The majority of studies that explore property portfolio construction and management strategies utilise highly aggregated ex-post data, but stock selection is known to be a significant determinant of portfolio performance. Thus, here we look at stock selection, focusing on the choices faced by investors, necessitating the collection and analysis of primary data, carried out utilising conjoint analysis. This represents a new step in property research, with the data collection undertaken using a simulation exercise. This enables fund managers to make hypothetical purchase decisions, viewing properties comprising a realistic bundle of attributes and making complex contemporaneous trade-offs between attributes, subject to their stated market and economic forecasts and sector specialism. In total 51 fund managers were surveyed, producing 918 purchase decisions for analysis, with additional data collected regarding fund and personal characteristics. The results reveal that 'fixed' property characteristics (location and obsolescence) are dominant in the decision-making process, over and above 'manageable' tenant and lease characteristics which can be explicitly included within models of probabilities of income variation. This reveals investors are making ex-ante risk judgements and are considering post acquisition risk management strategies. The study also reveals that behavioural factors affect acquisition decisions. 3 1.

Purpose -The main aim of this paper is to investigate the specific factors that influence fund managers' decisions to dispose of property. Design/methodology/approach -This study explores the reasons behind the decision-making processes associated with the disposal of real estate within a portfolio, and the information sources utilised by fund managers. A behavioural finance approach is adopted with the field research carried out as a survey-based analysis of the disposal decisions made by fund managers in the UK property fund market. Findings -The main reason for disposal of an investment is due, in part, to re-structuring the portfolio. This is also linked to under-performance of the asset involved, and current market expectations. The implications for the study are that it identifies that there are links between rational and irrational behaviour in the selection of assets, not only for disposal, but also in terms of investment as a whole. This can be based on the inefficiency of the property market, and the lack of accurately available information.Originality/value -The study is unique as it provides a comprehensive commentary on the disposal behaviour of fund managers at the individual property and portfolio-wide levels.

DedicationThis paper is dedicated to Nanda Nanthakumaran who died before it was published. He was, not only a dedicated teacher and researcher of international renown, but also a dear friend, sadly missed by everyone who knew him. We hope that the alterations we have made subsequent to his death are in keeping with the high standards he always set. A comparison of UK property and equity duration AbstractThis paper considers the duration of property and equity. A general formula for duration of asset classes is derived. It is shown that calculations which assume, usually implicitly, that the flow-through of inflation to cash flow is zero, produce misleadingly high durations for property and equities. These are typically in the range 15 to 25 years. Simulations using the formulae show that property has some bond-like characteristics. The results indicate that, for realistic flow-through rates, equities have a higher duration than property. The flow-through rate is the most important variable in the estimation of equities. Using historical data, equity duration is estimated at 8.65 years and property's at 3.15 years. These are substantially lower than those commonly cited. If these values can be substantiated, and if higher values are used in practice, portfolio immunisation strategies may need to be reconsidered.

The paper assesses the differential impact of property market constraints on the long-run rental trends in each of the commercial and industrial property market sectors. The perceived view that supply constraints are very inelastic in the retail sector, less so for offices and elastic for industrial properties is reconsidered. A series of hypotheses are derived and tested by an analysis of variance technique which decomposes rental change into local and national components. The paper concludes that changes in the pattern of spatial activity and specific property market processes have resculptured the nature of supply constraints. The result is that the spectrum of supply elasticities has narrowed.

Investment theory dictates that capitalisation (cap) rates for freehold real estate should be determined by the risk free nominal rate of return plus the risk premium (RP) less the expected growth rate, with an allowance for depreciation. However, importing the concept of the RP from the capital markets fails to guide investors through the complexities of the asset, or enable exploration of purchaser preferences and behaviour. A refined pricing model for real estate is proposed, based on a concept termed a risk scale, to distinguish between macro (market) and micro (stock) determinants of risk and growth within the RP. This pricing model is estimated for a major global investment market, using a cross-sectional intertemporal framework, with a dataset of 497 transactions in the London office sector over 2010Q2-2012Q3. Average cap rates are estimated at just over 5%, with asset-specific attributes dominating yield determination, with submarket quality and tenant covenant most important; and unexpired I investors bought at lower cap rates, despite the ongoing economic and financial instability of the study period. Improving understanding of pricing behaviour and market transparency is important and may be advanced through the pricing model. Key wordsProperty investment, office market, London, capitalisation rates, risk premium. 2Refining the real estate pricing model IntroductionThe nature and behaviour of commercial investors have radically altered in the wake of the globalisation and liberalisation of capital and investment markets during the second half of the 20 th Century and the first few years of the 21 st . A consequence of these changes has been that the ownership of larger, more valuable real estate has shifted from small local entrepreneurs to major real estate companies, financial institutions and funds, both national and international, with banks acting as a major source of finance for much of this change. Subsequently, commercial investment real estate pricing has developed within an increasingly sophisticated, analytical and global environment.However, the relative lack of transaction volumes in the direct real estate market, and the fact that many transactions are not in the public domain, has restricted analysis of pricing and investor behaviour in the acquisition and sale process, in performance measurement and in bank lending decision-making. This is significant given that G pricing model, used within real estate markets, has been adopted from the capital markets and might struggle to cope with the unique and complex nature of the asset. The aim of this study is to redress this imbalance by revisiting and extending the theoretical pricing model to fully reflect both the complex characteristics of the real estate market and of the asset attributes that drive returns, to provide a framework for systematic asset pricing.This new, explicit framework is operationalised in the second half of the paper, to provide an example of its utility by empirically estimating the perceived risk attached to...

