BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//RLASKEY//CALENDEROUS//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260915T165016Z
LAST-MODIFIED:20151106T143527Z
DTSTART:20151109T163000Z
DTEND:20151109T173000Z
UID:event1510@bu.edu
URL:http://physics.bu.edu/internal/events/show/1510
SUMMARY:Clustering and Dynamics of Foreign Exchange Markets
DESCRIPTION:Featuring Alexander Becker\n\nPart of the Preliminary Oral Exam
	.\n\nExamining Committee:\n\nH.E. Stanley\nIrena Vodenska\nOphelia Tsui\nKe
	vin Black\n\nAbstract:\nFinancial markets are highly complex and dynamic sy
	stems. The challenges posed by non-linearity and non-stationarity have attr
	acted interdisciplinary approaches to investigate new perspectives on this 
	complexity. \nWe study 12 of the most actively traded currencies from 2005 
	to 2014 with intraday resolution of 10 minutes\, yielding more than 300\,00
	0 observation points. Currencies are quoted in pairs\, such as USDEUR and U
	SDAUD\, which gives rise to a triangular structure in the foreign exchange 
	market. This calls for devising a novel way to study individual currencies 
	and their characteristics.\nWe introduce the symbolic performance to descri
	be the roles currencies play within the global market\, removing their pair
	wise dependence. This approach allows us to classify currencies as individu
	al entities. In order to study the dynamics of currency roles\, we employ m
	achine learning algorithms\, such as k-means to find clusters of characteri
	stic behaviors. Interestingly\, we find that the euro shows features of a r
	eference currency more so than the US dollar\, which is evidenced by their 
	respective distributions of the symbolic performance across the entire time
	 scale. We also demonstrate how our approach allows us to uncover currency 
	movements hidden in the pairwise dependencies.\n\n![Becker](/resources/even
	t-image/1510/d981a08_small)
LOCATION:PRB 261\, 3 Cummington Mall\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
END:VCALENDAR