Real estate capital flows and transitional economies

reign real estate capital was a major source of financing domestic property market office construction in Central Europe after the fall of the Berlin Wall in 1989. During the 1990s, over 800 office buildings were either newly constructed or refurbished in Budapest, Prague and Warsaw. The primary focus of this analysis is explaining the spatial construction and redevelopment patterns of the post-1989 office buildings in these cities. Secondarily, we analyze the correlation of foreign direct investment flows to annual construction of office buildings. We seek to explain the location of new or refurbished office buildings in the central business district (CBD) or in non-CBD locations in terms of the effect of time, size of property and other variables, and test whether there is a positive correlation relationship of foreign direct investment flows and new office construction or refurbishment. Integrating relevant foreign direct investment (FDI), economic geography and property theories in the research, the authors attempt to bridge existing gaps in the literature.

The consistency of private and public real estate within mixed-asset portfolios

This study considers the consistency of the role of both the private and public real estate markets within a mixed-asset context. While a vast literature has developed that has examined the potential role of both the private and public real estate markets, most studies have largely relied on both single time horizons and single sample periods. This paper builds upon the analysis of Lee and Stevenson (2005) who examined the consistency of REITs in a US capital market portfolio. The current paper extends that by also analyzing the role of the private market. To address the question, the allocation of both the private and traded markets is evaluated over different holding periods varying from 5- to 20-years. In general the results show that optimum mixed-asset portfolios already containing private real estate have little place for public real estate securities, especially in low risk portfolios and for longer investment horizons. Additionally, mixed-asset portfolios with public real estate either see the allocations to REITs diminished or eliminated if private real estate is also considered. The results demonstrate that there is a still a strong case for private real estate in the mixed-asset portfolio on the basis of an increase in risk-adjusted performance, even if the investor is already holding REITs, but that the reverse is not always the case.

International evidence on the predictability of returns to securitized real estate assets: econometric models versus neural networks

The performance of various statistical models and commonly used financial indicators for forecasting securitised real estate returns are examined for five European countries: the UK, Belgium, the Netherlands, France and Italy. Within a VAR framework, it is demonstrated that the gilt-equity yield ratio is in most cases a better predictor of securitized returns than the term structure or the dividend yield. In particular, investors should consider in their real estate return models the predictability of the gilt-equity yield ratio in Belgium, the Netherlands and France, and the term structure of interest rates in France. Predictions obtained from the VAR and univariate time-series models are compared with the predictions of an artificial neural network model. It is found that, whilst no single model is universally superior across all series, accuracy measures and horizons considered, the neural network model is generally able to offer the most accurate predictions for 1-month horizons. For quarterly and half-yearly forecasts, the random walk with a drift is the most successful for the UK, Belgian and Dutch returns and the neural network for French and Italian returns. Although this study underscores market context and forecast horizon as parameters relevant to the choice of the forecast model, it strongly indicates that analysts should exploit the potential of neural networks and assess more fully their forecast performance against more traditional models.

Monetary integration and real estate markets: an investigation of the impact of the introduction of a single currency on real estate performance

This paper assesses the impact of the monetary integration on different types of stock returns in Europe. In order to isolate European factors, the impact of global equity integration and small cap factors are investigated. European countries are sub-divided according to the process of monetary convergence. Analysis shows that national equity indices are strongly influenced by global market movements, with a European stock factor providing additional explanatory power. The global and European factors explain small cap and real estate stocks much less well –suggesting an increased importance of ‘local’ drivers. For real estate, there are notable differences between core and non-core countries. Core European countries exhibit convergence – a convergence to a European rather than a global factor. The non-core countries do not seem to exhibit common trends or movements. For the non-core countries, monetary integration has been associated with increased dispersion of returns, lower correlation and lower explanatory power of a European factor. It is concluded that this may be explained by divergence in underlying macro-economic drivers between core and non-core countries in the post-Euro period.

The transition of the Polish real estate market within a Central and Eastern European context

The real estate market in Poland is a relatively immature market, but one that has been experiencing substantial transformation. The development of the market has been encouraged by a number of factors, including changes arising as a result of new legislation and the migration of capital between capital markets. The progress of the real estate sector towards a western style competitive market has taken place within the gradual transformation of the Polish economy into a free market economy. As investment grade property is in relatively short supply in Poland, investors consider opportunities within the wider CEE block. An analysis of the risk-return characteristics of the three largest CEE real estate markets namely, Poland, Hungary and Czech Republic, shows that the returns in these markets have been negatively correlated with the UK. As these economies and markets evolve, and being part of the wider EU trading block, their economic performance will slowly converge and become more synchronized with their western counterparts. However, the catch-up of the CEE markets to western European performance cycles will be protracted and consequently there are likely to be significant ongoing portfolio risk reduction opportunities

Re-thinking commercial real estate market segmentation

Investments in direct real estate are inherently difficult to segment compared to other asset classes due to the complex and heterogeneous nature of the asset. The most common segmentation in real estate investment analysis relies on property sector and geographical region. In this paper, we compare the predictive power of existing industry classifications with a new type of segmentation using cluster analysis on a number of relevant property attributes including the equivalent yield and size of the property as well as information on lease terms, number of tenants and tenant concentration. The new segments are shown to be distinct and relatively stable over time. In a second stage of the analysis, we test whether the newly generated segments are able to better predict the resulting financial performance of the assets than the old dichotomous segments. Applying both discriminant and neural network analysis we find mixed evidence for this hypothesis. Overall, we conclude from our analysis that each of the two approaches to segmenting the market has its strengths and weaknesses so that both might be applied gainfully in real estate investment analysis and fund management.

An analysis of commercial real estate returns: an anatomy of smoothing in asset and index returns

In this article, we investigate the commonly used autoregressive filter method of adjusting appraisal-based real estate returns to correct for the perceived biases induced in the appraisal process. Many articles have been written on appraisal smoothing but remarkably few have considered the relationship between smoothing at the individual property level and the amount of persistence in the aggregate appraisal-based index. To investigate this issue we analyze a large sample of appraisal data at the individual property level from the Investment Property Databank. We find that commonly used unsmoothing estimates at the index level overstate the extent of smoothing that takes place at the individual property level. There is also strong support for an ARFIMA representation of appraisal returns at the index level and an ARMA model at the individual property level.

Risk management and the corporate real estate portfolio

In a global business economy, firms have a broad range of corporate real estate needs. During the past decade, multiple strategies and tactics have emerged in the corporate real estate community for meeting those needs. We propose here a framework for analysing and prioritising the various types of risk inherent in corporate real estate decisions. From a business strategy perspective, corporate real estate must serve needs beyond the simple one of shelter for the workforce and production process. Certain uses are strategic in that they allow access to externalities, embody the business strategy, or provide entrée to new markets. Other uses may be tactical, in that they arise from business activities of relatively short duration or provide an opportunity to pre-empt competitors. Still other corporate real estate uses can be considered “core” to the existence of the business enterprise. These might be special use properties or may be generic buildings that have become embodiments of the organisation’s culture. We argue that a multi-dimensional matrix approach organised around three broad themes and nine sub-categories allow the decision-maker to organise and evaluate choices with an acceptable degree of rigor and thoroughness. The three broad themes are Use (divided into Core, Cyclical or Casual) – Asset Type (which can be Strategic, Specialty or Generic) and Market Environment (which ranges from Mature Domestic to Emerging Economy). Proper understanding of each of these groupings brings critical variables to the fore and allows for efficient resource allocation and enhanced risk management.