Abstract
This paper examines the behavior of Bitcoin and Ripple compared to the three fiat currencies, EURUSD, GBPUSD and CNYUSD, by comparing their volatility and VaR during the period extending from March 01, 2016 to February 28, 2019. EWMA, GARCH (1, 1), GARCH (p, q) and EGARCH (1, 1) were used to forecast volatilities. EWMA model outperformed the rest of the models for all of the selected fiat and cryptocurrencies during the in-sample period and for EURUSD, GBPUSD and Bitcoin during the out-of-sample period. GARCH (p, q) was the optimal model for the CNYUSD and Ripple in the out-of-sample period. Bitcoin and Ripple exhibit an asymmetry in their volatility which is significantly higher than all the volatilities of the studied currencies. When estimated volatilities were compared to the implied volatility, the GARCH (1, 1), GARCH (6, 6) and EWMA were the optimal models for the EURUSD, CNYUSD and GBPUSD, respectively for the in-sample period. VaR results were accepted for the EURUSD, GBPUSD and Bitcoin at all confidence levels. For the CNYUSD, VaR measures underestimated the risk at the 99% confidence level unlike Ripple’s VaR that was accepted at the 90% and 99% confidence levels. Our results suggest that Bitcoin and generally the cryptocurrencies market cannot act as alternatives to fiat currencies at the moment.
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Notes
- 1.
VaR is a standard risk measure which summarizes the downside risk and is defined as the maximum loss expected with a given probability over a specific period of time.
- 2.
Maximum Likelihood involves choosing values for the parameters corresponding to each model that maximize the chance of the data occurring.
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Naimy, V., Chidiac, J.E., Khoury, R.E. (2020). Volatility and Value at Risk of Crypto Versus Fiat Currencies. In: Abramowicz, W., Klein, G. (eds) Business Information Systems Workshops. BIS 2020. Lecture Notes in Business Information Processing, vol 394. Springer, Cham. https://doi.org/10.1007/978-3-030-61146-0_12
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