HEAVY-TAILED-DISTRIBUTED THRESHOLD STOCHASTIC VOLATILITY MODELS IN FINANCIAL TIME SERIES

To capture mean and variance asymmetries and time‐varying volatility in financial time series, we generalize the threshold stochastic volatility (THSV) model and incorporate a heavy‐tailed error distribution. Unlike existing stochastic volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time‐delay parameter. Self‐exciting and exogenous threshold variables are considered to investigate the impact of a number of market news variables on volatility changes. Adopting a Bayesian approach, we use Markov chain Monte Carlo methods to estimate all unknown parameters and latent variables. A simulation experiment demonstrates good estimation performance for reasonable sample sizes. In a study of two international financial market indices, we consider two variants of the generalized THSV model, with US market news as the threshold variable. Finally, we compare models using Bayesian forecasting in a value‐at‐risk (VaR) study. The results show that our proposed model can generate more accurate VaR forecasts than can standard models.     

Population constraints on pooled surveys in demographic hazard modeling

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.     

论公司价值的创造

公司价值最大化已经成为公司管理的终极目标,如何实现价值创造便成为公司管理的现实目标。公司战略、公司治理和公司理财对公司价值的三个价值推动要素都有很大的影响,因此,需要融合公司战略、公司治理和公司理财来实现价值创造。     

加入WTO后学校德育工作的若干思考

中国加入世界贸易组织,对国内教育提出新的挑战,特别是学校的德育工作面临新形势、新挑战。因此,与时俱进地加强和改进学校德育工作势在必行。本文就此从德育的内容、教学方式及德育的评价方法等几方面提出作者的建议。     

国有企业人力资源管理的改革策略

进入知识经济时代，人力资源成为企业的第一竞争要素。国有企业应该通过建立现代企业制度、科学客观的考核评价机制和有效的组合激励机制，制定和推进职业生涯计划、科学的选人用人制度，塑造良好的企业文化氛围等六个方面改革现有的人力资源管理模式。     

A screening system for tardive dyskinesia: development and implementation.

1. Most diagnosed cases of tardive dyskinesia (TD) are mildly inconvenient to the patient, but some can be severe or life-threatening. The primary goal of intervention should be early identification of abnormal movements related to TD and the prescribing of an appropriate medication regimen. 2. Unless specific training occurs and a specific monitoring system is in place, TD movements may be missed. However, not all movements are necessarily related to TD. 3. Although screening and monitoring are valuable, nothing is more important than prevention. New medications must be developed that do not carry the risk of TD, and other approaches to treat TD must be developed.     

影响两系籼粳杂交水稻籽粒增重的因素分析

以19个两系籼梗杂交水稻组合为试验材料,应用通径分析法从形态学和生理学的角度分析了影响籼梗杂交水稻籽粒增重的因素。结果表明稻穗上、中、下部籽粒表现强、中、弱势粒灌浆生长特点。单株颖花数目与总干物重的相对比例、收获指数对稻穗不同粒位的籽粒增重产生较大的直接效应。单株总干物重对不同粒位千粒重的影响产生较大的间接效应。单株枝梗总干重对中、上部籽粒增重产生较大的直接效应,但对下部籽粒增重产生较大的直接负效应。此外,中、上部一次枝梗干重与其着生的颖花数目的相对比例,下部一次枝梗干重相应对其籽粒增重产生较大的直接效应。对提高两系籼梗杂交水稻籽粒增重进行了讨论。     

The analysis of incomplete data using stochastic covariates

In the development of many diseases there are often associated random variables which continuously reflect the progress of a subject towards the final expression of the disease (failure). At any given time these processes, which we call stochastic covariates, may provide information about the current hazard and the remaining time to failure. Likewise, in situations when the specific times of key prior events are not known, such as the time of onset of an occult tumour or the time of infection with HIV-1, it may be possible to identify a stochastic covariate which reveals, indirectly, when the event of interest occurred. The analysis of carcinogenicity trials which involve occult tumours is usually based on the time of death or sacrifice and an indicator of tumour presence for each animal in the experiment. However, the size of an occult tumour observed at the endpoint represents data concerning tumour development which may convey additional information concerning both the tumour incidence rate and the rate of death to which tumour-bearing animals are subject. We develop a stochastic model for tumour growth and suggest different ways in which the effect of this growth on the hazard of failure might be modelled. Using a combined model for tumour growth and additive competing risks of death, we show that if this tumour size information is used, assumptions concerning tumour lethality, the context of observation or multiple sacrifice times are no longer necessary in order to estimate the tumour incidence rate. Parametric estimation based on the method of maximum likelihood is outlined and is applied to simulated data from the combined model. The results of this limited study confirm that use of the stochastic covariate tumour size results in more precise estimation of the incidence rate for occult tumours.