Volume 13 • Issue 1 • PP: 37–44 • 2025
Predictability of Stock Price Fluctuations with an Application of Agricultural Companies Data
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© 2025 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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The research aimed to predict the fluctuations in closing Stock Price of four agricultural companies listed on the Iraq Stock Exchange using daily closing Stock Price data from 11/3/2015 to 15/3/2025. The symmetric and asymmetric ARCH model was applied to the research data. The results of the GARCH models showed that the closing price behavior of the companies (Al-Ahliyah for Agricultural Production, Middle East for Fish, Iraqi for Meat Production and Marketing) achieved a GARCH (1,1) rank, indicating that the effect of past error variance (ARCH) was of rank 1, in addition to the conditional variance element GARCH also being of rank 1. Meanwhile, the results showed that the closing prices for the Iraqi Seed Production Company were of rank GARCH (1,2). The results indicated that the first-order variance parameter was greater than one for all agricultural companies, suggesting that the fluctuations in stock closing prices exhibit a slight upward trend, which aligns with the logic of financial behavior in financial markets.
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