Can institutional investors bias real estate portfolio appraisals? Evidence from the market downturn

This paper investigates the extent to which institutional investors may have influenced independent real estate appraisals during the financial crisis. A conceptual model of the determinants of client influence on real estate appraisals is proposed. It is suggested that the extent of clients’ ability and willingness to bias appraisal outputs is contingent upon market and regulatory environments (ethical norms and legal and institutional frameworks), the salience of the appraisal(s) to the client, financial incentives for the appraiser to respond to client pressure, organisational culture, the level of moral reasoning of both individual clients and appraisers, client knowledge and the degree of appraisal uncertainty. The potential of client influence to bias ostensibly independent real estate appraisals is examined using the opportunity afforded by the market downturn commencing in 2007 in the UK. During the market turbulence at the end of 2007, the motivations of different types of owners to bias appraisals diverged clearly and temporarily provided a unique opportunity to assess potential appraisal bias. We use appraisal-based performance data for individual real estate assets to test whether there were significant ownership effects on performance during this period. The results support the hypothesis that real estate appraisals in this period reflected the differing needs of clients.

Direct investment in real estate

Momentum strategies have the potential to generate extra profits in private real estate markets. Tests of a variety of frequencies of portfolio reweighting identify periods of winner and loser performance. There are strong potential gains from momentum strategies that are based on prior returns over a 6- to 12-month period. Whether these gains are attainable for real-world investors depends on transaction costs, but some momentum strategies do produce net excess returns. The findings hold even if returns are unsmoothed to reflect underlying market prices.

Analysing UK real estate market forecast disagreement

Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The results suggest that real estate forecasts are biased, less volatile compared to market returns and inefficient in that forecast errors tend to persist. The strongest finding is that real estate forecasters display the characteristics associated with a consensus indicating herding.

When does direct real estate improve portfolio performance?

For over twenty years researchers have been recommending that investors diversify their portfolios by adding direct real estate. Based on the tenets of modern portfolio theory (MPT) investors are told that the primary reason they should include direct real estate is that they will enjoy decreased volatility (risk) through increased diversification. However, the MPT methodology hides where this reduction in risk originates. To over come this deficiency we use a four-quadrant approach to break down the co-movement between direct real estate and equities and bonds into negative and positive periods. Then using data for the last 25-years we show that for about 70% of the time a holding in direct real estate would have hurt portfolio returns, i.e. when the other assets showed positive performance. In other words, for only about 30% of the time would a holding in direct real estate lead to improvements in portfolio returns. However, this increase in performance occurs when the alternative asset showed negative returns. In addition, adding direct real estate always leads to reductions in portfolio risk, especially on the downside. In other words, although adding direct real estate helps the investor to avoid large losses it also reduces the potential for large gains. Thus, if the goal of the investor is offsetting losses, then the results show that direct real estate would have been of some benefit. So in answer to the question when does direct real estate improve portfolio performance the answer is on the downside, i.e. when it is most needed.

Ownership Advantages in Cross-border Real Estate Development: Some Evidence from European Markets

Drawing upon European industry and country case studies, this paper investigates the scope and drivers of cross-border real estate development. It is argued that the real estate development process encompasses a diverse range of activities and actors. It is inherently localised, the production process is complex and emphermal, and the outputs are heterogeneous. It analyses a transactions database of European real estate markets to provide insights into the extent of, and variations in, market penetration by non-domestic real estate developers. The data were consistent with the expectation that non-domestic real estate developers from mature markets would have a high level of market penetration in immature markets. Compared to western European markets, the CEE real estate office sales by developers were dominated by US, Israeli and other EU developers. This pattern is consistent with the argument that non-domestic developers have substantial Dunning-type ownership advantages when entering immature real estate markets. However, the data also suggested some unexpected patterns. Relative to their GDP, Austria, Belgium, Denmark, Sweden, Netherlands and Israel accounted for large proportions of sales by developers. All are EU countries (except Israel) with small, open, affluent, highly traded economies. Further, the data also indicate that there may be a threshold where locational disadvantages outweigh ownership advantages and deter cross-border real estate development.

Do responsible real estate companies outperform their peers?

