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The purpose of this paper is to investigate the volatility spectral of five major public real estate markets, namely, the USA, the UK, Japan (JP), Hong Kong (HK), and Singapore (SG), during the pre- and post-global financial crisis (GFC) periods.

First, univariate spectral analysis is concerned with discovering price cycles for the respective real estate markets. Second, bivariate cross-spectral analysis seeks to uncover whether any two real estate price series share common cycles with regard to their relative magnitudes and lead-lag patterns of the cyclical variations. Finally, to test the contagion effects, the authors estimate the exact percentage change in co-spectral density (cyclical covariance) due to high frequencies (short run) after the GFC.

The authors find that whilst none of the public real estate markets examined are spared from the crisis, the three Asian markets were less severely affected by the GFC and were accompanied by a reversal in volatility increase three years post-global financial crisis. Additionally, the public real estate markets studied have become more cyclically linked in recent years. This is particularly true at longer frequencies. Finally, these increased cyclical co-movements measure the outcomes of contagion and indicate fairly strong contagious effects between the public real estate markets examined due to the crisis.

The implication of this research is that benefits to investors from international real estate diversification may not be as great during the present time compared to previous periods because national public real estate markets have become more correlated. Nevertheless, the findings do not imply the complete absence of diversification benefits. This is because although cyclical correlations increase in the short run, many of the correlation values are still between low and moderate range, indicating that some diversification benefits may still be realized.

Given the significant market share and the highest levels of securitization in Asia-Pacific markets including JP, HK/China, and SG, this cyclical research including major public real estate markets has practical implications for ongoing international real estate investment strategies, particularly for the USA/UK and Asian portfolio managers.

This paper contributes to the limited research on the cyclical return and co-movement dynamics among major public real estate markets during financial/economic crisis in international finance. Moreover, the frequency-domain analysis conducted in this paper adds to better understanding regarding the impact of GFC on the cyclical return volatility and co-movement dynamics of major developed public real estate markets in international investing.

The purpose of this paper is to help us understand the real estate cycle and offers an analysis using a vector auto regression (VAR) model. The authors study the key international cities of Hong Kong, Kuala Lumpur and Singapore. The authors find four key outcomes. One, the real estate cycle is generally different from the underlying business cycle in local markets for the cities studies. Two, the real estate cycle is more exaggerated in the construction and development areas than in rents and vacancies. Three, the vacancy cycle tends to lead the rental cycle. And four, new construction completions tend to peak when vacancy is also peaking. The authors believe that future research should try to help understand the linkages that drive these outcomes. For example, are rigidities in the local permit and construction markets responsible for the link between construction peaks and vacancy peaks?

Real estate market cyclical dynamics and its estimation via VAR model offers an insightful set of practical and empirical models. It affirms a comprehensive theoretical underpinning for analysing the prime office and residential sectors of the capitol cities of Kuala Lumpur, Singapore and Hong Kong in the fast developing Asia region. Its unrestricted form also provides an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, furnished by real estate market data providers.

The office rental VAR model for Singapore (SOR), KL (KOR) and HK (HOR) show good fits. In the HOR model, rents and vacancies are negatively signed and significant for certain lagged relationships with other variables and with rents themselves. The office CV VAR model for Singapore (SOCV), KL (KOCV) and HK (HOCV) show good fits. In the HOCV model, capital values (CVs) and initial yields are negatively signed and significant for certain lagged relationships with other variables and with CVs themselves. Impulse response functions specified for seven years to mirror a medium-term real estate market cycle “die out” to zero for the stationary VAR models that are estimated for the endogenous variables. The accumulated responses asymptote to some non-zero constant.

The VAR model offers a complete and meaningful dynamic system of solely real estate variables for international real estate investors and policy makers in decision making. Its unrestricted form offers an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, which can be reliably provided by a dedicated real estate information and consultancy provider of international standing.

The theoretical model offers a complete dynamic model system of the real estate space market, comprising a unique system of six linked equations that denote the relationship among supply, demand, construction, vacancy and rent over time, inclusive of price response slopes and lags. The VAR model enables the investigation of the effect of the lagged values of all the variables concerned. It also enables the explicit and rigorous quantitative forecasts of say rents and CVs when the rest of the variable can be forecasted beforehand.

The purpose of this paper is to investigate the cross-spectra of stock, real estate and bond of ten selected Asian economies in the pre- and post-global financial crisis periods to detect whether there is greater cyclical co-movement post-financial crisis, and whether any observed increased co-movement measures the outcomes of contagion or integration.

