223 resultados para 150403 Real Estate and Valuation Services


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This paper investigates the degree of return volatility persistence and the time-varying behaviour of systematic risk (beta) for 31 market segments in the UK real estate market. The findings suggest that different property types exhibit differences in volatility persistence and time variability. There is also evidence that the volatility persistence of each market segment and its systematic risk are significantly positively related. Thus, the systematic risks of different property types tend to move in different directions during periods of increased market volatility. Finally, the market segments with systematic risks less than one tend to show negative time variability, while market segments with systematic risk greater than one generally show positive time variability, indicating a positive relationship between the volatility of the market and the systematic risk of individual market segments. Consequently safer and riskier market segments are affected differently by increases in market volatility.

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The success of any diversification strategy depends upon the quality of the estimated correlation between assets. It is well known, however, that there is a tendency for the average correlation among assets to increase when the market falls and vice-versa. Thus, assuming that the correlation between assets is a constant over time seems unrealistic. Nonetheless, these changes in the correlation structure as a consequence of changes in the market’s return suggests that correlation shifts can be modelled as a function of the market return. This is the idea behind the model of Spurgin et al (2000), which models the beta or systematic risk, of the asset as a function of the returns in the market. This is an approach that offers particular attractions to fund managers as it suggest ways by which they can adjust their portfolios to benefit from changes in overall market conditions. In this paper the Spurgin et al (2000) model is applied to 31 real estate market segments in the UK using monthly data over the period 1987:1 to 2000:12. The results show that a number of market segments display significant negative correlation shifts, while others show significantly positive correlation shifts. Using this information fund managers can make strategic and tactical portfolio allocation decisions based on expectations of market volatility alone and so help them achieve greater portfolio performance overall and especially during different phases of the real estate cycle.

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The use of MPT in the construction real estate portfolios has two serious limitations when used in an ex-ante framework: (1) the intertemporal instability of the portfolio weights and (2) the sharp deterioration in performance of the optimal portfolios outside the sample period used to estimate asset mean returns. Both problems can be traced to wide fluctuations in sample means Jorion (1985). Thus the use of a procedure that ignores the estimation risk due to the uncertain in mean returns is likely to produce sub-optimal results in subsequent periods. This suggests that the consideration of the issue of estimation risk is crucial in the use of MPT in developing a successful real estate portfolio strategy. Therefore, following Eun & Resnick (1988), this study extends previous ex-ante based studies by evaluating optimal portfolio allocations in subsequent test periods by using methods that have been proposed to reduce the effect of measurement error on optimal portfolio allocations.

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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.

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Firms are faced with a wider set of choices when they identify a need for new office space. They can build or purchase accommodation, lease space for long or short periods with or without the inclusion of services, or they can use “instant office” solutions provided by serviced office operators. But how do they evaluate these alternatives and are they able to make rational choices? The research found that the shortening of business horizons lead to the desire for more office space on short-term contracts often with the inclusion of at least some facilities management and business support services. The need for greater flexibility, particularly in financial terms, was highlighted as an important criteria when selecting new office accommodation. The current office portfolios held were perceived not to meet these requirements. However, there was often a lack of good quality data available within occupiers which could be used to help them analyse the range of choices in the market. Additionally, there were other organisational constraints to making decisions about inclusive real estate products. These included fragmentation of decisions-making, internal politics and the lack of assessment of business risk alongside real estate risk. Overall therefore, corporate occupiers themselves act as an interial force to the development of new and innovative real estate products.

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The literature on investors’ holding periods for equities and bonds suggest that high transaction costs are associated with longer holding periods. Return volatility, by contrast, is associated with short-term trading and hence shorter holding periods. High transaction costs and the perceived illiquidity of the real estate market leads to an expectation of longer holding periods. Further, work on depreciation and obsolescence might suggest that there is an optimal holding period. However, there is little empirical work in the area. In this paper, data from the Investment Property Databank are used to investigate sales rate and holding period for UK institutional real estate between 1981 and 1994. Sales rates are investigated using the Cox proportional hazards framework. The results show longer holding periods than those claimed by investors. There are marked differences by type of property and sales rates vary over time. Contemporaneous returns are positively associated with an increase in the rate of sale. The results shed light on investor behaviour.

