This paper extends a stochastic conditional duration (SCD) model for financial transaction data to allow for correlation between error processes or innovations of observed duration process and latent log duration process with the aim of improving the statistical fit of the model. Suitable...

Traditionally stationarity refers to shift invariance of the distribution of a stochastic process. In this paper, we rediscover stationarity as a path property instead of a distributional property. More precisely, we characterize a set of paths denoted as A, which corresponds to the notion of...

This paper starts from examining the performance of equally weighted 1/N stock portfolios over time. During the last four decades these portfolios outperformed the market. The construction of these portfolios implies that their constituent stocks are in general older than those in the market as...

This study investigates the development and sustainability of a firm’s IT capability reputation from an IT executive’s standpoint. Building on institutional theory, we argue that IT executives will try to achieve external legitimacy - i.e., project an image of superior IT capability to...

In this paper we provide several applications of Gram-Charlier expansions in financial derivative pricing. We first give an exposition on how to calculate swaption prices under a two-factor Cox-Ingersoll-Ross (CIR2) model. Then we apply this method to an extended version of the model (CIR2 ). We...

In this paper, we explore the use of Independent Component Analysis (ICA) from the field of signal processing to model and estimate the dynamics of multivariate volatilities of financial asset returns in the GARCH framework. The resulting ICA-GARCH approach is shown to provide a computationally...

This paper provides theoretical properties and Monte-Carlo studies of a stochastic conditional duration model with mixture-of-normal error distributions an effcient estimation approach via a continuous empirical characteristic function. The empirical version of this paper is studied in Xu,...

This paper provides a selected review of the recent developments and applications of mixture-of-normal (MN) distribution models in financial econometrics. One noted feature of the MN model is its flexibility in accommodating various shapes of continuous distributions, and its ability in...

This paper constructs Value at Risk (VaR) measures from a stochastic volatility model with a discrete bivariate mixture-of-normal error distribution - henceforth SV-MN. This volatility-gnerating model is able to accommodate many of the salient features of financial asset returns, such as...