Co-spectral approach is the proper econometric tool to deliver economic insight for this research.

Results indicate that Asian stock markets, and to a lesser degree, bond and real estate markets are more correlated post-financial crisis. Similarly, Asian financial markets have experienced increased co-movements with the US financial markets post-financial crisis. Moreover, these observed increased co-movements measure the outcomes of contagion in some cases of within-asset and cross-asset classes, as well as for some cross-US-Asian asset factor relationships along the high-frequency components of between two and four weeks. The stock markets are the most contagious, followed by the real estate markets and bond markets.

The results provide short-term investors with additional co-movement information at higher frequencies in order to identify short-term fluctuations of different asset classes. The empirical study also underscores the role of Asian real estate in investment portfolios in a mixed real estate, stock and bond context from a frequency domain perspective.

The practical implication of this research is that benefits to investors from international diversification may not be as great during the present time compared to previous periods because financial/asset market movements have become more correlated. However, it does not imply the complete absence of diversification benefits. This is because although cyclical correlations increase in the short run, many of the values are still between low and moderate range, indicating that some diversification benefits may still be realized.

In advancing the body of knowledge in international financial markets, this research is probably the first study to consider a multi-asset class portfolio context that includes stock, real estate and bond across the ten Asian economies and the USA in a single study. The frequency domain analysis conducted in this paper adds to the understanding of real estate, stock and bond market co-movement, integration and contagion dynamics, as well as the Asian cross-asset factor and US-Asian asset factor relationships in global mixed-investing environment.

The purpose of this paper is to improve the transparency of European emerging real estate market dynamics and performance attributes in the wake of the 2007-2008 global financial crisis (GFC). The paper examines the extent and nature of inter-relationships between three emerging real estate markets namely, the Czech Republic, Hungary and Poland as well as determining the rationale for including emerging real estate markets within a Pan-European investment portfolio. The paper affords a timely update following the reinstatement of lending provision for European emerging real estate investment markets in 2014.

The paper employs lead-lag correlations and Grainger causality to examine inter and intra relationships across three emerging European real estate markets, namely the Czech Republic, Hungary and Poland over the period 2006-2014. Optimal portfolio analysis is undertaken to explore the role of emerging real estate markets within the confines of a multi-asset investment portfolio as well as a Pan-European real estate investment portfolio.

The findings demonstrate the opportunities afforded by the European emerging real estate markets in terms of both performance enhancement and risk diversification. Significantly, the findings highlight the lack of “uniformity” across the European emerging markets in terms of their investment potential, with Grainger causality confirming that the real estate markets in the Czech Republic, Hungary and Poland are not endogenous functions of one-another’s performance.

This paper makes a considered contribution to the analytical interpretation of European emerging property market performance across the real estate cycle. The research demonstrates that the real estate markets in the Czech Republic, Hungary and Poland exhibit specific investment characteristics which differentiate them from the more developed real estate markets across Europe. Indeed emerging markets have the propensity to serve as both a risk diversifier as well as performance enhancer within the confines of a pan-European real estate investment portfolio. However, as the research clearly articulates, intricate understanding of the attributes afforded by the different emerging markets as well as the divergence in sectoral dynamics/performance is integral to portfolio allocation strategies.

Robust academic research on Europe’s emerging real estate markets has been hampered by deficiencies in data provision. This study makes an innovative and timely contribution to redressing the research vacuum through delineated examination of the performance dynamics of three markets namely, the Czech Republic, Hungary and Poland, across the real estate cycle. The role and function of emerging markets is depicted within the confines of a Pan-European direct real estate investment portfolio at the all property level and in terms of sectoral specific allocations comprising retail, office and industrial. The explicit added value of the paper is the propensity to bench-mark the performance of emerging markets real estate markets on a like-for-like basis with developed real estate markets across Europe facilitating the exploration of the role and function of emerging real estate markets within a Pan-European investment context.

This research aims to investigate whether and to what extent the co-movements of cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles are linked across G7 from February 1990 to June 2014.

The empirical approaches include correlation analysis on Hodrick–Prescott (HP) cycles, HP cycle return spillovers effects using Diebold and Yilmaz’s (2012) spillover index methodology, as well as Croux et al.’s (2001) dynamic correlation and cohesion methodology.

There are fairly strong cycle-return spillover effects between the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles. The interactions among the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles in G7 are less positively pronounced or exhibit counter-cyclical behavior at the traditional business cycle (medium-term) frequency band when “pure” stock market cycles are considered.

