Pricing the options inherent in leased commercial property: a UK case study

This paper sets out the findings of a group of research and development projects carried out at the Department of Real Estate & Planning at the University of Reading and at Oxford Property Systems over the period 1999 – 2003. The projects have several aims: these are to identify the fundamental drivers of the pricing of different lease terms in the UK property sector; to identify current and best market practice and uncover the main variations in lease terms; to identify key issues in pricing lease terms; and to develop a model for the pricing of rent under a variety of lease variations. From the landlord’s perspective, the main factors driving the required ‘compensation’ for a lease term amendment include expected rental volatility, expected probability of tenant vacation, and the expected costs of tenant vacation. These data are used in conjunction with simulation technology to reflect the options inherent in certain lease types to explore the required rent adjustment. The resulting cash flows have interesting qualities which illustrate the potential importance of option pricing in a non-complex and practical way.

Country, sector and regional factors in European property returns

For those portfolio managers who follow a top-down approach to fund management when they are trying to develop a pan-European investment strategy they need to know which are the most important factors affecting property returns, so as to concentrate their management and research efforts accordingly. In order to examine this issue this paper examines the relative importance of country, sector and regional effects in determining property returns across Europe using the largest database of individual property returns currently available. Using annual data over the period 1996 to 2002 for a sample of over 25,000 properties the results show that the country-specific effects dominate sector-specific factors, which in turn dominate the regional-specific factors. This is true even for different sub-sets of countries and sectors. In other words, real estate returns are mainly determined by local (country specific) conditions and are only mildly affected by general European factors. Thus, for those institutional investors contemplating investment into Europe the first level of analysis must be an examination of the individual countries, followed by the prospects of the property sectors within the country and then an assessment of the differences in expected performance between the main city and the rest of the country.

Real estate in the mixed-asset portfolio: the question of consistency

The recent poor performance of the equity market in the UK has meant that real estate is increasingly been seen as an attractive addition to the mixed-asset portfolio. However, determining whether the good return enjoyed by real estate is a temporary or long-term phenomenon is a question that remains largely unanswered. In other words, there is little or no evidence to indicate whether real estate should play a consistent role in the mixed-asset portfolio over short- and long-term investment horizons. Consistency in this context refers to the ability of an asset to maintain a positive allocation in an efficient portfolio over different holding periods. Such consistency is a desirable trait for any investment, but takes on particular significance when real estate is considered, as the asset class is generally perceived to be a long-term investment due to illiquidity. From an institutional investor’s perspective, it is therefore crucial to determine whether real estate can be reasonably expected to maintain a consistent allocation in the mixed-asset portfolio in both the short and long run and at what percentage. To address the question of consistency the allocation of real estate in the mixed-asset portfolio was calculated over different holding periods varying from 5- to 25-years.

Re-thinking commercial real estate market segmentation

Investments in direct real estate are inherently difficult to segment compared to other asset classes due to the complex and heterogeneous nature of the asset. The most common segmentation in real estate investment analysis relies on property sector and geographical region. In this paper, we compare the predictive power of existing industry classifications with a new type of segmentation using cluster analysis on a number of relevant property attributes including the equivalent yield and size of the property as well as information on lease terms, number of tenants and tenant concentration. The new segments are shown to be distinct and relatively stable over time. In a second stage of the analysis, we test whether the newly generated segments are able to better predict the resulting financial performance of the assets than the old dichotomous segments. Applying both discriminant and neural network analysis we find mixed evidence for this hypothesis. Overall, we conclude from our analysis that each of the two approaches to segmenting the market has its strengths and weaknesses so that both might be applied gainfully in real estate investment analysis and fund management.

A data framework for measuring the energy consumption of the non-domestic building stock

The transition to a low-carbon economy urgently demands better information on the drivers of energy consumption. UK government policy has prioritized energy efficiency in the built stock as a means of carbon reduction, but the sector is historically information poor, particularly the non-domestic building stock. This paper presents the results of a pilot study that investigated whether and how property and energy consumption data might be combined for non-domestic energy analysis. These data were combined in a ‘Non-Domestic Energy Efficiency Database’ to describe the location and physical attributes of each property and its energy consumption. The aim was to support the generation of a range of energy-efficiency statistics for the industrial, commercial and institutional sectors of the non-domestic building stock, and to provide robust evidence for national energy-efficiency and carbon-reduction policy development and monitoring. The work has brought together non-domestic energy data, property data and mapping in a ‘data framework’ for the first time. The results show what is possible when these data are integrated and the associated difficulties. A data framework offers the potential to inform energy-efficiency policy formation and to support its monitoring at a level of detail not previously possible.

