Predicting returns in U.S. financial sector indices

This study focuses on: (i) the responsiveness of the U.S. financial sector stock indices to foreign exchange (FX) and interest rate changes; and, (ii) the extent to which good model specification can enhance the forecasts from the associated models. Three models are considered. Only the error-correction model (ECM) generated efficient and consistent coefficient estimates. Furthermore, a simple zero lag model in differences which is clearly mis-specified, generated forecasts that are better than those of the ECM, even if the ECM depicts relationships that are more consistent with economic theory. In brief, FX and interest rate changes do not impact on the return-generating process of the stock indices in any substantial way. Most of the variation in the sector stock indices is associated with past variation in the indices themselves and variation in the market-wide stock index. These results have important implications for financial and economic policies.

Predicting general well-being from emotional intelligence and three broad personality traits

This paper examined the joint predictive effects of trait emotional intelligence (trait-EI), Extraversion, Conscientiousness, and Neuroticism on 2 facets of general well-being and job satisfaction. An employed community sample of 123 individuals from the Indian subcontinent participated in the study, and completed measures of the five-factor model of personality, trait-EI, job satisfaction, and general well-being facets worn-out and up-tight. Trait-EI was related but distinct from the 3 personality variables. Trait-EI demonstrated the strongest correlation with job satisfaction, but predicted general well-being no better than Neuroticism. In regression analyses, trait-EI predicted between 6% and 9% additional variance in the well-being criteria, beyond the 3 personality traits. It was concluded that trait-EI may be useful in examining dispositional influences on psychological well-being.

Drying of portland cement raw material slurries:predicting the performance of a counter-current spray drier

An extensive review of literature has been carried out concerning the drying of single drops, sprays of droplets and the prediction of spray drier performances. The experimental investigation has been divided into two broad parts mainly: (1) Single Drop Experiments, and (2) Spray Drying and Residence Time Distribution Experiments. The thermal conductivity of slurry cakes from five different sources have been experimentally determined using a modified Lee's Disc Apparatus and the data collected was correlated by the polynominal... Good agreement was observed between the experimental thermal conductivity values and the predicted ones. The fit gave a variance ... for the various samples experimented on. A mathematical model for estimating crust mass transfer coefficient at high drying temperatures was derived.

Effects of syllabic complexity in predicting accuracy of repetition and direction of errors in patients with articulatory and phonological difficulties

The purpose of this paper is to demonstrate the existence of a strong and significant effect of complexity in aphasia independent from other variables including length. Complexity was found to be a strong and significant predictor of accurate repetition in a group of 13 Italian aphasic patients when it was entered in a regression equation either simultaneously or after a large number of other variables. Significant effects were found both when complexity was measured in terms of number of complex onsets (as in a recent paper by Nickels & Howard, 2004) and when it was measured in a more comprehensive way. Significant complexity effects were also found with matched lists contrasting simple and complex words and in analyses of errors. Effects of complexity, however, were restricted to patients with articulatory difficulties. Reasons for this association and for the lack of significant results in Nickels and Howard (2004) are discussed. © 2005 Psychology Press Ltd.

Predicting prescribed magnification

Aim: To determine the best method of estimating the optimum magnification needed by visually impaired patients. Methods: The magnification of low vision aids prescribed to 187 presbyopic visually impaired patients for reading newspapers or books was compared with logMAR distance and near acuity (at 25 cm) and magnification predicted by +4 D step near additions. Results: Distance letter (r = 0.58) and near word visual acuity (r = 0.67) were strongly correlated to the prescribed magnification as were predictive formulae based on these measures. Prediction using the effect of proximal magnification resulted in a similar correlation (r = 0.67) and prediction was poorer in those who did not benefit from proximal magnification. The difference between prescribed and predicted magnification was found to be unrelated to the condition causing visual impairment (F = 2.57, p = 0.08), the central visual field status (F = 0.57, p = 0.57) and patient psychology (F = 0.44, p = 0.51), but was higher in those prescribed stand magnifiers than high near additions (F = 5.99, p < 0.01). Conclusions: The magnification necessary to perform normal visual tasks can be predicted in the majority of cases using visual acuity measures, although measuring the effect of proximal magnification demonstrates the effect of stronger glasses and identifies those in whom prescribed magnification is more difficult to predict.

