Hedging capabilities of bitcoin. Is it the virtual gold?

Dyhrberg, Anne Haubo

doi:10.1016/j.frl.2015.10.025

Cited by 795 publications

(474 citation statements)

References 6 publications

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“…Although the literature on Bitcoin is limited overall, there are still several related studies. Dyhrberg (2016a) investigated the hedging capabilities of Bitcoin by applying the asymmetric GARCH methodology and showed that Bitcoin can clearly be used as a hedge against stocks in the Financial Times Stock Exchange Index and against the American dollar in the shortterm. Dyhrberg (2016b) explored the financial asset capabilities of Bitcoin using GARCH models and showed several similarities to gold and the dollar indicating hedging capabilities and advantages as a medium of exchange.…”

Section: Literature Reviewmentioning

confidence: 99%

GARCH Model With Fat-Tailed Distributions and Bitcoin Exchange Rate Returns

Liu¹,

Shao²,

Wei³

et al. 2017

Journal of Accounting, Business and Finance Research

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In the era of diminishing power from US dollar and increasing competition among world currencies, Bitcoin, as a completely new concept as a medium of exchange, has received increasing attentions over the world. Nowadays, Bitcoin also becomes an investment vehicle, which carries attractive opportunities but also significant risks for the investment community. In this paper, we have compared the empirical performance of a newly-developed heavy-tailed distribution, the normal reciprocal inverse Gaussian (NRIG), with the most popular heavy-tailed distribution, the Student's t distribution, under the GARCH framework in fitting the daily Bitcoin exchange rate returns. Our results indicate the heavy-tailed distribution has better performance in capture the daily Bitcoin exchange rate returns dynamics than the standard normal distribution. Our results also show the older fashioned Student's t distribution still performs better than the new heavy-tailed distribution.

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Section: Literature Reviewmentioning

confidence: 99%

GARCH Model With Fat-Tailed Distributions and Bitcoin Exchange Rate Returns

Liu¹,

Shao²,

Wei³

et al. 2017

Journal of Accounting, Business and Finance Research

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“…They found that Bitcoin prices were influenced by popularity, but also that web content and Bitcoin prices had some predictable power. Dyhrberg (2016a) applied the asymmetric GARCH methodology to explore the hedging capabilities of Bitcoin. It was shown that Bitcoin can be used as a hedge against stocks in the Financial Times Stock Exchange Index and against the American dollar in the short term.…”

Section: Introductionmentioning

confidence: 99%

GARCH Modelling of Cryptocurrencies

Chu

Chan

Nadarajah

et al. 2017

JRFM

274

165

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With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms of five criteria. Conclusions are drawn on the best fitting models, forecasts and acceptability of value at risk estimates.

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“…Bouri et al (2016) examine the volatility persistence in the Bitcoin market. However, Dyhrberg (2015a) highlights the hedging ability of Bitcoin against the USD/EUR and USD/GBP exchange rates and UK equities, whereas Dyhrberg (2015b) situates the hedging capability of Bitcoin somewhere _________________________ 1 Dwyer (2015) explained in detail the principles of Bitcoin.…”

Section: Introductionmentioning

confidence: 99%

On the return-volatility relationship in the Bitcoin market around the price crash of 2013

2017

Self Cite

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The authors examine the relation between price returns and volatility changes in the Bitcoin market using a daily database denominated in US dollar. The results for the entire period provide no evidence of an asymmetric return-volatility relation in the Bitcoin market. The authors test if there is a difference in the return-volatility relation before and after the price crash of 2013 and show a significant inverse relation between past shocks and volatility before the crash and no significant relation after. This finding shows that, prior to the price crash of December 2013, positive shocks increased the conditional volatility more than negative shocks. This inverted asymmetric reaction of Bitcoin to positive and negative shocks is contrary to what one observes in equities. As leverage effect and volatility feedback do not adequately explain this reaction, the authors propose the safe-haven effect (Baur, Asymmetric volatility in the gold market, 2012). They highlight the benefits of adding Bitcoin to a US equity portfolio, especially in the pre-crash period. Robustness analyses show, among others, a negative relation between the US implied volatility index (VIX) and Bitcoin volatility. Those additional analyses further support the findings and provide useful information for economic actors who are interested in adding Bitcoin to their equity portfolios or are curious about the capabilities of Bitcoin as a financial asset. JEL G11 G15

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Hedging capabilities of bitcoin. Is it the virtual gold?

Cited by 795 publications

References 6 publications

GARCH Model With Fat-Tailed Distributions and Bitcoin Exchange Rate Returns

GARCH Model With Fat-Tailed Distributions and Bitcoin Exchange Rate Returns

GARCH Modelling of Cryptocurrencies

On the return-volatility relationship in the Bitcoin market around the price crash of 2013

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