MODELLING TRADE DURATIONS WITH THE BIRNBAUM-SAUNDERS AUTOREGRESSIVE MODEL

dc.contributor.advisor	Balakrishnan, Narayanaswamy	en_US
dc.contributor.author	Mayorov, Kirill	en_US
dc.contributor.department	Mathematics and Statistics	en_US
dc.date.accessioned	2014-06-18T16:53:34Z
dc.date.available	2014-06-18T16:53:34Z
dc.date.created	2011-08-30	en_US
dc.date.issued	2011-10	en_US
dc.description.abstract	<p>In this thesis we study the Birnbaum-Saunders autoregressive conditional du- ration (BS-ACD) model. As opposed to the standard ACD model, formulated in terms of the conditional mean duration, the BS-ACD model specifies the time-varying model dynamics in terms of the conditional median duration. By means of Monte Carlo simulations, we examine the asymptotic behaviour of the maximum likelihood estimators. We then present a study of numerical efficacy of some optimization algorithms in relation to the BS-ACD model. On a practical side, we fit the BS-ACD model to samples for six securities listed on the New York Stock Exchange.</p>	en_US
dc.description.degree	Master of Science (MSc)	en_US
dc.identifier.other	opendissertations/6088	en_US
dc.identifier.other	7114	en_US
dc.identifier.other	2204381	en_US
dc.identifier.uri	http://hdl.handle.net/11375/11092
dc.subject	high-frequency data	en_US
dc.subject	ACD model	en_US
dc.subject	Birnbaum-Saunders distribution	en_US
dc.subject	Statistics and Probability	en_US
dc.subject	Statistics and Probability	en_US
dc.title	MODELLING TRADE DURATIONS WITH THE BIRNBAUM-SAUNDERS AUTOREGRESSIVE MODEL	en_US
dc.type	thesis	en_US

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