TY - GEN
T1 - Actionable insights through association mining of exchange rates
T2 - 2011 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2011
AU - Arabaci, Mehmet
AU - Aktuǧ, Armaǧan
AU - Ertek, Gürdal
PY - 2011
Y1 - 2011
N2 - Association mining is the methodology within data mining that researches associations among the elements of a given set, based on how they appear together in multiple subsets of that set. Extensive literature exists on the development of efficient algorithms for association mining computations, and the fundamental motivation for this literature is that association mining reveals actionable insights and enables better policies. This motivation is proven valid for domains such as retailing, healthcare and software engineering, where elements of the analyzed set are physical or virtual items that appear in transactions. However, the literature does not prove this motivation for databases where items are "derived items", rather than actual items. This study investigates the association patterns in changes of exchange rates of US Dollar, Euro and Gold in the Turkish economy, by representing the percentage changes as "derived items" that appear in "derived market baskets", the day on which the observations are made. The study is one of the few in literature that applies such a mapping and applies association mining in exchange rate analysis, and the first one that considers the Turkish case. Actionable insights, along with their policy implications, demonstrate the usability of the developed analysis approach.
AB - Association mining is the methodology within data mining that researches associations among the elements of a given set, based on how they appear together in multiple subsets of that set. Extensive literature exists on the development of efficient algorithms for association mining computations, and the fundamental motivation for this literature is that association mining reveals actionable insights and enables better policies. This motivation is proven valid for domains such as retailing, healthcare and software engineering, where elements of the analyzed set are physical or virtual items that appear in transactions. However, the literature does not prove this motivation for databases where items are "derived items", rather than actual items. This study investigates the association patterns in changes of exchange rates of US Dollar, Euro and Gold in the Turkish economy, by representing the percentage changes as "derived items" that appear in "derived market baskets", the day on which the observations are made. The study is one of the few in literature that applies such a mapping and applies association mining in exchange rate analysis, and the first one that considers the Turkish case. Actionable insights, along with their policy implications, demonstrate the usability of the developed analysis approach.
KW - association mining
KW - case study
KW - exchange rates
KW - finance
KW - investment science
KW - portfolio management
UR - http://www.scopus.com/inward/record.url?scp=79961200471&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79961200471&partnerID=8YFLogxK
U2 - 10.1109/INISTA.2011.5946082
DO - 10.1109/INISTA.2011.5946082
M3 - Conference contribution
AN - SCOPUS:79961200471
SN - 9781612849195
T3 - INISTA 2011 - 2011 International Symposium on INnovations in Intelligent SysTems and Applications
SP - 101
EP - 106
BT - INISTA 2011 - 2011 International Symposium on INnovations in Intelligent SysTems and Applications
Y2 - 15 June 2011 through 18 June 2011
ER -