Some stylized facts of the Bitcoin market

TL;DR

This paper analyzes the statistical properties of Bitcoin's market, comparing it with traditional currencies, and investigates long-range dependence and self-similarity in Bitcoin returns from 2011 to 2017.

Contribution

It provides a detailed analysis of Bitcoin's return dynamics, highlighting the evolution of long memory and self-similarity over time using Hurst exponent analysis.

Findings

Hurst exponents changed significantly during Bitcoin's early years

Hurst exponents tend to stabilize in recent times

Bitcoin returns exhibit self-similar behavior

Abstract

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.