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dc.contributor.authorDr. Abed Ali Hamad-
dc.contributor.authorDr. Ahmad Hussein Battal-
dc.date.accessioned2022-10-23T04:04:31Z-
dc.date.available2022-10-23T04:04:31Z-
dc.date.issued2021-05-12-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/5377-
dc.description.abstractThis research aims to build a standard model for the analysis and prediction of the average daily closing price fluctuations for companies registered in the Iraq Stock Exchange for the period 07/01/2013 to 30/06/2016, using the conditional generalized Heteroscedasticity Generalized Autoregressive (GARCH) models. As these models deal with the fluctuations that occur in the financial time series. The results of the analysis showed that the best model for predicting the volatility of average closing prices in the Iraq Stock Exchange is the EGARCH model (3,1), depending on the statistical criteria used in the preference between the models (Akaike Information Criterion, Schwarz Criterion), and these models can provide information for investors in order to reduce the risk resulting from fluctuations in stock prices in the Iraqi financial market. Keyworden_US
dc.publisherweb ologyen_US
dc.subjectConditional Variance, Return, Akaike Information Criterion, Autoregressive Conditional Heteroskedastic (ARCH), Mean Absolute erroren_US
dc.titleUse GARCH models to build a Econometric model to predict average daily closing prices of the Iraqi Stock Exchange for the period 2016-2013en_US
Appears in Collections:قسم الاقتصاد

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