Innovation processes in logically constrained time series

Christoph Möller; Svetlozar T. Rachev; Young S. Kim; Frank J. Fabozzi

doi:10.1007/978-3-7908-2628-9_12

Innovation processes in logically constrained time series

Christoph Möller, Svetlozar T. Rachev, Young S. Kim, Frank J. Fabozzi

Mathematics and Statistics

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Scopus citations

Abstract

Capturing the relevant aspects of phenomena in an econometric model is a fine art. When it comes to the innovation process a trade of between a suitable process and its mathematical implications has to be found. In many phenomena the likelihood of extreme events plays a crucial role. At the same time, classical extreme value theory is based on assumptions that cannot logically be drawn for the phenomenon in question. In this paper, we exemplify the fitness of tempered stable laws to capture both the probability of extreme events, and the relevant boundary conditions in a back-coupled system, the German balancing energy demand.

Original language	English
Title of host publication	Advances in Directional and Linear Statistics
Subtitle of host publication	A Festschrift for Sreenivasa Rao Jammalamadaka
Publisher	Physica-Verlag
Pages	173-188
Number of pages	16
ISBN (Print)	9783790826272
DOIs	https://doi.org/10.1007/978-3-7908-2628-9_12
State	Published - 2011

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Innovation processes in logically constrained time series

Abstract

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