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.     

A note on interval‐censored lifetime data and the constant‐sum condition of oiler,gómez & calle (2004)

Oiler, Gomez & Calle (2004) give a constant sum condition for processes that generate interval‐censored lifetime data. They show that in models satisfying this condition, it is possible to estimate non‐parametrically the lifetime distribution based on a well‐known simplified likelihood. The author shows that this constant‐sum condition is equivalent to the existence of an observation process that is independent of lifetimes and which gives the same probability distribution for the observed data as the underlying true process.     

A general inverse sampling scheme and its application to adaptive cluster sampling

Not having a variance estimator is a seriously weak point of a sampling design from a practical perspective. This paper provides unbiased variance estimators for several sampling designs based on inverse sampling, both with and without an adaptive component. It proposes a new design, which is called the general inverse sampling design, that avoids sampling an infeasibly large number of units. The paper provide estimators for this design as well as its adaptive modification. A simple artificial example is used to demonstrate the computations. The adaptive and non‐adaptive designs are compared using simulations based on real data sets. The results indicate that, for appropriate populations, the adaptive version can have a substantial variance reduction compared with the non‐adaptive version. Also, adaptive general inverse sampling with a limitation on the initial sample size has a greater variance reduction than without the limitation.     

The Exclusion of Disabled People from Positions of Power in British Voluntary Organisations

Disabled people are excluded in various ways from a wide range of social privileges, activities and institutions. Voluntary and charitable organisations promote themselves as champions of disabled people in their struggle for access to the ordinary choices and opportunities of everyday life. This paper reports the findings of an empirical study which demonstrate that in voluntary agencies governed by able-bodied people, disabled people are excluded from positions of power and influence, and they experience the same sorts of barriers and constraints as those with which they are confronted in the wider world. Furthermore, the development of agencies governed by disabled people themselves is constrained by their lack of access to money, staff and other resources.     

Female Victim Perceptions of the Causes of Male Spouse Abuse*

Victims of spouse abuse were interviewed concerning their views of why their husbands were abusive. It was hypothesized that by concentrating on one specific characteristic of this kind previously undocumented patterns of response would be elicited from the subjects. It was concluded that the women's reasons for the violence perpetrated by their spouses serve as justification for the abusers’actions and legitimize maintenance of the relationship.     

Tax-based research and data on non-profit organisations

Tax-exempt, non-profit organisations represent a significant and growing sector within the US economy. Between 1975 and 1990, assets of tax-exempt organisations increased in real terms by over 150 per cent while the revenue increased by over 227 per cent. This compares to a growth in real GDP of 52 per cent over the same period. A variety of tax policy issues on tax-exempt organisations and the non-profit sector can be addressed using several sources of data collected by the IRS from federal information and tax returns of exempt organisations. The Statistics of Income (SOI) Division, using sample data, conducts studies of many of the different components of the tax-exempt sector, including non-profit charitable organisations, organisations exempt under sections 501(c)(4)-(c)(9), private foundations and 4947(a) charitable trusts, and the unrelated business income of tax-exempt organisations. Income statement, balance sheet and other financial data, as well as a great amount of non-financial information, are collected in these SOI studies. The primary purposes of this article are: first, to document the role of the non-profit sector in the US economy and the evolving growth and change within the sector from the mid-1970s through to the present; and, second, to describe the ongoing SOI studies of tax-exempt organisations, the products and services available through SOI, and the future statistical plans at SOI for data collection and analysis of tax-exempt organisations and the non-profit sector.