Self-consistent field theory for diblock copolymers grafted to a sphere

An efficient numerical self-consistent field theory (SCFT) algorithm is developed for treating structured polymers on spherical surfaces. The method solves the diffusion equations of SCFT with a pseudospectral approach that combines a spherical-harmonics expansion for the angular coordinates with a modified real-space Crank–Nicolson method for the radial direction. The self-consistent field equations are solved with Anderson-mixing iterations using dynamical parameters and an alignment procedure to prevent angular drift of the solution. A demonstration of the algorithm is provided for thin films of diblock copolymer grafted to the surface of a spherical core, in which the sequence of equilibrium morphologies is predicted as a function of diblock composition. The study reveals an array of interesting behaviors as the block copolymer pattern is forced to adapt to the finite surface area of the sphere.

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.

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.

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.

Stochastic perturbations to dynamical systems: a response theory approach

Using the formalism of the Ruelle response theory, we study how the invariant measure of an Axiom A dynamical system changes as a result of adding noise, and describe how the stochastic perturbation can be used to explore the properties of the underlying deterministic dynamics. We first find the expression for the change in the expectation value of a general observable when a white noise forcing is introduced in the system, both in the additive and in the multiplicative case. We also show that the difference between the expectation value of the power spectrum of an observable in the stochastically perturbed case and of the same observable in the unperturbed case is equal to the variance of the noise times the square of the modulus of the linear susceptibility describing the frequency-dependent response of the system to perturbations with the same spatial patterns as the considered stochastic forcing. This provides a conceptual bridge between the change in the fluctuation properties of the system due to the presence of noise and the response of the unperturbed system to deterministic forcings. Using Kramers-Kronig theory, it is then possible to derive the real and imaginary part of the susceptibility and thus deduce the Green function of the system for any desired observable. We then extend our results to rather general patterns of random forcing, from the case of several white noise forcings, to noise terms with memory, up to the case of a space-time random field. Explicit formulas are provided for each relevant case analysed. As a general result, we find, using an argument of positive-definiteness, that the power spectrum of the stochastically perturbed system is larger at all frequencies than the power spectrum of the unperturbed system. We provide an example of application of our results by considering the spatially extended chaotic Lorenz 96 model. These results clarify the property of stochastic stability of SRB measures in Axiom A flows, provide tools for analysing stochastic parameterisations and related closure ansatz to be implemented in modelling studies, and introduce new ways to study the response of a system to external perturbations. Taking into account the chaotic hypothesis, we expect that our results have practical relevance for a more general class of system than those belonging to Axiom A.

Persistence of UK Real Estate returns: a Markov chain analysis

The persistence of investment performance is a topic of perennial interest to investors. Efficient Markets theory tells us that past performance can not be used to predict future performance yet investors appear to be influenced by the historical performance in making their investment allocation decisions. The problem has been of particular interest to investors in real estate; not least because reported returns from investment in real estate are serially correlated thus implying some persistence in investment performance. This paper applies the established approach of Markov Chain analysis to investigate the relationship between past and present performance of UK real estate over the period 1981 to 1996. The data are analysed by sector, region and size. Furthermore some variations in investment performance classification are reported and the results are shown to be robust.

A note on the use of spreadsheet optimisers in real estate analysis

Modern Portfolio Theory (MPT) has been advocated as a more rational approach to the construction of real estate portfolios. The application of MPT can now be achieved with relative ease using the powerful facilities of modern spreadsheet, and does not necessarily need specialist software. This capability is to be found in the use of an add-in Tool now found in several spreadsheets, called an Optimiser or Solver. The value in using this kind of more sophisticated analysis feature of spreadsheets is increasingly difficult to ignore. This paper examines the use of the spreadsheet Optimiser in handling asset allocation problems. Using the Markowitz Mean-Variance approach, the paper introduces the necessary calculations, and shows, by means of an elementary example implemented in Microsoft's Excel, how the Optimiser may be used. Emphasis is placed on understanding the inputs and outputs from the portfolio optimisation process, and the danger of treating the Optimiser as a Black Box is discussed.

