Dampak Nilai Tukar Mata Uang Perdagangan China Terhadap Risiko Pasar Pertambangan Indonesia: Analisis Menggunakan Pendekatan GARCH dan Quantile Regression Forest

Izzaty, Nabiela Rahma (2025) Dampak Nilai Tukar Mata Uang Perdagangan China Terhadap Risiko Pasar Pertambangan Indonesia: Analisis Menggunakan Pendekatan GARCH dan Quantile Regression Forest. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian ini bertujuan untuk mengukur dan membandingkan risiko pasar saham sektor pertambangan di Indonesia dengan mempertimbangkan pengaruh variabel eksternal berupa nilai tukar mata uang perdagangan internasional sebagai salah satu determinan penting dalam pembentukan risiko sistemik. Objek penelitian terdiri atas dua saham unggulan di sektor pertambangan, yaitu ADRO (PT Adaro Energy Indonesia Tbk), sebuah perusahaan tambang batu bara terintegrasi yang memiliki peran besar dalam ekspor energi nasional, dan INCO (PT Vale Indonesia Tbk), perusahaan pertambangan nikel berskala besar yang menjadi bagian vital dalam rantai pasok bahan baku baterai kendaraan listrik dunia. Kedua saham tersebut dipilih karena sangat terpapar oleh gejolak pasar global, termasuk fluktuasi nilai tukar mata uang negara mitra dagang. Estimasi risiko dilakukan menggunakan dua pendekatan utama, yaitu Value at Risk (VaR) dengan model GARCH(1,0) untuk mengukur volatilitas log return saham secara univariat, dan Conditional Value at Risk (CoVaR) dengan metode Quantile Regression Forest (QRF), yang memungkinkan pemodelan sistemik secara non-parametrik dan mempertimbangkan variabel USD/IDR dan CNY/IDR sebagai indikator eksternal. Untuk menilai dampak nilai tukar terhadap risiko sistemik, dilakukan perbandingan nilai Expected Shortfall (ES) yang dihasilkan dari kedua pendekatan tersebut. Hasil penelitian menunjukkan bahwa nilai tukar berpengaruh signifikan terhadap peningkatan akurasi estimasi risiko sistemik, terutama pada kuantil ekstrem sebesar 1%, di mana model CoVaR-QRF memberikan nilai ES yang lebih rendah dan lebih dekat dengan estimasi ideal dibandingkan VaR-GARCH. Saham ADRO tercatat memiliki risiko pasar lebih tinggi dibandingkan INCO. Temuan ini menyimpulkan bahwa nilai tukar mata uang mitra dagang utama seperti China harus menjadi komponen penting dalam strategi pengukuran dan pengelolaan risiko pasar di sektor pertambangan Indonesia yang bergantung pada ekspor.
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This study aims to measure and compare the market risk of the mining sector stocks in Indonesia by considering the influence of external variables, specifically exchange rates of international trade currencies, as a key determinant in the formation of systemic risk. The objects of this study are two leading mining stocks: ADRO (PT Adaro Energy Indonesia Tbk), an integrated coal mining company with a major role in national energy exports, and INCO (PT Vale Indonesia Tbk), a large-scale nickel mining company that plays a vital role in the global electric vehicle battery supply chain. These stocks were selected due to their high exposure to global market volatility, including fluctuations in the exchange rates of major trading partner countries. Risk estimation is conducted using two main approaches: Value at Risk (VaR) with a GARCH(1,0) model to measure the volatility of stock log returns univariately, and Conditional Value at Risk (CoVaR) using the Quantile Regression Forest (QRF) method, which enables non-parametric systemic modeling and incorporates USD/IDR and CNY/IDR exchange rates as external indicators. To assess the impact of exchange rates on systemic risk, a comparison of the Expected Shortfall (ES) values generated from both approaches is conducted. The results show that exchange rate variables significantly improve the accuracy of systemic risk estimation, especially at the 1% extreme quantile, where the CoVaR-QRF model yields lower ES values and aligns more closely with the ideal estimates compared to the VaR-GARCH model. ADRO is found to have higher market risk compared to INCO. These findings conclude that the exchange rates of major trading partners, such as China, should be considered essential components in the risk measurement and management strategies of Indonesia's export-dependent mining sector.

Item Type: Thesis (Masters)
Uncontrolled Keywords: CoVaR, GARCH, Nilai Tukar, Quantile Regression Forest, Risiko Pasar, CoVaR, Exchange Rate, GARCH, Market Risk, Quantile Regression Forest
Subjects: H Social Sciences > HA Statistics > HA30.3 Time-series analysis
H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis.
H Social Sciences > HD Industries. Land use. Labor > HD30.23 Decision making. Business requirements analysis.
H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
H Social Sciences > HG Finance > HG4529 Investment analysis
H Social Sciences > HG Finance > HG4910 Investments
H Social Sciences > HG Finance > HG4915 Stocks--Prices
Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry)
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49101-(S2) Master Thesis
Depositing User: Nabiela Rahma Izzaty
Date Deposited: 06 Aug 2025 04:34
Last Modified: 06 Aug 2025 04:34
URI: http://repository.its.ac.id/id/eprint/127651

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