Hedging capability of cryptocurrencies toward U.S. stock market returns: Does structural change matter?

Gan, Han Xin and Lim, Sye Wei and Loh, Poh Wai and Then, Min Kong (2023) Hedging capability of cryptocurrencies toward U.S. stock market returns: Does structural change matter? Final Year Project, UTAR.

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Abstract

This research examines the relationship between cryptocurrency market and the U.S. market following a structural shift in China. The study reveals a positive correlation between the returns of the U.S. stock market and cryptocurrencies. Time series data collected on a weekly basis, spanning from January 4, 2017, to March 1, 2023, is utilized for this research. This research data has gone through various tests such as Augmented Dickey-Fuller (ADF) Test, Phillips-Perron (PP) Test, Generalized Autoregressive Conditional Heteroscedasticity model (GARCH), Feasible Generalized Least Square (FGLS), Jarque-Bera test, Breusch-Godfrey LM test, and ARCH Lagrange Multiplier (LM) Test. Hence, the regression model has proven to free from unit root, heteroscedasticity, autocorrelation and error term's normal distribution. The FGLS model is applied is to examine the hedging capability of cryptocurrencies against the U.S. stock market return before and after the structural change. The findings indicates that before the structural change cryptocurrencies return and U.S. stock market return exhibit a positive coefficient but insignificance. Whereas the outcome of cryptocurrencies returns and U.S stock market return becomes significant and positively correlated after the structural change. Furthermore, the finding of this research indicate that all independent variables have positive relationship toward U.S stock market. In brief, these results bring significant implication to investors, policymakers, and future researchers.

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