Aryaputra, Rafi Aditya (2025) Analisis Risiko Saham Perusahaan Market Capitalization Terbesar Menggunakan Value at Risk dengan Pendekatan Extreme Value Theory dan Conditional Value at Risk dengan Pendekatan Quantile Regression. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Perekonomian suatu negara sering mengalami fluktuasi dan salah satu cara untuk menilai perkembangannya adalah melalui pasar modal. Pasar modal berperan penting dalam melakukan mobilisasi dana masyarakat untuk investasi, dengan tujuan utama meraih keuntungan meskipun terdapat ketidakpastian ekonomi. Investasi dapat dilakukan pada aset riil atau keuangan, dengan risiko yang menjadi faktor utama dalam pengambilan keputusan investasi. Diversifikasi investasi, khususnya pada saham perusahaan dengan market capitalization besar, dapat membantu mengurangi risiko. Saham sebagai instrumen investasi utama memiliki potensi keuntungan yang tinggi, namun disertai dengan risiko yang besar karena dipengaruhi oleh faktor ekonomi, politik, dan kinerja perusahaan. Oleh karena itu, pengukuran risiko menjadi hal penting, salah satunya menggunakan metode Value at Risk (VaR) dengan pendekatan Extreme Value Theory (EVT) yang dapat mengestimasi kerugian maksimal dan Conditional Value at Risk (CoVaR) dengan pendekatan Quantile Regression memberikan metode yang lebih akurat dalam mengukur risiko yang dipengaruhi oleh ketergantungan antar saham. Selain itu, penelitian ini juga menguji hubungan antar saham-saham perusahaan dengan market capitalization terbesar menggunakan Granger Causality Test. Hasil analisis statistika deskriptif menunjukkan bahwa data return saham tidak berdistribusi normal, dengan karakteristik leptokurtik dan skewness positif. Saham BYAN dan TPIA tercatat paling volatil, sementara BBCA dan BBRI cenderung stabil. Estimasi VaR dengan pendekatan EVT menunjukkan bahwa saham TPIA memiliki risiko kerugian terbesar, sedangkan BBCA paling rendah. Uji kausalitas Granger menyatakan hubungan signifikan antar sektor, dengan TLKM sebagai saham paling berpengaruh dan BBCA paling dipengaruhi. Estimasi CoVaR dengan pendekatan Quantile Regression mengonfirmasi bahwa TPIA memiliki risiko sistemik tertinggi, sedangkan BBCA paling rendah. Evaluasi model menunjukkan bahwa CoVaR dengan Quantile Regression lebih akurat dan valid dalam mengestimasi risiko dibandingkan model VaR dengan EVT, berdasarkan hasil Expected Shortfall dan Kupiec Test.
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The economy of a country often experiences fluctuations and a way to assess its development is through the capital market. The capital market plays a crucial role in mobilizing public funds for investment, with the primary goal of achieving profits despite economic uncertainties. Investments can be made in real or financial assets, with risk being a key factor in investment decision-making. Investment diversification, particularly in stocks of companies with large market capitalization, can help reduce risk. Stocks, as a primary investment instrument, offer high profit potential but are accompanied by significant risks due to economic, political, and company performance factors. Therefore, risk measurement becomes essential, including using the Value at Risk (VaR) method with the Extreme Value Theory (EVT) approach to estimate maximum losses and Conditional Value at Risk (CoVaR) with the Quantile Regression approach, which provides a more accurate method for measuring risk influenced by stock interdependencies. Additionally, this study examines the relationships between stocks of companies with the largest market capitalizations using the Granger Causality Test. The results of descriptive statistical analysis indicate that stock return data do not follow a normal distribution, exhibiting leptokurtic characteristics and positive skewness. BYAN and TPIA stocks are the most volatile, while BBCA and BBRI are more stable. Value at Risk (VaR) estimation using the Extreme Value Theory (EVT) approach shows that TPIA has the highest potential loss, whereas BBCA has the lowest. The Granger Causality Test reveals significant inter-sector relationships, with TLKM being the most influential stock and BBCA the most affected. CoVaR estimation using the Quantile Regression approach confirms that TPIA has the highest systemic risk, while BBCA has the lowest. The model evaluation shows that CoVaR with Quantile Regression is more accurate and statistically valid in estimating risk compared to the VaR model with EVT, as supported by the results of the Expected Shortfall and Kupiec Test.
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