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Conditional market beta for REITs: A comparison of modeling techniques

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  • Zhou, Jian

Abstract

There has accumulated strong evidence in the literature that market beta (β) is time varying. This paper contributes to the literature by studying how to best model the time varying beta for REITs. We include several commonly used methods and evaluate their performances in terms of in-sample beta estimates and out-of-sample beta forecasts. We apply these methods to U.S. equity REITs. Our results overwhelmingly suggest that the state space model is the best performer. Such a conclusion is supported by different evaluation criteria and robust to different sample splitting. Our findings have direct financial implications. The forecasted betas (preferably through the state space model) can be used in many applications such as estimating the cost of capital for the purpose of capital budgeting involving REITs, identifying equity REIT mispricing, evaluating the performance of managed REIT portfolios, etc.

Suggested Citation

  • Zhou, Jian, 2013. "Conditional market beta for REITs: A comparison of modeling techniques," Economic Modelling, Elsevier, vol. 30(C), pages 196-204.
  • Handle: RePEc:eee:ecmode:v:30:y:2013:i:c:p:196-204
    DOI: 10.1016/j.econmod.2012.09.030
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    1. 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.
    2. Juan Yao & Jiti Gao, 2004. "Computer-Intensive Time-Varying Model Approach to the Systematic Risk of Australian Industrial Stock Returns," Australian Journal of Management, Australian School of Business, vol. 29(1), pages 121-145, June.
    3. Kalaba, Robert E. & Tesfatsion, Leigh S., 1989. "Time-Varying Linear Regression Via Flexible Least Squares," Staff General Research Papers Archive 11196, Iowa State University, Department of Economics.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," American Economic Review, American Economic Association, vol. 95(2), pages 398-404, May.
    5. Braun, Phillip A & Nelson, Daniel B & Sunier, Alain M, 1995. "Good News, Bad News, Volatility, and Betas," Journal of Finance, American Finance Association, vol. 50(5), pages 1575-1603, December.
    6. Ho-Chuan Huang, 2000. "Tests of regimes - switching CAPM," Applied Financial Economics, Taylor & Francis Journals, vol. 10(5), pages 573-578.
    7. Robert D. Brooks & Robert W. Faff & Michael D. McKenzie, 1998. "Time†Varying Beta Risk of Australian Industry Portfolios: A Comparison of Modelling Techniques," Australian Journal of Management, Australian School of Business, vol. 23(1), pages 1-22, June.
    8. Kalaba, Robert & Rasakhoo, Nima & Tesfatsion, Leigh, 1989. "A FORTRAN program for time-varying linear regression via flexible least squares," Computational Statistics & Data Analysis, Elsevier, vol. 7(3), pages 291-309, February.
    9. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    10. Willard McIntosh & Youguo Liang & Daniel L. Tompkins, 1991. "An Examination of the Small-Firm Effect within the REIT Industry," Journal of Real Estate Research, American Real Estate Society, vol. 6(1), pages 9-18.
    11. Lynne B. Sagalyn, 1990. "Real Estate Risk and the Business Cycle: Evidence from Security Markets," Journal of Real Estate Research, American Real Estate Society, vol. 5(2), pages 203-220.
    12. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    13. Kladroba, Andreas, 2005. "Flexible least squares estimation of state space models: an alternative to Kalman-filtering," IBES Diskussionsbeiträge 149, University of Duisburg-Essen, Institute of Business and Economic Studie (IBES).
    14. Collins, Daniel W & Ledolter, Johannes & Rayburn, Judy Dawson, 1987. "Some Further Evidence on the Stochastic Properties of Systematic Risk," The Journal of Business, University of Chicago Press, vol. 60(3), pages 425-448, July.
    15. Nicolaas Groenewald & Patricia Fraser, 2000. "Forecasting Beta: How Well Does the 'Five-Year Rule of Thumb' Do?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(7&8), pages 953-982.
    16. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    17. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.
