29 resultados para Value at Risk

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.

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Background Previous research has shown that home ownership is associated with a reduced risk of admission to institutional care. The extent to which this reflects associations between wealth and health, between wealth and ability to buy in care or increased motivation to avoid admission related to policies on charging is unclear. Taking account of the value of the home, as well as housing tenure, may provide some clarification as to the relative importance of these factors.
Aims To analyse the probability of admission to residential and nursing home care according to housing tenure and house value.
Methods Cox regression was used to examine the association between home ownership, house value and risk of care home admissions over 6 years of follow-up among a cohort of 51 619 people aged 65 years or older drawn from the Northern Ireland Longitudinal Study, a representative sample of approximate to 28% of the population of Northern Ireland.
Results 4% of the cohort (2138) was admitted during follow-up. Homeowners were less likely than those who rented to be admitted to care homes (HR 0.77, 95% CI 0.70 to 0.85, after adjusting for age, sex, health, living arrangement and urban/rural differences). There was a strong association between house value/tenure and health with those in the highest valued houses having the lowest odds of less than good health or limiting long-term illness. However, there was no difference in probability of admission according to house value; HRs of 0.78 (95% CI 0.67 to 0.90) and 0.81 (95% CI 0.70 to 0.95), respectively, for the lowest and highest value houses compared with renters.
Conclusions The requirement for people in the UK with capital resources to contribute to their care is a significant disincentive to institutional admission. This may place an additional burden on carers.

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We propose two simple evaluation methods for time varying density forecasts of continuous higher dimensional random variables. Both methods are based on the probability integral transformation for unidimensional forecasts. The first method tests multinormal densities and relies on the rotation of the coordinate system. The advantage of the second method is not only its applicability to any continuous distribution but also the evaluation of the forecast accuracy in specific regions of its domain as defined by the user’s interest. We show that the latter property is particularly useful for evaluating a multidimensional generalization of the Value at Risk. In simulations and in an empirical study, we examine the performance of both tests.

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Background: There has been relatively little research into health inequalities in older populations. This may be partly explained by the difficulty in identifying appropriate indicators of socio-economic status for older people. Ideally, indicators of socio-economic status to be used in studies of health inequalities in older populations should incorporate some measure of life-time socio-economic standing, and house value may fill this role. This study examined whether an indicator of accumulated wealth based on a combination of housing tenure and house value was a strong predictor of ill-health in older populations.
Methods: A total of 191 848 people aged =65 years and not living in communal establishments were identified from the 2001 Northern Ireland Census and followed for 5 years. Self-reported health and mortality risk by housing tenure/house value groupings were examined while controlling for a range of other demographic and socio-economic characteristics.
Results: Housing tenure/house value was highly correlated with other indicators of socio-economic status. Public-sector renters had worse self-reported health and higher mortality rates than owner occupiers but significant gradients were also found between those living in the highest-and lowest-valued owner-occupier properties. The relationship between housing tenure and value was unchanged by adjustment for indicators of social support and quality of the physical environment. Adjustment for limiting long-term illness and self-reported health at baseline narrowed but did not eliminate the health gains associated with living in more expensive housing.
Conclusions: House value of residence is an accessible and powerful indicator of accumulated wealth that is highly correlated with current health status and predictive of future mortality risk in older populations.

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OBJECTIVES: To improve understanding about the potential underlying biological mechanisms in the link between depression and all-cause mortality and to investigate the role that inflammatory and other cardiovascular risk factors may play in the relationship between depressive symptoms and mortality.

METHODS: Depression and blood-based biological markers were assessed in the Belfast PRIME prospective cohort study (N = 2389 men, aged 50-59 years) in which participants were followed up for 18 years. Depression was measured using the 10-item Welsh Pure Depression Inventory. Inflammation markers (C-reactive protein [CRP], neopterin, interleukin [IL]-1 receptor antagonist [IL-1Ra], and IL-18) and cardiovascular-specific risk factors (N-terminal pro-b-type natriuretic peptide, midregion pro-atrial natriuretic peptide, midregion pro-adrenomedullin, C-terminal pro-endothelin-1 [CT-proET]) were obtained at baseline. We used Cox proportional hazards modeling to examine the association between depression and biological measures in relation to all-cause mortality and explore the mediating effects.

RESULTS: During follow-up, 418 participants died. Higher levels of depressive symptoms were associated with higher levels of CRP, IL-1Ra, and CT-proET. After adjustment for socioeconomic and life-style risk factors, depressive symptoms were significantly associated with all-cause mortality (hazard ratio = 1.10 per scale unit, 95% confidence interval = 1.04-1.16). This association was partly explained by CRP (7.3%) suggesting a minimal mediation effect. IL-1Ra, N-terminal pro-b-type natriuretic peptide, midregion pro-atrial natriuretic peptide, midregion pro-adrenomedullin, and CT-proET contributed marginally to the association between depression and subsequent mortality.

CONCLUSIONS: Inflammatory and cardiovascular risk markers are associated with depression and with increased mortality. However, depression and biological measures show additive effects rather than a pattern of meditation of biological factors in the association between depression and mortality.

