ASYMMETRIC POWER AND FRACTIONALLY INTEGRATED SUPPORT VECTOR AND NEURAL NETWORK GARCH MODELS WITH AN APPLICATION TO FORECASTING FINANCIAL RETURNS IN ISE100 STOCK INDEX

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dc.contributor.authorBildirici, Melike
dc.contributor.authorErsin, Ozgur Omer
dc.date.accessioned2024-03-13T10:33:39Z
dc.date.available2024-03-13T10:33:39Z
dc.date.issued2014
dc.departmentİstanbul Beykent Üniversitesien_US
dc.description.abstractThe study aims to augment commonly applied volatility models with support vector machines and neural networks. Further, fractional integration and asymmetric powers will be introduced. The proposed modeling strategy benefits from neural network based GARCH models and SVR-GARCH models. Following these approaches, the study proposed fractional integration and asymmetric power GARCH structures to obtain SVR-FIAPGARCH and NN-FIAPGARCH models to be evaluated in terms of learning algorithms. Models are evaluated for in-sample and out-of-sample forecasting of daily returns in Istanbul ISE100 stock index. Results suggest several findings: i. fractional integration and asymmetric power structures could be modeled with learning algorithms. ii. volatility clustering, asymmetry and nonlinearity characteristics are modeled more effectively with SVR-GARCH and MLP-GARCH models compared to the GARCH models. iii. SVR-GARCH models provided the lowest error criteria levels in out-of-sample and are closely followed by the MLP-GARCH models.en_US
dc.identifier.endpage184en_US
dc.identifier.issn0424-267X
dc.identifier.issn1842-3264
dc.identifier.issue2en_US
dc.identifier.startpage163en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12662/4085
dc.identifier.volume48en_US
dc.identifier.wosWOS:000338090100010en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherEditura Aseen_US
dc.relation.ispartofEconomic Computation And Economic Cybernetics Studies And Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectVolatilityen_US
dc.subjectStock Returnsen_US
dc.subjectARCHen_US
dc.subjectFractional Integrationen_US
dc.subjectMLPen_US
dc.titleASYMMETRIC POWER AND FRACTIONALLY INTEGRATED SUPPORT VECTOR AND NEURAL NETWORK GARCH MODELS WITH AN APPLICATION TO FORECASTING FINANCIAL RETURNS IN ISE100 STOCK INDEXen_US
dc.typeArticleen_US

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