Prediction of Istanbul Securities Exchange composite index

buir.advisorMuradoğlu, Gülnur
dc.contributor.authorTimur, Murat
dc.date.accessioned2016-01-08T20:11:07Z
dc.date.available2016-01-08T20:11:07Z
dc.date.issued1993
dc.descriptionAnkara : The Department of Management and the Graduate School of Business Administration of Bilkent Univ., 1993.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 1993.en_US
dc.descriptionIncludes bibliographical references leaves 63-66.en_US
dc.description.abstractThis study presents a software developed by using Nested Generalized Exemplars, for predicting Istanbul Securities Exchange Composite Index. Information reflected in the past values of frequently used monetary variables are used to predict stock returns. Daily returns of the composite index are predicted by using: Central Bank effective selling price of US Dollar and Deutsche Mark, Istanbul Tahtakale closing selling price of Turkish Republic gold coin and one ounce of gold, Commercial Banks (İş Bank, Akbank, Yapı Kredi Bank, and Ziraat Bank) 3-month average deposit rate and 3-month Government bond interest rates. Data prior to the dates on which the predictions are made are used to learn the forecasting power of variables on composite index and to generate the appropriate rules. The results reveal that the information reflected in the past prices of the variables have significant effects on the ISE composite index.en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T20:11:07Z (GMT). No. of bitstreams: 1 1.pdf: 78510 bytes, checksum: d85492f20c2362aa2bcf4aad49380397 (MD5)en
dc.description.statementofresponsibilityTimur, Muraten_US
dc.format.extentviii, 66 leavesen_US
dc.identifier.itemidBILKUTUPB022919
dc.identifier.urihttp://hdl.handle.net/11693/17531
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectIstanbul Securities Exchange (ISE)en_US
dc.subjectNested Generalized Exemplars (NGE)en_US
dc.subject.lccHG5706.5.I88 T56 1993en_US
dc.subject.lcshStock exchanges--Turkey.en_US
dc.titlePrediction of Istanbul Securities Exchange composite indexen_US
dc.typeThesisen_US
thesis.degree.disciplineBusiness Administration
thesis.degree.grantorBilkent University
thesis.degree.levelMaster's
thesis.degree.nameMBA (Master of Business Administration)

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