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We propose a new and flexible non-parametric framework for estimating the jump tails of Itô semimartingale processes. The approach is based on a relatively simple-to-implement set of estimating equations associated with the compensator for the jump measure, or its "intensity", that only...
Persistent link: https://www.econbiz.de/10013133664
Consider a random sample from a continuous multivariate distribution function F with copula C. In order to test the null hypothesis that C belongs to a certain parametric family, we construct an under H0 asymptotically distribution-free process that serves as a tests generator. The process is a...
Persistent link: https://www.econbiz.de/10012941154
Let (X1, Y1), … , (Xn, Yn) be an i.i.d. sample from a bivariate distribution function that lies in the max-domain of attraction of an extreme value distribution. The asymptotic joint distribution of the standardized component-wise maxima max( Xi) and max(Yi) is then characterized by the...
Persistent link: https://www.econbiz.de/10013051730
We propose a new and flexible non-parametric framework for estimating the jump tails of Itô semimartingale processes. The approach is based on a relatively simple-to-implement set of estimating equations associated with the compensator for the jump measure, or its "intensity", that only...
Persistent link: https://www.econbiz.de/10013144212
Persistent link: https://www.econbiz.de/10011974668
estimates and truncated Two Scales Realized Volatility of these estimates, together with its central limit theory and feasible … statistics. As a byproduct, we provide estimation and feasible limit theory of the branching ratio (i.e. the L1-norm of the …-varying baseline, and for the absence of Brownian diffusion in the baseline. Simulation studies corroborate the theory, and document …
Persistent link: https://www.econbiz.de/10013403725
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