Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58575
Title: Estimating and Predicting Financial Series by Entropy-Based Inferential Model
Authors: Tanarat Rattanadamrongaksorn
Duangthip Sirikanchanarak
Jirakom Sirisrisakulchai
Songsak Sriboonchitta
Keywords: Computer Science
Mathematics
Issue Date: 1-Jan-2018
Abstract: © 2018, Springer International Publishing AG, part of Springer Nature. In this study, the non-parametric Inferential Model or IM with the entropy-based random set has been proposed for the investigation of financial data in the two statistical domains i.e. estimation and prediction. The samples from five financial markets were chosen for representing the different types of financial assets to make a conclusion about this new framework. We found that the Inferential Model performed equally well compared with the traditional method but was more robust so that it might be more appropriate for some specific uses.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85043980484&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/58575
ISSN: 16113349
03029743
Appears in Collections:CMUL: Journal Articles

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