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This paper review the literature on the distribution of commercial real estate returns. There is growing evidence that the assumption of normality in returns is not safe. Distributions are found to be peaked, fat-tailed and, tentatively, skewed. There is some evidence of compound distributions and non-linearity. Public traded real estate assets (such as property company or REIT shares) behave in a fashion more similar to other common stocks. However, as in equity markets, it would be unwise to assume normality uncritically. Empirical evidence for UK real estate markets is obtained by applying distribution fitting routines to IPD Monthly Index data for the aggregate index and selected sub-sectors. It is clear that normality is rejected in most cases. It is often argued that observed differences in real estate returns are a measurement issue resulting from appraiser behaviour. However, unsmoothing the series does not assist in modelling returns. A large proportion of returns are close to zero. This would be characteristic of a thinly-traded market where new information arrives infrequently. Analysis of quarterly data suggests that, over longer trading periods, return distributions may conform more closely to those found in other asset markets. These results have implications for the formulation and implementation of a multi-asset portfolio allocation strategy.

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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.

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It has been asserted that business reorganisation and new working practices are transforming the nature of demand for business space. Downsizing, delayering, business process reengineering and associated initiatives alter the amount, type and location of space required by firms. The literature has neglected the impact of real estate market structures on the ability of organisations to successfully implement these new organisational forms or contemporary working practices. Drawing from UK research, the paper demonstrates that, while new working practices are widespread, their impact on the corporate real estate portfolio is less dramatic than often supposed. In part, this is attributed to inflexibility in market structures which constrains the supply of appropriate space.

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This paper investigates the potential benefits and limitations of equal and value-weighted diversification using as the example the UK institutional property market. To achieve this it uses the largest sample (392) of actual property returns that is currently available, over the period 1981 to 1996. To evaluate these issues two approaches are adopted; first, an analysis of the correlations within the sectors and regions and secondly simulations of property portfolios of increasing size constructed both naively and with value-weighting. Using these methods it is shown that the extent of possible risk reduction is limited because of the high positive correlations between assets in any portfolio, even when naively diversified. It is also shown that portfolios exhibit high levels of variability around the average risk, suggesting that previous work seriously understates the number of properties needed to achieve a satisfactory level of diversification. The results have implications for the development and maintenance of a property portfolio because they indicate that the achievable level of risk reduction depends upon the availability of assets, the weighting system used and the investor’s risk tolerance.

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Despite a number of papers that discuss the advantages of increased size on risk levels in real estate portfolios there is remarkably little empirical evidence based on actual portfolios. The objective of this paper is to remedy this deficiency by examining the portfolio risk of a large sample of actual property data over the period 1981 to 1996. The results show that all that can be said is that portfolios of properties of a large size, on the average, tend to have lower risks than small sized portfolios. More importantly portfolios of a few properties can have very high or very low risk.

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This paper identifies the long-term rental depreciation rates for UK commercial properties and rates of capital expenditure incurred to offset depreciation over the same period. It starts by reviewing the economic depreciation literature and the rationale for adopting a longitudinal method of measurement, before discussing the data used and results. Data from 1993 to 2009 were sourced from Investment Property Databank and CB Richard Ellis real estate consultants. This is used to compare the change in values of new buildings in different locations with the change in values of individual properties in those locations. The analysis is conducted using observations on 742 assets drawn from all major segments of the commercial real estate market. Overall rental depreciation and capital expenditure rates are similar to those in other recent UK studies. Depreciation rates are 0.8% pa for offices, 0.5% pa for industrial properties and 0.3% pa for standard retail properties. These results hide interesting variations at a segment level, notably in retail where location often dominates value rather than the building. The majority of properties had little (if any) money spent on them over the last 16 years, but those subject to higher rates of expenditure were found to have lower depreciation rates.

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Private sector commercial property represents some #400 bn, or 34% of total UK business assets and is a vital fabric for housing commercial enterprise. Yet social and economic forces for change, linked with new technology, are making owners and occupiers question the very nature and purpose of property and real estate.

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This study investigates the impact of experience upon trained behaviours in real estate investment decision‐making. In a controlled experiment design, two groups of subjects, experts and novices, conduct an evaluation and reach a decision about two investment options. Using a process‐tracing technique, each subject’s behaviour is observed and recorded. Differences between the groups are discovered in relation to some behaviour characteristics, but experience appears not to impact all behaviours. These findings are discussed in relation to the current absence of a universal normative model of real estate investment decision‐making. In an associated component of the study, the belief that monetary compensation is needed in order to render valid results from studies such as this is tested. We find this not to be the case.

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The purpose of the study is to seek a better understanding of the investment allocation behaviour of the real estate mutual funds by focusing on asset allocation at the country level. Analysing the country allocation of 553 real estate mutual funds domiciled in 20 countries, we attempt to trace how investment bias exists across countries and affects their country allocations. Our results evidence the existence of disproportionate country allocation to their domestic markets (domestic bias) and to each foreign market (foreign bias). We also find each bias is influenced by different sets of variables: real estate market influences for domestic bias and familiarity influences for foreign bias. This difference in factors influential for each bias in part explains the conflated relationship between the two biases.