Predicting changes in measured introcular pressure with non-contact tonometry after LASIK

Purpose: Optometrists are becoming more integrally involved in the diagnosis of and care for glaucoma patients in the UK. The correlation of apparent change in non contact tonometry (NCT) IOP measurement and change in other ocular parameters such as refractive error, corneal curvature, corneal thickness and treatment zone size (data available to optometrists after LASIK) would facilitate care of these patients. Setting: A UK Laser Eye Clinic. Methods: This is a retrospective study study of 200 sequential eyes with myopia with or without astigmatism which underwent LASIK using a Hansatome and an Alcon LADARvision 4000 excimer laser. Refraction keratometry, pachymetry and NCT IOP mesurements were taken before treatmebnt and agian 3 months after treatment. The relationship between these variables anfd teh treatment zones were studied using stepwise multiple regression analysis. Results: There was a mean difference of 5.54mmHg comnparing pre and postoperative NCT IOP. IOP change correlates with refractive error change (P < 0.001), preoperative corneal thickness (P < 0.001) and treatment zone size (P = 0.047). Preoperative corneal thickness correlates with preoperative IOP (P < 0.001) and postoperative IOP (P < 0.001). Using these correlations, the measured difference in NCT IIOP can be predicted preoperatively or postoperatively using derived equations.Conclusion: There is a significant reduction in measured NCT IOP after LASIK. The amount of reduction can be calculated using data acquired by optometrists. This is helpful for opthalmologists and optometrists who co-manage glaucoma patients who have had LASIK or with glaucoma pateints who are consideraing having LASIK.

Gender differences in factors predicting unsafe crossing decisions in adult pedestrians across the lifespan: a simulation study

Adult pedestrian accident data has demonstrated that the risk of being killed or seriously injured varies with age and gender. A range of factors affecting road crossing choices of 218 adults aged 17-90+ were examined in a simulation study using filmed real traffic. With increasing age, women were shown to make more unsafe crossing decisions, to leave small safety margins and to become poorer at estimating their walking speed. However, the age effects on all of these were ameliorated by driving experience. Men differed from women in that age was not a major factor in predicting unsafe crossing decisions. Rather, reduced mobility was the key factor, leading them to make more unsafe crossings and delay longer in leaving the kerb. For men, driving experience did not predict unsafe road crossing decisions. Although male drivers were more likely to look both ways before crossing than male non-drivers, the impact of being a driver had a negative effect in terms of smaller safety margins and delay in leaving the kerb. The implications of the different predictor variables for men and women for unsafe road crossing are discussed and possible reasons for the differences explored.

Predicting and diagnosing faults in wastewater treatment process by Bayesian Belief Networks

Diagnosing faults in wastewater treatment, like diagnosis of most problems, requires bi-directional plausible reasoning. This means that both predictive (from causes to symptoms) and diagnostic (from symptoms to causes) inferences have to be made, depending on the evidence available, in reasoning for the final diagnosis. The use of computer technology for the purpose of diagnosing faults in the wastewater process has been explored, and a rule-based expert system was initiated. It was found that such an approach has serious limitations in its ability to reason bi-directionally, which makes it unsuitable for diagnosing tasks under the conditions of uncertainty. The probabilistic approach known as Bayesian Belief Networks (BBNS) was then critically reviewed, and was found to be well-suited for diagnosis under uncertainty. The theory and application of BBNs are outlined. A full-scale BBN for the diagnosis of faults in a wastewater treatment plant based on the activated sludge system has been developed in this research. Results from the BBN show good agreement with the predictions of wastewater experts. It can be concluded that the BBNs are far superior to rule-based systems based on certainty factors in their ability to diagnose faults and predict systems in complex operating systems having inherently uncertain behaviour.