Forecasting the Timing of Transactions in Tehran Stock Exchange
Objective: Due to the complexity of the stock market in Tehran, the timing of transactions is very important. The timing of trading transactions helps analysts and traders to predict the stock prices movement. Therefore, the purpose of this study is to predict the timing of stock trading of listed c...
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| Format: | Article |
| Language: | fas |
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Shahid Bahonar University of Kerman
2020-08-01
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| Series: | مجله توسعه و سرمایه |
| Subjects: | |
| Online Access: | https://jdc.uk.ac.ir/article_2579_80ca848c978a82fe1f0004a5e54b2890.pdf |
| _version_ | 1797835594067345408 |
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| author | Vahid BekhradiNasab Fatemeh Zholanezhad |
| author_facet | Vahid BekhradiNasab Fatemeh Zholanezhad |
| author_sort | Vahid BekhradiNasab |
| collection | DOAJ |
| description | Objective: Due to the complexity of the stock market in Tehran, the timing of transactions is very important. The timing of trading transactions helps analysts and traders to predict the stock prices movement. Therefore, the purpose of this study is to predict the timing of stock trading of listed companies in TSE. Methods: The statistical population of the study consisted of all companies listed in TSE between 2013-2016. The sample is based on the systematic elimination method of 17 active companies in the TSE. Research method based on stepwise regression and fuzzy neural network based on indicators of relative strength, Moving Average Convergence-Divergence, simple moving average, Stochastic, EMA and Signal line. Results: The results showed that the average prediction accuracy of all networks created (96.55%) was more than random (50%). By applying the trading rules, the predicted values were converted to the signal It was suggested that the final signal of the designed system be obtained from the sum of the signals generated by the five technical indicators. Next, to evaluate the returns of the proposed transactions, the model AE using the trading strategy proposed study is a trading simulation assumptions were. Conclusion: The efficiency of transactions made on the basis of the final signal proposed system efficiency methods, technical and purchasing methods and stored (in two cases before the deduction of transaction costs and after deduction of transaction costs ). Due to the positive results of SMA, EMA, SO and the proposed method, we can conclude that using these technical analysis indices in the Iranian stock market can predict the stock price trend. Meanwhile, the simple moving average method has the highest credit for predicting stock price trends. As a result, the Tehran Stock Exchange has the potential to apply various technical analysis indicators. |
| first_indexed | 2024-04-09T14:55:08Z |
| format | Article |
| id | doaj.art-2bf3a68f5af84eb5a5376b0ce066d705 |
| institution | Directory Open Access Journal |
| issn | 2008-2428 2645-3606 |
| language | fas |
| last_indexed | 2024-04-09T14:55:08Z |
| publishDate | 2020-08-01 |
| publisher | Shahid Bahonar University of Kerman |
| record_format | Article |
| series | مجله توسعه و سرمایه |
| spelling | doaj.art-2bf3a68f5af84eb5a5376b0ce066d7052023-05-02T06:54:36ZfasShahid Bahonar University of Kermanمجله توسعه و سرمایه2008-24282645-36062020-08-0151679210.22103/jdc.2020.12002.10482579Forecasting the Timing of Transactions in Tehran Stock ExchangeVahid BekhradiNasab0Fatemeh Zholanezhad1Ph.D Student of Accounting, Najaf Abad Branch, University of Islamic Azad, Najaf Abad, Iran.Ph.D Student of Accounting, Najaf Abad branch, University of Islamic Azad, Najaf Abad, Iran.Objective: Due to the complexity of the stock market in Tehran, the timing of transactions is very important. The timing of trading transactions helps analysts and traders to predict the stock prices movement. Therefore, the purpose of this study is to predict the timing of stock trading of listed companies in TSE. Methods: The statistical population of the study consisted of all companies listed in TSE between 2013-2016. The sample is based on the systematic elimination method of 17 active companies in the TSE. Research method based on stepwise regression and fuzzy neural network based on indicators of relative strength, Moving Average Convergence-Divergence, simple moving average, Stochastic, EMA and Signal line. Results: The results showed that the average prediction accuracy of all networks created (96.55%) was more than random (50%). By applying the trading rules, the predicted values were converted to the signal It was suggested that the final signal of the designed system be obtained from the sum of the signals generated by the five technical indicators. Next, to evaluate the returns of the proposed transactions, the model AE using the trading strategy proposed study is a trading simulation assumptions were. Conclusion: The efficiency of transactions made on the basis of the final signal proposed system efficiency methods, technical and purchasing methods and stored (in two cases before the deduction of transaction costs and after deduction of transaction costs ). Due to the positive results of SMA, EMA, SO and the proposed method, we can conclude that using these technical analysis indices in the Iranian stock market can predict the stock price trend. Meanwhile, the simple moving average method has the highest credit for predicting stock price trends. As a result, the Tehran Stock Exchange has the potential to apply various technical analysis indicators.https://jdc.uk.ac.ir/article_2579_80ca848c978a82fe1f0004a5e54b2890.pdftransaction timingpredictiontechnical analysisfuzzy neural networktse |
| spellingShingle | Vahid BekhradiNasab Fatemeh Zholanezhad Forecasting the Timing of Transactions in Tehran Stock Exchange مجله توسعه و سرمایه transaction timing prediction technical analysis fuzzy neural network tse |
| title | Forecasting the Timing of Transactions in Tehran Stock Exchange |
| title_full | Forecasting the Timing of Transactions in Tehran Stock Exchange |
| title_fullStr | Forecasting the Timing of Transactions in Tehran Stock Exchange |
| title_full_unstemmed | Forecasting the Timing of Transactions in Tehran Stock Exchange |
| title_short | Forecasting the Timing of Transactions in Tehran Stock Exchange |
| title_sort | forecasting the timing of transactions in tehran stock exchange |
| topic | transaction timing prediction technical analysis fuzzy neural network tse |
| url | https://jdc.uk.ac.ir/article_2579_80ca848c978a82fe1f0004a5e54b2890.pdf |
| work_keys_str_mv | AT vahidbekhradinasab forecastingthetimingoftransactionsintehranstockexchange AT fatemehzholanezhad forecastingthetimingoftransactionsintehranstockexchange |