The strategic technical vision of this thesis proposal is to seek to systematically trailblaze a novel vol-umetric modeling framework/methdology to represent 3D solids. The rapid advances in 3D scanning and acquisition techniques have given rise to the explosive increase of volumetric digital models in recent years. The strong need to explore more efficient and robust 3D modeling techniques has...

this paper investigates the nature of volatility characteristics of stock returns in the bangladesh stock markets employing daily all share price index return data of dhaka stock exchange (dse) and chittagong stock exchange (cse) from 02 january 1993 to 27 january 2013 and 01 january 2004 to 20 august 2015 respectively.  furthermore, the study explores the adequate volatility model for the stoc...

Empirical research on European stock markets has shown that they behave differently according to the performance of the leading financial market identified as the US market. A positive sign is viewed as good news in the international financial markets, a negative sign means, conversely, bad news. As a result, we assume that European stock market returns are affected by endogenous and exogenous ...

In this paper the class of BL-GARCH (Bilinear General AutoregRessive Conditional Heteroskedasticity) models is introduced. The proposed model is a modification to the BL-GARCH model proposed by Storti and Vitale (2003). Stationary conditions and autocorrelation structure for special cases of these new models are derived. Maximum likelihood estimation of the model is also considered. Some simula...

This paper develops a smooth transition GARCH model with an asymmetric transition function, which allows for an asymmetric response of volatility to the size and sign of shocks, and an asymmetric transition dynamics for positive and negative shocks. We apply our model to the empirical financial data: the NASDAQ index and the individual stock IBM daily returns. The empirical evidence shows that ...

We analyze the time-dependence of exchange rate correlations using a new multivariate GARCH model. This model consists of two parts. First, we transform the exchange rate changes into their principal components and specify univariate GARCH models for all components. Second, we use the inverse of the principal components construction to transform the conditional component moments back into those...

We consider the estimation of a random level shift model for which the series of interest is the sum of a short memory process and a jump or level shift component. For the latter component, we specify the commonly used simple mixture model such that the component is the cumulative sum of a process which is 0 with some probability (1−α) and is a random variable with probability α. Our estimation...

The paper estimate 1-day Value at Risk (VaR) taking into consideration the financial integration of Indian capital market (BSE-SENSEX and NSE-NIFTY) with other global indicators and its own volatility using daily returns covering the period January 2003 to December 2009. The paper specifies a generalized autoregressive conditional heteroscedasticity (GARCH) framework to model the phenomena of v...

Modelling and detecting structural changes in GARCH processes have attracted a great amount of attention in econometrics over the past few years. We generalize Dahlhaus and Rao (2006)’s time varying ARCH processes to time varying GARCH processes and show the consistency of the weighted quasi maximum likelihood estimator. A class of generalized likelihood ratio tests are proposed to check smooth...

We propose a new stochastic frontier model with sample selection, in which the dependencies between selection mechanism, inefficiency term and two-sided error production equation are modeled by trivariate Gaussian copula. This is compared to Greene's original an alternative based on two bivariate copulas. The relative performances of three models analyzed using simulated data cross-sectional ab...