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فارسی
shahabaldin shams
Academic rank:
Assistant Professor
ORCID:
Education:
PhD.
ScopusId:
HIndex:
Faculty:
Address:
Phone:
9122175819
E-mail:
shams [at] umz.ac.ir
Home
Research activities
Research
Title
Comparative analysis of stocks returns' predictable factors in Tehran Stocks Exchange and New York Stocks Exchange using artificial neural network and linear regression
Type
JournalPaper
Keywords
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Year
2012
Journal
African Journal of Business ManagementISI1.105
DOI
Researchers
shahabaldin shams
،
،
،
Abstract
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