume, dollar volume and turnover rate, of the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) into trend, cycle, seasonal and irregular components, we conduct advanced bivariate analysis to extract common components, visualize them, and make a comparison among them at last. Evidence suggests that not only do these three liquidity proxies highly co-move with one another, but dollar volume seems to co-move slightly closer with share volume than with turnover rate. In the end, where this phenomenon, co-movement in market liquidity measures, accrues from is another long story and needs some further work not covered in this study.
    Reference: References
    Aoki, M., 1990. State Space Modeling of Time Series. Springer-
    Verlag, Berlin.
    Bernstein, P.L., 1987. Liquidity, stock markets, and market
    makers. Financial Management, 54-62.
    Black, F., 1986. Noise. Journal of Finance 41, 529-543.
    Box, G. E. P., Cox, D. R., 1964. An analysis of
    transformations. Journal of the Royal Statistical Society B
    (26), 211-243.
    Box, G. E. P., Jenkins, G. M., Reinsel, G. C., 1994. Time
    Series Analysis: Forecasting and Control, 3rd Edition.
    Prentice Hall , Englewood Cliffs, N.J..
    Brockman, P., Chung, D. Y., 2002. Commonality in liquidity:
    evidence from an order-driven market structure. The Journal
    of Financial Research 25(4), 521-539.
    Burman, J.P., 1980. Seasonal adjustment by signal extraction.
    Journal of the Royal Statistical Society A (143), 321-337.
    Casals, J., Jerez, M., Sotoca, S., 2000. Exact smoothing for
    stationary and nonstationary time series. International
    Journal of Forecasting 16(1), 59-69.
    Casals, J., Jerez, M., Sotoca, S., 2002. An exact multivariate
    model-based structural decomposition. Journal of the American
    Statistical Association 97(458), 553-564.
    Casals, J., Sotoca, S., Jerez, M., 1999. A fast and stable
    method to compute the likelihood of time invariant State-
    Space models. Economics Letters 65, 329-337.
    Chordia, T., Roll, R., Subrahmanyam, A., 2000. Commonality in
    liquidity. Journal of Financial Economics 56, 3-28.
    Engle, R.F., and Kozicki, S., 1993. Testing for common
    features. Journal of Business and Economic Statistics 11, 369-
    380.
    Harvey, A.C., 1989. Forecasting, Structural Time Series Models
    and the Kalman Filter. Cambridge University Press, Cambridge.
    Hasbrouck, J., Seppi, D. J., 2001. Common factors in prices,
    order flows and liquidity. Journal of Financial Economics 59,
    383-411.
    Huberman, G., Halka, D., 2001. Systematic liquidity. The
    Journal of Financial Research 24(2), 161-178.
    Jenkins, G.M., Alavi, A.S., 1981. Some aspects of modelling and
    forecasting multivariate time series. Journal of Time Series
    Analysis 2(1), 1-47.
    Kyle, A.S., 1985. Continuous auctions and insider trading.
    Econometrica 53, 1315-1335.
    Petkov, P. Hr., Christov, N.D., Konstantinov, M.M., 1991.
    Computational Methods for Linear Control Systems. Prentice-
    Hall, Englewood Cliffs, N.J..
    Terceiro, J., 1990. Estimation of Dynamic Econometric Models
    with Errors in Variables. Springer-Verlag, Berlin.
    West, M., 1997. Time series decomposition and analysis in a
    study of Oxygen Isotope records. Biometrika 84, 489-494.
    Description: 碩士
    國立政治大學
    國際經營與貿易研究所
    90351024
    91
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0090351024
    Data Type: thesis
    Appears in Collections:[國際經營與貿易學系 ] 學位論文

    Files in This Item:

    File SizeFormat
    index.html0KbHTML323View/Open


    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
    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。
    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。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback