Purpose -The purpose of this paper is to provide conclusive evidence that infrastructure constitutes a separate asset class and cannot be classified as real estate from an investment point-of-view. Furthermore, optimal allocations are determined for direct and indirect infrastructure within a multi-asset portfolio. Design/methodology/approach -Portfolio allocations are optimized by using an algorithm, which accounts for downside risk, rather than variance. This approach is more in accordance with the actual investor behaviour and might meet their investment objectives more effectively. An Australian dataset comprising stocks, bonds, direct real estate, direct infrastructure and indirect infrastructure is applied for portfolio construction. Findings -Although infrastructure and real estate have common characteristics, the conclusion is that that they constitute two different asset classes. Furthermore, the diversification benefits of direct and indirect infrastructure within multi-asset portfolios are highlighted and determine efficient allocations up to 78 percent for target rates of 0.0 percent, 1.5 percent and 3.0 percent quarterly. Practical implications -The results will help investors and portfolio managers to efficiently allocate funds to various asset classes. Most institutional investors are not familiar with investments in infrastructure. The study facilitates a better understanding of the asset class infrastructure and yields some important implications for the optimal allocation of infrastructure within institutional investment portfolios. Originality/value -This is the first study to examine the role of direct and indirect infrastructure within a multi-asset portfolio by applying a downside-risk approach.

Purpose The purpose of this paper is to determine systematically the broader relationship between news media sentiment, extracted through textual analysis of articles published by leading US newspapers, and the securitized real estate market. Design/methodology/approach The methodology is divided into two stages. First, roughly 125,000 US newspaper article headlines from Bloomberg, The Financial Times, Forbes and The Wall Street Journal are investigated with a dictionary-based approach, and different measures of sentiment are created. Second, a vector autoregressive framework is used to analyse the relationship between media-expressed sentiment and REIT market movements over the period 2005–2015. Findings The empirical results provide significant evidence for a leading relationship between media sentiment and future REIT market movements. Furthermore, applying the dictionary-based approach for textual analysis, the results exhibit that a domain-specific dictionary is superior to a general dictionary. In addition, better results are achieved by a sentiment measure incorporating both positive and negative sentiment, rather than just one polarity. Practical implications In connection with fundamentals of the REIT market, these findings can be utilised to further improve the understanding of securitized real estate market movements and investment decisions. Furthermore, this paper highlights the importance of paying attention to new media and digitalization. The results are robust for different REIT sectors and when conventional control variables are considered. Originality/value This paper demonstrates for the first time, that textual analysis is able to capture media sentiment from news relevant to the US securitized real estate market. Furthermore, the broad collection of newspaper articles from four different sources is unique.

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Purpose – Similar to real estate, infrastructure investments are regarded as providing a good inflation hedge and inflation protection. However, the empirical literature on infrastructure and inflation is scarce. Therefore, the purpose of this paper is to investigate the short- and long-term inflation-hedging characteristics, as well as the inflation protection associated with infrastructure and real estate assets. Design/methodology/approach – Based on a unique data set for direct infrastructure performance, a listed infrastructure index, common direct and listed real estate indices, the authors test for short- and long-term inflation-hedging characteristics of these assets in the USA from 1991-2013. The authors employ the traditional Fama and Schwert (1977) framework, as well as Engle and Granger (1987) co-integration tests. Granger causality tests are further conducted, so as to gain insight into the short-run dynamics. Finally, shortfall risk measures are applied to investigate the inflation protection characteristics of the different assets over increasingly long investment horizons. Findings – The empirical results indicate that in the short run, only direct infrastructure provides a partial hedge against inflation. However, co-integration tests suggest that all series have a long-run co-movement with inflation, implying a long-term hedge. The causality tests reveal reverse unidirectional causality – while real estate asset returns are Granger-caused by inflation, infrastructure asset returns seem to cause inflation. These findings further confirm that both assets represent a distinct asset class. Ultimately, direct infrastructure investments exhibit the most desirable inflation protection characteristics among the set of assets. Research limitations/implications – This study only presents results based on a composite direct infrastructure index, as no sub-indices for sub-sectors are available yet. Practical implications – Investors seeking assets that are sensitive to inflation and mitigate inflation risk should consider direct infrastructure investments in their asset allocation strategy. Originality/value – This is the first study to examine the ability of direct infrastructure to assess inflation risk.

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