This paper uses a dynamic conditional correlation model to examine whether Bitcoin can act as a hedge and safe haven for major world stock indices, bonds, oil, gold, the general commodity index and the US dollar index. Daily and weekly data span from July 2011 to December 2015. Overall, the empirical results indicate that Bitcoin is a poor hedge and is suitable for diversification purposes only. However, Bitcoin can only serve as a strong safe haven against weekly extreme down movements in Asian stocks. We also show that Bitcoin hedging and safe haven properties vary between horizons.
In this study, we analyse whether Bitcoin can hedge uncertainty using daily data for the period of 17 th March, 2011, to 7 th October, 2016. Global uncertainty is measured by the first principal component of the VIXs of 14 developed and developing equity markets. We first use wavelets to decompose Bitcoin returns into various frequencies, i.e., investment horizons. Then, we apply standard OLS regressions and observe that uncertainty negatively affects raw Bitcoin return and its longer-term movements. However, given the heavy tails of the variables, we rely on quantile methods and reveal much more nuanced and interesting results. Quantile regressions indicate that Bitcoin does act as a hedge against uncertainty, that is, it reacts positively to uncertainty at both higher quantiles and shorter frequency movements of Bitcoin returns. Finally, when we use quantile-on-quantile regressions, we observe that hedging is observed at shorter investment horizons, and at both lower and upper ends of Bitcoin returns and global uncertainty.
Prior studies on the price formation in the Bitcoin market consider the role of Bitcoin transactions at the conditional mean of the returns distribution. This study employs in contrast a non-parametric causality-in-quantiles test to analyse the causal relation between trading volume and Bitcoin returns and volatility, over the whole of their respective conditional distributions. The nonparametric characteristics of our test control for misspecification due to nonlinearity and structural breaks, two features of our data that cover 19th December 2011 to 25th April 2016. The causality-in-quantiles test reveals that volume can predict returns-except in Bitcoin bear and bull market regimes. This result highlights the importance of modelling nonlinearity and accounting for the tail behaviour when analysing causal relationships between Bitcoin returns and trading volume. We show, however, that volume cannot help predict the volatility of Bitcoin returns at any point of the conditional distribution.
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