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The Weibull distribution is often used to model the earthquake interevent times distribution (ITD). We propose a link between the earthquake ITD on single faults with the Earth’s crustal shear strength distribution by means of a phenomenological stick–slip model. For single faults or fault...
Persistent link: https://www.econbiz.de/10010595175
In this paper, a statistical analysis of log-return fluctuations of the IPC, the Mexican Stock Market Index is presented. A sample of daily data covering the period from 04/09/2000–04/09/2010 was analyzed, and fitted to different distributions. Tests of the goodness of fit were performed in...
Persistent link: https://www.econbiz.de/10011060025
In this paper we perform a statistical analysis of the high-frequency returns of the Ibex35 Madrid stock exchange index. We find that its probability distribution seems to be stable over different time scales, a stylized fact observed in many different financial time series. However, an in-depth...
Persistent link: https://www.econbiz.de/10011063001
results on univariate and multivariate GARCH type models where our estimator coincides with the QMLE. In the EGARCH(1,1)model …
Persistent link: https://www.econbiz.de/10009147705
Exponential models of Autoregressive Conditional Heteroscedasticity (ARCH) enable richer dynamics (e.g. contrarian or cyclical), provide greater robustness to jumps and outliers, and guarantee the positivity of volatility. The latter is not guaranteed in ordinary ARCH models, in particular when...
Persistent link: https://www.econbiz.de/10011185384
A critique that has been directed towards the log-GARCH model is that its log-volatility specification does not exist in the presence of zero returns. A common ``remedy" is to replace the zeros with a small (in the absolute sense) non-zero value. However, this renders Quasi Maximum Likelihood...
Persistent link: https://www.econbiz.de/10011109685
used by Nelson (1991) for the EGARCH(1,1) model under explicit but non observable conditions. In practice, we propose to …, called Stable QMLE (SQMLE), is strongly consistent when the observations follow an invertible EGARCH(1,1) model. We also give …
Persistent link: https://www.econbiz.de/10011113070
This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares...
Persistent link: https://www.econbiz.de/10012814196
Unanticipated shocks could lead to instability, which is reflected in statistically significant changes in distributions of independent Gaussian random variables. Changes in the conditional moments of stationary variables are predictable. We provide a framework based on a statistic for the...
Persistent link: https://www.econbiz.de/10008533249
12 for sensitivity analysis, our estimation results employing contemporaneous exponential GARCH (EGARCH) methodology of …
Persistent link: https://www.econbiz.de/10008623473