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The purpose of this paper is to establish an optimum mix of liquid, publicly traded assets that may be added to a real estate portfolio, such as those held by open-ended funds, to provide the liquidity required by institutional investors, such as UK defined contribution pension funds. This is with the objective of securing liquidity while not unduly compromising the risk-return characteristics of the underlying asset class. This paper considers the best mix of liquid assets at different thresholds for a liquid asset allocation, with the performance then evaluated against that of a direct real estate benchmark index.

The authors employ a mean-tracking error optimisation approach in determining the optimal combination of liquid assets that can be added to a real estate fund portfolio. The returns of the optimised portfolios are compared to the returns for portfolios that employ the use of either cash or listed real estate alone as a liquidity buffer. Multivariate generalised autoregressive models are used along with rolling correlations and tracking errors to gauge the effectiveness of the various portfolios in tracking the performance of the benchmark index.

The results indicate that applying formal optimisation techniques leads to a considerable improvement in the ability of the returns from blended real estate portfolios to track the underlying real estate market. This is the case at a number of different thresholds for the liquid asset allocation and in cases where a minimum return requirement is imposed.

The results suggest that real estate fund managers can realise the liquidity benefits of incorporating publicly traded assets into their portfolios without sacrificing the ability to deliver real estate-like returns. However, in order to do so, a wider range of liquid assets must be considered, not just cash.

Despite their importance in the real estate investment industry, comparatively few studies have examined the structure and operation of open-ended real estate funds. To the authors’ knowledge, this is the first study to analyse the optimal composition of liquid assets within blended or hybrid real estate portfolios.

The use of modern portfolio theory (MPT) in the construction real estate portfolios has two serious limitations when used in an ex ante framework: the intertemporal instability of the portfolio weights; and the sharp deterioration in performance of the optimal portfolios outside the sample period used to estimate asset mean returns. Both problems can be traced to wide fluctuations in sample means. Aims to prove that the use of a procedure that ignores the estimation risk due to the uncertain in mean returns is likely to produce sub‐optimal results in subsequent periods.

This study extends previous ex ante‐based studies by evaluating ex post optimal portfolio allocations in subsequent test periods by using methods that have been proposed to reduce the effect of measurement error on optimal portfolio allocations.

While techniques designed to handle estimation risk in capital market studies have yielded promising results, they are not completely successful in improving out‐of‐sample performance in this case. It is hypothesised that such results are due to the cyclical nature of property and that the contrarian and mean‐reversion effects picked up in studies of stocks and bonds are not captured when an asset such as direct property is examined. This conclusion is also supported by the strong performance of the tangency portfolios, and in particular the classical unadjusted Sharpe portfolio, over the shorter horizons, which would be consistent with a cyclical momentum effect.

The results suggest that the consideration of the issue of estimation risk is crucial in the use of MPT in developing a successful real estate portfolio strategy.

This study re‐examines the potential role that direct real estate can play in institutional mixed‐asset portfolios. The paper examines the statistical improvement in performance that can result from the inclusion of real estate in an international mixed asset portfolio, using both in‐sample and out‐of‐sample data. Using US real estate data the results provide evidence that in most cases real estate does not lead to a significant improvement in portfolio performance in sample. However, out‐of‐sample tests indicate that the asset does provide a valuable diversification asset, with significant improvements in performance relative to a base capital market only portfolio.

This study utilises style analysis to examine the effective asset mix of UK property companies, using both an unadjusted data set and one adjusted for leverage and general stock market sentiment. The findings illustrate that the style benchmarks are largely spilt between mid and small cap stocks and government bonds, while when the adjusted data set is examined, the role of fixed‐income securities is enhanced together with that of Treasury Bills and the direct property market. The resulting style portfolios are then used to assess the investment performance of the property companies. The results reveal that there is a high degree of consistency in terms of the performance ranking obtained, across both alternative performance measures and between the original and adjusted samples. However, very few of the performance statistics are found to be statistically significant at conventional levels.

In estimating the inputs into the modern portfolio theory (MPT) portfolio optimisation problem, it is usual to use equal weighted historic data. Equal weighting of the data, however, does not take account of the current state of the market. Consequently this approach is unlikely to perform well in any subsequent period as the data is still reflecting market conditions that are no longer valid. The need for some return weighting scheme that gives greater weight to the most recent data would seem desirable. Therefore, this study uses returns data which are weighted to give greater weight to the most recent observations to see if such a weighting scheme can offer improved ex ante performance over that based on unweighted data.

