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The measurement of property portfolio performance is an important issue that, superficially, appears very straightforward. All that is required is an index of property market movements which can then be used as a reference point for comparing performance. Problems can arise, however, if the statistical characteristics of the index are different from the portfolio being analysed. This is not a trivial issue as the difference can be large enough to obscure the true performance of the portfolio and can lead to an inaccurate diagnosis of investment skill. Draws on recent research into index construction and examines some of the issues surrounding these problems. Discusses tracking errors and benchmarking issues.

Investigates the investment performance of listed Singapore property companies over the past 21 years. Risk‐adjusted performance for the companies remained inferior to stock market performance. There is some evidence that the companies’ investment performance was not consistent over time. Also finds that property companies’ performance is tied to the stock and property markets. Finally, property stocks failed to provide hedges against observed, expected and unanticipated inflation.

Socially responsible property investment (SRPI) has taken on increased significance in recent years, as property investors have given an increased priority to environmental, social and governance issues in their property investment decision making. The purpose of this paper is to establish SRPI performance indices for UK property companies and empirically benchmark their risk‐adjusted performance and portfolio diversification benefits over recent years.

Using five socially responsible investment (SRI) performance eligibility criteria, the UK property companies contributing to these SRI measures are identified. These UK property companies are used to establish a number of SRPI market cap‐weighted performance indices over 2003‐2008. These SRPI performance indices are used to assess the risk‐adjusted performance and portfolio diversification benefits of UK SRPI property companies.

This paper objectively identifies the UK property companies actively involved in SRPI and finds that the UK SRPI property companies delivered superior risk‐adjusted returns than the overall UK property companies sector, with this performance being achieved with no loss of portfolio diversification benefits.

Much of the previous SRPI research has focused on the broad concept of SRPI with no empirical analysis. This paper is the first attempt to rigorously and empirically assess the risk‐adjusted performance of UK SRPI property companies by establishing SRPI performance indices for UK property companies. Given the increasing significance of SRPI, this research enables empirically validated, more informed and practical investment decision making regarding the performance‐based supporting of the SRPI agenda by property investors.

Introduction The principal objective of a portfolio manager's work is the construction and maintenance of successful, efficient portfolios of investment assets. It is necessary, therefore, that methods are designed and made available through which the success and efficiency of portfolios may be assessed. Only through the continuous monitoring of the achieved results can long term investment strategies succeed.

Property performance assessment has become increasingly important in property management because of the emergence of a number of trends as issues of concern of property owners and occupiers. There are, however, many problems facing the consideration of performance measurement. Perhaps the main obstacle is the lack of a structured process for property performance measurement. The prime objective of the research work that underpins this paper therefore is to address this gap by the development of a structured model for property performance measurement. This involved three main steps. First, basic characteristics of an effective performance assessment in property managements are identified and the framework for a generic model is outlined. Next, key processes of performance measurement and property management tasks are identified. Then, these processes are set out into steps for better understanding and applicability of the model to actual property management practices. Some unique features of the model include consideration of clients and tenants requirements, integration of the functions of property management in the model and the inclusion of two property and resource databases to aid storage and retrieval of information. Besides, it is the first step in developing a dedicated computer tool for property performance assessment.

Considers the important ways in which property is different from other investments and the problems associated with measurement of investment performance in the property market. Outlines the features of the difference of property investment as providing a medium‐level ′secure′ income, a different performance cycle, and a lower level of risk. Discusses the issues creating concern over the pricing of property and the ability to measure its performance, and looks at recent developments in the market. Suggests that the processes of evaluation and performance measurement are providing data on a more comparable basis as the property market itself becomes more efficient.

Examines the investment performance of Singapore real estate and property stocks over the past 25 years. Evaluations using coefficient of variation (CV), Sharpe index (SI) and time‐varying Jensen abnormal return index (JI) suggest that real estate outperformed property stocks on a risk‐adjusted basis. Results also indicate that risk‐adjusted investment performance for residential properties remained superior to performance for other real estate types and property stocks. Further analysis using time‐varying JI reveals that the excess return performance of property stocks could differ significantly from that of direct properties, and performance of property stock led real estate market performance. Finally, the performance implications arising from the study are evaluated.

Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Since the mid‐1990s, in a generally strongly performing property market, there has been huge growth in the aggregate size and number of global property funds in both listed and unlisted formats. Managers have been able to raise significant capital, which potentially rewards them with performance fees without necessarily being able to provide clear evidence of out‐performance against defined market benchmarks or performance targets. In a more challenging, mature and increasingly transparent market this is unlikely to continue to be the case as it will be increasingly possible to assemble performance records. The purpose of this paper is to describe the sources of risk and return within property funds and set out a more holistic performance attribution framework encompassing the concepts of alpha (out‐performance) and beta (risk), which traditional attribution frameworks in property fund management do not.

A four component risk and return attribution framework is put forward. The first two components are portfolio structure which measures the impact of allocations to more or less risky markets, and stock selection which considers more or less risky assets. Fund structure, measures the impact of financial leverage and fees and finally the return impact of timing is attributed to the movement of capital into and out of the fund.

A case study of a single unlisted fund has been used to compare traditional attribution results with an examination of alpha and beta return attribution. In this instance fund structure, which is largely the financial leverage impact, is found to be significant. This simply reflects extra risk taking and there is no clear evidence of manager out‐performance, yet significant performance fees are paid to the manager.

The paper provides a complete framework for the performance measurement and attribution of property funds, which enables investors to gain a fuller understanding of these increasingly used investment conduits.

Describes the means by which the performance of property investments can be measured and analysed. Reports on the results of a questionnaire survey looking into the practice of UK independent property portfolio managers. Suggests that a survey of financial institutions, namely insurance companies and pension funds, would reveal more about the objectives of performance measurement.