    18. Schwert, G William & Seguin, Paul J, 1990. "Heteroskedasticity in Stock Returns," Journal of Finance, American Finance Association, vol. 45(4), pages 1129-1155, September.
    19. Markus Ebner & Thorsten Neumann, 2005. "Time-Varying Betas of German Stock Returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 19(1), pages 29-46, June.
    20. Fabozzi, Frank J. & Francis, Jack Clark, 1978. "Beta as a Random Coefficient," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 13(1), pages 101-116, March.
    21. Juan Cabrera & Tao Wang & Jian Yang, 2011. "Linear and Nonlinear Predictability of International Securitized Real Estate Returns: A Reality Check," Journal of Real Estate Research, American Real Estate Society, vol. 33(4), pages 565-594.
    22. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    23. Black, A. & Fraser, P. & Power, D., 1992. "UK unit trust performance 1980-1989: A passive time-varying approach," Journal of Banking & Finance, Elsevier, vol. 16(5), pages 1015-1033, September.
    24. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    25. Eugene F. Fama & Kenneth R. French, 2004. "The Capital Asset Pricing Model: Theory and Evidence," Journal of Economic Perspectives, American Economic Association, vol. 18(3), pages 25-46, Summer.
    26. Koutmos, Gregory & Lee, Unro & Theodossiu, Panayiotis, 1994. "Time-varying betas and volatility persistence in International Stock markets," Journal of Economics and Business, Elsevier, vol. 46(2), pages 101-112, May.
    27. Sunder, Shyam, 1980. "Stationarity of Market Risk: Random Coefficients Tests for Individual Stocks," Journal of Finance, American Finance Association, vol. 35(4), pages 883-896, September.
    28. Abell, John D. & Krueger, Thomas M., 1989. "Macroeconomic influences on beta," Journal of Economics and Business, Elsevier, vol. 41(2), pages 185-193, May.
    29. R. D. Brooks & R. W. Faff & M. McKenzie, 2002. "Time varying country risk: an assessment of alternative modelling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 8(3), pages 249-274.
    30. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    31. 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.
    32. Bos, T & Newbold, P, 1984. "An Empirical Investigation of the Possibility of Stochastic Systematic Risk in the Market Model," The Journal of Business, University of Chicago Press, vol. 57(1), pages 35-41, January.
    33. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5‐6), pages 523-554, June.
    34. Taufiq Choudhry & Hao Wu, 2009. "Forecasting the weekly time-varying beta of UK firms: GARCH models vs. Kalman filter method," The European Journal of Finance, Taylor & Francis Journals, vol. 15(4), pages 437-444.
    35. Blume, Marshall E, 1971. "On the Assessment of Risk," Journal of Finance, American Finance Association, vol. 26(1), pages 1-10, March.
    36. Terence Khoo & David Hartzell & Martin Hoesli, 1993. "An Investigation of the Change in Real Estate Investment Trust Betas," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 21(2), pages 107-130, June.
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    Cited by:

    1. Mokhtar, Maznita & Masih, Mansur, 2014. "Are diversification benefits obtainable within the same asset class? New evidence from Malaysian Islamic REITS," MPRA Paper 56990, University Library of Munich, Germany.
    2. Meichi Huang & Chih-Chiang Wu, 2015. "Economic benefits and determinants of extreme dependences between REIT and stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 44(2), pages 299-327, February.
    3. Alptekin, Aynur & Broadstock, David C. & Chen, Xiaoqi & Wang, Dong, 2019. "Time-varying parameter energy demand functions: Benchmarking state-space methods against rolling-regressions," Energy Economics, Elsevier, vol. 82(C), pages 26-41.
    4. Mi, Lin & Benson, Karen & Faff, Robert, 2018. "A specialised volatility index for the new GICS sector - Real estate," Economic Modelling, Elsevier, vol. 70(C), pages 438-446.
    5. Horváth, Lajos & Li, Bo & Li, Hemei & Liu, Zhenya, 2020. "Time-varying beta in functional factor models: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    Conditional market beta; Modeling techniques; In-sample estimate; Out-of-sample forecast; REITs;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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