Real estate research needs of the plan sponsor community:what do the plan sponsor real estate investment managers want to know?

This article reports the results of a web-based survey of real estate portfolio managers in the pension fund industry. The study focused on ascertaining the real estate research interests of the respondents as well as whether or not research funding should be allocated to various research topics. Performance measures of real estate assets and portfolios, microeconomic factors affecting real estate and the role of real estate in a mixed-asset portfolio were the top three real estate research interests. There was some variation by the type and size of fund providing evidence that segmentation is important within the money management industry. Respondents were also queried on more focused research subtopics and additional questions in the survey focused on satisfaction with existing real estate benchmarks, and perceptions of the usefulness of published research. Findings should be used to guide research practitioners and academics as to the most important research interests of plan sponsor real estate investment managers.

Selectivity and timing performance of UK investment trusts

This study examines the selectivity and timing performance of 218 UK investment trusts over the period July 1981 to June 2009. We estimate the Treynor and Mazuy (1966) and Henriksson and Merton (1981) models augmented with the size, value, and momentum factors, either under the OLS method adjusted with the Newey-West procedure or under the GARCH(1,1)-in-mean method following the specification of Glosten et al. (1993; hereafter GJR-GARCH-M). We find that the OLS method provides little evidence in favour of the selectivity and timing ability, consistent with previous studies. Interestingly, the GJR-GARCH-M method reverses this result, showing some relatively strong evidence on favourable selectivity ability, particularly for international funds, as well as favourable timing ability, particularly for domestic funds. We conclude that the GJR-GARCH-M method performs better in evaluating fund performance compared with the OLS method and the non-parametric approach, as it essentially accounts for the time-varying characteristics of factor loadings and hence obtains more reliable results, in particular, when the high frequency data, such as the daily returns, are used in the analysis. Our results are robust to various in-sample and out-of-sample tests and have valuable implications for practitioners in making their asset allocation decisions across different fund styles. © 2012 Elsevier B.V.