Proceedings of the 3rd international conference on disability, virtual reality and associated technologies (ICDVRAT 2000)

The proceedings of the conference

Back from beyond the bid-ask spread: perspectives on liquidity

Research into the topic of liquidity has greatly benefited from the availability of data. Although bid-ask spreads were inaccessible to researchers, Roll (1984) provided a conceptual model that estimated the effective bid-ask prices from regular time series data, recorded on a daily or longer interval. Later data availability improved and researchers were able to address questions regarding the factors that influenced the spreads and the relationship between spreads and risk, return and liquidity. More recently transaction data have been used to measure the effective spread and researchers have been able to refine the concepts of liquidity to include the impact of transactions on price movements (Clayton and McKinnon, 2000) on a trade-by-trade analysis. This paper aims to use techniques that combine elements from all three approaches and, by studying US data over a relatively long time period, to throw light on earlier research as well as to reveal the changes in liquidity over the period controlling for extraneous factors such as market, age and size of REIT. It also reveals some comparable results for the UK market over the same period.

Perspectives on the role of UK planning in land and property markets

There is a popular view that land use planning regulations (‘planning’) is hostile to both development and the development industry. Part of the reason for the prominence of this view is the homogenising of the notion of ‘planning’ and its reduction to development control. This paper argues that panning controls in the UK are far more sophisticated and, drawing upon empirical evidence of key property interests proposes a more complex and nuanced view of planning controls that, in large part, has the support of the developers and others.

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.

Energy and protein interactions and their effect on nitrogen excretion in dairy cows

The principal driver of nitrogen (N) losses from the body including excretion and secretion in milk is N intake. However, other covariates may also play a role in modifying the partitioning of N. This study tests the hypothesis that N partitioning in dairy cows is affected by energy and protein interactions. A database containing 470 dairy cow observations was collated from calorimetry experiments. The data include N and energy parameters of the diet and N utilization by the animal. Univariate and multivariate meta-analyses that considered both within and between study effects were conducted to generate prediction equations based on N intake alone or with an energy component. The univariate models showed that there was a strong positive linear relationships between N intake and N excretion in faeces, urine and milk. The slopes were 0.28 faeces N, 0.38 urine N and 0.20 milk N. Multivariate model analysis did not improve the fit. Metabolizable energy intake had a significant positive effect on the amount of milk N in proportion to faeces and urine N, which is also supported by other studies. Another measure of energy considered as a covariate to N intake was diet quality or metabolizability (the concentration of metabolizable energy relative to gross energy of the diet). Diet quality also had a positive linear relationship with the proportion of milk N relative to N excreted in faeces and urine. Metabolizability had the largest effect on faeces N due to lower protein digestibility of low quality diets. Urine N was also affected by diet quality and the magnitude of the effect was higher than for milk N. This research shows that including a measure of diet quality as a covariate with N intake in a model of N execration can enhance our understanding of the effects of diet composition on N losses from dairy cows. The new prediction equations developed in this study could be used to monitor N losses from dairy systems.