The consistency of private and public real estate within mixed-asset portfolios

This study considers the consistency of the role of both the private and public real estate markets within a mixed-asset context. While a vast literature has developed that has examined the potential role of both the private and public real estate markets, most studies have largely relied on both single time horizons and single sample periods. This paper builds upon the analysis of Lee and Stevenson (2005) who examined the consistency of REITs in a US capital market portfolio. The current paper extends that by also analyzing the role of the private market. To address the question, the allocation of both the private and traded markets is evaluated over different holding periods varying from 5- to 20-years. In general the results show that optimum mixed-asset portfolios already containing private real estate have little place for public real estate securities, especially in low risk portfolios and for longer investment horizons. Additionally, mixed-asset portfolios with public real estate either see the allocations to REITs diminished or eliminated if private real estate is also considered. The results demonstrate that there is a still a strong case for private real estate in the mixed-asset portfolio on the basis of an increase in risk-adjusted performance, even if the investor is already holding REITs, but that the reverse is not always the case.

Analysing UK real estate market forecast disagreement

Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The results suggest that real estate forecasts are biased, less volatile compared to market returns and inefficient in that forecast errors tend to persist. The strongest finding is that real estate forecasters display the characteristics associated with a consensus indicating herding.

An evaluation of the performance of UK real estate forecasters

Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. It compares the performance of real estate forecasters with non-real estate forecasters. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters and a similar survey of macro-economic and capital market forecasters, these forecasts are compared with actual performance to assess a number of forecasting issues in the UK over 1999-2004, including forecast error, bias and consensus. The results suggest that both groups are biased, less volatile compared to market returns and inefficient in that forecast errors tend to persist. The strongest finding is that forecasters display the characteristics associated with a consensus indicating herding.

International evidence on the predictability of returns to securitized real estate assets: econometric models versus neural networks

The performance of various statistical models and commonly used financial indicators for forecasting securitised real estate returns are examined for five European countries: the UK, Belgium, the Netherlands, France and Italy. Within a VAR framework, it is demonstrated that the gilt-equity yield ratio is in most cases a better predictor of securitized returns than the term structure or the dividend yield. In particular, investors should consider in their real estate return models the predictability of the gilt-equity yield ratio in Belgium, the Netherlands and France, and the term structure of interest rates in France. Predictions obtained from the VAR and univariate time-series models are compared with the predictions of an artificial neural network model. It is found that, whilst no single model is universally superior across all series, accuracy measures and horizons considered, the neural network model is generally able to offer the most accurate predictions for 1-month horizons. For quarterly and half-yearly forecasts, the random walk with a drift is the most successful for the UK, Belgian and Dutch returns and the neural network for French and Italian returns. Although this study underscores market context and forecast horizon as parameters relevant to the choice of the forecast model, it strongly indicates that analysts should exploit the potential of neural networks and assess more fully their forecast performance against more traditional models.

Non-normal real estate return distributions by property type in the U.K.

Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD database over the period 1981 to 2003 than Normally distributed risk models, which mirrors results in the U.S. and Australia using identical methodology. Real estate investment risk is heteroscedastic, but the Characteristic Exponent of the investment risk function is constant across time yet may vary by property type. Asset diversification is far less effective at reducing the impact of non-systematic investment risk on real estate portfolios than in the case of assets with Normally distributed investment risk. Multi-risk factor portfolio allocation models based on measures of investment codependence from finite-variance statistics are ineffectual in the real estate context.

The impact of real estate on the terminal wealth of the UK mixed-asset portfolio

The argument for the inclusion of real estate in the mixed-asset portfolio has concentrated on examining its effect in reducing the portfolio risk - the time series standard deviation (TSSD), mainly using ex-post time series data. However, the past as such is not really relevant to the long-term institutional investors, such as the insurance companies and pension funds, who are more concerned the terminal wealth (TW) of their investments and the variability of this wealth, the terminal wealth standard deviation (TWSD), since it is from the TW of their investment portfolio that policyholders and pensioners will derive their benefits. These kinds of investors with particular holding period requirements will be less concerned about the within period volatility of their portfolios and more by the possibility that their portfolio returns will fail to finance their liabilities. This variability in TW will be closely linked to the risk of shortfall in the quantity of assets needed to match the institution’s liabilities. The question remains therefore can real estate enhance the TW of the mixed-asset portfolio and/or reduce the variability of the TW. This paper uses annual data from the United Kingdom (UK) for the period 1972-2001 to test whether real estate is an asset class that not only reduces ex-post portfolio risk but also enhances portfolio TW and/or reduces the variability of TW.

