Recurrence Network Analysis of Financial Data

Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/997

Full metadata record

DC Field	Value	Language
dc.contributor.advisor	AMBIKA, G.	en_US
dc.contributor.author	AMANAGI, AMEY	en_US
dc.date.accessioned	2018-05-16T10:41:27Z
dc.date.available	2018-05-16T10:41:27Z
dc.date.issued	2018-04	en_US
dc.identifier.uri	http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/997	-
dc.description.abstract	The project applies techniques of statistics and nonlinear dynamics on financial data to study underlying dynamics in financial markets. We have used framework suggested by George Soros to interpret our results. We have found out that technique of recurrence network analysis gives some early warning signals of 2008 financial crash, although further analysis is needed to make forecasts with reasonable confidence.	en_US
dc.language.iso	en	en_US
dc.subject	2018
dc.subject	Physics	en_US
dc.subject	Financial Data	en_US
dc.subject	Nonlilnear Dynamics	en_US
dc.title	Recurrence Network Analysis of Financial Data	en_US
dc.type	Thesis	en_US
dc.type.degree	BS-MS	en_US
dc.contributor.department	Dept. of Physics	en_US
dc.contributor.registration	20131101	en_US
Appears in Collections:	MS THESES

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Recurrence Network Analysis of Financial Data.pdf	Fifth year thesis on recurrence network analysis of financial data	16.45 MB	Adobe PDF	View/Open