Some stylized facts of the Bitcoin market

By Aurelio Fernández Bariviera, Mar'ia Jos'e Basgall, Waldo Hasperué, Marcelo R. Naiouf. 2017

431 citations recorded by the source corpus.

In recent years a new type of tradable assets appeared, generically known as cryptocurrencies. Among them, the most widespread is Bitcoin. Given its novelty, this paper investigates some statistical properties of the Bitcoin market. This study compares Bitcoin and standard currencies dynamics and focuses on the analysis of returns at different time scales. We test the presence of long memory in return time series from 2011 to 2017, using transaction data from one Bitcoin platform. We compute the Hurst exponent by means of the Detrended Fluctuation Analysis method, using a sliding window in order to measure long range dependence. We detect that Hurst exponents changes significantly during the first years of existence of Bitcoin, tending to stabilize in recent times. Additionally, multiscale analysis shows a similar behavior of the Hurst exponent, implying a self-similar process.

Subfields: Condensed Matter Physics, Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/572271b7f4d35459aaa4d8d84c3b26c9f2380765

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Condensed Matter Physics

In Economics and Econometrics

In Statistical and Nonlinear Physics

Citations in the corpus

An Empirical Study on Modeling and Prediction of Bitcoin Prices With Bayesian Neural Networks Based on Blockchain Information (2018, background): “Various studies on statistical or economical properties and characterizations of Bitcoin prices refer to its capabilities as a financial asset; these research focus on statistical properties [4], [5], inefficiency of Bitcoin according to efficient market hypothesis [6], [7], hedging capability [8], ”
Datestamping the Bitcoin and Ethereum bubbles (2017, neutral): “To be considered as a currency (i.e. money), cryptocurrencies should serve as a medium of exchange, be used as a unit of account, and allow to store value; however, cryptocurrencies are barely managing to fulﬁl all those properties (Bariviera et al. [2017]).”
The impact of macroeconomic news on Bitcoin returns (2020, neutral): “…the relationship between cryptocurrencies and commodities such as oil and gold (Kang et al. [2019]; Celeste et al. [2019]), liquidity (as per Bariviera et al. [2017]) and interest rate and regulatory decisions across a variety of central banks and governing authorities (McHugh et al.…”
Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting (2019, result): “…Baek & Elbeck (2015) find no evidence of predictability, whereas later studies report contradicting evidence (Urquhart, 2016, Nadarajah & Chu, 2017, Bariviera, 2017, Kristoufek, 2018, Sensoy, 2019), which suggest the possibility to predict Bitcoin volatility.6 Lastly, our work is related to…”
Cryptocurrencies as a financial asset: A systematic analysis (2019, methodology): “Bariviera et al. [2017] investigated the statistical properties of the Bitcoin market, comparing Bitcoin and standard currencies dynamics and focuses on the analysis of returns at different time scales. The authors test the presence of long memory in return time series from 2011 to 2017, using trans”
Volatility estimation for Bitcoin: A comparison of GARCH models (2017, methodology): “Moreover, the presence of longmemory and persistent volatility (Bariviera et al., 2017) justifies the application of GARCH-type models.”
Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance (2018, neutral): “For a detailed introduction into the key concepts of cryptocurrencies and Bitcoin, we refer to Bariviera et al. (2017), Chuen (2015), Dwyer (2015), and Elendner et al. (2018). Cryptocurrencies, in particular Bitcoin, have been labeled the New Gold by some media, banks, and also data providers throug”
Rough volatility of Bitcoin (2019, background): “Many studies have investigated the statistical properties of Bitcoin, showing that stylized facts are also present in Bitcoin returns, see for example, Bariviera et al. (2017); Chu et al. (2015); Takaishi (2018).”
Testing Stylized Facts of Bitcoin Limit Order Books (2019, background): “…interest for several reasons: Leaving technological advances aside, cryptocurrency markets represent a unique opportunity to study properties of an emerging market for a largely unregulated asset, which does not (yet) “fulfill the main properties of a standard currency” (Bariviera et al. 2017).”