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Information flow around stock market collapse
Author(s) -
Bossomaier Terry,
Barnett Lionel,
Steen Adam,
Harré Mike,
d'Alessandro Steve,
Duncan Rod
Publication year - 2018
Publication title -
accounting and finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.645
H-Index - 49
eISSN - 1467-629X
pISSN - 0810-5391
DOI - 10.1111/acfi.12390
Subject(s) - econometrics , crash , tipping point (physics) , information flow , stock market , transition (genetics) , stock (firearms) , financial economics , economics , transition point , flow (mathematics) , computer science , physics , geology , mechanics , engineering , chemistry , mechanical engineering , paleontology , linguistics , philosophy , biochemistry , horse , electrical engineering , gene , programming language
Strong correlations among share prices appear during a market transitions. Numerous measures have been proposed to predict crash events, but they all show a trend which peaks at the transition itself. Information flow among share prices peaks before a transition, whereas correlation‐based indices peak at the transition itself. The classic spin model used in physics describes one type of tipping point where there is a peak in information flow located away from the transition point itself and is thus predictive. Information theoretic metrics of this kind have not been applied to prediction in real‐world systems, such as stock markets.