This paper investigates the relationship between corporate social and environmental performance and financial performance for a sample of publicly traded US real estate companies. Using the MSCI ESG (formerly KLD) database on seven Environmental, Social & Governance dimensions in the 2003-2010 period, and weighting the dimensions according to prominence in the real estate sector, we model Tobin's Q and annual total return in a panel data framework. The results indicate a positive relationship between ESG rating and Tobin's Q but this effect is driven by ESG concerns rather than strengths. Consistently across all model specifications, overall ESG ratings are associated with lower returns. Negative scores appear to result in higher returns in the short run but positive scores have no significant impact on returns.

Can sentiment surveys pre-empt real estate market activities?

We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting the demand and supply activities. Our focus lies on sector-specific surveys targeting the players from the supply-side of both residential and non-residential real estate markets. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework, we test the efficacy of these indices by comparing them with other coincident indicators in predicting real estate returns. Overall, our analysis suggests that sentiment indicators convey important information which should be embedded in the modeling exercise to predict real estate market returns. Generally, sentiment indices show better information content than broad economic indicators. The goodness of fit of our models is higher for the residential market than for the non-residential real estate sector. The impulse responses, in general, conform to our theoretical expectations. Variance decompositions and out-of-sample predictions generally show desired contribution and reasonable improvement respectively, thus upholding our hypothesis. Quite remarkably, consistent with the theory, the predictability swings when we look through different phases of the cycle. This perhaps suggests that, e.g. during recessions, market players’ expectations may be more accurate predictor of the future performances, conceivably indicating a ‘negative’ information processing bias and thus conforming to the precautionary motive of consumer behaviour.

Sector and regional factors in real estate returns

This paper presents a simple method to measure the effect of sector and regional factors in real estate returns, and thus provides a quantitative framework for analysing the relative impact of these two diversification categories to real estate portfolio selection. Using data on Retail, Office and Industrial properties spread across 326 real estate locations in the UK, over the period 1981 to 1995, the results show that the performance of real estate is largely sector-driven. A result in line with previous work. Which implies that the sector composition of the real estate fund should be the first level of analysis in constructing and managing the real estate portfolio. As a consequence real estate fund managers need to pay more attention to the sector allocation of their portfolios than the regional spread.

Futures trading, spot price volatility and market efficiency: evidence from European real estate securities futures

In 2007 futures contracts were introduced based upon the listed real estate market in Europe. Following their launch they have received increasing attention from property investors, however, few studies have considered the impact their introduction has had. This study considers two key elements. Firstly, a traditional Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, the approach of Bessembinder & Seguin (1992) and the Gray’s (1996) Markov-switching-GARCH model are used to examine the impact of futures trading on the European real estate securities market. The results show that futures trading did not destabilize the underlying listed market. Importantly, the results also reveal that the introduction of a futures market has improved the speed and quality of information flowing to the spot market. Secondly, we assess the hedging effectiveness of the contracts using two alternative strategies (naïve and Ordinary Least Squares models). The empirical results also show that the contracts are effective hedging instruments, leading to a reduction in risk of 64 %.

Threshold autoregressive and Markov switching models: an application to commercial real estate

Although financial theory rests heavily upon the assumption that asset returns are normally distributed, value indices of commercial real estate display significant departures from normality. In this paper, we apply and compare the properties of two recently proposed regime switching models for value indices of commercial real estate in the US and the UK, both of which relax the assumption that observations are drawn from a single distribution with constant mean and variance. Statistical tests of the models' specification indicate that the Markov switching model is better able to capture the non-stationary features of the data than the threshold autoregressive model, although both represent superior descriptions of the data than the models that allow for only one state. Our results have several implications for theoretical models and empirical research in finance.

Timing and the holding periods of institutional real estate

Literature on investors' holding periods for securities suggests that high transaction costs are associated with longer holding periods. Return volatility, by contrast, is associated with shorter holding periods. In real estate, high transaction costs and illiquidity imply longer holding periods. Research on depreciation and obsolescence suggests that there might be an optimal holding period. Sales rates and holding periods for U.K. institutional real estate are analyzed, using a proportional hazards model, over an 18-year period. The results show longer holding periods than those claimed by investors, with marked differences by type of property and over time. The results shed light on investor behavior.