Multiple regression approach to fit suitable model for all share price index with other important related factors

Jahufer, A.; Imras, A.H.M.

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dc.contributor.author	Jahufer, A.
dc.contributor.author	Imras, A.H.M.
dc.date.accessioned	2016-11-21T06:58:38Z
dc.date.accessioned	2016-11-23T06:18:59Z
dc.date.available	2016-11-21T06:58:38Z
dc.date.available	2016-11-23T06:18:59Z
dc.date.issued	2015-11-25
dc.identifier.citation	In Proceedings of 4th Annual International Research Conference – 2015, on “Innovative Perspective in Business, Finance and Information Management”, pp 223-229.	en_US
dc.identifier.isbn	978-955-627-065-5
dc.identifier.uri	http://ir.lib.seu.ac.lk/handle/123456789/1827
dc.description.abstract	This study investigates the effects of some important sectors indices such as: Bank Finance & Insurance, Manufacturing, Trading, Hotels & Travels and Services on All Share Price Index (ASPI) in emerging Sri Lankan stock market using monthly data for the period from January 2005 to December 2014. It is aimed to find a suitable multiple regression model for Bank Finance & Insurance, Manufacturing, Trading, Hotels & Travels and Services on ASPI. In this paper, multiple linear regression model, multiple log linear model and multiple first difference of log linear models are analyzed using appropriate statistical tests. The first difference of log linear model is more appropriate to fit ASPI and other important related factors.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Faculty of Management and Commerce, South Eastern University of Sri Lanka (SEUSL).	en_US
dc.subject	Stock market	en_US
dc.subject	ASPI	en_US
dc.subject	Multiple regression	en_US
dc.title	Multiple regression approach to fit suitable model for all share price index with other important related factors	en_US
dc.type	Article	en_US