This paper investigates conditional variance patterns in daily return series of stock market indices in the G-7 and 6 selected economies of Central and Eastern Europe. For this purpose, various linear and asymmetric GARCH models are employed. The analysis is conducted for Canada,
Motivated by the relationship between trading intensity and volatility and the attractiveness of duration‐based volatility estimators, this paper investigates the ability of price duration to forecast realized volatility of Bitcoin. Using high‐frequency transaction data, trading intensity is measured by price duration and incorporated in the class of heterogeneous autoregressive (HAR) models. Results provide compelling evidence that trading intensity improves the forecasting performance of a highly competitive set of HAR models, commonly used in the literature. HAR extensions that incorporate price duration systematically deliver the lowest forecast errors and generate economically significant gains in volatility targeting exercise over multiple horizons. However, results show no evidence in favor of a unique duration‐augmented model. The predictive ability of price duration is supported by a number of robustness checks, including alternative estimation windows, bull and bear market states, and alternative thresholds that define price events.
This paper is devoted to investigating the matching process for Tunisia using desaggregated data by assuming that the rising of the unemployment rate result from regional disparities which yield variation of matching efficiencies across regions. Since most econometric aspects of spatial heterogeneity can be handled by means of the standard panel data methods, we focus our discussion on the new technique: Panel Smooth Transition Regression models (PSTR). The distinction is that we can compute regional specific sensibilities for 23 regions over the period . Given this objective, we consider three structural factors that allow explaining the regional imbalances. Contrary to the previous econometric techniques of the matching theory, estimates of the coefficients depend, of three transition variables. The results show that women insertion, the qualification share and population density significantly contribute to explain the asymmetry of the matching process across regions. Our main conclusion is that the hiring in Tunisia is driven essentially by the stock of vacancies about is the region. The willingness of job seekers, obviously, remains low, although it is different between regions and seems relatively important in urban zones.
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