Required returns for real estate in UK pension fund portfolios

The position of Real Estate within a multi-asset portfolio has received considerable attention recently. Previous research has concentrated on the percentage holding property would achieve given its risk/return characteristics. Such studies have invariably used Modern Portfolio Theory and these approaches have been criticised for both the quality of the real estate data and problems with the methodology itself. The first problem is now well understood, and the second can be addressed by the use of realistic constraints on asset holdings. This paper takes a different approach. We determine the level of return that Real Estate needs to achieve to justify an allocation within the multi asset portfolio. In order to test the importance of the quality of the data we use historic appraisal based and desmoothed returns to examine the sensitivity of the results. Consideration is also given to the Holding period and the imposition of realistic constraints on the asset holdings in order to model portfolios held by pension fund investors. We conclude, using several benchmark levels of portfolio risk and return, that using appraisal based data the required level of return for Real Estate was less than that achieved over the period 1972-1993. The use of desmoothed series can reverse this result at the highest levels of desmoothing although within a restricted holding period Real Estate offered returns in excess of those required to enter the portfolio and might have a role to play in the multi-asset portfolio.

Experience and real estate investment decision-making: a process-tracing investigation

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.

Optimal tax theory and the taxation of housing in the US and the UK

First, we survey recent research in the application of optimal tax theory to housing. This work suggests that the under-taxation of housing for owner occupation distorts investment so that owner occupiers are encouraged to over-invest in housing. Simulations of the US economy suggest that this is true there. But, the theoretical work excludes consideration of land and the simulations exclude consideration of taxes other than income taxes. These exclusions are important for the US and UK economies. In the US, the property tax is relatively high. We argue that excluding the property tax is wrong, so that, when the property tax is taken into account, owner occupied housing is not undertaxed in the US. In the UK, property taxes are relatively low but the cost of land has been increasing in real terms for forty years as a result of a policy of constraining land for development. The price of land for housing is now higher than elsewhere. Effectively, an implicit tax is paid by first time buyers which has reduced housing investment. When land is taken into account over-investment in housing is not encouraged in the UK either.

The tenant as a customer: can good service improve real estate performance?

Customer Relationship Management (CRM) theory suggests that good customer service results in satisfied customers, who in turn are more likely to remain loyal and recommend the service provider to others. Proponents of good customer service for tenants claim that landlords should see a return on any investment in their customer service, in the form of enhanced real estate performance. This paper begins by reviewing research on customer service returns in other industries. Through consideration of the characteristics of real estate markets, the paper explains how factors such as (inter alia) lease terms, property market cycles, and property type, might determine the relationship between customer service and real estate performance. The paper concludes that further research is needed to isolate specific aspects of customer service that are most appreciated by customers. It suggests that the financial returns which accrue to landlords adopting a customer-focused approach might indeed be quantified, and suggests an appropriate method for such future research.

Bias or rationality? The case of UK commercial real estate investment

Purpose – The purpose of this paper is to test the hypothesis that investment decision making in the UK direct property market does not conform to the assumption of economic rationality underpinning portfolio theory. Design/methodology/approach – The developing behavioural real estate paradigm is used to challenge the idea that investor “man” is able to perform with economic rationality, specifically with reference to the analysis of the spatial dispersion of the entire UK “investible stock” and “investible locations” against observed spatial patterns of institutional investment. Location quotients are derived, combining different data sets. Findings – Considerably greater variation in institutional property holdings is found across the UK than would be expected given the economic and stock characteristics of local areas. This appears to provide evidence of irrationality (in the strict traditional economic sense) in the behaviour of institutional investors, with possible herding underpinning levels of investment that cannot be explained otherwise. Research limitations/implications – Over time a lack of distinction has developed between the cause and effect of comparatively low levels of development and institutional property investment across the regions. A critical examination of decision making and behaviour in practice could break this cycle, and could in turn promote regional economic growth. Originality/value – The entire “population” of observations is used to demonstrate the relationships between economic theory and investor performance exploring, for the first time, stock and local area characteristics.