Abstract
This study aims to investigate whether conditional higher moments offer additional and distinct information compared to lower moments in spillover effect analysis, and to examine their relevance for portfolio construction and hedging strategies. We use the autoregressive conditional density (ACD) model to estimate the conditional skewness and kurtosis of nine major cryptocurrency markets. We explore the higher moment spillovers among these markets using the Diebold Yilmaz spillover approach. The results confirm that the magnitude and direction of spillover effects vary across different moments in the cryptocurrency market, each providing unique insights. Additionally, we find that although the spillover effects exhibit variations over different time periods and market conditions, the skewness spillover and kurtosis spillover, which track the transmission of downside (upside) risk and tail risk respectively, demonstrate similarities in their patterns. These variations differ noticeably from the changes observed in volatility spillover, which tracks the transmission of volatility risk. Comparing the minimum connectedness portfolio (MCoP) based on different moment spillovers, we discover that the MCoP derived from higher moment spillovers exhibits superior hedge effectiveness and Sharpe ratios.
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