The research is subject to the usual limitations concerning empirical research.

This study finds that real estate is an important factor in influencing the degree and behavior of the relationship between cross-country business cycles and cross-country stock market cycles in G7. It provides important empirical insights for portfolio investors to understand and forecast the differential benefits and pitfalls of portfolio diversification in the long-, medium- and short-cycle horizons, as well as for research studying the linkages between the real economy and financial sectors.

In adding to the existing body of knowledge concerning economic globalization and financial market interdependence, this study evaluates the linkages between business cycles, stock market cycles and public real estate market cycles cross G7 and adds to the academic real estate literature. Because public real estate market is a subset of stock market, our approach is to use an original stock market index, as well as a “pure” stock market index (with the influence of real estate market removed) to offer additional empirical insights from two key complementary perspectives.

The paper seeks to examine cycles and common cycles in the real estate markets of the UK, Japan, Singapore, Hong Kong and Malaysia using a combination of time domain and frequency domain methods.

The paper identifies the patterns of cyclical movement (if any) in the five public real estate markets, and searches for common cycle characteristics and patterns in international real estate markets. In addition to the time domain analyses, these empirical investigations are further empowered by a frequency domain method that includes spectral and co‐spectral analyses.

International real estate markets are characterized by cyclical behavior that exhibits phenomenal fluctuations. The markets are also pro‐cyclical; they do tend to move together. Furthermore, some differences in the patterns of the common cycles and their lead‐lag linkages are evident.

International investors would probably benefit from diversifying real estate stocks across the UK and Asian real estate markets, especially in the short and medium terms. However, the long‐term cyclical patterns across the national real estate stock markets are not sharply different, indicating that smaller diversification benefits are to be expected in the long term.

Common cycle analysis advances investors' understanding of the long‐term relationship and medium‐ and short‐term linkages across international real estate markets, thereby allowing investors and portfolio managers an opportunity to discern any contrasting cyclical patterns at all frequencies so as to assist in their portfolio decisions.

This paper aims to propose a new valuation method for income producing properties. The model originally called cyclical dividend discount models (d’Amato, 2003) has been recently proposed as a family of income approach methodologies called cyclical capitalization (d’Amato, 2013; d’Amato, 2015; d’Amato, 2017).

The proposed methodology tries to integrate real estate market cycle analysis and forecast inside the valuation process allowing the appraiser to deal with real estate market phases analysis and their consequence in the local real estate market.

The findings consist in the creation of a methodology proposed for market value and in particular for mortgage lending determination, as the model may have the capability to reach prudent opinion of value in all the real estate market phase.

Research limitation consists mainly in a limited number of sample of time series of rent and in the forecast of more than a cap rate or yield rate even if it is quite commonly accepted the cyclical nature of the real estate market.

The implication of the proposed methodology is a modified approach to direct capitalization finding more flexible approaches to appraise income producing properties sensitive to the upturn and downturn of the real estate market.

The model proposed can be considered useful for the valuation process of those property affected by the property market cycle, both in the mortgage lending and market value determination.

These methodologies try to integrate in the appraisal process the role of property market cycles. Cyclical capitalization modelling includes in the traditional dividend discount model more than one g-factor to plot property market cycle dealing with the future in a different way. It must be stressed the countercyclical nature of the cyclical capitalization that may be helpful in the determination of mortgage lending value. This is a very important characteristic of such models.

The purpose of this paper is to provide a dating system for the Italian residential real estate market from 1927 to 2019 and investigate its interaction with credit and business cycles.

To detect the local turning point of the Italian residential real estate market, the authors apply the honeycomb cycle developed by Janssen et al. (1994) based on the joint analysis of house prices and the number of transactions. To this end, the authors use a unique historical reconstruction of house price levels by Baffigi and Piselli (2019) in addition to data on transactions.

This study confirms the validity of the honeycomb model for the last four decades of the Italian housing market. In addition, the results show that the severe downsizing of the housing market is largely associated with business and credit contraction, certainly contributing to exacerbating the severity of the recession. Finally, preliminary evidence suggests that whenever a price bubble occurs, it is coincident with the start of phase 2 of the honeycomb cycle.

To the best of the authors’ knowledge, this is the first time that the honeycomb approach has been tested over such a long historical period and compared to the cyclic features of financial and real aggregates. In addition, even if the honeycomb cycle is not a model for detecting booms and busts in the housing market, the preliminary evidence might suggest a role for volume/transactions in detecting housing market bubbles.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.