IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/94707.html
   My bibliography  Save this paper

Mean and Volatility Spillovers between REIT and Stocks Returns A STVAR-BTGARCH-M Model

Author

Listed:
  • Das, Mahamitra
  • Kundu, Srikanta
  • Sarkar, Nityananda

Abstract

In this study we have examined volatility spillovers as well as volatility-in-mean effect between REIT returns and stock returns for both the USA and the UK by applying a bivariate GARCH-M model where the conditional mean is specified by a smooth transition VAR model. Dynamic conditional correlation approach has been applied with the GJR-GARCH specification so that the intrinsic nature of asymmetric volatility in case of positive and negative shocks can be duly captured. The major findings that we have empirically found is that the mean spillover effect from stock returns to REIT returns is significant for both the countries while the same from REIT returns to stock returns is significant only in the UK. It is also evident from the results that own risk-return relationship of REIT market is positive and significant only in the bear market situation in both the countries while for the stock market own risk-return relationship is insignificant for both the bull and bear markets in the USA but it is negative in the bear market condition and positive in the bull market situation for the UK. We have also found that asymmetric nature of conditional variance and dynamic behavior in the conditional correlation holds as well. Finally, several tests of hypotheses regarding equality of various kinds of spillover effects in the bull and bear market situations show that these spillover effects are not the same in the two market conditions in most of the aspects considered in this study.

Suggested Citation

  • Das, Mahamitra & Kundu, Srikanta & Sarkar, Nityananda, 2019. "Mean and Volatility Spillovers between REIT and Stocks Returns A STVAR-BTGARCH-M Model," MPRA Paper 94707, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:94707
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/94707/1/MPRA_paper_94707.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. He, Changli & Teräsvirta, Timo & Malmsten, Hans, 2002. "Moment Structure Of A Family Of First-Order Exponential Garch Models," Econometric Theory, Cambridge University Press, vol. 18(4), pages 868-885, August.
    2. Turner, Christopher M. & Startz, Richard & Nelson, Charles R., 1989. "A Markov model of heteroskedasticity, risk, and learning in the stock market," Journal of Financial Economics, Elsevier, vol. 25(1), pages 3-22, November.
    3. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    4. David Michayluk & Patrick J. Wilson & Ralf Zurbruegg, 2006. "Asymmetric Volatility, Correlation and Returns Dynamics Between the U.S. and U.K. Securitized Real Estate Markets," Published Paper Series 2006-5, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    5. Chkili, Walid & Nguyen, Duc Khuong, 2014. "Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 31(C), pages 46-56.
    6. John Cotter & Simon Stevenson, 2006. "Multivariate Modeling of Daily REIT Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 32(3), pages 305-325, May.
    7. Bertero, Elisabetta & Mayer, Colin, 1990. "Structure and performance: Global interdependence of stock markets around the crash of October 1987," European Economic Review, Elsevier, vol. 34(6), pages 1155-1180, September.
    8. Liu, Crocker H. & Hartzell, David J. & Greig, Wylie & Grissom, Terry V., 1990. "The Integration of the Real Estate Market and the Stock Market: Some Preliminary Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 3(3), pages 261-282, September.
    9. Elie Bouri & Mahamitra Das & Rangan Gupta & David Roubaud, 2018. "Spillovers between Bitcoin and other assets during bear and bull markets," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5935-5949, November.
    10. Patrick Wilson & Ralf Zurbruegg & David Michayluk, 2004. "Real Estate Markets," ERES eres2004_560, European Real Estate Society (ERES).
    11. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    12. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    13. Christodoulakis, George A. & Satchell, Stephen E., 2002. "Correlated ARCH (CorrARCH): Modelling the time-varying conditional correlation between financial asset returns," European Journal of Operational Research, Elsevier, vol. 139(2), pages 351-370, June.
    14. Chan, K. C. & Karolyi, G. Andrew & Stulz, ReneM., 1992. "Global financial markets and the risk premium on U.S. equity," Journal of Financial Economics, Elsevier, vol. 32(2), pages 137-167, October.
    15. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 373-401, June.
    16. Kim, Moon K. & Zumwalt, J. Kenton, 1979. "An Analysis of Risk in Bull and Bear Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 14(5), pages 1015-1025, December.
    17. Chen, Shiu-Sheng, 2009. "Predicting the bear stock market: Macroeconomic variables as leading indicators," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 211-223, February.
    18. Yougou Liang & Michael J. Seiler & Arjun Chatrath, 1998. "Are REIT Returns Hedgeable?," Journal of Real Estate Research, American Real Estate Society, vol. 16(1), pages 87-98.
    19. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    20. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    21. Jun Han & Youguo Liang, 1995. "The Historical Performance of Real Estate Investment Trusts," Journal of Real Estate Research, American Real Estate Society, vol. 10(3), pages 235-262.
    22. David Michayluk & Patrick J. Wilson & Ralf Zurbruegg, 2006. "Asymmetric Volatility, Correlation and Returns Dynamics Between the U.S. and U.K. Securitized Real Estate Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 34(1), pages 109-131, March.
    23. James D. Peterson & Cheng‐Ho Hsieh, 1997. "Do Common Risk Factors in the Returns on Stocks and Bonds Explain Returns on REITs?," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 25(2), pages 321-345, June.
    24. Tse, Y K & Tsui, Albert K C, 2002. "A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 351-362, July.
    25. Heaney, Richard & Sriananthakumar, Sivagowry, 2012. "Time-varying correlation between stock market returns and real estate returns," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 583-594.
    26. Jian Yang & Yinggang Zhou & Wai Leung, 2012. "Asymmetric Correlation and Volatility Dynamics among Stock, Bond, and Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 491-521, August.
    27. Maximo Camacho, 2004. "Vector smooth transition regression models for US GDP and the composite index of leading indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(3), pages 173-196.
    28. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    29. Lundbergh, Stefan & Teräsvirta, Timo, 1998. "Modelling economic high-frequency time series with STAR-STGARCH models," SSE/EFI Working Paper Series in Economics and Finance 291, Stockholm School of Economics.
    30. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    31. Brad Case & Massimo Guidolin & Yildiray Yildirim, 2014. "Markov Switching Dynamics in REIT Returns: Univariate and Multivariate Evidence on Forecasting Performance," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(2), pages 279-342, June.
    32. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
    33. Jian Zhou & Zhixin Kang, 2011. "A Comparison of Alternative Forecast Models of REIT Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 275-294, April.
    34. K. C. Chan & Patric H. Hendershott & Anthony B. Sanders, 1990. "Risk and Return on Real Estate: Evidence from Equity REITs," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 18(4), pages 431-452, December.
    35. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    36. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
    37. David C. Ling & Andy Naranjo, 1999. "The Integration of Commercial Real Estate Markets and Stock Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 27(3), pages 483-515, September.
    38. Kundu, Srikanta & Sarkar, Nityananda, 2016. "Return and volatility interdependences in up and down markets across developed and emerging countries," Research in International Business and Finance, Elsevier, vol. 36(C), pages 297-311.
    39. Brent W. Ambrose & Dong Wook Lee & Joe Peek, 2007. "Comovement After Joining an Index: Spillovers of Nonfundamental Effects," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 35(1), pages 57-90, March.
    40. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    Full references (including those not matched with items on IDEAS)

