Modeling and Forecasting Return Volatilities of Inter-Capital Market Indices using GARCH-Fractional Cointegration Model Variation

Abstract

This research compares modeling and forecasting the volatility of the IHSG, N225, and BSESN30 capital market indices using the GARCH variation model against the GARCH-fractional cointegration variation. The data used is secondary data obtained from www.investing.com from 01/01/2012 to 04/30/2023. Based on the performance measurement using the sMAPE criterion, the best model for forecasting the period 05/01/2023 to 05/31/2023 is the std-ALLGARCH (1,2)-fractional cointegration model for IHSG, the std-ALLGARCH(1,1) model for N225, and the sstd-ALLGARCH (1,2) model for BSESN30. This empirical finding means that the Japanese and Indian capital markets affect the volatility of the Indonesian capital market.