COMPARING THE ABILITY OF INTERNAL AND COMPARATIVE DATA ANALYSIS IN NON-LINEAR GENETIC ALGORITHM IN PREDICTING CORPORATE PROFITABILITY

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POURZAMANI ZAHRA

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: The Financial Accounting and Auditing Researches Year:2014 | Volume:6 | Issue:23 Page(s): 117-131

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Title

COMPARING THE ABILITY OF INTERNAL AND COMPARATIVE DATA ANALYSIS IN NON-LINEAR GENETIC ALGORITHM IN PREDICTING CORPORATE PROFITABILITY

Author(s)

POURZAMANI ZAHRA | Issue Writer Certificate

Keywords

BANKRUPTCY PREDICTIONQ2

NON-LINEAR GENETIC ALGORITHMQ2

NEURAL NETWORKQ2

INTERNAL DATA ANALYSISQ2

COMPARATIVE DATA ANALYSISQ2

Abstract

Although knowledge about how users of financial statements make decisions is limited, it certainly can be said that a part of decision-making relates to predictability of future profitability. Also, profitability is used as a basis for assessing the efficiency of corporate managers. This study, with the aim of introducing an appropriate algorithm for predicting the profitability to the decision makers, by the top 24 financial ratios as independent variables, compares the abilities of internal and COMPARATIVE DATA ANALYSIS in NON-LINEAR GENETIC ALGORITHM in anticipating the future profitability of companies listed in Tehran Stock Exchange during the years 2002 to 2012. Results of tests indicated that prediction accuracy of INTERNAL DATA ANALYSIS in NON-LINEAR GENETIC ALGORITHM (90.04%) was greater than that of COMPARATIVE DATA ANALYSIS in NON-LINEAR GENETIC ALGORITHM (72.85%).

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APA: Copy

POURZAMANI, ZAHRA. (2014). COMPARING THE ABILITY OF INTERNAL AND COMPARATIVE DATA ANALYSIS IN NON-LINEAR GENETIC ALGORITHM IN PREDICTING CORPORATE PROFITABILITY. THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES, 6(23), 117-131. SID. https://sid.ir/paper/198155/en

Vancouver: Copy

POURZAMANI ZAHRA. COMPARING THE ABILITY OF INTERNAL AND COMPARATIVE DATA ANALYSIS IN NON-LINEAR GENETIC ALGORITHM IN PREDICTING CORPORATE PROFITABILITY. THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES[Internet]. 2014;6(23):117-131. Available from: https://sid.ir/paper/198155/en

IEEE: Copy

ZAHRA POURZAMANI, “COMPARING THE ABILITY OF INTERNAL AND COMPARATIVE DATA ANALYSIS IN NON-LINEAR GENETIC ALGORITHM IN PREDICTING CORPORATE PROFITABILITY,” THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES, vol. 6, no. 23, pp. 117–131, 2014, [Online]. Available: https://sid.ir/paper/198155/en

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