Evaluating and assessing risk of big three stocks' pharmaceutical sector in Indonesia based on asymmetric GARCH-EVT modeling

Darmanto, and Darti, Isnani and Astutik, Suci and Nurjannah, (2025) Evaluating and assessing risk of big three stocks' pharmaceutical sector in Indonesia based on asymmetric GARCH-EVT modeling. HUNGARIAN STATISTICAL REVIEW, 8 (2). pp. 63-93. ISSN 2630-9130

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Abstract

This study aims to model the volatility of the top three pharmaceutical sector stocks in Indonesia using a two-stage modeling approach. The first stage involves GARCH and its variations, followed by residual modeling using the GPD-based EVT approach. The three stocks analyzed are Mitra Keluarga Karyasehat Tbk (IDX: MIKA), Kalbe Farma Tbk (IDX: KLBF), and Medikaloka Hermina Tbk (IDX: HEAL). The dataset comprises return data spanning July 1, 2019, to April 30, 2025 (a total of 1,412 observations), sourced from Yahoo Finance. The findings reveal that the best-fitting models for capturing volatility are ARMA(0,1)–GARCH(1,1) for MIKA.JK, ARMA(1,2)–TGARCH(1,1) for KLBF.JK, and ARMA(0,0)–GJRGARCH(1,1) for HEAL.JK. Backtesting and the Kupiec test confirm that these models provide highly accurate VaR predictions at the 1%, 2.5%, and 5% quantiles.

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