This article introduces a new spatial price analysis methodology based on maximum
likelihood estimation of a mixture distribution model incorporating price, transfer cost, and …

We propose a practical and flexible method to introduce skewness in multivariate symmetric
distributions. Applying this procedure to the multivariate Student density leads to a …

We investigate the predictive performance of various classes of value‐at‐risk (VaR) models
in several dimensions—unfiltered versus filtered VaR models, parametric versus …

In many applications, it has been found that the autoregressive conditional
heteroskedasticity (ARCH) model under the conditional normal or Student'st distributions are …

An EGARCH model in which the conditional distribution is heavy-tailed and skewed is
proposed. The properties of the model, including unconditional moments, autocorrelations …

Some recent specifications for GARCH error processes explicitly assume a conditional
variance that is generated by a mixture of normal components, albeit with some parameter …

Autoregressive Conditional Heteroskedastic (ARCH) processes are used in finance to
model asset price volatility over time. This book introduces both the theory and applications …

This paper takes a new empirical look at the long-standing question of the effect of
exchange rate volatility on international trade flows by studying the case of Taiwan's exports …

Standard asset pricing models based on rational expectations and homogeneity have
problems explaining the complex and volatile nature of financial markets. Recently …

This paper proposes a method for pricing derivatives under the generalized autoregressive
conditional heteroskedasticity (GARCH) assumption for underlying assets in the context of a" …