This paper considers measures of uncertainty used in economic estimation. Our first contribution is to address the theoretical relationship between cross-section and time series measures, highlighting the reasons why these might diverge. In a subsequent empirical section, we compare measures of...

This paper introduces a nonparametric estimator for tail dependence in the constant conditional correlation GARCH framework, in contrast to existing estimators that impose the iid assumption. So long as stationarity is satisfied, the difference between the distribution of the tail dependence...

Markov switching GARCH models have been developed in order to address the statistical regularity observed in financial time series such as strong persistence of conditional variance. However, Maximum Likelihood Estimation faces a implementation problem since the conditional variance depends on...

Using the tick-by-tick yen/dollar exchange rate, this paper examines the effect of Japanese banking crisis in late 1997 on the foreign exchange market. By high-frequency methodology, GARCH estimation and variance-ratio tests, the existence of a structural break in the foreign exchange market at...

When a price limit regime exists for all of the stocks involved in an index, the index return is an aggregate of limited variables and thereby it is restricted to the same limits. We argue that neither a censored nor a truncated distribution model is appropriate for the aggregate return. The...

The properties and applications of the normal log-normal (NLN) mixture are considered. The moment of the NLN mixture is shown to be finite for any positive order. The expectations of exponential functions of a NLN mixture variable are also investigated. The kurtosis and skewness of the NLN...

In this paper we consider different periodic extensions of regression models with autoregressive fractionally integrated moving average disturbances for the analysis of daily spot prices of electricity. We show that day-of-the-week periodicity and long memory are important determinants for the...

Markov switching GARCH models have been developed in order to address the statistical regularity observed in financial time series such as strong persistence of conditional variance. However, Maximum Likelihood Estimation faces a implementation problem since the conditional variance depends on...