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dc.contributor.authorMatteo, Tiziana D.
dc.date.accessioned2017-12-27T11:19:53Z
dc.date.available2017-12-27T11:19:53Z
dc.date.issued2017-11-10
dc.identifier.urihttp://hdl.handle.net/11718/20122
dc.descriptionThe R & P seminar held at Wing 11 Committee Room, IIM Ahmedabad on November 10, 2017 by Prof. Tiziana D. Matteo, King’s College London on Multiscaling in Finance.en_US
dc.description.abstractThe multiscaling behaviour of financial time-series is one of the acknowledged stylized facts in the literature [1]. The source of the measured multifractality in financial markets has been long debated and it has been attributed to mainly two sources: the power law tails and the non linear autocorrelation of the analysed time-series [2,3]. In this talk I will discuss the origin of multiscaling in financial time-series and investigate how to best quantify it [4,5]. In particular I will show results on the application of the Generalized Hurst exponent tool to different financial time series and I will show the powerfulness of such tool to detect changes in markets’ behaviours, to differentiate markets accordingly to their degree of development, to asses risk and to provide a new tool for forecasting. [1] T. Di Matteo, Quantitative Finance 7(1) (2007) 21. [2] J. W Kantelhardt, Stephan A Zschiegner, Eva Koscielny-Bunde, Shlomo Havlin, Armin Bunde, and H Eugene Stanley, Physica A 316 (2002)87-114 [3] Jozef Barunik, Tomaso Aste, T. Di Matteo, Ruipeng Liu, Physica A 391 (2012) 4234–4251. [4] R. J. Buonocore, T. Aste, T. Di Matteo, Chaos, Solitons and Fractals 88 (2016) 38-47. [5] R. J. Buonocore, T. Di Matteo, T. Aste, (2017), Phys.Rev.E, 95 (4) (2017) 042311.en_US
dc.publisherIndian Institute of Management Ahmedabaden_US
dc.subjectFinanceen_US
dc.subjectMultiscalingen_US
dc.subjectfinancial time-seriesen_US
dc.titleMultiscaling in Financeen_US
dc.typeVideoen_US


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