The impact of real estate on the mixed-asset portfolio in periods of financial stress

The case for holding real estate in the mixed-asset portfolio is typically made on its stabilising effect as a result of its diversification benefits. However, portfolio diversification often fails when it is most needed, i.e. during periods of financial stress. In these periods, the variability of returns for most asset classes increases thus reducing the stabilising effect of a diversified portfolio. This paper applies the approach of Chow et al (1999) to the US domestic mixed-asset portfolio to establish whether real estate, represented by REITs, is especially useful in times of financial stress. To this end monthly returns data on five assets classes: large cap stocks, small cap stocks, long dated government bonds, cash (T-Bills) and real estate (REITs) are evaluated over the period January 1972 to December 2001. The results indicate that the inclusion of REITs in the mixed-asset portfolio can lead to increases or decreases in returns depending on the asset class replaced and whether the period is one of calm or stress. However, the inclusion of REITs invariably leads to reductions in portfolio risk that are greater than any loss in return, especially in periods of financial stress. In other words, REITs acts as a stabilising force on the mixed-asset portfolio when it is most needed, i.e. in periods of financial stress.

The persistence of real estate fund performance

This paper examines the short and long-term persistence of tax-exempt real estate funds in the UK through the use of winner-loser contingency table methodology. The persistence tests are applied to a database of varying numbers of funds from a low of 16 to a high of 27 using quarterly returns over the 12 years from 1990 Q1 to 2001 Q4. The overall conclusion is that the real estate funds in the UK show little evidence of persistence in the short-term (quarterly and semi-annual data) or for data over a considerable length of time (bi-annual to six yearly intervals). In contrast, the results are better for annual data with evidence of significant performance persistence. Thus at this stage, it seems that an annual evaluation period, provides the best discrimination of the winner and loser phenomenon in the real estate market. This result is different from equity and bond studies, where it seems that the repeat winner phenomenon is stronger over shorter periods of evaluation. These results require careful interpretation, however, as the results show that when only small samples are used significant adjustments must be made to correct for small sample bias and second the conclusions are sensitive to the length of the evaluation period and specific test used. Nonetheless, it seems that persistence in performance of real estate funds in the UK does exist, at least for the annual data, and it appears to be a guide to beating the pack in the long run. Furthermore, although the evidence of persistence in performance for the overall sample of funds is limited, we have found evidence that two funds were consistent winners over this period, whereas no one fund could be said to be a consistent loser.

The return due to diversification of real estate to the US mixed-asset portfolio

Booth and Fama (1992) observe that the compound return and so the terminal wealth of a portfolio is greater than the weighted average of the compound returns of the individual investments, a difference referred to as the return due to diversification (RDD). Thus assets that offer high RDD should be particularly attractive investments. This paper test the proposition that US direct real estate is such an asset class using annual data over the period 1951-2001. The results show that adding real estate to an existing mixed-asset portfolio increases the compound return and so the terminal wealth of the fund. However, the results are dependent on the percentage allocation to real estate and the asset class replaced.

When does direct real estate improve portfolio performance?

For over twenty years researchers have been recommending that investors diversify their portfolios by adding direct real estate. Based on the tenets of modern portfolio theory (MPT) investors are told that the primary reason they should include direct real estate is that they will enjoy decreased volatility (risk) through increased diversification. However, the MPT methodology hides where this reduction in risk originates. To over come this deficiency we use a four-quadrant approach to break down the co-movement between direct real estate and equities and bonds into negative and positive periods. Then using data for the last 25-years we show that for about 70% of the time a holding in direct real estate would have hurt portfolio returns, i.e. when the other assets showed positive performance. In other words, for only about 30% of the time would a holding in direct real estate lead to improvements in portfolio returns. However, this increase in performance occurs when the alternative asset showed negative returns. In addition, adding direct real estate always leads to reductions in portfolio risk, especially on the downside. In other words, although adding direct real estate helps the investor to avoid large losses it also reduces the potential for large gains. Thus, if the goal of the investor is offsetting losses, then the results show that direct real estate would have been of some benefit. So in answer to the question when does direct real estate improve portfolio performance the answer is on the downside, i.e. when it is most needed.