Several methods have been proposed for identifying clusters of extreme values leading to estimators of the extremal … clusters of extremes is relevant for the class of processes commonly used in financial econometrics, such as GARCH processes …

for the limiting distribution of the size of clusters of extremes for GARCH(1,1) processes with t-distributed innovations …

The financial time series are often characterized by similar volatility structures. The selection of series having a … similar behavior could be important for the analysis of the transmission mechanisms of volatility and to forecast the time … agglomerative algorithm in order to detect clusters of homogeneous series. …

In the Cont–Bouchaud model [cond-mat/9712318] of stock markets, percolation clusters act as buying or selling investors … connectivity artificially at or close to the critical value, we propose that clusters shatter and aggregate continuously as the …

volatility. The research also examines the impact of powerful foreign capital markets on the Greek Stock Exchange market, the … seasonality returns (Day-of-the-Week effect) and the volatility structure. Design/methodology/approach - The analysis of data is …-GARCH model demonstrate that the debt crisis and, therefore, its consequences increase the FTSE / ASE 20 index volatility and the …

volatility of a time series. We derive the main properties of the model and apply it to all agricultural commodities in the … volatility process and, according to homoscedasticity tests, outperforms the ARCH(1) and GARCH(1,1) models, some of the most … popular approaches used in the literature to analyze price volatility. Keywords: Agricultural prices, volatility, GARCH models. …