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Examines the role of property in a portfolio investment context. Demonstrates that the return an asset is required to achieve depends on the variability and correlation of returns and not simply average returns. Shows that property, as measured by the Jones Lang Wootton Index, should have been included in institutional portfolios using both nominal and real returns, even if the variability of property was more than doubled. Suggests that property portfolios still offer considerable benefits to existing gilt/equity dominated funds in terms of improved risk‐adjusted performance.

Investors commonly use debt finance in the purchase of income‐producing properties with the aim of enhancing their return on equity. Describes how the past effects of borrowing can be assessed from property returns and loan interest rates in recent years. Methods for measuring the past consequences of financial leverage are considered and tested. Based on data from the residential property market in Perth, Western Australia between 1982 and 1994, borrowing at a variable interest rate would have shown a modest increase in return and added considerably to the volatility or risk. The impact of inflation and taxation on the benefits and risks of financial leverage is also assessed.

This paper investigates the risk incurred in UK property investment by the major investing institutions. The historic variability of investment returns from property is compared with that from long dated British government bonds (gilts) and ordinary shares (equities) using data from the JLW Property Index.1 A variety of definitions of risk are examined in order to assess the relative risk of property, considered both in isolation and as an integral part of the overall institutional portfolio. The investigation concludes that, since the late 1960s, property has involved significantly less risk than either of the two alternative investments.

Reviews the evidence on the inflation‐hedging characteristics of UK commercial property as an asset class. That evidence suggests that commercial property is a very imperfect hedge against unanticipated inflation. Furthermore, the returns have been substantially lower than on equities and residential property. Describes and considers new financial contracts which might allow investors to gain exposure to movements in house price without becoming landlords.

Investigates the investment performance of listed Singapore property companies over the past 21 years. Risk‐adjusted performance for the companies remained inferior to stock market performance. There is some evidence that the companies’ investment performance was not consistent over time. Also finds that property companies’ performance is tied to the stock and property markets. Finally, property stocks failed to provide hedges against observed, expected and unanticipated inflation.

It is conventional to assume that property investments in the UK are priced on the basis that investors require a total return approximately 2 per cent above the current redemption yield on long dated gilts. Some yield premium seems intuitively appropriate due to certain apparent disadvantages of property relative to gilts, eg higher risk, poorer liquidity and greater transfer and management costs. However, the purpose of this paper is to illustrate that such apparent demerits are largely illusory, and to promote the view that investors in growth freeholds need require no yield premium, and indeed may justifiably accept a discount on yields available from long dated gilts valued around par.

The lack of portfolio‐based property indices in European property markets has led researchers to consider the use of notional property indices to determine the risk and return rewards of investing in these markets. Owing to the computation assumptions underlying notional indices, in particular their inability to capture the prevalent lease structure in a market, they are unsuitable for this purpose, and investors devising European investment strategies around them need to be wary. This paper demonstrates the differences in property investment return delivery between notional and portfolio‐based indices, concentrating particularly on lease structures, and utilises data from the UK for this purpose. German lease structures are then considered in this context.

Correlation coefficients measuring the historical relationships of returns on commercial property and both equities and conventional gilts appear to be low. Conversely, the correlation between gilts and equities appears to be relatively high. This implies that property provides diversification benefits to a mixed asset portfolio dominated by equities and gilts. However, there is some debate as to the reliability of these correlations and property’s diversification benefits. In this paper we use Granger causality tests and cointegration techniques to demonstrate that there is no long‐run relationship between property returns and those of either gilts or equities. This confirms the diversification benefits of including property in a mixed asset portfolio.

Investment in Australia’s property market, whether directly or indirectly through Australian real estate investment trusts (A-REITs), grew remarkably since the 1990s. The degree of segregation between the property market and other financial assets, such as shares and bonds, can influence the diversification benefits within multi-asset portfolios. This raises the question of whether direct and indirect property investments are substitutable. Establishing how information transmits between asset classes and impacts the predictability of returns is of interest to investors. The paper aims to discuss these issues.

The authors study the linkages between direct and indirect Australian property sectors from 1985 to 2013, with shares and bonds. This paper employs an Autoregressive Fractionally Integrated Moving Average (ARFIMA) process to de-smooth a valuation-based direct property index. The authors establish directional lead-lag relationships between markets using bi-variate Granger causality tests. Johansen cointegration tests are carried out to examine how direct and indirect property markets adjust to an equilibrium long-term relationship and short-term deviations from such a relationship with other asset classes.

The authors find the use of appraisal-based property data creates a smoothing bias which masks the extent of how information is transmitted between the indirect property sector, stock and bond markets, and influences returns. The authors demonstrate that an ARFIMA process accounting for a smoothing bias up to lags of four quarters can overcome the overstatement of the smoothing bias from traditional AR models, after individually appraised constituent properties are aggregated into an overall index. The results show that direct property adjusts to information transmitted from market-traded A-REITs and stocks.

The study shows direct property investments and A-REITs are substitutible in a multi-asset portfolio in the long and short term.

The authors apply an ARFIMA(p,d,q) model to de-smooth Australian property returns, as proposed by Bond and Hwang (2007). The authors expect the findings will contribute to the discussion on whether direct property and REITs are substitutes in a multi-asset portfolio.

The purpose of this paper is to explore capital gains, income, and total returns in various property markets in Europe. In a comparative study the nature of returns for different commercial and residential properties is investigated. Hereby, total returns, income returns, and capital growth are distinguished. The paper further presents an analysis of the risk‐return relationship of the different markets and investigates the interactions between property markets, other local financial markets, and macroeconomic variables.

Focusing on the risk‐return relationship of the different asset classes and countries, the Sharpe ratio is used as a risk‐adjusted performance measure to investigate the European markets. Using a simple linear regression model, a comparison of the European commercial property markets with respect to their returns and risk are provided. Finally, a capital asset pricing model (CAPM) and factor models based on arbitrage pricing theory (APT) are used in an effort to further explain the spreads and risk premiums for individual property markets.

The large differences between the markets regarding spreads, risk premiums, and risk‐return relationships are found. Overall, the Dutch market can be regarded as giving the highest compensation for the risk taken by the investors in the last decade, while the German market performed the worst and was the only market with negative capital growth rates for the considered period. Applying the CAPM, It has also been found total returns in commercial property markets are not significantly related to the performance of stock market indices. On the other hand, factor models using macroeconomic variables are able to explain a higher fraction of property total return spreads over the risk‐free rate in the considered countries. But depending on the country, different macroeconomic variables were estimated to be significant such that there is no single factor model available that could be applied to all European markets. Overall, these findings indicate that classic financial models drawing on existing datasets are unable to satisfactorily explain the performance of property as an asset class. On the other hand, the fact that property office markets yield relatively high returns that exhibit rather low correlations with stock market returns, makes them a very suitable candidate for portfolio diversification.

The paper investigates the risk‐return relationship in various European property markets. The large differences between the markets observed also partly explain the diversity of literature results on this relationship across single countries by, e.g. Goetzmann, Englund, or Bourassa et al. By using classic financial models like the CAPM or APT a contribution to the literature is made by explaining the factors that actually determine property returns over the risk free rate in different countries.