Analisis Efek Spillover antara Cryptocurrency dan Indeks Saham Asia: Perhitungan Risiko dengan Pendekatan EGARCH-EVT-Copula

Anisti, Jihan Ariqah (2025) Analisis Efek Spillover antara Cryptocurrency dan Indeks Saham Asia: Perhitungan Risiko dengan Pendekatan EGARCH-EVT-Copula. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Perkembangan cryptocurrency sebagai aset digital telah membawa dampak signifikan terhadap pasar keuangan global, termasuk pasar saham di Asia. Fenomena spillover antara cryptocurrency dan indeks saham menjadi topik yang semakin relevan dalam konteks manajemen risiko keuangan. Penelitian ini bertujuan untuk menganalisis efek spillover antara return cryptocurrency, khususnya Bitcoin dan Ethereum, dengan indeks saham Asia seperti Jakarta Composite Stock Exchange (JKSE) dan Nikkei 225 selama periode Januari 2017 hingga Desember 2024. Metodologi yang digunakan menggabungkan model Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH), Extreme Value Theory (EVT), dan Copula. Model EGARCH digunakan untuk mengestimasi volatilitas log-return dengan mempertimbangkan efek asimetris. EVT diterapkan pada residual untuk menangkap risiko ekstrem, sementara pendekatan Copula digunakan untuk memodelkan ketergantungan antara distribusi marjinal secara lebih fleksibel, khususnya pada kondisi ekstrem. Selanjutnya, simulasi Monte Carlo digunakan untuk menghitung nilai Value at Risk (VaR) dan Conditional Value at Risk (CVaR), serta Spillover Index Diebold-Yilmaz untuk mengukur transmisi risiko antar pasar. Hasil penelitian menunjukkan bahwa volatilitas return pada cryptocurrency dan indeks saham bersifat asimetris, dengan efek leverage yang signifikan di seluruh aset. Model EGARCH yang digunakan menunjukkan variasi struktur terbaik antar aset sesuai karakteristik masing-masing. Distribusi GPD–Normal–GPD berhasil menangkap risiko ekstrem, dengan hasil bahwa Bitcoin dan Ethereum memiliki ekor distribusi yang lebih berat dibandingkan indeks saham, menandakan risiko ekstrem yang lebih tinggi. Pendekatan copula mengungkap adanya ketergantungan ekstrem, khususnya di ekor bawah, pada sebagian besar pasangan aset, terutama antara cryptocurrency dan indeks saham. Nilai Value at Risk (VaR) dan Conditional Value at Risk (CVaR) yang lebih ekstrem muncul pada pasangan dengan ketergantungan tail bawah yang kuat. Selain itu, analisis spillover menunjukkan adanya transmisi risiko moderat antar pasar, dengan Bitcoin dan Ethereum sebagai kontributor utama terhadap volatilitas pasar global, sementara JKSE dan Nikkei cenderung berperan sebagai penerima risiko.
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The development of cryptocurrency as a digital asset has had a significant impact on global financial markets, including Asian stock markets. The spillover phenomenon between cryptocurrency and stock indices has become increasingly relevant in the context of financial risk management. This study aims to analyze the spillover effects between cryptocurrency returns, specifically Bitcoin and Ethereum with Asian stock indices, namely the Jakarta Composite Index (JKSE) and the Nikkei 225, during the period from January 2017 to December 2024. The methodology integrates the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model, Extreme Value Theory (EVT), and Copula approach. The EGARCH model is employed to estimate the log-return volatility while accounting for asymmetric effects. EVT is applied to the residuals to capture extreme risk, whereas the Copula approach models the dependence between marginal distributions more flexibly, especially under extreme conditions. Monte Carlo simulation is then used to calculate Value at Risk (VaR) and Conditional Value at Risk (CVaR), and the Diebold-Yilmaz Spillover Index is utilized to measure risk transmission across markets. The results reveal that return volatility in both cryptocurrency and stock indices is asymmetric, with significant leverage effects across all assets. The EGARCH model shows varying optimal structures across assets, reflecting their distinct characteristics. The GPD–Normal–GPD distribution successfully captures extreme risks, with findings indicating that Bitcoin and Ethereum exhibit heavier tails compared to stock indices, implying higher extreme risk. The copula approach uncovers significant tail dependence, particularly in the lower tail, among most asset pairs especially between cryptocurrencies and stock indices. More extreme VaR and CVaR values are observed in pairs with strong lower-tail dependence. Furthermore, the spillover analysis indicates moderate risk transmission across markets, with Bitcoin and Ethereum acting as major contributors to global market volatility, while JKSE and Nikkei tend to serve as risk receivers.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Copula, Cryptocurrency, EGARCH, EVT, Spillover, Copula, Cryptocurrency, EGARCH, EVT, Spillover
Subjects:	H Social Sciences > HA Statistics > HA30.3 Time-series analysis
Divisions:	Faculty of Mathematics, Computation, and Data Science > Actuaria > 94203-(S1) Undergraduate Thesis
Depositing User:	Jihan Ariqah Anisti
Date Deposited:	24 Jul 2025 08:21
Last Modified:	24 Jul 2025 08:21
URI:	http://repository.its.ac.id/id/eprint/121478

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