Providing a smart trading system based on the combination of technical analysis indicators, meta-heuristic algorithms and neural network in Tehran Stock Exchange
Quarterly Journal of Securities Exchange

Quarterly Journal of Securities Exchange

Providing a smart trading system based on the combination of technical analysis indicators, meta-heuristic algorithms and neural network in Tehran Stock Exchange

Document Type : Original Article

Authors
Fatemeh Asiaei Taheri 1
gholamreza zomorodian 2
Mirfeiz Fallahshams 2
1 Department of Financial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
2 Department of Financial Management, central Tehran Branch, Islamic Azad University. Tehran, Iran and member of Modern Financial Risk Research Group
10.22034/jse.2023.12263.2161
Abstract
The main goal of investing in the stock market is to get the highest return at the desired time. Successful trading in financial markets should be done close to key reversal points.
In this research, we are trying to select the widely used technical rules by studying the previous researches and improving the decision parameters in the mentioned technical rules for each stock by using the firefly and gray wolf algorithm and converting contradictory signals issued from the optimized indicators to the unit. And finally, through the LSTM neural network, we will try to predict the entry and exit positions of the stock market.
This research was conducted from 1390 to September 1401 on Tehran Stock Exchange companies. The proposed model has been able to correctly identify buy, sell and hold points for a future trading day for long-term investors with an error of about thirty-six percent.

Keywords: Technical indicators, firefly algorithm, GWO and LSTM
Keywords
Technical indicators
firefly algorithm
GWO and LSTM
Subjects

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Quarterly Journal of Securities Exchange
Volume 17, Issue 65
Summer 2024
Pages 133-152