Bitcoin, gold and the US dollar – A replication and extension

By Dirk G. Baur, Thomas Dimpfl, Konstantin Kuck. Finance Research Letters, 2017

468 citations recorded by the source corpus.

Dyhrberg [2016. Bitcoin, gold and the dollar – A GARCH volatility analysis. Finance Research Letters 16, 85–92] analyzes the relationship between Bitcoin, gold and the US dollar and states that Bitcoin can be classified as something in between gold and the US dollar. This paper uses the same sample and econometric models to replicate the findings and demonstrates that exact replication is not possible and that alternative statistical methods provide more reliable, yet very different results. The findings based on the original sample and an extended sample period show that Bitcoin exhibits distinctively different return, volatility and correlation characteristics compared to other assets including gold and the US dollar.

Subfields: Economics and Econometrics, Information Systems

View Paper: https://www.semanticscholar.org/paper/6eb7bb60ded45918cc3e3821c58b277cb53b7009

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Citations in the corpus

Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance (2018, unknown): “The sensitivity of results regarding the underlying distribution is also discussed in Baur et al. (2017) whose findings are in line with those presented above. Thus, we conjecture that using a better suited distribution reveals the property of asymmetric effects for Bitcoin as shown by Catania & Gra”
Cryptocurrencies as a financial asset: A systematic analysis (2019, methodology): “Baur et al. [2017] analysed the statistical properties of Bitcoin to find that it is uncorrelated with traditional asset classes in periods of financial turmoil.”
The relationship between implied volatility and cryptocurrency returns (2020, background): “While Corbet et al. [2019] have provided a concise systematic review of the literature associated with cryptocurrency markets at large, they note the broad variety in research that provides evidence outlining improvements in the market efficiency of cryptocurrencies. Tiwari et al. [2018] identify si”
Cryptocurrency trading: a comprehensive survey (2020, background): “[16] extended the research of Dyhrberg et al.”