Analisis Risiko Sistemik Antar Saham Subsektor Logistik Dan Transportasi Dengan Conditional-At-Risk Pendekatan Regresi Kuantil

Sasmito, Andreansyah Budi (2025) Analisis Risiko Sistemik Antar Saham Subsektor Logistik Dan Transportasi Dengan Conditional-At-Risk Pendekatan Regresi Kuantil. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Saham merupakan salah satu instrumen investasi yang memiliki volatilitas tinggi sehingga pengukuran risiko menjadi penting untuk memahami kondisi pasar. Risiko yang tidak dapat dihilangkan melalui diversifikasi disebut sebagai risiko sistemik karena diduga terdapat keterhubungan antar emiten. Sektor transportasi dan logistik merupakan salah satu sektor strategis yang mendukung perekonomian Indonesia. Penelitian ini bertujuan untuk mengestimasi risiko individu dan risiko sistemik antar saham subsektor transportasi dan logistik di Bursa Efek Indonesia (BEI) menggunakan pendekatan Conditional Value-at-Risk (CoVaR). Estimasi risiko individu dilakukan dengan Value-at-Risk (VaR) berbasis Extreme Value Theory menggunakan metode Peaks Over Threshold (POT) dengan threshold 1% dan moving window sepanjang 63 hari. Hasil estimasi menunjukkan bahwa risiko individu tertinggi terdapat pada saham SAPX sebesar -0,129319 pada kuantil 1% dan sebesar -0,083460 pada kuantil 5%, menjadikan SAPX sebagai saham dengan tingkat risiko individu paling tinggi di kedua kuantil tersebut. Sebaliknya, risiko individu terendah ditemukan pada saham TMAS sebesar -0,058233 untuk kuantil 1% dan ELPI sebesar -0,047801 untuk kuantil 5%. Risiko sistemik antar saham diukur menggunakan Conditional Value-at-Risk (CoVaR) dengan pendekatan regresi kuantil. Estimasi menunjukkan bahwa SAPX juga memiliki risiko sistemik tertinggi dengan nilai CoVaR sebesar -0,164907 pada kuantil 1% dan sebesar -0,098508 pada kuantil 5%. Sebaliknya, CoVaR terendah ditemukan pada saham TMAS sebesar -0,041565 pada kuantil 1% dan sebesar -0,029186 pada kuantil 5%. Nilai ∆CoVaR pada beberapa pasangan saham menunjukkan fluktuasi, di mana nilai positif menandakan bahwa ketika sistem bergerak dari kondisi normal menuju distress, tingkat risiko ekstrim saham terkait justru menurun. Sebaliknya, nilai negatif menunjukkan adanya tambahan risiko terhadap saham tersebut dalam kondisi distress sistemik. Pengujian hubungan antar saham menggunakan Granger Causality Test dilakukan secara berpasangan antar delapan saham selama 10 lag dan menghasilkan 64 pasang saham signifikan. Hasil pengujian menunjukkan bahwa ASSA dan HATM cenderung bersifat sebagai risk transmitter, karena keduanya tidak dipengaruhi oleh saham lain, namun mempengaruhi beberapa saham lainnya pada beberapa lag dari lag 1 hingga 10. Temuan ini memberikan gambaran bahwa subsektor transportasi dan logistik memiliki risiko sistemik yang signifikan, dengan beberapa saham berperan dominan sebagai sumber risiko bagi saham lain dalam sektor yang sama.
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Stocks are one of the investment instruments with high volatility, making risk measurement essential to understand market conditions. Risks that cannot be eliminated through diversification are referred to as systemic risks, as they are suspected to arise from interdependencies among issuers. The transportation and logistics sector is one of the strategic sectors that supports Indonesia's economy. This study aims to estimate individual risks and systemic risks among stocks in the transportation and logistics subsector listed on the Indonesia Stock Exchange (IDX) using the Conditional Value-at-Risk (CoVaR) approach. Individual risk estimation is carried out using Value-at-Risk (VaR) based on Extreme Value Theory with the Peaks Over Threshold (POT) method, applying a 1% threshold and a 63-day moving window. The results show that the highest individual risk is found in SAPX shares, with an estimated mean of -0.129319 at the 1% quantile and -0.083460 at the 5% quantile, making SAPX the stock with the highest individual risk in both quantiles. Conversely, the lowest individual risk is observed in TMAS shares at -0.058233 for the 1% quantile and in ELPI shares at -0.047801 for the 5% quantile. Systemic risks among stocks are measured using Conditional Value-at-Risk (CoVaR) with a quantile regression approach. The estimation shows that SAPX also has the highest systemic risk, with CoVaR values of -0.164907 at the 1% quantile and -0.098508 at the 5% quantile. Conversely, the lowest CoVaR is found in TMAS at -0.041565 for the 1% quantile and -0.029186 for the 5% quantile. The ∆CoVaR values across stock pairs fluctuate, where positive values indicate that as the system moves from normal to distress conditions, the risk of the related stock decreases. Conversely, negative values indicate that systemic distress adds additional risk to the corresponding stock. The interconnection among stocks is tested using the Granger Causality Test on paired combinations of the eight stocks over 10 lags, producing 64 significant stock pairs. The test results show that ASSA and HATM tend to act as risk transmitters, as they are not influenced by other stocks but influence several others at various lags from lag 1 to lag 10. These findings provide a comprehensive overview of systemic risk in the transportation and logistics subsector, with several stocks playing dominant roles as sources of risk for other stocks within the same sector.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Conditional Value-at-Risk, Granger Causality, Peaks Over Threshold, Regresi kuantil, Sektor transportasi dan logistik BEI, Value-at-Risk Conditional Value-at-Risk, Granger Causality, Peaks Over Threshold, Quantile Regression, Transportation and Logistics Sector of the Indonesia Stock Exchange (IDX), Value-at-Risk
Subjects:	H Social Sciences > HG Finance > HG8054.5 Risk (Insurance)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Andreansyah Budi Sasmito
Date Deposited:	01 Aug 2025 07:27
Last Modified:	01 Aug 2025 07:27
URI:	http://repository.its.ac.id/id/eprint/125982

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