Investment Styles and Performance in the Australian Unlisted Wholesale Property Fund Market

Higgins, David M.

doi:10.2139/ssrn.1648641

Cited by 3 publications

(15 citation statements)

References 12 publications

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“…Fourth, the performance of the different active management strategies identified through the two sources of active risk varies with diverse market conditions, which supports the findings of Higgins (2010) and Baum et al (2012).…”

Section: Active Management and Returnssupporting

confidence: 80%

“…The approach of Alford et al (2003) has also been used to categorise both wholesale securitised property funds and unlisted wholesale property funds in Australia (Higgins andNg, 2009 andHiggins, 2010). A wholesale securitised property fund invests in Real Estate Investment Trusts (REITs) with the aim of replicating a particular property index.…”

Section: Tracking Errormentioning

confidence: 99%

“…We define good (bad) performance as being in the top (bottom) five funds in the sample. Following the suggestion of Higgins (2010), that other characteristics should also be evaluated, we also report fund size (£m) and leverage (Debt to GAV %) at the start of each sample period to avoid biasing the results 8 . Over the full sample period Table 2 shows that the funds achieved an average return of 1.16% per quarter with an Active Share of 54% and an annualised tracking error of 7%.…”

Section: Active Management and Returnsmentioning

confidence: 99%

“…The traditional way to measure the active management of a fund is to calculate its tracking error: as measured by the standard deviation of the difference in a fund's returns versus its benchmark returns (see inter alia, Alford et al, 2003, Higgins and Ng, 2009, and Higgins, 2010. However, tracking error alone is an inadequate measure of fund active management since even very actively managed funds can in fact have rather low tracking errors.…”

Section: Introductionmentioning

confidence: 99%

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Real estate fund active management

Morri

2015

Journal of Property Investment &Amp; Finance

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link: Abstract:The traditional way to measure the active management of a fund is to calculate its tracking error: as measured by the standard deviation of the difference in a fund's returns versus its benchmark returns. However, tracking error alone is an inadequate measure of fund activity since even very actively managed funds can in fact generate rather low tracking errors. Therefore judging the activity level of a fund based solely on tracking error can be misleading. In addition, while tracking error volatility is easy to calculate it only infers what the manager is doing at the portfolio level and does tell you how the tracking errors were generated. For instance, Cremers and Petajisto (2009) argue that the two distinct approaches to active management, stock selection or factor risk, can produce significantly different tracking errors.Instead of using tracking error alone Cremers and Petajisto (2009) suggest that a more comprehensive picture of active management can be achieved by including Active Share into the calculations, where the Active Share of the fund is measured as half the sum of the absolute difference between the fund's holdings and those of the benchmark portfolio. In other words, Cremers and Petajisto (2009) claim that using Active Share and tracking error together enables investors to distinguish between the types of active management used by funds, stock selection and factor risk, and so classify funds by their investment management strategy: pure indexes, closet indexes, diversified stock pickers, concentrated stock pickers, and factor bets.

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Section: Active Management and Returnssupporting

confidence: 80%

Section: Tracking Errormentioning

confidence: 99%

Section: Active Management and Returnsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Real estate fund active management

Morri

2015

Journal of Property Investment &Amp; Finance

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“…Unlisted property funds offer wholesale institutional investors (such as superannuation funds and sovereign wealth funds) access to the private property equity market and high quality commercial properties seldom available on the open market, the services of experienced property fund managers, a total return focus with low risk and low gearing and performance aligned with the underlying property assets but with low liquidity, significant minimum investment levels and high entry costs (Newell, 2007;Higgins, 2010), being particularly attractive to superannuation funds in Australia's fast expanding superannuation system.…”

Section: Introductionmentioning

confidence: 99%

Property investment decision making by Australian unlisted property funds

Parker

2016

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Purpose The purpose of this paper is to investigate the property investment decision-making process of Australian unlisted property funds. Design/methodology/approach Drawing on previous research into property investment decision making by Australian REITs, a normative model of the unlisted property fund investment decision-making process is proposed. Based on exploratory investigation through semi-structured interviews with senior Australian unlisted property fund decision makers, a descriptive model of the property investment decision-making process by Australian unlisted property funds is developed. The normative model and descriptive model are compared and a prescriptive model of the Australian unlisted property fund investment decision-making process proposed. Findings A four-stage, 20-step process proposed in the normative model was found to be generally supported by the descriptive model developed, potentially comprising a possible prescriptive model for the Australian unlisted property fund investment decision-making process. Research limitations/implications Further research is required to investigate risk-return issues, whether the prescriptive model is generalisable across other property investment decision-making groups or over time and whether it may lead to “good” decisions. Practical implications The prescriptive model proposed may contribute consistency and transparency to the decision-making process, if adopted by Australian unlisted property funds, potentially leading to better decisions. Social implications Greater consistency and transparency in property investment decision making by Australian unlisted property funds may lead to the optimal allocation of capital and greater investor confidence in the sector. Originality/value The findings comprise the first possible prescriptive model of the Australian unlisted property fund investment decision-making process, forming a basis for comparative investigation of that process adopted by other property investment decision-making groups such as Australian REITs and Australian retail property funds.

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An investigation of property-related decision practice of Australian fund managers

Reddy

Higgins

Wakefield

2014

Journal of Property Investment &Amp; Finance

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Purpose -In Australia, the A$2.2 trillion managed funds industry including the large pension funds (known locally as superannuation funds) are the dominant institutional property investors. While statistical information on the level of Australian managed fund investments in property assets is widely available, comprehensive practical evidence on property asset allocation decision-making process is underdeveloped. The purpose of this research is to identify Australian fund manager's property asset allocation strategies and decision-making frameworks at strategic level. Design/methodology/approach -The research was undertaken in May-August 2011 using an in-depth semi-structured questionnaire administered by mail. The survey was targeted at 130 leading managed funds and asset consultants within Australia. Findings -The evaluation of the 79 survey respondents indicated that Australian fund manager's property allocation decision-making process is an interactive, sequential and continuous process involving multiple decision-makers (internal and external) complete with feedback loops. It involves a combination of quantitative analysis (mainly mean-variance analysis) and qualitative overlay (mainly judgement, or "gut-feeling", and experience). In addition, the research provided evidence that the property allocation decision-making process varies depending on the size and type of managed fund. Practical implications -This research makes important contributions to both practical and academic fields. Information on strategic property allocation models and variables is not widely available, and there is little guiding theory related to the subject. Therefore, the conceptual frameworks developed from the research will help enhance academic theory and understanding in the area of property allocation decision making. Furthermore, the research provides small fund managers and industry practitioners with a platform from which to improve their own property allocation processes. Originality/value -In contrast to previous property decision-making research in Australia which has mainly focused on strategies at the property fund investment level, this research investigates the institutional property allocation decision-making process from a strategic position involving all major groups in the Australian managed funds industry.

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Investment Styles and Performance in the Australian Unlisted Wholesale Property Fund Market

Cited by 3 publications

References 12 publications

Real estate fund active management

Real estate fund active management

Property investment decision making by Australian unlisted property funds

An investigation of property-related decision practice of Australian fund managers

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