ARIMA models have been extensively examined in the context of the real estate market. The purpose of this paper is to examine issues relating to their application in a forecasting context. Specifically, the paper seeks to examine whether in‐sample measures of best‐fit and also past forecasting accuracy bear any relation to future forecasting performance.

The forecasting performance of alternative ARIMA specifications are compared over rolling estimation and forecasting windows. The forecasting accuracy of the alternative specifications is compared with specific attention placed on the accuracy of the respective specification that in‐sample provides the best fitting model.

The results highlight the limitations in using the conventional approach to identifying the best‐specified ARIMA model in sample, when the purpose of the analysis is to provide forecasts. The results show that while ARIMA models can be useful in anticipating broad market trends, there are substantial differences in the forecasts obtained using alternative specifications. The use of conventional measures of best‐fit provide little indication as to future forecasting ability, nor does the forecasting performance of a specification in previous periods.

ARIMA modelling has frequently been highlighted as a useful forecasting approach. This paper illustrates that care needs to be paid in their use in a forecasting context and full appreciation of the strengths and limitations of the ARIMA approach.

This paper re‐examines the role of real estate within mixed asset portfolios from the perspective of an Irish portfolio manager. The nature of the investment market in the Republic of Ireland leads to the study extending the existing literature by expanding the universe of assets beyond a solely domestic setting and by imposing constraints on the optimal portfolios. Irish funds generally hold proportionately more in international equities than in the domestic market due to the small and illiquid nature of the Irish market; therefore, unconstrained tests do not adequately model the behaviour of Irish portfolio managers. The study finds that while real estate plays an important role in both the domestic and international unconstrained portfolios, it exits the optimal portfolios at relatively low return levels. Additionally, the real estate series adjusted for smoothing fails to enter any of the optimal portfolios. However, the use of 20 per cent band constraints leads to an increase in the diversification role real estate can play in a mixed asset portfolio, with the asset maintaining a presence up to more acceptable return levels.

This study examines the relationship between guide and sale prices for residential properties in Greater Dublin during the recent housing boom. The results indicate that degrees of divergence can be present, auctioned properties tend to sell more frequently at a premium to their guide price and that the average level of premium is also higher. These findings are confirmed by econometric analysis. It is proposed that the two potential causes behind this mis‐pricing are the speculative boom in the Dublin market during the period and the possibility that agents build into auction guide prices an element of underpricing in order to increase interest in the properties on the market.

This paper seeks to address the question of consistency, regarding the allocation of real estate in the mixed‐asset portfolio.

To address the question of consistency the allocation of real estate in the mixed‐asset portfolio was calculated over different holding periods varying from five to 25 years. For each portfolio and holding period, the percentage of portfolios with real estate was computed, as was the average real estate allocation in the optimum solution. Then, the risk and return differences between the two efficient frontiers, with and without real estate, were calculated to estimate real estate's marginal impact on portfolio performance.

First, the results suggest strongly that real estate has possessed the attribute of consistency in optimised portfolios. Second, the benefits from including real estate in the mixed‐asset portfolio tend to increase as the investment horizon is extended. Third, the position of real estate changes across the efficient frontier from its return enhancing ability to its risk‐reducing facility. Finally, the results show that the gain in return from adding real estate to the mixed‐asset portfolio is typically less compared with the reduction in portfolio risk.

The results highlight a number of issues in relation to the role of direct real estate within a mixed‐asset framework. In particular, the rationale behind the inclusion of real estate in the mixed‐asset portfolio depends on the length of the holding period of the investor and their position on the efficient frontier.

The study examines the attractiveness of direct real estate in the context of mixed‐asset portfolio.

There is a general consensus that residential submarkets exist, but the basis upon which these are specified remains the subject of debate. The purpose of this paper is to model data on different residential locations in Ghana to show how the submarkets have performed over the past 16 years.

The paper employs hedonic modelling based on 3,250 sale transactions and 1,130 rental transactions from 1992 to 2007.

The results demonstrate that five residential real estate characteristics – location, detached, landscaping quality, gross internal areas and plot size – predominate in the explanation of both rental and transactions prices across all submarkets. They also highlight points of variation between the submarkets. An understanding of the impact of these features on residential price and rent is important for capital and rental valuation.

This paper analyses historic performance of the residential market, both at the aggregate and disaggregate level to place the housing market in an investment context.