Dynamic Volatility Dependence Analysis Between Cryptocurrency and the Indonesian Stock Market Using the DCC-GARCH-Copula Approach

Anindya Zhafira Noer; Prilyandari Dina Saputri

doi:10.30998/faktorexacta.v19i2.1585

Authors

Anindya Zhafira Noer Hafizhah Author
Prilyandari Dina Saputri Sepuluh Nopember Institute of Technology Author

DOI:

https://doi.org/10.30998/faktorexacta.v19i2.1585

Keywords:

Bitcoin (BTC), Cryptocurrency, DCC-GARCH-Copula, IHSG

Abstract

The popularity of cryptocurrency as an investment instrument has surged in recent years despite its high volatility, particularly for Bitcoin (BTC) and Ethereum (ETH). This study analyzed the volatility dependence between BTC, ETH, and the Indonesia Composite Index (IHSG) using the DCC-GARCH-Copula approach. The data consisted of daily closing prices from January 1, 2022, to December 31, 2024. The analysis began with univariate ARIMA-GARCH modeling, followed by the estimation of the DCC-GARCH model, and concluded with non-linear dependence modeling using Gaussian and Student-t copulas. The results indicated that BTC and ETH exhibited significantly higher volatility compared to the IHSG. The average dynamic correlation between IHSG-BTC and IHSG-ETH was relatively low, whereas the correlation between BTC-ETH was strongly positive, averaging 0.8399. The Student-t copula model demonstrated superior performance in capturing dependencies, especially during extreme events (tail dependence), with the highest tail dependence observed in the BTC-ETH pair, averaging 0.3798. These findings suggest a weak volatility connection between the stock market and cryptocurrencies, but a strong interdependence among crypto assets themselves, indicating that cryptocurrencies may serve as potential diversification instruments, albeit with considerable extreme risk that must be managed.

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