Skip to main content
SpringerLink
Log in

Regime dependent volatilities and correlation in international securitized real estate markets

  • Original Paper
  • Published:
Empirica Aims and scope Submit manuscript

Abstract

This paper studies the role of regime shifts and time-varying volatilities in market integration in a Markov-switching volatility regime environment among the US, European and Asian developed securitized real estate markets. With a two-state volatility model, the study finds the co-dependence, co-movement and synchronization of volatility regime at the high volatility state are stronger between the US and European securitized real estate markets. Although correlations among the markets are higher in a high volatility regime than in a low volatility regime, there is limited evidence of contagious effects during the high volatility periods between some markets. Moreover, the unsecuritized real estate markets are different from their securitized equivalent in the volatility regime characteristics, correlation pattern and level, as well as the extent of correlation change and contagion effect in high volatility state. Thus, the regime-switching results from stock markets may not be automatically extended to the corresponding public real estate markets, and requires rigorous empirical scrutiny.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. There are two forms of real estate investment: private real estate investment and public (securitized) real estate investment. The former refers to physical real estate assets with steady cash flows. The latter is a more liquid and low-cost channel to gain real estate exposure such as listed property companies and Real Estate Investment Trusts (known as REITs). Securitized real estate is also referred as “public real estate”. From this point onward, the terms “securitized real estate”, “public real estate”, “listed real estate” and “real estate” will be used interchangeably throughout the paper.

  2. There is growing recognition on the important role of real estate such as its contribution to lower overall portfolio risk, providing high absolute returns and hedging against unexpected inflation or deflation (Hudson-Wilson et al. 2003).

  3. EPRA stands for European Public Real Estate Association; INREV is the European Association for Investors in Non-listed Real Estate Vehicles.

  4. The EPRA and National Association of Real Estate Investment Trusts NAREIT) estimate the market capitalization of these eight markets is at least about 90% of the global public real estate market.

  5. As in Edwards and Susmel (2001), since our interest is on bivariate switching and three states (k− = 3) considerably complicate the estimation, we focus our attention on a two-state system (k − 2), although we recognise that in some public real estate markets, a three-state SWARCH model may be more appropriate (Liow and Ye 2014). Ramchand and Susmel (1998) also find a two-state (k = 2) formulation is a parsimonious way to capture the shift in variance, “In fact a two-state formulation is able to capture in a statistical and economic sense, the changes in variance regimes, while a three-state regime is rejected (page 399).” Finally, there are two states/regimes which are widely discussed and analysed in the literature: bullish and bearish. A bullish market corresponds to a state of high return and low volatility, while a bearish market indicates low return and high volatility.

  6. As a first step in our analysis of public real estate market volatility, we find high volatility persistence and evidence of structural change in the volatility process for all series. After rejecting the null hypothesis of no regime switch, we propose a bivariate SWARCH model that links correlations to the volatility regime.

  7. For the purpose of this study and for parsimonious reason, we will only investigate across nine market-pairs (out of 28 pairs):

    1. (a)

      US and AU, US and HK, US and JP, US and SG

    2. (b)

      US and FR, US and GE, US and UK

    3. (c)

      UK and FR, UK and GE

    In (a) and (b) above, US is the “originator” (defined as a market whose change in the volatility state causes a change in the correlation coefficient with a recipient market) of each pair. Hence the correlation coefficients are state-dependent. Moreover, the covariance matrix is specified as a constant correlation matrix with the diagonal elements follow a SWARCH process. Finally, given the leading position of the US securitized real estate market in the global setting and considered plausible. For (c), the UK market (the largest in Europe) is specified as the volatility “originator” among the three European real estate markets.

  8. The optimal lag length (p) of the eight-variable MS-VAR (p) is chosen as p = 2 based on the minimized AIC criterion (AIC at lag 2 = 38175.436). The model is estimated by BFGS and with a function value of 20264.9221.

  9. The mean volatility values in regime 1 (low volatility) are 0.000316 (US), 0.000521 (UK), 0.000516 (FR), 0.000640(GE), 0.000425 (AU), 0.00109 (HK), 0.00130 (JP) and 0.000914 (SG). They are: 0.00330 (US), 0.00328 (UK), 0.00230 (FR), 0.00434 (GE), 0.00317 (AU), 0.00483 (HK), 0.00414 (JP) and 0.00550 (SG) in regime 2 (high volatility).

  10. Please consult Forbes and Rigobon (2002) for a detailed description of contagion test methodology.

  11. We first specify the GFC period to cover the period from August 1, 2007 to March 31, 2009 following the timeline provided by the Fed Reserve Board of St. Louis. From this, a pre-crisis period (before August 1, 2007) of equal duration is specified. For the eight markets, we then estimate their respective conditional volatilities [based on a GARCH (1,1) model] for both the pre-GFC and GFC period, conditional volatility correlation during the GFC period, and finally the unconditional return correlation during the pre-GFC and GFC periods. The results are not presented for brevity reason.

