Long memory in Tehran Stock Market Index Compared to Exchange Rate (USD) in Iran Economic
Long memory in Tehran Stock Market Index Compared to Exchange Rate (USD) in Iran Economic
Subject Areas : Financial Knowledge of Securities Analysis
mojtaba abolhasani poorashkezar 1 , Ahmad Sarlak 2 , Teimur Mohammadi 3 , Gholam Ali Haji 4
1 - PhD student, Department of Economics , Arak Branch, Islamic Azad University, Arak, Iran
2 - Assistant Professor, Department of Economics, Arak Branch, Islamic Azad University Arak, Iran (Corresponding Author)
3 - Professor, Department of Economics, Allamah Tabatabaei University, Tehran, Iran
4 - Assistant Professor, Department of Economics, Arak Branch, Islamic Azad University, Rak, Iran
Keywords: TEPIX, Long Memory, Fractional Integration, GARCH Type Models,
Abstract :
In recent years, processes with long-term memory have played substantial role in time series analysis. The existence of long-term memory in assets return time series has momentous applications in examining market efficiency, investor’s behavioral logics, pricing, and asset portfolio selection. In present study, using the AutoRegressive Fractionally Integrated Moving Average model (ARFIMA) and the Fractionally integrated generalized autoregressive conditional (FIGARCH) and hyperbolic GARCH (HYGARCH) models to investigate the existence of long-term memory in the Tehran Stock Exchange's main index (TEPIX) and exchange rate ( US dollars) in using daily data during the period Novamber, 2011 to July, 2023. The results indicate the existence of long-term memory in TEPIX and exchange rate (US dollar) is confirmed in ARFIMA model in both ML and GLS approaches and in GARCH family models in both FIGARCH and HYGARCH models. According to these results, price behavior in each of the mentioned time series is a function of the past amounts.
