Empirically, we show that the proportion of stocks exhibiting conditional heteroscedastic residuals, is high. We suggested to use the market model with GARCH(1,1) residuals in order to describe daily stock returns and derived a test statistics for the null hypothesis of no abnormal returns,...

We present a multivariate, non-parametric technique for constructing reliable daily VaR predictions for individual assets belonging to a common equity market segment, which takes also into account the possible dependence structure between the assets and is still computationally feasible in large...

This paper employs an augmented version of the UECCC GARCH specificationproposed in Conrad and Karanasos (2010) which allows for lagged in-mean effects,level effects as well as asymmetries in the conditional variances. In this unifiedframework we examine the twelve potential intertemporal...

This paper employs the unrestricted extended constant conditional correlationGARCH specification proposed in Conrad and Karanasos (2008) to examine theintertemporal relationship between the uncertainties of in°ation and output growthin the US. We find that inflation uncertainty effects output...

We consider time series models in which the conditional mean of the response variable given thepast depends on latent covariates. We assume that the covariates can be estimated consistentlyand use an iterative nonparametric kernel smoothing procedure for estimating the conditional meanfunction....

Tse (1998) proposes a model which combines the fractionally integrated GARCH formulationof Baillie, Bollerslev and Mikkelsen (1996) with the asymmetric power ARCH specification of Ding,Granger and Engle (1993). This paper analyzes the applicability of a multivariate constant...

It is well-known in empirical finance that virtually all asset returns, whether monthly,daily, or intraday, are heavy-tailed and, particularly for stock returns, are mildly but oftensignificantly negatively skewed. However, the tail indices, or maximally existing moments ofthe returns, can...

We examine the effects of the Czech National Bank communication, macroeconomic newsand interest rate differential on exchange rate volatility using generalized autoregressiveconditional heteroscedasticity model. Our results suggest that central bank communicationhas a calming effect on exchange...

Most time series models used in econometrics and empirical finance are estimated withmaximum likelihood methods, in particular when interest centers on density and Value{at{Risk (VaR) prediction. The standard maximum likelihood principle implicitly placesequal weight on each of the observations...

A small strand of recent literature is occupied with identifying simultaneity in multipleequation systems through autoregressive conditional heteroscedasticity. Since thisapproach assumes that the structural innovations are uncorrelated, any contemporaneousconnection of the endogenous variables...