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All Journal JURISMA: Jurnal Riset Bisnis & Manajemen
Laith Haleem Al-Hchemi*
University of Al-Qadisiyah
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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CLOSING PRICE PREDICTION OF STOCK LISTED ON THE IRAQ STOCK EXCHANGE USING ANN-LSTM Salim Sallal Al-Hasnawi; Laith Haleem Al-Hchemi*
JURISMA : Jurnal Riset Bisnis & Manajemen Vol 12 No 2: Oktober 2022
Publisher : Program Studi Manajemen, Fakultas Ekonomi dan Bisnis, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jurisma.v12i2.8103

Abstract

Financial markets are highly reactive to events and situations, as seen by the very volatile movement of stock values. As a result, investors are having difficulties guessing prices and making investment decisions, especially when statistical techniques have failed to model historical prices. This paper aims to propose an RNNs-based predictive model using the LSTM model for predicting the closing price of four stocks listed on the Iraq Stock Exchange (ISX). The data used are historical closing prices provided by ISX for the period from 2/1/2019 to 24/12/2020. Several attempts were conducted to improve model training and minimize the prediction error, as models were evaluated using MSE, RMSE, and R2. The models performed with high accuracy in predicting closing price movement, despite the Intense volatility of time series. The empirical study concluded the possibility of relying on the RNN-LSTM model in predicting close prices at the ISX as well as decisions making upon. Keywords: Stock, LSTM, Prediction, ANN, RNN, ISX
Co-Authors Salim Sallal Al-Hasnawi