911 resultados para Investor attention


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In this study, sustained, selective, divided, and switching attention, and reloading of working memory were investigated in schizophrenia by using a newly developed Visual Attention Battery (VAB). Twenty-four outpatients with schizophrenia and 24 control participants were studied using the VAB. Performance on VAB components was correlated with performance of standard tests. Patients with schizophrenia were significantly impaired on VAB tasks that required switching of attention and reloading of working memory but had normal performance on tasks involving sustained attention or attention to multiple stimulus features. Switching attention and reloading of working memory were highly correlated with Trails (B - A) score for patients. The decline in performance on the switching-attention task in patients with schizophrenia met criteria for a differential deficit in switching attention. Future research should examine the neurophysiological basis of the switching deficit and its sensitivity and specificity to schizophrenia.

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Objective: This study examines the association between maternal anxiety from pregnancy to 5 years and child attention problems at 5 and 14 years. Method: Birth cohort of 3,982 individuals born in Brisbane between 1981 and 1983 are assessed. Self-reported measures of maternal anxiety are assessed at four time points. Maternal reports of child attention problems using Achenbach’s Child Behavior Checklist are assessed at 5 and 14 years. Results: Children of mothers experiencing anxiety during or after pregnancy are at greater risk of experiencing attention problems at 5 and 14 years. After adjusting for maternal age and child’s gender, antenatal anxiety is strongly associated with persistent attention problems (OR = 3.65, 95% CI = 2.19, 6.07). Children with chronically anxious mothers are 5.67 (95% CI = 3.56, 9.03) times more likely to have persistent attention problems. These associations remain consistent after adjusting for potential confounders. Conclusions: Maternal anxiety appears to increase the rate of child attention problems and identifies a need for treatment programs to have a dual focus—the mother and her child. (J. of Att. Dis. 2009; XX(X) 1-XX)

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In this thesis we are interested in financial risk and the instrument we want to use is Value-at-Risk (VaR). VaR is the maximum loss over a given period of time at a given confidence level. Many definitions of VaR exist and some will be introduced throughout this thesis. There two main ways to measure risk and VaR: through volatility and through percentiles. Large volatility in financial returns implies greater probability of large losses, but also larger probability of large profits. Percentiles describe tail behaviour. The estimation of VaR is a complex task. It is important to know the main characteristics of financial data to choose the best model. The existing literature is very wide, maybe controversial, but helpful in drawing a picture of the problem. It is commonly recognised that financial data are characterised by heavy tails, time-varying volatility, asymmetric response to bad and good news, and skewness. Ignoring any of these features can lead to underestimating VaR with a possible ultimate consequence being the default of the protagonist (firm, bank or investor). In recent years, skewness has attracted special attention. An open problem is the detection and modelling of time-varying skewness. Is skewness constant or there is some significant variability which in turn can affect the estimation of VaR? This thesis aims to answer this question and to open the way to a new approach to model simultaneously time-varying volatility (conditional variance) and skewness. The new tools are modifications of the Generalised Lambda Distributions (GLDs). They are four-parameter distributions, which allow the first four moments to be modelled nearly independently: in particular we are interested in what we will call para-moments, i.e., mean, variance, skewness and kurtosis. The GLDs will be used in two different ways. Firstly, semi-parametrically, we consider a moving window to estimate the parameters and calculate the percentiles of the GLDs. Secondly, parametrically, we attempt to extend the GLDs to include time-varying dependence in the parameters. We used the local linear regression to estimate semi-parametrically conditional mean and conditional variance. The method is not efficient enough to capture all the dependence structure in the three indices —ASX 200, S&P 500 and FT 30—, however it provides an idea of the DGP underlying the process and helps choosing a good technique to model the data. We find that GLDs suggest that moments up to the fourth order do not always exist, there existence appears to vary over time. This is a very important finding, considering that past papers (see for example Bali et al., 2008; Hashmi and Tay, 2007; Lanne and Pentti, 2007) modelled time-varying skewness, implicitly assuming the existence of the third moment. However, the GLDs suggest that mean, variance, skewness and in general the conditional distribution vary over time, as already suggested by the existing literature. The GLDs give good results in estimating VaR on three real indices, ASX 200, S&P 500 and FT 30, with results very similar to the results provided by historical simulation.

