Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/55576
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dc.contributor.authorPhachongchit Tibprasornen_US
dc.contributor.authorSomsak Chanaimen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T02:58:01Z-
dc.date.available2018-09-05T02:58:01Z-
dc.date.issued2016-01-01en_US
dc.identifier.issn16113349en_US
dc.identifier.issn03029743en_US
dc.identifier.other2-s2.0-85006074139en_US
dc.identifier.other10.1007/978-3-319-49046-5_54en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85006074139&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/55576-
dc.description.abstract© Springer International Publishing AG 2016. This study applies the concept of stochastic frontier model (SFM) to estimate stock efficiencies of the top 50 companies with the highest market capitalization in the Stock Exchange of Thailand (SET50). We decompose the actual return deviation from its expected return into a stochastic noise and inefficiency term, and use copula approach to join these two error components. Four copulas are considered, and the most appropriate copula is selected using the lowest AIC. The empirical results show that the majority of average return efficiencies (60% of stocks) lie between 0.9571 and 0.9999, suggesting that most of the stocks are quite efficient. However, the overall average of all return efficiencies is found to be 0.7313, indicating that stock price does not reflect all relevant information in the market.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleA copula-based stochastic frontier model and efficiency analysis: Evidence from stock exchange of Thailanden_US
dc.typeBook Seriesen_US
article.title.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
article.volume9978 LNAIen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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