بررسی ویژگی‌های حافظه بلندمدت بورس اوراق بهادار در مقایسه با نرخ ارز در بازار آزاد در اقتصاد ایران Journal Article

Writer: ابوالحسنی پوراشکذر، مجتبی ؛ محمدی، تیمور ؛ حاجی، غلامعلی ؛

دانش مالی تحلیل اوراق بهادار (مطالعات مالی) تابستان 1403 - شماره 62 ، A (Azad University/ISC (‎12 page(s) - From 146 to 157 )

Keywords: حافظه بلندمدت شاخص بورس اوراق بهادار میانگین متحرک خودهمبسته با انباشتگی جزئی واریانس ناهمسانی شرطی خودهمبسته با انباشتگی جزئی GARCH Type Models Long Memory TEPIX Fractional Integration

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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.

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