The production and consumption of commercial real estate market forecasts

Whilst the vast majority of the research on property market forecasting has concentrated on statistical methods of forecasting future rents, this report investigates the process of property market forecast production with particular reference to the level and effect of judgemental intervention in this process. Expectations of future investment performance at the levels of individual asset, sector, region, country and asset class are crucial to stock selection and tactical and strategic asset allocation decisions. Given their centrality to investment performance, we focus on the process by which forecasts of rents and yields are generated and expectations formed. A review of the wider literature on forecasting suggests that there are strong grounds to expect that forecast outcomes are not the result of purely mechanical calculations.

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.

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.

Monetary integration and real estate markets: an investigation of the impact of the introduction of a single currency on real estate performance

This paper assesses the impact of the monetary integration on different types of stock returns in Europe. In order to isolate European factors, the impact of global equity integration and small cap factors are investigated. European countries are sub-divided according to the process of monetary convergence. Analysis shows that national equity indices are strongly influenced by global market movements, with a European stock factor providing additional explanatory power. The global and European factors explain small cap and real estate stocks much less well –suggesting an increased importance of ‘local’ drivers. For real estate, there are notable differences between core and non-core countries. Core European countries exhibit convergence – a convergence to a European rather than a global factor. The non-core countries do not seem to exhibit common trends or movements. For the non-core countries, monetary integration has been associated with increased dispersion of returns, lower correlation and lower explanatory power of a European factor. It is concluded that this may be explained by divergence in underlying macro-economic drivers between core and non-core countries in the post-Euro period.