Information flow around stock market collapse

Terence Bossomaier, Lionel Barnett, Adam Steen, Michael Harre, Steven D'Alessandro, Roderick Duncan

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

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
Original languageEnglish
Pages (from-to)45-58
Number of pages14
JournalAccounting and Finance
Volume58
Issue number51
Early online date05 Jul 2018
DOIs
Publication statusPublished - Nov 2018

Fingerprint

Dive into the research topics of 'Information flow around stock market collapse'. Together they form a unique fingerprint.

Cite this