Recurrence entropy and financial crashes

DOI

10.2991/mdsmes-19.2019.73How to use a DOI?

Keywords

Recurrence plot, recurrence quantification analysis, recurrence entropy

Abstract

Entropy is one of the most frequently and effectively used measure of the complexity of systems of various nature. And if the Shannon's canonical entropy is more a measure of the randomness of the system, then the approximate, sample, permutation and other new type entropy that have appeared recently, exploiting the Shannon entropy form have allowed us to quantify the complexity of the systems in question using fast and efficient algorithms. For the first time, a new type of recurrence entropy is used to analyze the dynamics of financial time series under crashes conditions. It is shown that recurrent entropy can be used as the indicator-predictor of financial crashes.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Vladimir Soloviev
AU  - Olexandr Serdiuk
AU  - Serhiy Semerikov
AU  - Oksana Kohut-Ferens
PY  - 2019/10
DA  - 2019/10
TI  - Recurrence entropy and financial crashes
BT  - Proceedings of the 2019 7th International Conference on Modeling, Development and Strategic Management of Economic System (MDSMES 2019)
PB  - Atlantis Press
SP  - 385
EP  - 388
SN  - 2352-5428
UR  - https://doi.org/10.2991/mdsmes-19.2019.73
DO  - 10.2991/mdsmes-19.2019.73
ID  - Soloviev2019/10
ER  -