Modeling and Forecasting Return Volatilities of Inter-Capital Market Indices using GARCH-Fractional Cointegration Model Variation
Procedia Computer Science(2024)
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.
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Key words
Capital Market,Fractional Cointegration,GARCH,Return,Volatility
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