Please use this identifier to cite or link to this item: http://ir.lib.seu.ac.lk/handle/123456789/1393
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dc.contributor.authorImras, A.H.M-
dc.contributor.authorJahufer, Aboobacker-
dc.date.accessioned2016-03-15T04:49:07Z-
dc.date.available2016-03-15T04:49:07Z-
dc.date.issued2015-
dc.identifier.citationSouth Eastern University of Sri- Lanka, Oluvil, Sri- Lanka, ASRS-2015en_US
dc.identifier.urihttp://ir.lib.seu.ac.lk/handle/123456789/1393-
dc.description.abstractThis research study attempts to explore whether there is an improvement in the performance of the each sector listed on Colombo Stock Exchange (CSE) in the periods from 2005 to 2014. To measure the performance of the CSE some important indicators were used namely: Bank Finance & Insurance (BFI), Manufacturing (MFG), Trading (TRD), Hotels & Travels (H&T) and Services (SRV) of the CSE and key market ratios. This study has examined the relationship of each sector with All Share Price Index (ASPI); however, it is recommended that in future, a study that examines how the BFI, MFG, TRD, H&T and SRV sectors interlinks with ASPI should be conducted, which will show how the linkages between these sectors could be strengthened so as to contribute to the share market development of Sri Lanka. In this paper simple linear regression model, simple log linear model and simple first difference of log linear models are analyzed using appropriate statistical analysis such as: normality of the variables, normality of the error terms, unit root test, auto correlation and serial correlation test, constant error variance test and stability test. The first difference of log linear model satisfied all the statistical conditions. Hence, the first difference of log linear model is more appropriate to fit ASPI and other important related factors individually.en_US
dc.language.isoen_USen_US
dc.publisherFaculty of Applied science South Eastern University of Sri Lanka Oluvil # 32360 Sri Lankaen_US
dc.subjectStock Marketen_US
dc.subjectSectorsen_US
dc.subjectASPIen_US
dc.subjectAuto Correlationen_US
dc.subjectSerial Correlationen_US
dc.titleHow the important related factors contributed on all share price index?en_US
dc.typeArticleen_US
Appears in Collections:ASRS - FAS 2015

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