Stock price dynamics before crashes : a complex network study on the U.S. stock market

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dc.contributor.authorRen, Jiajia
dc.contributor.authorUniversity of Lethbridge. Faculty of Management
dc.contributor.supervisorYalamova, Rossitsa
dc.date.accessioned2016-01-07T20:56:05Z
dc.date.available2016-01-07T20:56:05Z
dc.date.issued2015
dc.degree.levelMastersen_US
dc.description.abstractHistorically, stock market crashes have caused trillions of dollars in losses and have dramatically destroyed investors’ confidence in the stock market. Independent empirical studies have converged to prove the synchronization phenomenon as the trigger of stock market crashes (Tse, Liu, & Lau, 2010). As well, the Phase Transition Model explains the building-up mechanism and the critical point existing in stock market crash (Yalamova & McKelvey, 2011). In this study, we propose to add more empirical evidence to the current studies and provide an indicator to possibly predict the stock market crashes. We apply the Potential-based Hierarchical Agglomerative (PHA) Method, the Backbone Extraction Method, and the Dot Matrix Plot to extract and display the changing clusters’ structure dynamics from the market equilibrium state to a bubble building-up state by applying the Standard & Poor 500 (S&P 500) index constituents’ daily price correlation matrix.en_US
dc.embargoNoen_US
dc.identifier.urihttps://hdl.handle.net/10133/3859
dc.language.isoen_CAen_US
dc.proquest.subject0508en_US
dc.proquestyesYesen_US
dc.publisherLethbridge, Alta. : University of Lethbridge, Faculty of Management.
dc.publisher.facultyManagementen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Management)
dc.subjectnetwork methods
dc.subjectnetwork theory
dc.subjectstock market crashes
dc.subjectsynchronization phenomenon
dc.subjecttriggers
dc.titleStock price dynamics before crashes : a complex network study on the U.S. stock marketen_US
dc.typeThesisen_US
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