Semi-strong efficiency of Bitcoin

Abstract This research examines the semi-strong efficiency of Bitcoin in the Bitstamp and Mt.Gox markets, showing how the digital currency responds to monetary policy and Bitcoin events. On the one hand, we observe that Bitcoin has become more efficient over time in relation to its own events. On the other hand, Bitcoin is not affected by monetary policy news, highlighting the absence of any kind of control on Bitcoin. These findings are relevant for investors and policymakers since Bitcoin is a financial asset without any connection to the measures of central banks.

[1]  Steven Pennings,et al.  The impact of monetary policy on financial markets in small open economies: More or less effective during the global financial crisis? , 2015 .

[2]  Melanie Swan,et al.  Blockchain: Blueprint for a New Economy , 2015 .

[3]  Aviral Kumar Tiwari,et al.  Informational efficiency of Bitcoin—An extension , 2018 .

[4]  Shelton Peiris,et al.  A new look at Cryptocurrencies , 2018 .

[5]  Weihua Ruan,et al.  Time-varying long-term memory in Bitcoin market , 2017, Finance Research Letters.

[6]  M. Elbeck,et al.  Bitcoins as an investment or speculative vehicle? A first look , 2015 .

[7]  Andrew Urquhart.  The Inefficiency of Bitcoin , 2016 .

[8]  Thomas S. Kim.  On the transaction cost of Bitcoin , 2017 .

[9]  Eng-Tuck Cheah,et al.  Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin , 2015 .

[10]  P. Ciaian,et al.  Virtual Relationships: Short- and Long-run Evidence from BitCoin and Altcoin Markets , 2017, 1706.07216.

[11]  D. Baur,et al.  Bitcoin, gold and the US dollar – A replication and extension , 2017, Finance Research Letters.

[12]  A. Tiwari,et al.  Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions , 2016 .

[13]  Andrew Urquhart.  Price clustering in Bitcoin , 2017 .

[14]  S. Corbet,et al.  Datestamping the Bitcoin and Ethereum Bubbles , 2017, Finance Research Letters.

[15]  Ladislav Kristoufek,et al.  BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era , 2013, Scientific Reports.

[16]  E. Fama.  The Behavior of Stock-Market Prices , 1965 .

[17]  Paolo Pasquariello,et al.  On the Volatility and Comovement of U.S. Financial Markets Around Macroeconomic News Announcements , 2009 .

[18]  S. Corbet,et al.  Cryptocurrency Reaction to FOMC Announcements: Evidence of Heterogeneity Based on Blockchain Stack Position , 2018, Journal of Financial Stability.

[19]  Paraskevi Katsiampa.  Volatility estimation for Bitcoin: A comparison of GARCH models , 2017 .

[20]  S. Nadarajah,et al.  On the inefficiency of Bitcoin , 2017 .

[21]  Larisa Yarovaya,et al.  Exploring the Dynamic Relationships between Cryptocurrencies and Other Financial Assets , 2017 .

[22]  Lars Ivar Hagfors,et al.  On the Hedge and Safe Haven Properties of Bitcoin: Is it Really More than a Diversifier? , 2016 .

[23]  A. H. Dyhrberg.  Hedging capabilities of bitcoin. Is it the virtual gold , 2016 .

[24]  P. Ciaian,et al.  The economics of BitCoin price formation , 2014, 1405.4498.

[25]  Zhengjun Zhang,et al.  Informed trading in the Bitcoin market , 2017, Finance Research Letters.

[26]  A. H. Dyhrberg.  Bitcoin, gold and the dollar – A GARCH volatility analysis , 2016 .

[27]  A. F. Bariviera.  The Inefficiency of Bitcoin Revisited: A Dynamic Approach , 2017, 1709.08090.