Price clustering in Bitcoin
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TLDR
In this paper, the authors study the behavior of Bitcoin prices and find significant evidence of clustering at round numbers, with over 10% of prices ending with 00 decimals compared to other variations but there is no significant pattern of returns after the round number.About:
This article is published in Economics Letters.The article was published on 2017-10-01 and is currently open access. It has received 266 citations till now. The article focuses on the topics: Round number & Cryptocurrency.read more
Citations
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Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis
TL;DR: In this paper, the first empirical evidence on the relationship between trading volume and return volatility of the Bitcoin denominated in fifteen foreign currencies by investigating two competing hypotheses, i.e., mixture of distribution hypothesis (MDH) and sequential information arrival hypothesis (SIAH), was given.
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The Financial Market Effects of Cryptocurrency Energy Usage
TL;DR: Investigation of how Bitcoin's price volatility and the underlying dynamics of cryptocurrency's mining characteristics affect the energy markets, utilities companies, and green ETFs shows that continued cryptocurrency energy-usage impacts the performance of energy sector.
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Asymmetric Mean Reversion of Bitcoin Price Returns
TL;DR: In this article, the authors explore whether cryptocurrency returns, as represented by Bitcoin, exhibit similar asymmetric reverting patterns for minutely, hourly, daily and weekly returns between June 2010 and February 2018.
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Is it possible to establish the link between drug busts and the cryptocurrency market? Yes, we can
Laith Almaqableh,Damien Wallace,Vijay Pereira,Vikash Ramiah,Geoffrey Wood,Jose Francisco Veron,Imad A. Moosa,Alastair Watson +7 more
TL;DR: In this article , the authors explore the impact of 24 major drug busts on the systematic risk and return of the world cryptocurrency market and find that drug bust news tends to create uncertainty, and accordingly impart risk into cryptocurrency markets.
Posted Content
Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach to Forecasting
Thomas Walther,Tony Klein +1 more
TL;DR: The authors applied the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility of four highly capitalized Cryptocurrencies (Bitcoin, Etherium, Litecoin, and Ripple) as well as the Cryptocurrency index CRIX.
References
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The inefficiency of Bitcoin
TL;DR: In this article, the authors study the market efficiency of Bitcoin and find that returns are significantly inefficient over the full sample, but when split into two subsample periods, some tests indicate that Bitcoin is efficient in the latter period.
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Volatility estimation for Bitcoin: A comparison of GARCH models
TL;DR: In this article, the authors explore the optimal conditional heteroskedasticity model with regards to goodness-of-fit to Bitcoin price data and find that the best model is the AR-CGARCH model, highlighting the significance of including both a short run and a long run component of the conditional variance.
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Stock Price Clustering and Discreteness
TL;DR: In this paper, an econometric model of stock price clustering was derived and estimated, and it was shown that traders would frequently use odd sixteenths when trading low-price stocks, if exchange regulations permitted trading on sixteenth's.
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Can volume predict Bitcoin returns and volatility? A quantiles-based approach
TL;DR: In this article, a non-parametric causality-in-quantiles test was employed to analyse the causal relation between trading volume and Bitcoin returns and volatility, over the whole of their respective conditional distributions.
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The Economics of Bitcoin and Similar Private Digital Currencies
Gerald P. Dwyer,Gerald P. Dwyer +1 more
TL;DR: In this paper, the use of peer-to-peer networks and open-source software to stop double spending and create finality of transactions is discussed, and the rise of 24/7 trading on computerized markets in Bitcoin in which there are no brokers or other agents is discussed.