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Modeling and forecasting volatility in the Iraq stock exchange: A survey study using ARCH and GARCH models
International Journal of Statistics and Applied Mathematics · 2025 · Vol. 10(2) · pp. 35–45
Abstract
This study aimed at the effectiveness of self-regression models conditional on the instability of variance ARCH in predicting the returns of shares traded for the Iraq Stock Exchange, in addition to the possibility of proposing a model in providing predictions with relatively small errors during the period from 5/1/2021 to 18/10/2024 by daily observations over the studied period, and to achieve the objectives of the study, the daily closing price was calculated as an indicator to predict fluctuations and estimate self-regression conditional on the instability of variance based on self-regression models conditional on heterogeneity variance. ARCH:
Market Dynamics and VolatilityFinancial Risk and Volatility ModelingStock Market Forecasting MethodsAutoregressive conditional heteroskedasticityArchEconometricsVolatility (finance)Stock exchangeEconomicsStock (firearms)Financial economicsEngineeringFinance
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