The focus of this paper is the analysis and prediction of local office rents and in particular the development of econometric models for two UK cities, Edinburgh and Glasgow. This paper reviews the current state of modelling and forecasting for office markets and notes the sparsity of urban office rent models. The urban models that exist suffer from data problems and either make the fatal flaw of ignoring supply constraints or consider supply in terms of net change in floorspace. The objective of this paper is to address some of the deficiencies in this empirical work on office market dynamics; it is the first attempt to use local take-up as a variable to model urban rents. Two approaches to modelling urban office rents are undertaken. The first model adopts a single reduced-form price equation using direct demand and supply measures, and suggests that variation in market dynamics exists between the two centres. However, these equations for the two cities have statistical weaknesses. The second model is a three-equation 'structural' model. The results of this analysis also suggest that Edinburgh responds more quickly to fundamental changes in supply-demand imbalances than Glasgow in the determination of office rents. The variation between Edinburgh and Glasgow, two cities within one administrative region of the UK, exemplifies the arguments in favour of urban analysis and the deficiencies in the regional approach to forecasting. The results of the empirical analysis also emphasise the importance of including local supply variables. Urban analysis still suffers from a paucity of published local economic data and recourse to regional data remains theoretically unsatisfactory. However, the use of a demand flow variable as demonstrated here is not only significant but arguably encompasses local economic drivers, and thereby negates to some extent the need for local economic indicators.

The volatility of commercial property markets in the United Kingdom has stimulated the development of explanatory models of ‘price’ determination. These models have tended to focus on the demand-side as the driver of change. A corollary of this is that, despite the fact that construction lags are known to exacerbate cyclical fluctuations, the supply-side adjustment mechanism has been subject to relatively little research effort. In this paper the authors develop a new model of commercial property markets in the United Kingdom. The model is adapted from Poterba's two-equation asset-market approach to modelling the housing market. The first equation is an arbitrage relationship where the return on property is made up of rent, as determined in the user market for property services, and the capital gain, which is dependent on the return on alternative assets. This can be interpreted as a ‘stock’ demand equation. The second equation explains that ‘flow’ supply is determined by real capital values. The long-run empirical generalisation of the two-equation model allows the authors to estimate two key behavioural parameters required in explaining supply-side adjustment to market change. First, the authors interpret the coefficient on the capital value variable in the supply equation as an estimate of the long-run ‘price’ elasticity of supply. Second, from the demand equation, they estimate the extent to which new supply can act as an ‘automatic stabiliser’ on property values. It is argued that although increases in demand drive up property values, new development is also initiated and will, in turn, dampen down the growth in real capital values. The equations are estimated for the office, industrial, and retail sectors. Although there are no comparable estimates of supply elasticities in the real estate economics literature, the results are generally consistent with prior knowledge. Estimates of the stabiliser effect are also plausible and, taken together, the supply-side parameters help provide insights required in understanding property market dynamics in the last twenty-five years.

IntroductionProperty analysts and researchers have a fundamental requirement for reliable property market data. Historically, data on the commercial and industrial property market are weak, but a number of property indices have now been published for 20 years. These time series are now becoming just long enough to undertake meaningful econometric analysis. There has been considerable debate concerning the appropriateness of these published property data sources and the extent to which confidence can be placed on research which depends on such sources. Morrell (1991), for example, has dissected the composition of the main property indices and their statistical relationships.This paper seeks to consider the form and the nature of spatial property data, and to examine the implications for their interpretation and analysis. A particular focus is the use of property valuations as perhaps the most important question mark over the use of these data. Throughout the paper there is continuous reference to commercial property. Following the Society of Property Researchers (1995), this term refers to property designed for business use and encompasses shops, offices and industrial units.Our primary concern is the provision of statistical information on rental values and yields (and the associated capital values and returns that can be derived). There is only marginal discussion of other indicators of demand-andsupply flows as these are available on a spatially and temporally limited basis.