Using GARCH models to predict stock prices and returns of the Bank of Baghdad For the period (2013-2022(

Abstract

The research aims to use GARCH models in predicting stock price fluctuations and returns to assist in asset allocation and hedging, risk management, and portfolio improvement decisions. In addition to reducing errors in forecasting by calculating errors in advance forecasting and enhancing the accuracy of ongoing forecasts using the model. This research was applied to one of the Iraqi banks listed on the Iraqi Stock Exchange, which is the Bank of Baghdad. For the period from January 2013 to December 2022, using many financial, statistical and mathematical methods. The study reached a number of conclusions, the most important of which is that GARCH models demonstrate their predictive ability by relying on a set of related matrices for the purpose of producing the best analytical results for the investor. As well as the ability to detect changes in the temporal structure of prices and returns, such as time fluctuations. The study came out with a number of recommendations, the most important of which is, before using GARCH models for forecasting, the historical data for the stocks in question must be analyzed, as the analysis must include a sufficient time period to correctly estimate the parameters and determine the most appropriate model according to the nature of Financial data and statistical characteristics of prices or returns.