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The purpose of the paper is to examine the role of securitised real estate within the confines of a multi‐asset investment portfolio and to identify if indeed securitised real estate can afford investors the desired investment benefits of direct property investment whilst mitigating many of the recognised barriers and risks.

The paper employs a suite of analytical techniques; lead‐lag correlations are utilised to examine market dynamics between listed and direct real estate markets across jurisdictions. Grainger causality and co‐integration techniques are applied to examine the nature and extent of relationships between investment markets with optimal portfolio analysis utilised to explore the role of securitised real estate and the optimum weighting allocation within the confines of a multi‐asset investment portfolio.

The findings demonstrated the unresponsive nature of direct real estate markets relative to listed real estate markets – in some jurisdictions the extent of lag can be as much as 12 months. Whilst the research did not identify a Grainger causality relationship between listed and direct property markets across the jurisdictions, co‐integration analysis does infer trend reverting price behaviour in the long run (ten years) between direct and listed real estate markets. Optimal portfolio analysis serves to demonstrate the crucial role of real estate within a multi‐asset portfolio in terms of both mitigating risk and enhancing performance over the ten‐year time series. Indeed, the optimal portfolio analysis highlights the compatibility and complementarity of listed and direct real estate within a multi‐asset investment portfolio.

The question if securitised real estate is a viable proxy for direct property investment is as inconclusive as it is enduring. In contrast to the large embodiment of previous work, this paper adopts an international market perspective depicting the global nature of securitised real estate investment markets whilst also reflecting on the extent of co‐integration between asset classes and across jurisdictions during a period of extreme financial and economic distress.

Given the growing market awareness concerning responsible investments in recent years, the purpose of this paper is to bridge the gap between real estate companies which implemented a corporate social responsibility (CSR) agenda and the possible role within a multi‐asset portfolio optimisation framework. The behaviour of the asset class sustainable real estate (SRE) together with its diversification characteristics are the main focus.

The study is an explorative empirical analysis applying a portfolio optimisation algorithm. First, the authors developed a sustainable real estate index comprehending listed real estate companies from 2004 until 2010 acting in line with a CSR agenda. Second, the authors introduced SRE into the opportunity set of an UK investor and finally, generated the theoretical optimal asset allocation of SRE within different risk‐return portfolios.

The unique risk‐return pattern of SRE enables the asset class to be allocated across all portfolios ranging from low to high risk along the efficient frontier. In the low‐risk levels, SRE behaves as a diversifier whereas in the medium‐ to high‐risk portfolios SRE is represented as the main allocated asset. Sustainable real estate thus offers opportunities to numerous investors in view of their investment preferences and corporate strategies.

The results could encourage institutional investors to take investments in CSR‐driven listed real estate companies into account and to rethink their strategic asset allocation approach in view of the identified asset characteristics and the behaviour within a portfolio framework.

The paper provides a first insight in the field of portfolio management by introducing SRE into the opportunity set of a UK investor. The study raises SRE to an aggregated level and delivers theoretical as well as empirical evidence of the role sustainable real estate is playing within a multi‐asset portfolio.

This paper compares the benefits of direct international real estate investments in a mixed asset portfolio from the perspective of a passive investor with high and low bond allocation.

Due to high data availability and its professionalism, the Norwegian sovereign wealth fund was used as a representative example. Real estate indices from 8 countries were used for the portfolio analysis. The data were desmoothed according to Geltners’s 1993 approach.

The optimal real estate ratio in the present case is around 20–55%. However, this is strongly dependent on the bond ratio of the multi-asset portfolio. Portfolios with a high equity ratio benefit more from the additional direct real estate investments than portfolios with high bond ratios.

A rebalancing of individual stocks and bonds was not analysed. Only indexes from MSCI (Morgan Stanley Capital International) were available.

Concludes that the weighting of stocks and bonds has a strong influence on the optimal real estate ratio and therefore structural changes that affect this weighting.

The originality of the paper lies in the analysis with different weights of stocks and bonds, the consideration of 8 real estate markets and the observation period. The results of the work highlight areas of interest for further research.

