APPLYING THE LINEAR GENETIC ALGORITHM AND NON-LINEAR GENETIC TO INCREASING THE EFFICIENCY OF PREDICTING CORPORATE PROFITABILITY

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POORZAMANI ZAHRA

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Journal: FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT) Year:2015 | Volume:6 | Issue:22 Page(s): 81-94

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Title

APPLYING THE LINEAR GENETIC ALGORITHM AND NON-LINEAR GENETIC TO INCREASING THE EFFICIENCY OF PREDICTING CORPORATE PROFITABILITY

Author(s)

POORZAMANI ZAHRA | Issue Writer Certificate

Keywords

PROFITABILITY PREDICTIONQ2

NON-LINEAR GENETIC ALGORITHMQ2

NEURAL NETWORKQ2

LINEAR GENETIC ALGORITHMQ2

Abstract

Profitability the basis for performance evaluation of corporate executives should be used. As well as it certainly can be said to is part of the decision-making ability to predict the future profitability of the companies concerned. Today, financial ratio analysis is a powerful technique and suitable tool for users to understand and assess the past, present and predict the future is companies. One of the problems in the use of financial ratios to assess the financial situation of the companies is that each set of financial to measure one aspect of the performance of companies. To surmount this problem can be multi-criteria decisionmaking methods, including Data envelopment analysis, NEURAL NETWORKs, fuzzy logic and genetic algorithm are used.Purpose of this study is investigating PROFITABILITY PREDICTION strength of LINEAR GENETIC ALGORITHM and LINEAR GENETIC ALGORITHM/fa?page=1&sort=1&ftyp=all&fgrp=all&fyrs=all" target="_blank"> NON-LINEAR GENETIC ALGORITHM to increase the ability of decision making for financial statement users to predicate profitability. Then, respecting the obtained results these pattern are compared with each other and the best pattern is extracted. Based on available information and statistics, of all companies listed in Tehran Stock Exchange during the period 2002-2012, the top 24 financial ratios as independent variables are used. Results of tests indicated that prediction accuracy of LINEAR GENETIC ALGORITHM/fa?page=1&sort=1&ftyp=all&fgrp=all&fyrs=all" target="_blank"> NON-LINEAR GENETIC ALGORITHM (90.04%) was greater than that of LINEAR GENETIC ALGORITHM (87.14%).

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APA: Copy

POORZAMANI, ZAHRA. (2015). APPLYING THE LINEAR GENETIC ALGORITHM AND NON-LINEAR GENETIC TO INCREASING THE EFFICIENCY OF PREDICTING CORPORATE PROFITABILITY. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), 6(22), 81-94. SID. https://sid.ir/paper/197596/en

Vancouver: Copy

POORZAMANI ZAHRA. APPLYING THE LINEAR GENETIC ALGORITHM AND NON-LINEAR GENETIC TO INCREASING THE EFFICIENCY OF PREDICTING CORPORATE PROFITABILITY. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)[Internet]. 2015;6(22):81-94. Available from: https://sid.ir/paper/197596/en

IEEE: Copy

ZAHRA POORZAMANI, “APPLYING THE LINEAR GENETIC ALGORITHM AND NON-LINEAR GENETIC TO INCREASING THE EFFICIENCY OF PREDICTING CORPORATE PROFITABILITY,” FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), vol. 6, no. 22, pp. 81–94, 2015, [Online]. Available: https://sid.ir/paper/197596/en

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