An overview of domestic energy models and a new approach with agent based modelling

Government targets for CO2 reductions are being progressively tightened, the Climate Change Act set the UK target as an 80% reduction by 2050 on 1990 figures. The residential sector accounts for about 30% of emissions. This paper discusses current modelling techniques in the residential sector: principally top-down and bottom-up. Top-down models work on a macro-economic basis and can be used to consider large scale economic changes; bottom-up models are detail rich to model technological changes. Bottom-up models demonstrate what is technically possible. However, there are differences between the technical potential and what is likely given the limited economic rationality of the typical householder. This paper recommends research to better understand individuals’ behaviour. Such research needs to include actual choices, stated preferences and opinion research to allow a detailed understanding of the individual end user. This increased understanding can then be used in an agent based model (ABM). In an ABM, agents are used to model real world actors and can be given a rule set intended to emulate the actions and behaviours of real people. This can help in understanding how new technologies diffuse. In this way a degree of micro-economic realism can be added to domestic carbon modelling. Such a model should then be of use for both forward projections of CO2 and to analyse the cost effectiveness of various policy measures.

Why do research on commercial property management? Somebody HAS to!

This paper identifies some significant gaps in our knowledge of the configuration and performance of the property asset management sector. It is argued that, as many leading academic property researchers have focussed on financial vehicles and modelling, in-depth analysis of property assets and their management has been neglected. In terms of potential for future in-depth research, three key broad preliminary research themes or questions are identified. First, how do the active management opportunities presented, costs of management and the key management tasks vary with market conditions, asset type and life-cycle stage? Second, how is property asset management delivered and what are the main costs and benefits of different models of procurement? Finally, what are the appropriate metrics for measuring the performance of different property managers and approaches to property management? It is concluded that the lack of published materials addressing these issues has implications for educating property students.

Understanding the barriers to real estate investment in developing economies

Baum (2008a) related the number of real estate funds investing in developing economies to simple economic and demographic variables, and showed that, while the popularity of markets was explained by population and GDP per capita, some countries receive more or less investment than the model predicted. Why is this? In this paper we undertake a literature review to identify the barriers which inhibit international real estate investment. We test our initial findings by questioning property investment professionals through semi-structured interviews. By doing this we were able to verify our list of barriers, identify those barriers which are most likely to affect real estate investors, and to indicate whether there are any real estate-specific variables that create barriers which have not received any academic attention. We show that distortions in international capital flows may be explained by a combination of these formal and informal barriers.

Real options and game theoretical approaches to real estate development projects: multiple equilibria and the implications of different tie-breaking rules

This paper contributes to a fast growing literature which introduces game theory in the analysis of real option investments in a competitive setting. Specifically, in this paper we focus on the issue of multiple equilibria and on the implications that different equilibrium selections may have for the pricing of real options and for subsequent strategic decisions. We present some theoretical results of the necessary conditions to have multiple equilibria and we show under which conditions different tie-breaking rules result in different economic decisions. We then present a numerical exercise using the in formation set obtained on a real estate development in South London. We find that risk aversion reduces option value and this reduction decreases marginally as negative externalities decrease.

Spatial concentration in institutional industrial real estate investment in the England and Wales

In two recent papers Byrne and Lee (2006, 2007) examined the geographical concentration of institutional office and retail investment in England and Wales at two points in time; 1998 and 2003. The findings indicate that commercial office portfolios are concentrated in a very few urban areas, whereas retail holdings correlate more closely with the urban hierarchy of England and Wales and consequently are essentially ubiquitous. Research into the industrial sector is very much less developed, and this paper therefore makes a significant contribution to understanding the structure of industrial property investment in the UK. It shows that industrial investment concentration is between that of retail and office and is focussed on LAs with high levels of manual workers in areas with smaller industrial units. It also shows that during the period studied the structure of the sector changed, with greater emphasis on the distributional element, for which location is a principal consideration.

Unlisted property funds and the emerging property markets

This paper sets out to describe the changing nature of global property investment, to provide background information regarding the nature of unlisted property funds and their managers and investors, and especially the role played by unlisted property funds in facilitating cross-border investing. In particular, it focuses on the development of unlisted funds as intermediary structures carrying institutional capital from developed to developing markets. It presents the results of new research by UK research firm Property Funds Research (PFR) and the University of Reading which explores the extent to which this new vehicle has been effective in delivering capital to emerging markets. The research relates the number of funds targetting particular countries and to population and GDP per capita. It finds that there is a very strong relationship between the popularity of a country for investment through this vehicle format and these independent variables. More interesting, perhaps, is the identification of outlier countries where the amount of investment is significantly less - or greater - than that predicted by population and GDP per capita.

Volatility persistence and time-varying betas in the UK real estate market

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.