VTechWorks staff will be away for the Thanksgiving holiday beginning at noon on Wednesday, November 27, through Friday, November 29. We will resume normal operations on Monday, December 2. Thank you for your patience.
 

Industry Based Fundamental Analysis: Using Neural Networks and a Dual-Layered Genetic Algorithm Approach

Simple item page
dc.contributor.authorStivason, Charles T.en
dc.contributor.committeechairSen, Tarun K.en
dc.contributor.committeememberSumichrast, Robert T.en
dc.contributor.committeememberMaher, John J.en
dc.contributor.committeememberBrown, Robert M.en
dc.contributor.committeememberEasterwood, Cintia M.en
dc.contributor.departmentAccounting and Information Systemsen
dc.date.accessioned2014-03-14T21:23:24Zen
dc.date.adate1999-01-06en
dc.date.available2014-03-14T21:23:24Zen
dc.date.issued1998-11-16en
dc.date.rdate2000-01-06en
dc.date.sdate1998-12-14en
dc.description.abstractThis research tests the ability of artificial learning methodologies to map market returns better than logistic regression. The learning methodologies used are neural networks and dual-layered genetic algorithms. These methodologies are used to develop a trading strategy to generate excess returns. The excess returns are compared to test the trading strategy's effectiveness. Market-adjusted and size-adjusted excess returns are calculated. Using a trading strategy based approach the logistic regression models generated greater returns than the neural network and dual-layered genetic algorithm models. It appears that the noise in the financial markets prevents the artificial learning methodologies from properly mapping the market returns. The results confirm the findings that fundamental analysis can be used to generate excess returns.en
dc.description.degreePh. D.en
dc.identifier.otheretd-121498-112557en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-121498-112557/en
dc.identifier.urihttp://hdl.handle.net/10919/40422en
dc.publisherVirginia Techen
dc.relation.haspart03vitae.pdfen
dc.relation.haspart01body.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectneural networksen
dc.subjectgenetic algorithmsen
dc.subjectfundamental analysisen
dc.titleIndustry Based Fundamental Analysis: Using Neural Networks and a Dual-Layered Genetic Algorithm Approachen
dc.typeDissertationen
thesis.degree.disciplineAccounting and Information Systemsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

Files

Original bundle
Now showing 1 - 2 of 2
Thumbnail Image
Name:
01body.pdf
Size:
251.85 KB
Format:
Adobe Portable Document Format
Download
Thumbnail Image
Name:
03vitae.pdf
Size:
7.64 KB
Format:
Adobe Portable Document Format
Download

Collections

Doctoral Dissertations