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This paper examines (i) whether value-growth characteristics have more power than past performance in predicting return reversals; and (ii) whether typical rational behaviour such as incentives to delay paying capital gain taxes can better explain long-term reversals than past performance. We find that value-growth characteristics generally provide better explanations for long-term stock returns than past performance. The evidence also shows that winners identified by capital gains dominate past performance winners in predicting reversals in the cross-sectional comparison. However, in the time-series analysis, when returns on capital gain winners are adjusted by the Fama and French (1996) risk factors, the predictive power of capital gain winners disappears. Our results show that capital gain winners are heavily featured as growth stocks. Return reversals in capital gain winners potentially reflect market price corrections for growth stocks. We conclude that investors’ incentives to delay paying capital gain taxes cannot fully rationalise long-term reversals in the UK market. Our results also imply that the long-term return pattern potentially reflects a mixture of investor rational and irrational behaviour.

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The valuation of environmental benefits has been well researched in the forestry sector. This is not generally the case in the agriculture sector although schemes to compensate farmers for provision of officially defined environmental benefits are already in place throughout the European Union. This paper draws on empirical findings from forestry and deductions from economic theory to challenge the notion of the universality of such benefits. Empirical findings from forestry suggest recreational use value is location specific rather than widely spread. Household utility theory predicts zero willingness to pay to maintain the status quo level of a previously unpaid for environmental benefit (when provision is not perceived as under risk) but a positive willingness to pay for an increase. Thus, non use values cannot be attributed to the major part of existing commercial forestry area but to spatially restricted schemes such as additional afforestation or preservation of ancient natural woodlands.

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A key pathological feature of late-onset Alzheimer's disease (LOAD) is the abnormal extracellular accumulation of the amyloid-ß (Aß) peptide. Thus, altered Aß degradation could be a major contributor to the development of LOAD. Variants in the gene encoding the Aß-degrading enzyme, angiotensin-1 converting enzyme (ACE) therefore represent plausible candidates for association with LOAD pathology and risk. Following Alzgene meta-analyses of all published case-control studies, the ACE variants rs4291 and rs1800764 showed significant association with LOAD risk. Furthermore ACE haplotypes are associated with both plasma ACE levels and LOAD risk. We tested three ACE variants (rs4291, rs4343, and rs1800764) for association with LOAD in ten Caucasian case-control populations (n = 8,212). No association was found using multiple logistic models (all p > 0.09). We found no population heterogeneity (all p > 0.38) or evidence for association with LOAD risk following meta-analysis of the ten populations for rs4343 (OR = 1.00), rs4291 (OR = 0.97), or rs1800764 (OR = 0.99). Although we found no haplotypic association in our complete dataset (p = 0.51), a significant global haplotypic p-value was observed in one population (p = 0.007) due to an association of the H3 haplotype (OR = 0.72, p = 0.02) and a trend towards an association of H4 (OR = 1.38, p = 0.09) and H7 (OR = 2.07, p = 0.08) although these did not survive Bonferroni correction. Previously reported associations of ACE variants with LOAD will be diminished following this study. At best, ACE variants have modest effect sizes, which are likely part of a complex interaction between genetic, phenotypic and pharmacological effects that would be undetected in traditional case-control studies.

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Background

Endocrine disrupting chemicals and carcinogens, some of which may not yet have been classified as such, are present in many occupational environments and could increase breast cancer risk. Prior research has identified associations with breast cancer and work in agricultural and industrial settings. The purpose of this study was to further characterize possible links between breast cancer risk and occupation, particularly in farming and manufacturing, as well as to examine the impacts of early agricultural exposures, and exposure effects that are specific to the endocrine receptor status of tumours.

Methods

1005 breast cancer cases referred by a regional cancer center and 1147 randomly-selected community controls provided detailed data including occupational and reproductive histories. All reported jobs were industry- and occupation-coded for the construction of cumulative exposure metrics representing likely exposure to carcinogens and endocrine disruptors. In a frequency-matched case?control design, exposure effects were estimated using conditional logistic regression.

Results

Across all sectors, women in jobs with potentially high exposures to carcinogens and endocrine disruptors had elevated breast cancer risk (OR = 1.42; 95% CI, 1.18-1.73, for 10 years exposure duration). Specific sectors with elevated risk included: agriculture (OR = 1.36; 95% CI, 1.01-1.82); bars-gambling (OR = 2.28; 95% CI, 0.94-5.53); automotive plastics manufacturing (OR = 2.68; 95% CI, 1.47-4.88), food canning (OR = 2.35; 95% CI, 1.00-5.53), and metalworking (OR = 1.73; 95% CI, 1.02-2.92). Estrogen receptor status of tumors with elevated risk differed by occupational grouping. Premenopausal breast cancer risk was highest for automotive plastics (OR = 4.76; 95% CI, 1.58-14.4) and food canning (OR = 5.70; 95% CI, 1.03-31.5).

Conclusions

These observations support hypotheses linking breast cancer risk and exposures likely to include carcinogens and endocrine disruptors, and demonstrate the value of detailed work histories in environmental and occupational epidemiology.