  12. The bivariate SWARCH results are not presented for brevity reason.

  13. The optimal lag length (p) of the eight-variable unsecuritized MS-VAR (1) is chosen as p = 1 based on the minimized AIC criterion (AIC at lag 1 = −39.379958). The model is estimated by BFGS and converges in 13 iterations with a function value of 23612.7511.

  14. The detailed MS-VAR (1) results for the eight unsecuritized real estate markets are not reported for brevity.

References

  • Ahmad W, Bhanumurthy NR, Sehgal S (2015) Regime dependent dynamics and European stock markets: is asset allocation really possible. Empirica 42:77–107

    Article  Google Scholar 

  • Ang A, Bekaert G (2002) International asset allocation with regime shifts. Rev Financ Stud 15:1137–1187

    Article  Google Scholar 

  • Ang A, Chen J (2002) Asymmetric correlations of equity portfolios. J Financ Econ 63:443–494

    Article  Google Scholar 

  • Bai J, Perron P (2003) Computation and analysis of multiple structural change models. J Appl Econom 18:1–22

    Article  Google Scholar 

  • Bond SA, Dungey M, Fry R (2006) A web of shocks: crises across Asian real estate markets. J Real Estate Financ Econ 32:253–274

    Article  Google Scholar 

  • Cai J (1994) A Markov model of unconditional variance in ARCH. J Bus Econ Stat 12:309–316

    Google Scholar 

  • Canarella G, Pollard SK (2007) A switching ARCH (SWARCH) model of stock market volatility: some evidence from Latin America. Int Rev Econ 54(4):445–462

    Article  Google Scholar 

  • Case B, Guidolin M, Yildrim Y (2014) Markov switching dynamics in REIT returns: univariate and multivariate evdience on foredcasting performance. Real Estate Econ 42(2):279–342

    Article  Google Scholar 

  • Chang GD, Chen CS (2014) Evidence of contagion in global REITs investment. Int Rev Econ Financ 31:148–158

    Article  Google Scholar 

  • Chkili W, Nguyen DK (2014) Exchange rate movements and stock market returns in a regime-switching environment: evidence for BRIS countries. Res Int Bus Financ 31:36–56

    Article  Google Scholar 

  • Chow GC (1960) Tests of equality between sets of coefficients in two linear regressions. Econometrica 28:591–605

    Article  Google Scholar 

  • Crawford GW, Fratantoni MC (2003) Assessing the forecasting performance of regime-switching, ARIMA and GARCH models of house prices. Real Estate Econ 31(2):223–243

    Article  Google Scholar 

  • Diamandis P (2008) Financial liberalization and changes in the dynamic behavior of emerging market volatility: evidence from four Latin American equity markets. Res Int Bus Financ 22:362–377

    Article  Google Scholar 

  • Edwards S, Susmel R (2001) Volatility dependence and contagion in emerging equity markets. J Dev Econ 66:505–532

    Article  Google Scholar 

  • Eichholtz PM (1996) Does international diversification work better for real estate than for stocks and bonds? Financ Anal J 52(1):56–62

    Article  Google Scholar 

  • Forbes KJ, Rigobon R (2002) No contagion, only interdependence: measuring stock market comovements. J Financ 57:2223–2261

    Article  Google Scholar 

  • Gerlach R, Wilson P, Zurbruegg R (2006) Structural breaks and diversification: the impact of the 1997 Asian financial crisis on the integration of Asia-Pacific real estate markets. J Int Money Financ 25:974–991

    Article  Google Scholar 

  • Giliberto S (1990) Equity real estate trusts and real estate return. J Real Estate Res 5:259–273

    Google Scholar 

  • Guidolin M, Timmermann A (2007) Asset allocation under multivariate regime switching. J Econ Dyn Control 31(11):3503–3544

    Article  Google Scholar 

  • Guo F, Chen CR, Huang YS (2011) Markets contagion during financial crisis: a regime-switching approach. Int Rev Econ Financ 20(1):95–109

    Article  Google Scholar 

  • Hamilton JD (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econom J Econom Soc 357–384

  • Hamilton JD, Susmel R (1994) Autoregressive conditional heteroskedasticity and changes in regime. J Econ 64:307–333

    Article  Google Scholar 

  • Hoesli M, Reka K (2013) Volatility spillovers, comovements and contagion in securitized real estate markets. J Real Estate Financ Econ 47:1–35

    Article  Google Scholar 

  • Hoesli M, Reka K (2015) Contagion channels between real estate and financial markets. Real Estate Econ 43(1):101–138

    Article  Google Scholar 

  • Hudson-Wilson S, Fabozzi FJ, Gordon JN (2003) Why real estate? J Portf Manag 29:12–25

    Article  Google Scholar 

  • Jochun C (2001) Is the covariance of international stock market returns regime dependent? Eur J Financ 7:247–268

    Article  Google Scholar 

  • Kallberg JG, Liu CH, Pasquariello P (2002) Regime shifts in Asian equity and real estate markets. Real Estate Econ 30:263–291

