Prediction of Related Party Transactions Using Artificial Neural Network
Recent scandals of companies in America (Adelfia, Enron) and Europe (Parmalt) have magnified transactions with related parties. Experience has shown that transactions with related parties not only can disrupt in create value for shareholders, but also can provide caused of the collapse of firms. In...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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EconJournals
2017-07-01
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| Series: | International Journal of Economics and Financial Issues |
| Online Access: | http://mail.econjournals.com/index.php/ijefi/article/view/5183 |
| _version_ | 1797908469646360576 |
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| author | Sayed Ali Vaez Mohammad Banafi |
| author_facet | Sayed Ali Vaez Mohammad Banafi |
| author_sort | Sayed Ali Vaez |
| collection | DOAJ |
| description |
Recent scandals of companies in America (Adelfia, Enron) and Europe (Parmalt) have magnified transactions with related parties. Experience has shown that transactions with related parties not only can disrupt in create value for shareholders, but also can provide caused of the collapse of firms. In this line, the aim of this study is to predict the amount of transactions with related parties using artificial neural network in companies listed in the Tehran Stock Exchange. Multi-layer artificial perceptron Neural Network with backwards propagation algorithm, the duality of the Board of Directors, the independence of the board of directors, financial leverage, Institutional ownership, the ratio of market value to book value of assets, company size and profitability were used to predict the amount of transactions with related parties , the predictor variables of board size. Finally, a network with the mean square error 0.229 , 0.424, 0.299, 0.268 were chosen respectively for educational data, validation, test and total data, and coefficient of determination more than 76%, as the best network to predict the amount of transactions with related people were selected.
Keywords: Forecast transactions with related parties, Propagation algorithm
JEL Classifications: C32; O13; O47
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| first_indexed | 2024-04-10T10:53:06Z |
| format | Article |
| id | doaj.art-5bd8a9b07e8543209a7938537f3e3073 |
| institution | Directory Open Access Journal |
| issn | 2146-4138 |
| language | English |
| last_indexed | 2024-04-10T10:53:06Z |
| publishDate | 2017-07-01 |
| publisher | EconJournals |
| record_format | Article |
| series | International Journal of Economics and Financial Issues |
| spelling | doaj.art-5bd8a9b07e8543209a7938537f3e30732023-02-15T16:20:04ZengEconJournalsInternational Journal of Economics and Financial Issues2146-41382017-07-0174Prediction of Related Party Transactions Using Artificial Neural NetworkSayed Ali VaezMohammad Banafi Recent scandals of companies in America (Adelfia, Enron) and Europe (Parmalt) have magnified transactions with related parties. Experience has shown that transactions with related parties not only can disrupt in create value for shareholders, but also can provide caused of the collapse of firms. In this line, the aim of this study is to predict the amount of transactions with related parties using artificial neural network in companies listed in the Tehran Stock Exchange. Multi-layer artificial perceptron Neural Network with backwards propagation algorithm, the duality of the Board of Directors, the independence of the board of directors, financial leverage, Institutional ownership, the ratio of market value to book value of assets, company size and profitability were used to predict the amount of transactions with related parties , the predictor variables of board size. Finally, a network with the mean square error 0.229 , 0.424, 0.299, 0.268 were chosen respectively for educational data, validation, test and total data, and coefficient of determination more than 76%, as the best network to predict the amount of transactions with related people were selected. Keywords: Forecast transactions with related parties, Propagation algorithm JEL Classifications: C32; O13; O47 http://mail.econjournals.com/index.php/ijefi/article/view/5183 |
| spellingShingle | Sayed Ali Vaez Mohammad Banafi Prediction of Related Party Transactions Using Artificial Neural Network International Journal of Economics and Financial Issues |
| title | Prediction of Related Party Transactions Using Artificial Neural Network |
| title_full | Prediction of Related Party Transactions Using Artificial Neural Network |
| title_fullStr | Prediction of Related Party Transactions Using Artificial Neural Network |
| title_full_unstemmed | Prediction of Related Party Transactions Using Artificial Neural Network |
| title_short | Prediction of Related Party Transactions Using Artificial Neural Network |
| title_sort | prediction of related party transactions using artificial neural network |
| url | http://mail.econjournals.com/index.php/ijefi/article/view/5183 |
| work_keys_str_mv | AT sayedalivaez predictionofrelatedpartytransactionsusingartificialneuralnetwork AT mohammadbanafi predictionofrelatedpartytransactionsusingartificialneuralnetwork |