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

Magdalena Effendi, Dedy Dwi Prastyo*, Muhammad Sjahid Akbar

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

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.

Original languageEnglish
Pages (from-to)389-396
Number of pages8
JournalProcedia Computer Science
Volume234
DOIs
Publication statusPublished - 2024
Event7th Information Systems International Conference, ISICO 2023 - Washington, United States
Duration: 26 Jul 202328 Jul 2023

Keywords

  • Capital Market
  • Fractional Cointegration
  • GARCH
  • Return
  • Volatility

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