IDEAS home Printed from https://ideas.repec.org/p/ecm/ausm04/55.html
   My bibliography  Save this paper

Modeling dependence structure in size-sorted portfolios: A Structural Multivariate GARCH Model

Author

Listed:
  • George Milunovich

Abstract

A new model is developed that augments a structural VAR specification with a GARCH covariance matrix. The model is utilised to study time series dependencies between three size-sorted portfolios from the Australian Stock Exchange. Even after accounting for contemporaneous correlations the returns on small and medium firm portfolios are found to lag the large firm portfolio returns. An asymmetric lag structure is also found in the structural variance equations. The evidence is consistent with the Lo and MacKinlay (1990) lead-lag effect and the volatility spill-over hypothesis of Condrad, Gultekin and Kaul (1991).

Suggested Citation

  • George Milunovich, 2004. "Modeling dependence structure in size-sorted portfolios: A Structural Multivariate GARCH Model," Econometric Society 2004 Australasian Meetings 55, Econometric Society.
    • Handle: RePEc:ecm:ausm04:55
    as

    Download full text from publisher

    File URL: http://repec.org/esAUSM04/up.6226.1076301814.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    3. Adrian Pagan, 1986. "Two Stage and Related Estimators and Their Applications," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 517-538.
    4. McQueen, Grant & Pinegar, Michael & Thorley, Steven, 1996. "Delayed Reaction to Good News and the Cross-Autocorrelation of Portfolio Returns," Journal of Finance, American Finance Association, vol. 51(3), pages 889-919, July.
    5. Conrad, Jennifer & Gultekin, Mustafa N & Kaul, Gautam, 1991. "Asymmetric Predictability of Conditional Variances," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 597-622.
    6. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    7. Lo, Andrew W. & Craig MacKinlay, A., 1990. "An econometric analysis of nonsynchronous trading," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 181-211.
    8. Cha, Baekin & Oh, Sekyung, 2000. "The relationship between developed equity markets and the Pacific Basin's emerging equity markets," International Review of Economics & Finance, Elsevier, vol. 9(4), pages 299-322, October.
    9. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    10. Fargher, Neil L & Weigand, Robert A, 1998. "Changes in the Stock Price Reaction of Small Firms to Common Information," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 21(1), pages 105-121, Spring.
    11. Conrad, Jennifer & Kaul, Gautam, 1989. "Mean Reversion in Short-Horizon Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 2(2), pages 225-240.
    12. Chang, Eric C. & McQueen, Grant R. & Pinegar, J. Michael, 1999. "Cross-autocorrelation in Asian stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 7(5), pages 471-493, December.
    13. Mech, Timothy S., 1993. "Portfolio return autocorrelation," Journal of Financial Economics, Elsevier, vol. 34(3), pages 307-344, December.
    14. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    15. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    16. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    17. Neil L. Fargher & Robert A. Weigand, 1998. "Changes In The Stock Price Reaction Of Small Firms To Common Information," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 21(1), pages 105-121, March.
    18. Jegadeesh N. & Titman S., 1995. "Short-Horizon Return Reversals and the Bid-Ask Spread," Journal of Financial Intermediation, Elsevier, vol. 4(2), pages 116-132, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vargas, Gregorio A., 2006. "An Asymmetric Block Dynamic Conditional Correlation Multivariate GARCH Model," MPRA Paper 189, University Library of Munich, Germany, revised Aug 2006.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chiao, Chaoshin & Hung, Ken & Lee, Cheng F., 2004. "The price adjustment and lead-lag relations between stock returns: microstructure evidence from the Taiwan stock market," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 709-731, December.
    2. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    3. Palani-Rajan Kadapakkam & Timothy Krause & Yiuman Tse, 2015. "Exchange traded funds, size-based portfolios, and market efficiency," Review of Quantitative Finance and Accounting, Springer, vol. 45(1), pages 89-110, July.
    4. Palani-Rajan Kadapakkam & Timothy Krause & Yiuman Tse, 2013. "Exchange Traded Funds, Size-Based Portfolios, And Market Efficiency," Working Papers 0214fin, College of Business, University of Texas at San Antonio.
    5. Chang, Eric C. & McQueen, Grant R. & Pinegar, J. Michael, 1999. "Cross-autocorrelation in Asian stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 7(5), pages 471-493, December.
    6. Francis, Bill B. & Mougoué, Mbodja & Panchenko, Valentyn, 2010. "Is there a symmetric nonlinear causal relationship between large and small firms?," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 23-38, January.
    7. McKenzie, Michael D. & Faff, Robert W., 2005. "Modeling conditional return autocorrelation," International Review of Financial Analysis, Elsevier, vol. 14(1), pages 23-42.
    8. Chaoshin Chiao & Ken Hung & Suresh Srivastava, 2004. "Testing lead-lag relations between portfolio returns under price-limits," Applied Economics Letters, Taylor & Francis Journals, vol. 11(5), pages 313-317.
    9. Drakos, Anastassios A., 2016. "Does the relationship between small and large portfolios’ returns confirm the lead–lag effect? Evidence from the Athens Stock Exchange," Research in International Business and Finance, Elsevier, vol. 36(C), pages 546-561.
    10. Ewing, Bradley T. & Malik, Farooq, 2005. "Re-examining the asymmetric predictability of conditional variances: The role of sudden changes in variance," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2655-2673, October.
    11. Kanas, Angelos & Kouretas, Georgios P., 2005. "A cointegration approach to the lead-lag effect among size-sorted equity portfolios," International Review of Economics & Finance, Elsevier, vol. 14(2), pages 181-201.
    12. Koulakiotis, Athanasios & Babalos, Vassilios & Papasyriopoulos, Nicholas, 2016. "Financial crisis, liquidity and dynamic linkages between large and small stocks: Evidence from the Athens Stock Exchange," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 40(C), pages 46-62.
    13. de Goeij, P. C. & Marquering, W., 2004. "Modeling the conditional covariance between stock and bond returns : A multivariate GARCH approach," Other publications TiSEM 94fe5ada-715a-4339-b94c-f, Tilburg University, School of Economics and Management.
    14. Jeffrey Jarrett & Zhenzhen Sun, 2011. "Evidence and explanations for the association among six Asian (Pacific-Basin) financial markets," Applied Economics, Taylor & Francis Journals, vol. 43(12), pages 1485-1496.
    15. Dong-Hyun Ahn & Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 1999. "Behavioralize This! International Evidence on Autocorrelation Patterns of Stock Index and Futures Returns," NBER Working Papers 7214, National Bureau of Economic Research, Inc.
    16. Dong-Hyun Ahn & Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 2002. "Partial Adjustment or Stale Prices? Implications from Stock Index and Futures Return Autocorrelations," The Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 655-689, March.
    17. Pan, Ming-Shiun & Liano, Kartono & Huang, Gow-Cheng, 2004. "Industry momentum strategies and autocorrelations in stock returns," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 185-202, March.
    18. Baltussen, Guido & van Bekkum, Sjoerd & Da, Zhi, 2019. "Indexing and stock market serial dependence around the world," Journal of Financial Economics, Elsevier, vol. 132(1), pages 26-48.
    19. Angel Pardo & Hipòlit Torró, 2007. "Trading with Asymmetric Volatility Spillovers," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 34(9‐10), pages 1548-1568, November.
    20. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.

    More about this item

    Keywords

    Heteroschedasticity; Simultaneous Equations; Multivariate GARCH; Size-Sorted Portfolios; Conditional Impulse Responses; Conditional Variance Decomposition;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ecm:ausm04:55. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.