We examine asset properties of Bitcoin and its portfolio performance and discuss issues around the approval of Bitcoin spot ETFs. A deep learning-based predictive model is employed to analyze causality between Bitcoin and KOSPI index, and the similari...
We examine asset properties of Bitcoin and its portfolio performance and discuss issues around the approval of Bitcoin spot ETFs. A deep learning-based predictive model is employed to analyze causality between Bitcoin and KOSPI index, and the similarity between Bitcoin and other assets. Then, we analyze whether and how Bitcoin improves portfolio performance according to market volatility and relationship strength. We apply the same experimental framework to Ethereum to compare its performance with Bitcoin’s. We find that Bitcoin acting as a leading variable exhibits a strong causal relationship with the KOSPI index, and its return pattern is similar to that of multiple global indices and Technology Sector ETF. In portfolio simulations, Bitcoin contributes positively to return-maximization strategies, providing diversification benefits particularly during mid-volatility regimes. However, gold outperforms Bitcoin under low and high volatility, suggesting that Bitcoin serves better as a diversifier rather than a safe-haven asset. Also, portfolio performance is maximized when Bitcoin and KOSPI have non-linear causality. Findings imply that Bitcoin spot ETFs could be used as an investment asset in the domestic market.
However, several legal and practical issues need to be addressed for the Bitcoin spot ETF approval. These include the legal status of Bitcoin as an underlying asset and the designation of custodians Additionally, setting a reliable benchmark index price for Bitcoin is a prerequisite. Auditors should be prepared for internal control audit of custodians and valuation of ETFs. Furthermore, effective and strong regulatory mechanisms are necessary to protect retail investors.