Pricing inefficiencies in private real estate markets using total return swaps

Efficient markets should guarantee the existence of zero spreads for total return swaps. However, real estate markets have recorded values that are significantly different from zero in both directions. Possible explanations might suggest non-rational behaviour by inexperienced market players or unusual features of the underlying asset market. We find that institutional characteristics in the underlying market lead to market inefficiencies and, hence, to the creation of a rational trading window with upper and lower bounds within which transactions do not offer arbitrage opportunities. Given the existence of this rational trading window, we also argue that the observed spreads can substantially be explained by trading imbalances due to the limited liquidity of a newly formed market and/or to the effect of market sentiment, complementing explanations based on the lag between underlying market returns and index returns.

Gauging the investment potential of international real estate markets

Investing in real estate markets overseas means venturing into the unknown, where you meet unfamiliar political and economic environments, unstable currencies, strange cultures and languages, and so although the advantages of international diversification might appear attractive, the risks of international investment must not be overlooked. However, capital markets are becoming global markets, and commercial real estate markets are no exception, accordingly despite the difficulties posed by venturing overseas no investor can overlook the potential international investment holds out. Thus, what strategies are appropriate for capitalising on this potential? Three issues must be considered: (1) the potential of the countries real estate market in general; (2) the potential of the individual market sectors; and (3) the investment process itself. Although each step in foreign real estate investment is critical, the initial assessment of opportunities is especially important. Various methods can be used to achieve this but a formal and systematic analysis of aggregate market potential should prove particularly fruitful. The work reported here, therefore, develops and illustrates such a methodology for the over 50 international real estate markets.

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.

Style analysis in real estate markets: beyond the sectors and regions dichotomy

While style analysis has been studied extensively in equity markets, applications of this valuable tool for measuring and benchmarking performance and risk in a real estate context are still relatively new. Most previous real estate studies on this topic have identified three investment categories (rather than styles): sectors, administrative regions and economic regions. However, the low explanatory power reveals the need to extend this analysis to other investment styles. We identify four main real estate investment styles and apply a multivariate model to randomly generated portfolios to test the significance of each style in explaining portfolio returns. Results show that significant alpha performance is significantly reduced when we account for the new investment styles, with small vs. big properties being the dominant one. Secondly, we find that the probability of obtaining alpha performance is dependent upon the actual exposure of funds to style factors. Finally we obtain that both alpha and systematic risk levels are linked to the actual characteristics of portfolios. Our overall results suggest that it would be beneficial for real estate fund managers to use these style factors to set benchmarks and to analyze portfolio returns.

The risks of investing in the real estate markets of the asian region

The Asian region has become a focus of attention for investors in recent years. Due to the strong economic performance of the region, the higher expected returns in the area compared with Europe and the USA and the additional diversification benefits investment in the region would offer. Nonetheless many investors have doubts about the prudence of investing in such areas. In particular it may be felt that the expected returns offered in the countries of the Asian region are not sufficient to compensate investors for the increased risks of investing in such markets. These risks can be categorised into under four headings: investment risk, currency risk, political risk, and institutional risk. This paper analyses each of these risks in turn to see if they are sufficiently large to deter real estate investment in the region in general or in a particular country.

Evidence of cycles in European commercial real estate markets and some hypotheses

In this paper, we seek to achieve four objectives. First, we provide some contextual material concerning the performance of the UK real estate market relative to stocks and bonds over a long period. Second, we provide UK – and some non-UK European - evidence of the tendency for property demand, supply, prices and returns to fluctuate around their long term trends or averages. Third, we briefly examine some hypotheses which suggest institutional contributions to property cycles in European markets. Fourth, we suggest some reasons why the future may not be as cyclical as the past.

Real estate markets and the macroeconomy: a dynamic coherence framework

This paper analyzes the dynamic interactions between real estate markets, in the US and the UK and their macroeconomic environments. We apply a new approach based on a dynamic coherence function (DCF) to study these interactions bringing together different real estate markets (the securitized market, the commercial market and the residential market). The results suggest that there is a common trend that drives the different real estate markets in the UK and the US, particularly in the long run, since they have a similar shape of the DCF. We also find that, in the US, wealth and housing expenditure channels are very conductive during real estate crises. However, in the UK, only the wealth effect is significant as a transmission channel during real estate market downturns. In addition, real estate markets in the UK and the US react differently to institutional shocks. This brings some insights on the conduct of monetary policy in order to avoid disturbances in real estate markets.

On the predictive content of leading indicators: the case of U.S. real estate markets

This paper employs a probit and a Markov switching model using information from the Conference Board Leading Indicator and other predictor variables to forecast the signs of future rental growth in four key U.S. commercial rent series. We find that both approaches have considerable power to predict changes in the direction of commercial rents up to two years ahead, exhibiting strong improvements over a naïve model, especially for the warehouse and apartment sectors. We find that while the Markov switching model appears to be more successful, it lags behind actual turnarounds in market outcomes whereas the probit is able to detect whether rental growth will be positive or negative several quarters ahead.

Assessing macro uncertainty in real-time when data are subject to revision

Model-based estimates of future uncertainty are generally based on the in-sample fit of the model, as when Box-Jenkins prediction intervals are calculated. However, this approach will generate biased uncertainty estimates in real time when there are data revisions. A simple remedy is suggested, and used to generate more accurate prediction intervals for 25 macroeconomic variables, in line with the theory. A simulation study based on an empirically-estimated model of data revisions for US output growth is used to investigate small-sample properties.