The role of serviced offices in the corporate real estate supply chain

The paper analyses the evolving corporate real estate supply chain and the interaction of this evolution with emerging business models in the serviced office sector. An enhanced model of the corporate real estate portfolio is first presented incorporating vacant, alienated and transitory space. It is argued that the serviced office sector has evolved in response to an increasingly diverse corporate real estate portfolio. For the peripheral corporate real estate portfolio, the core serviced workspace product provides the ability to rapidly acquire high-quality workspace and associated support services on very flexible bases. Whilst it is arguably a beta product, the core workspace offer is now being augmented by managed office or back-to-back leases which enables clients to complement the advantages of serviced offices with a wider choice of premises. Joint venture business models are aligned with solutions to problems of vacant space.

Forecasting real estate returns using financial spreads

This paper examines the predictability of real estate asset returns using a number of time series techniques. A vector autoregressive model, which incorporates financial spreads, is able to improve upon the out of sample forecasting performance of univariate time series models at a short forecasting horizon. However, as the forecasting horizon increases, the explanatory power of such models is reduced, so that returns on real estate assets are best forecast using the long term mean of the series. In the case of indirect property returns, such short-term forecasts can be turned into a trading rule that can generate excess returns over a buy-and-hold strategy gross of transactions costs, although none of the trading rules developed could cover the associated transactions costs. It is therefore concluded that such forecastability is entirely consistent with stock market efficiency.

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.

A comparative analysis of the accuracy and uncertainty in real estate and macroeconomic forecasts

We compare and contrast the accuracy and uncertainty in forecasts of rents with those for a variety of macroeconomic series. The results show that in general forecasters tend to be marginally more accurate in the case of macro-economic series than with rents. In common across all of the series, forecasts tend to be smoothed with forecasters under-estimating performance during economic booms, and vice-versa in recessions We find that property forecasts are affected by economic uncertainty, as measured by disagreement across the macro-forecasters. Increased uncertainty leads to increased dispersion in the rental forecasts and a reduction in forecast accuracy.

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.

Public real estate and the term structure of interest rates: a cross-country study

Using a variation of the Nelson-Siegel term structure model we examine the sensitivity of real estate securities in six key global markets to unexpected changes in the level, slop and curvature of the yield curve. Our results confirm the time-sensitive nature of the exposure and sensitivity to interest rates and highlight the importance of considering the entire term structure of interest rates. One issue that is of particular of interest is that despite the 2007-9 financial crisis the importance of unanticipated interest rate risk weakens post 2003. Although the analysis does examine a range of markets the empirical analysis is unable to provide definitive evidence as to whether REIT and property-company markets display heightened or reduced exposure.

Do laws influence the cost of real estate brokerage services? A state fixed effects approach

A FTC-DOJ study argues that state laws and regulations may inhibit the unbundling of real estate brokerage services in response to new technology. Our data show that 18 states have changed laws in ways that promote unbundling since 2000. We model brokerage costs as measured by number of agents in a state-level annual panel vector autoregressive framework, a novel way of analyzing wasteful competition. Our findings support a positive relationship between brokerage costs and lagged house price and transactions. We find that change in full-service brokers responds negatively (by well over two percentage points per year) to legal changes facilitating unbundling

The blended approach to real estate allocations: performance implications of combining an exposure to German Spezialfonds with Global Listed Real Estate Securities

This paper seeks to increase the understanding of the performance implications for investors who choose to combine an unlisted real estate portfolio (in this case German Spezialfonds) with a (global) listed real estate element. We call this a “blended” approach to real estate allocations. For the avoidance of doubt, in this paper we are dealing purely with real estate equity (listed and unlisted) allocations, and do not incorporate real estate debt (listed or unlisted) or direct property into the process. A previous paper (Moss and Farrelly 2014) showed the benefits of the blended approach as it applied to UK Defined Contribution Pension Schemes. The catalyst for this paper has been the recent attention focused on German pension fund allocations, which have a relatively low (real estate) equity content, and a high bond content. We have used the MSCI Spezialfonds Index as a proxy for domestic German institutional real estate allocations, and the EPRA Global Developed Index as a proxy for a global listed real estate allocation. We also examine whether a rules based trading strategy, in this case Trend Following, can improve the risk adjusted returns above those of a simple buy and hold strategy for our sample period 2004-2015. Our findings are that by blending a 30% global listed portfolio with a 70% allocation (as opposed to a typical 100% weighting) to Spezialfonds, the real estate allocation returns increase from 2.88% p.a. to 5.42% pa. Volatility increases, but only to 6.53%., but there is a noticeable impact on maximum drawdown which increases to 19.4%. By using a Trend Following strategy raw returns are improved from 2.88% to 6.94% p.a. , The Sharpe Ratio increases from 1.05 to 1.49 and the Maximum Drawdown ratio is now only 1.83% compared to 19.4% using a buy and hold strategy . Finally, adding this (9%) real estate allocation to a mixed asset portfolio allocation typical for German pension funds there is an improvement in both the raw return (from 7.66% to 8.28%) and the Sharpe Ratio (from 0.91 to 0.98).

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.

Flight to quality? An investigation of changing price spreads in commercial real estate markets

Purpose – The purpose of this paper is to investigate the effect of the crisis on the pricing of asset quality attributes. This paper uses sales transaction data to examine whether flight from risk phenomena took place in the US office market during the financial crisis of 2007-2009. Design/methodology/approach – Hedonic regression procedures are used to test the hypothesis that the spread between the pricing of low-quality and high-quality characteristics increased during the crisis period compared to the pre-crisis period. Findings – The results of the hedonic regression models suggest that the price spread between Class A and other properties grew significantly during the downturn. Research limitations/implications – Our results are consistent with the hypothesis of an increased price spread following a market downturn between Class A and non-Class A offices. The evidence suggests that the relationships between the returns on Class A and non-Class A assets changed during the period of market stress or crisis. Practical implications – These findings have implications for real estate portfolio construction. If regime switches can be predicted and/or responded to rapidly, portfolios may be rebalanced. In crisis periods, portfolios might be reweighted towards Class A properties and in positive market periods, the reweighting would be towards non-Class A assets. Social implications – The global financial crisis has demonstrated that real estate markets play a crucial role in modern economies and that negative developments in these markets have the potential to spillover and create contagion for the larger economy, thereby affecting jobs, incomes and ultimately people’s livelihoods. Originality/value – This is one of the first studies that address the flight to quality phenomenon in commercial real estate markets during periods of financial crisis and market turmoil.

Decomposing Consumer Wealth Effects: Evidence on the Role of Real Estate Assets Following the Wealth Cycle of 1990-2002

During the period of 1990-2002 US households experienced a dramatic wealth cycle, induced by a 369% appreciation in the value of real per capita liquid stock market assets followed by a 55% decline. However, consumer spending in real terms continued to rise throughout this period. Using data from 1990-2005, traditional life-cycle approaches to estimating macroeconomic wealth effects confront two puzzles: (i) econometric evidence of a stable cointegrating relationship among consumption, income, and wealth is weak at best; and (ii) life-cycle models that rely on aggregate measures of wealth cannot explain why consumption did not collapse when the value of stock market assets declined so dramatically. We address both puzzles by decomposing wealth according to the liquidity of household assets. We find that the significant appreciation in the value of real estate assets that occurred after the peak of the wealth cycle helped sustain consumer spending from 2001 to 2005.