The inefficiency of Bitcoin

By Andrew Urquhart. 2016

1,185 citations recorded by the source corpus.

Bitcoin has received much attention in the media and by investors in recent years, although there remains scepticism and a lack of understanding of this cryptocurrency. We add to the literature on Bitcoin by studying the market efficiency of Bitcoin. Through a battery of robust tests, evidence reveals that returns are significantly inefficient over our full sample, but when we split our sample into two subsample periods, we find that some tests indicate that Bitcoin is efficient in the latter period. Therefore we conclude that Bitcoin in an inefficient market but may be in the process of moving towards an efficient market.

Subfields: Economics and Econometrics, Information Systems

View Paper: https://www.semanticscholar.org/paper/99d1e84f089518c9f74a9b4487a95caa794fde9c

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Citations in the corpus

Should investors include Bitcoin in their portfolios? A portfolio theory approach (2020, background): “Dwyer (2015) shows that the average monthly volatility of Bitcoin is higher than that of gold or a set of foreign currencies while Urquhart (2016) shows that Bitcoin returns are inefficient, which is supported by Nadarajah and Chu (2017) and Bariviera (2017).”
The predictive power of public Twitter sentiment for forecasting cryptocurrency prices (2020, background): “From a research perspective, the cryptocurrency's market e ciency is researched by Urquhart (2016), who observed Bitcoin prices between 2010 and 2016, and discovers that the Bitcoin market is ine cient but might be moving towards a more e cient market.”
Cryptocurrencies as a financial asset: A systematic analysis (2019, background): “Urquhart (2018). Optimal vs naïve diversification in cryptocurrencies.”
Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks (2020, neutral): “The literature on cryptocurrencies is growing, with many papers reporting the inefficiency of Bitcoin (Urquhart 2016; Khuntia and Pattanayak 2018; Nadarajah and Chu 2018; Tiwari et al 2018), the hedging and diversification benefits (Bouri et al 2017; Corbet et al 2018a; Urquhart and Zhang 2018;…”
On the inefficiency of Bitcoin (2017, methodology): “A plot of the data is shown in Figure 1 in Urquhart (2016).”
The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies (2019, positive): “The results on improved efficiency at intraday price levels are in line with the findings of Urquhart (2016) and Bariviera (2017) on the improved efficiency at the daily price levels.”
Statistical properties and multifractality of Bitcoin (2017, methodology): “By examining the market efficiency of Bitcoin with the Hurst exponent, Ref.[8] finds that the Hurst exponent is less than 0.”
Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios (2019, background): “In the meantime, authors such as Urquhart (2016); Caporale et al. (2018), as well as, Sensoy (2018) emphasize that the Bitcoin market is rather becoming more efficient over time.”
Testing for Bubbles in Cryptocurrencies with Time-Varying Volatility (2018, neutral): “Urquhart (2016) shows that the Bitcoin market is not weak-form market efficient, while Nadarajah and Chu (2017) use odd-power transformations of returns to obtain market efficiency.”
An empirical investigation of volatility dynamics in the cryptocurrency market (2019, positive): “More specifically, in a relatively early study of the efficiency of Bitcoin, Urquhart (2016) concluded that the Bitcoin market is an inefficient market, although it could be in the process of becoming an efficient market.”
The asymmetric effect of bitcoin on altcoins: evidence from the nonlinear autoregressive distributed lag (NARDL) model (2020, background): “2018), the efficiency of cryptocurrencies (Urquhart, 2016; Sensoy, 2019), hedging capabilities of cryptocurrencies against other assets (Bouri et al.”