Forecasting the Timing of Transactions in Tehran Stock Exchange

Document Type : Research Paper

Authors

1 Ph.D Student of Accounting, Najaf Abad Branch, University of Islamic Azad, Najaf Abad, Iran.

2 Ph.D Student of Accounting, Najaf Abad branch, University of Islamic Azad, Najaf Abad, Iran.

10.22103/jdc.2020.12002.1048

Abstract

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.

Keywords

References

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History

  • Receive Date: 20 April 2018
  • Revise Date: 11 August 2019
  • Accept Date: 22 April 2020

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