the complex system containing n elements, each having three dependent components are described. the reliability and mean residual life of such systems with intact components at time t are investigated using a trivariate binomial model. considering a farlie-gumbel-morgenstern family, some graphical representations are given.

A new variant of the ARCH class of models for forecasting conditional variance, to be called the Generalized AutoRegressive Conditional Heteroskedasticity Parkinson Range (GARCH-PARK-R) Model, is proposed. The GARCH-PARK-R model, utilizing the extreme values, is a good alternative to the Realized Volatility that requires a large amount of intra-daily data, which remain relatively costly and are...

This paper studies volatility forecasting in the financial stock market. In general, stock market volatility is time-varying and exhibits clustering properties. Thus, this paper presents the results of using a fuzzy system method to analyze clustering in generalized autoregressive conditional heteroskedasticity (GARCH) models. It also uses the adaptive method of recursive least-squares (RLS) to...

We conduct empirical analyses to model the volatility of stock market in Malaysia. The GARCH type models (symmetric and asymmetric GARCH) are used to model the volatility of stock market in Malaysia. Their performances are compared based on three statistical error measures tools, i.e. mean squared error, root means squared error and mean absolute percentage error for in sample and out sample an...

We present a framework for generating a trivariate B-spline parametrization of turbine blades from measurement data generated by optical scanners. This new representation replaces the standard patchbased representation of industrial blade designs. In a first step, the blade surface is represented by a smoothly varying family of B-spline curves. In a second step, the blade is parametrized by a t...

There is a compelling need to accurately and efficiently compute option values. Existing literature shows that models based on constant stock volatilities have been widely used in option valuation. However, stock volatilities change constantly in real life situations. The introduction of the Auto Regressive Conditional Heteroskedasticity (ARCH) model and subsequently, the Generalized Auto Regre...

GARCH is one of the most prominent nonlinear time series models, both widely applied and thoroughly studied. Recently, it has been shown that the COGARCH model, which has been introduced a few years ago by Klüppelberg, Lindner and Maller, and Nelson’s diffusion limit are the only functional continuous-time limits of GARCH in distribution. In contrast to Nelson’s diffusion limit, COGARCH reprodu...