Innovative Approaches to Foracasting Intraday Stock Market Volatility: A case study of Tehran Stock Exchange

The main objective of this study is to develop a robust framework for estimating stock marketfluctuations in Tehran Stock Exchange using ARMA-GARCH modeling approach. Specifically, thisstudy focuses on the analysis of intraday data of stock indices to improve the forecasting accuracy.Fifteen-minute intraday data from June ۱۰, ۲۰۱۸ to March ۱۸, ۲۰۱۹ were collected and analyzed forTop ۵۰ Companies Index. Key statistical parameters, including the opening, closing, maximum andminimum values of the index, were included in the analysis. The ARMA-GARCH framework wasimplemented using Python ۳.۹, utilizing libraries such as Pandas, Numpy, and armagarch for datamanipulation and model fitting. Goodness-of-fit tests were used to evaluate the appropriateness of thefitted models. The results indicate that the ARMA-GARCH frameworks effectively estimate marketfluctuations, with the Akaike Information Criterion (AIC) assisting in the selection of the mostappropriate models.

کلیدواژه ها:

Time Series ، Market Shock ، Volatility ، ARMA - GARCH Model