    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. Kundu, Srikanta & Sarkar, Nityananda, 2016. "Return and volatility interdependences in up and down markets across developed and emerging countries," Research in International Business and Finance, Elsevier, vol. 36(C), pages 297-311.
    2. Martin Hoesli & Kustrim Reka, 2013. "Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 1-35, July.
    3. Elie Bouri & Mahamitra Das & Rangan Gupta & David Roubaud, 2018. "Spillovers between Bitcoin and other assets during bear and bull markets," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5935-5949, November.
    4. Esta Lestari, 2010. "Volatility Spillover Effects in East Asian Capital Markets: A Case Study of the Real Estate Sectors," Economics and Finance in Indonesia, Faculty of Economics and Business, University of Indonesia, vol. 58, pages 57-82, April.
    5. Kim Liow & Kim Ho & Muhammad Ibrahim & Ziwei Chen, 2009. "Correlation and Volatility Dynamics in International Real Estate Securities Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 39(2), pages 202-223, August.
    6. Kim Hiang Liow, 2010. "Integration among USA, UK, Japanese and Australian securitised real estate markets: an empirical exploration," Journal of Property Research, Taylor & Francis Journals, vol. 27(4), pages 289-308, February.
    7. Liow, Kim Hiang & Huang, Yuting, 2018. "The dynamics of volatility connectedness in international real estate investment trusts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 195-210.
    8. Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.
    9. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    10. James Chong & Alexandra Krystalogianni & Simon Stevenson, "undated". "Dynamic Correlations across REIT Sub-Sectors," Real Estate & Planning Working Papers rep-wp2011-07, Henley Business School, University of Reading.
    11. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    12. Jian Yang & Yinggang Zhou & Wai Leung, 2012. "Asymmetric Correlation and Volatility Dynamics among Stock, Bond, and Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 491-521, August.
    13. Rotta, Pedro Nielsen & Pereira, Pedro L. Valls, 2013. "Analysis of contagion from the constant conditional correlation model with Markov regime switching," Textos para discussão 340, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    14. Brad Case & Massimo Guidolin & Yildiray Yildirim, 2014. "Markov Switching Dynamics in REIT Returns: Univariate and Multivariate Evidence on Forecasting Performance," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(2), pages 279-342, June.
    15. Matthias R. Fengler & Helmut Herwartz & Christian Werner, 2012. "A Dynamic Copula Approach to Recovering the Index Implied Volatility Skew," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 457-493, June.
    16. Charlotte Christiansen, 2010. "Decomposing European bond and equity volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(2), pages 105-122.
    17. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    18. Zhou, Jian, 2014. "Modeling conditional covariance for mixed-asset portfolios," Economic Modelling, Elsevier, vol. 40(C), pages 242-249.
    19. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & María de la Cruz Del Río-Rama & José Álvarez-García, 2022. "Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black–Litterman Context (Part 1)," Mathematics, MDPI, vol. 10(8), pages 1-28, April.
    20. Chang, Kuang-Liang, 2009. "Do macroeconomic variables have regime-dependent effects on stock return dynamics? Evidence from the Markov regime switching model," Economic Modelling, Elsevier, vol. 26(6), pages 1283-1299, November.

    More about this item

    Keywords

    REIT; Volatility Spillover; STVAR-BTGARCH_M;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G1 - Financial Economics - - General Financial Markets
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:pra:mprapa:94707. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.