Quantifying stock return distributions in financial markets
dc.contributor.author | Botta, F | |
dc.contributor.author | Moat, HS | |
dc.contributor.author | Stanley, HE | |
dc.contributor.author | Preis, T | |
dc.contributor.author | Chen, Y | |
dc.date.accessioned | 2020-07-23T09:14:13Z | |
dc.date.issued | 2015-09-01 | |
dc.description.abstract | Being able to quantify the probability of large price changes in stock markets is of crucial importance in understanding financial crises that affect the lives of people worldwide. Large changes in stock market prices can arise abruptly, within a matter of minutes, or develop across much longer time scales. Here, we analyze a dataset comprising the stocks forming the Dow Jones Industrial Average at a second by second resolution in the period from January 2008 to July 2010 in order to quantify the distribution of changes in market prices at a range of time scales. We find that the tails of the distributions of logarithmic price changes, or returns, exhibit power law decays for time scales ranging from 300 seconds to 3600 seconds. For larger time scales, we find that the distributions tails exhibit exponential decay. Our findings may inform the development of models of market behavior across varying time scales. | en_GB |
dc.description.sponsorship | EPSRC | en_GB |
dc.description.sponsorship | IARPA | en_GB |
dc.description.sponsorship | NSF | en_GB |
dc.identifier.citation | Vol. 10 (9): e0135600. | en_GB |
dc.identifier.doi | 10.1371/journal.pone.0135600 | |
dc.identifier.grantnumber | EP/E501311/1 | en_GB |
dc.identifier.grantnumber | EP/K039830/1 | en_GB |
dc.identifier.grantnumber | 1411158 | en_GB |
dc.identifier.grantnumber | 1452061 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/122096 | |
dc.language.iso | en | en_GB |
dc.publisher | Public Library of Science | en_GB |
dc.rights | Copyright: © 2015 Botta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_GB |
dc.subject | Stock markets | en_GB |
dc.subject | Probability distribution | en_GB |
dc.subject | Statistical distributions | en_GB |
dc.subject | Financial markets | en_GB |
dc.subject | Finance | en_GB |
dc.subject | Computational sociology | en_GB |
dc.subject | Normal distribution | en_GB |
dc.subject | Visual inspection | en_GB |
dc.title | Quantifying stock return distributions in financial markets | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-07-23T09:14:13Z | |
dc.description | This is the final version. Available from Public Library of Science via the DOI in this record. | en_GB |
dc.description | Data Availability: Relevant data were obtained by the authors from the third party Wharton Research Data Services. Raw data sets from the Trades and Quotes database are available from the following URL: https://wrds-web.wharton.upenn.edu/wrds/. | en_GB |
dc.identifier.eissn | 1932-6203 | |
dc.identifier.journal | PLoS ONE | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2015-07-23 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2015-07-23 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-07-23T09:11:36Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2020-07-23T09:14:18Z | |
refterms.panel | B | en_GB |
Files in this item
This item appears in the following Collection(s)
Except where otherwise noted, this item's licence is described as Copyright: © 2015 Botta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.