Modelling, predicting and forecasting commercial rents are now seen as necessary and explicit processes in real estate investment. Decisions on the prospects for specific investments, the real estate portfolio and multi‐asset portfolio are made as a result of these processes and thus it is the accuracy of these models, predictions and forecasts in capturing future movements in rents that are implicitly tested in the marketplace. Despite the amount of theoretical and empirical research that has been conducted into modelling and predicting rents, it is unusual to find research which explicitly considers the predictive accuracy of models on an ex ante basis. This paper seeks to demonstrate the importance and possible value of such a procedure by examining the predictability of commercial rents in the office, industrial and retail markets of Great Britain over a real estate “cycle”. The paper concludes that theory appears to be a better indicator of the “correct” model structure than maximising historic fit. Often naïve competitors are better predictors than the model selection strategy employed.

The purpose of this paper is to explore how tenant end demand dependence and investment market segmentation, as estimated through sector type, impacts real estate portfolio strategy in the context of the multi-asset portfolio.

The analysis is performed for six investor domeciles, for domestic and international investments over several cycles. The analysis is performed in a mean variance framework.

The findings are consistent with the hypothesis that an investor benefits from investing in real estate assets where end demand is dependent on local factors rather than global factors.

The efficiency of the overall multi-asset portfolio benefits from a deeper understanding of how the real estate portfolio is constructed. Locally dependent real estate, i.e. real estate that is dependent on local economic factors, tends to better support the overall portfolio than do real estate that is dependent upon global factors.

The paper contributes to the broader knowledge through extending earlier studies using similar methodology by extending the data series to cover the impact of the latest global financial crises, as well through extending the knowledge how the real estate portfolio should be constructed to better support the overall objectives of the multi-asset portfolio.

Academic research has shown that diversification today may not only include stocks and bonds but also alternative investments like hedge funds. However, practical and effective methods to identify the hedge fund styles that really enhance the risk return characteristics of a traditional portfolio as well as optimal allocation sizes are not available. The aim of the paper is to try to close this gap by proposing a portfolio optimization approach based upon the traditional market exposures of the different hedge fund strategies.

For this purpose, the paper first measures the bull and bear market betas of the main hedge fund strategies (equity market neutral, event driven, global macro, relative value, and managed futures). Based on the strategy characteristics, the authors then develop a systematic framework that calculates what percentage of each basic asset should be substituted for by hedge fund strategies to achieve the maximum results. The paper uses hedge fund index data from Hedge Fund Research and Barclay Hedge for the January 1999‐April 2011 sample period.

The empirical results show that this approach leads to an improvement in the annualized return of the optimized portfolio.

The paper adds to the existing literature by showing that it is possible to substitute traditional assets with hedge fund indices based on their exposures (beta) in varying market environments as a way to optimize the overall portfolio.

Considers the role of property in a multi‐asset portfolio and highlights the need for property to be subject to the same analytical framework as other assets in the portfolio. Discusses the principles of portfolio construction, consisting of development of economic scenarios; forecasts of return on asset classes; asset allocation and portfolio construction; and stock selection. Sets out a strategic framework for the construction of a property portfolio, which involves an explicit consideration of risk and return relative to an appropriate benchmark. States that both the structure and stock of the fund need to be considered. Suggests that most of the published work on the subject is seriously flawed by inadequate data.

Uses modern portfolio theory and a spreadsheet optimizer to make an ex‐post examination of the strategic diversification effects of including property in a multi‐asset portfolio, using UK appraisal‐based (smoothed) data and several derived desmoothed series. Includes an additional low‐risk asset (cash) to investigate whether property′s place in the portfolio is maintained. In particular, considers the significance of constraining assets to match typical institutional portfolio levels. Concludes that previously supposed benefits of including property are overstated. Property still has a place in an institutional portfolio, but the analyses should not be based simply on the use of appraisal or desmoothed data in a portfolio optimizer without applying appropriate constraints.

Puts forward the case for European property in a multi‐asset portfolio. Presents a quantitative approach for the construction of a Euro‐property portfolio. Concludes that this preliminary mean‐variable analysis shows that European property does provide significant diversification benefits both within a multi‐asset portfolio and within a pure European property portfolio context.

Residential property in a multi‐asset portfolio context has been considered from two substantially different perspectives: institutional investor's and the household's perspective. This paper constitutes the first of two related surveys on the role of residential property in a multi‐asset portfolio. The paper provides an introduction to housing property investment at a macro level and reviews the main empirical issues related to housing investment in an institutional portfolio context. The literature in this regard generally supports the evidence that residential property is a more effective hedge against inflation than both shares and bonds. Additionally, the reviewed studies generally report that unsecuritised housing investment not only generates risk‐adjusted returns comparable to those of bonds and shares, but also exhibits low levels of correlation with classic asset groups of institutional portfolios.