    Article  Google Scholar 

  • Krolzig H-M (1997) Markov-switching vector autoregressions (modelling, statistical interference, and application to business cycle analysis). Lecture notes in economics and mathematical systems

  • Lamoureux CG, Lastrapes WD (1990) Heteroskedasticity in stock return data: volume versus GARCH effects. J Financ 45(1):221–229

    Article  Google Scholar 

  • Li M (2007) Volatility states and international diversification of international stock markets. Appl Econ 39(14):1867–1876

    Article  Google Scholar 

  • Lin TC, Lin ZH (2011) Are stock and real estate markets integrated? An empirical study of six Asian economies. Pacific-Basin Financ J 19(5):571–585

    Article  Google Scholar 

  • Ling D, Naranjo A (2002) Commercial real estate return performance: a cross-country analysis. J Real Estate Financ Econ 24:119–142

    Article  Google Scholar 

  • LIow KH (2008) Financial crisis and Asian real estate securities market interdependence: some additional evidence. J Prop Res 25:127–155

    Article  Google Scholar 

  • Liow KH, Ye Q (2014) Switching volatility and cross-market linkages in public property markets. J Prop Res 31(4):287–314

    Article  Google Scholar 

  • Liow KH, Zhu H (2007) Regime switching and asset allocation: evidence from international real estate security markets. J Prop Invest Financ 25(3):274–288

    Article  Google Scholar 

  • Liow KH, Zhu H, Ho DK, Addae-Dapaah K (2005) Regime changes in international securitized property markets. J Real Estate Portf Manag 11:147–165

    Google Scholar 

  • Liow KH, Ho KH, Ibrahim MF, Chen Z (2009) Correlation and volatility dynamics in international real estate securities markets. J Real Estate Financ Econ 39:202–223

    Article  Google Scholar 

  • Liow KH, Chen Z, Liu J (2011) Multiple regimes and volatility transmission in securitized real estate markets. J Real Estate Financ Econ 42:295–328

    Article  Google Scholar 

  • Lizieri C (2013) After the fall: real estate in the mixed-asset portfolio in the aftermath of the global financial crisis. J Portf Manag 39(5):43

    Article  Google Scholar 

  • Longin F, Solnik B (2001) Extreme correlation of international equity markets. J Financ 56:649–676

    Article  Google Scholar 

  • Lu C, Tse Y, Williams M (2013) Returns transmission, value at risk, and diversification benefits in international REITs: evidence from the financial crisis. Rev Quant Financ Acc 40(2):293–318

    Article  Google Scholar 

  • Maitland-Smith JK, Brooks C (1999) Threshold autoregressive and Markov switching models: an application to commercial real estate. J Prop Res 16:1–19

    Article  Google Scholar 

  • McCue TE, Kling JL (1994) Real estate returns and the macroeconomy: some empirical evidence from real estate investment trust data, 1972–1991. J Real Estate Res 9:277–287

    Google Scholar 

  • Milunovich G, Trück S (2013) Regional and global contagion in real estate investment trusts: the case of the financial crisis of 2007-2009. J Prop Invest Financ 31(1):53–77

    Article  Google Scholar 

  • Nishiyama K (1998) Some evidence on regime shifts in international stock markets. Manag Financ 24(4):30–55

    Google Scholar 

  • Qiao Z, Li Y, Wong W-K (2010) Regime-dependent relationships among the stock markets of the US, Australia and New Zealand: a Markov-switching VAR approach. Appl Financ Econ 21(24):1831–1841

    Article  Google Scholar 

  • Ramchand L, Susmel R (1998) Volatility and cross correlation across major stock markets. J Empir Financ 5:397–416

    Article  Google Scholar 

  • Schaller H, Van Norden S (1997) Regime switching in stock market returns. Appl Financ Econ 7:177–191

    Article  Google Scholar 

  • Wang P, Thebold M (2008) Regime-switching volatility of six East Asian emerging markets. Res Int Bus Financ 22:267–283

    Article  Google Scholar 

  • Yunus N (2009) Increasing convergence between US and international securitized property markets: evidence based on co-integration tests. Real Estate Econ 37(3):383–411

    Article  Google Scholar 

Download references

Acknowledgements

The first author wishes to acknowledge the funding support given by the Ministry of Education, Singapore, in respect of the research project R-297-000-119-112 to which this paper is related to. The funding agency had no involvement in study design, data collection and analysis, development of results and final preparation of report, as well as decision to submit the article for publication.

Author information

Authors and Affiliations

  1. Department of Real Estate, National University of Singapore, 4 Architecture Drive, Singapore, 117566, Singapore

    Kim Hiang Liow & Qing Ye

Authors
  1. Kim Hiang Liow
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qing Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kim Hiang Liow.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liow, K.H., Ye, Q. Regime dependent volatilities and correlation in international securitized real estate markets. Empirica 45, 457–487 (2018). https://doi.org/10.1007/s10663-017-9368-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10663-017-9368-4

Keywords

Search

Navigation