Are cryptocurrencies connected to forex? A quantile cross-spectral approach
By Eduard Baumöhl. Finance Research Letters, 2019
152 citations recorded by the source corpus.
This paper aims to elucidate the connectedness between major forex currencies and cryptocurrencies using the quantile cross-spectral approach recently proposed by Barunik and Kley (2015). The sample covers six forex currencies and six cryptocurrencies over the period of 1 September 2015 to 29 December 2017. Compared with the results obtained from standard correlations and detrended moving-average cross-correlation analysis (DMCA), the quantile cross-spectral approach provides richer information on the dependence structure across different quantiles and frequencies. The most interesting result is that the intra-group dependencies are positive in the lower extreme quantiles, while inter-group dependencies are negative. This result holds in both the short- and long-term perspectives. Thus, it is worth diversifying between these two currency groups.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/f2240e555cfe422938ea825c13b86d9c7b0b03e9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
In Finance
Citations in the corpus
- A crypto safe haven against Bitcoin (2020, methodology): “Whilst the evidence for the safe haven hypothesis of stablecoins is rather weak, there is stronger evidence against the “stable” hypothesis given the non-zero reaction of stablecoins to one-minute price changes.”
- A time–frequency analysis of the impact of the Covid-19 induced panic on the volatility of currency and cryptocurrency markets (2020, background): “…markets have been attracting a vast esearch interest from the point of view of contagion, adversely mpacting portfolio risk management, strategic asset allocation, nd financial instruments pricing (Baumohl, 2019; Kristjanpoller nd Bouri, 2019; Malik and Umar, 2019; Celeste et al., 2020).”
- Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting (2019, methodology): “, 2018, Baur et al., 2018b). Accordingly, investors and traders in the Cryptocurrency market are eager to refine their knowledge of the determinants of volatility for the sake of risk and portfolio management. However, the related literature provides inconclusive findings and is generally limited in”