Penerapan Diagram Kendali Shewhart pada Model ARMA-GARCH dalam Memantau Proses Keuangan di Pasar Modal Indonesia
DOI:
https://doi.org/10.29313/bcss.v5i2.20556Keywords:
Diagram Kendali Shewhart, ARMA-GARCH, IHSGAbstract
Abstract. The capital market has significant potential to drive the country's economic growth. The Indonesian capital market is inseparable from market uncertainty which influences risk considerations in investing. Financial data modeling using time series methods is effective in modeling stock market returns and volatility. The ARMA model is unable to handle the problem of non-constant residual variance, requiring advanced modeling, namely ARMA-GARCH. However, this model has limitations in monitoring the stability of financial processes. Therefore, a statistical method capable of monitoring financial process stability, namely the Shewhart control chart, is applied. This study uses the ARMA-GARCH model and the Shewhart control chart to model returns and volatility with statistical control tools useful for providing an overview of investment risk in the Indonesian capital market. This study uses data from the Jakarta Composite Index for the period January 2000 to December 2024, totaling 6,089 observations. The results show that the ARMA (1,2) - GARCH (2,1) model is the best model with the smallest AIC and SIC values. The Shewhart control chart for the ARMA (1,2) - GARCH (2,1) model shows 101 uncontrolled signals. This indicates that there were at least 101 market volatility shocks in the Indonesian capital market from January 2000 to December 2024.
Abstrak. Pasar modal memiliki potensi besar menjadi motor penggerak pertumbuhan ekonomi negara. Pasar modal Indonesia tidak terlepas dari ketidakpastian pasar yang berpengaruh pada pertimbangan risiko dalam berinvestasi. Pemodelan data keuangan menggunakan metode deret waktu sangat efektif dalam memodelkan return dan volatilitas pasar saham. Model ARMA tidak mampu menangani masalah ragam sisaan yang tidak konstan sehingga diperlukan pemodelan lanjutan yaitu ARMA-GARCH. Namun, model ini memiliki keterbatasan dalam memantau stabilitas proses keuangan. Maka diterapkan metode statistik yang mampu memantau stabilitas proses keuangan yaitu diagram kendali Shewhart. Penelitian ini menggunakan model ARMA-GARCH dan diagram kendali Shewhart untuk memodelkan return dan volatilitas dengan alat kontrol statistik yang berguna untuk memberikan gambaran risiko investasi di pasar modal Indonesia. Penelitian ini menggunakan data Indeks Harga Saham Gabungan (IHSG) periode Januari 2000 sampai Desember 2024 sebanyak 6.089 pengamatan. Hasil penelitian menunjukkan bahwa model ARMA (1,2) – GARCH (2,1) merupakan model terbaik dengan nilai AIC dan SIC terkecil. Diagram kendali Shewhart pada model ARMA (1,2) – GARCH (2,1) menunjukkan sinyal yang tidak terkendali sebanyak 101 kali. Hal ini menandakan bahwa sepanjang periode Januari 2000 sampai Desember 2024 terjadi setidaknya 101 kali guncangan (market volatility) di pasar modal Indonesia.
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