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We investigate whether characteristics of the home country capital environment, such as information disclosure and investor rights protection continue to affect ADRs cross-listed in the U.S. Using microstructure measures as proxies for adverse selection, we find that characteristics of the home markets continue to be relevant, especially for emerging market firms. Less transparent disclosure, poorer protection of investor rights and weaker legal institutions are associated with higher levels of information asymmetry. Developed market firms appear to be affected by whether or not home business laws are common law or civil law legal origin. Our finding contributes to the bonding literature. It suggests that cross-listing in the U.S. should not be viewed as a substitute for improvement in the quality of local institutions, and attention must be paid to improve investor protection in order to achieve the full benefits of improved disclosure. Improvement in the domestic capital market environment can attract more investors even for U.S. cross-listed firms.

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Vigilance declines when exposed to highly predictable and uneventful tasks. Monotonous tasks provide little cognitive and motor stimulation and contribute to human errors. This paper aims to model and detect vigilance decline in real time through participant’s reaction times during a monotonous task. A lab-based experiment adapting the Sustained Attention to Response Task (SART) is conducted to quantify the effect of monotony on overall performance. Then relevant parameters are used to build a model detecting hypovigilance throughout the experiment. The accuracy of different mathematical models are compared to detect in real-time – minute by minute - the lapses in vigilance during the task. We show that monotonous tasks can lead to an average decline in performance of 45%. Furthermore, vigilance modelling enables to detect vigilance decline through reaction times with an accuracy of 72% and a 29% false alarm rate. Bayesian models are identified as a better model to detect lapses in vigilance as compared to Neural Networks and Generalised Linear Mixed Models. This modelling could be used as a framework to detect vigilance decline of any human performing monotonous tasks.

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Investigations into the relative effectiveness of either focusing on movement form (internal focus) or movement effects (external focus) have tended to dominate research on instructional constraints. However, rather than adopting a comparative approach to determine which focus of attention is more effective, analysis of the relative efficacy of each specific instruction focus during motor learning could be more relevant for both researchers and practitioners. Theoretical advances in the motor learning literature from a nonlinear dynamics perspective might explain the processes that underlie the effect of different attentional focus instructions. Referencing ideas and concepts from a current motor learning model, differential effects of either internal or external focus of instructions are examined. This paper also highlights some deficiencies in extant theory and research design on focus of attention which require further investigations.

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It is possible for the visual attention characteristics of a person to be exploited as a biometric for authentication or identification of individual viewers. The visual attention characteristics of a person can be easily monitored by tracking the gaze of a viewer during the presentation of a known or unknown visual scene. The positions and sequences of gaze locations during viewing may be determined by overt (conscious) or covert (sub-conscious) viewing behaviour. This paper presents a method to authenticate individuals using their covert viewing behaviour, thus yielding a unique behavioural biometric. A method to quantify the spatial and temporal patterns established by the viewer for their covert behaviour is proposed utilsing a principal component analysis technique called `eigenGaze'. Experimental results suggest that it is possible to capture the unique visual attention characteristics of a person to provide a simple behavioural biometric.

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Affect modulates the blink startle reflex in the picture-viewing paradigm, however, the process responsible for reflex modulation during conditional stimuli (CSs) that have acquired valence through affective conditioning remains unclear. In Experiment 1, neutral shapes (CSs) and valenced or neutral pictures (USs) were paired in a forward (CS → US) manner. Pleasantness ratings supported affective learning of positive and negative valence. Post-acquisition, blink reflexes were larger during the pleasant and unpleasant CSs than during the neutral CS. Rather than affect, attention or anticipatory arousal were suggested as sources of startle modulation. Experiment 2 confirmed that affective learning in the picture–picture paradigm was not affected by whether the CS preceded the US. Pleasantness ratings and affective priming revealed similar extents of affective learning following forward, backward or simultaneous pairings of CSs and USs. Experiment 3 utilized a backward conditioning procedure (US → CS) to minimize effects of US anticipation. Again, blink reflexes were larger during CSs paired with valenced USs regardless of US valence implicating attention rather than anticipatory arousal or affect as the process modulating startle in this paradigm.

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It is imperative that we consider the use of current and emerging technologies in terms of the nature of our learners, the physical environment of the lecture theatre, and how technology may help to support appropriate pedagogies that facilitate the capturing of student attention in active engaging learning experiences. It is argued that a re-evaluation of pedagogy is required to address the tech-savy traits of the 21st century learner and the extent to which their mobile devices are capable of not only distracting them from learning but also enhancing face-to-face learning experiences.