Introduction!

agplanetvs(40)

Published in

#cryptocurrency

Words

764

Reading

4 min

Listen

Play

Introduction
Bitcoin (BTC) is the most popular cryptocurrency with a capitalization of about $40.5 billion by
mid-2017. Launched in 2009, the Bitcon market is based on information technology infrastructure
For maintaining an accounting ledger while relying the processing transactions on the lack of central
authority. In contrast to traditional currencies, Bitcoin transactions do not rely on central banks, but
rather on a decentralized computer network to validate transactions and grow money supply . That is, Bitcoin is a currency unit that is transferred between pseudonymous addresses through
complex computational networks. Bitcoin users and investors have perceived huge financial
potential in the Bitcoin market, driving the Bitcoin price from US dollar parity in early 2011 to
about 1,500 $/BTC in mid-2017.
In the early stage (2010-2013), Bitcoin exchange was handled by Mt. Gox, an administration
system based on Shibuya, Japan. By the last months of 2013, Mt. Gox was handling about 70% of
transactions worldwide. In February 2014, Mt. Gox system suffered hacking attacks, resulting in the
theft of about 850,000 Bitcoins (about $450 million at the time) belonging to customers. In
February 2014, Mt. Gox suspended trading and filed for bankruptcy from creditors, and in April
42 2014 the company started liquidation process. As a consequence, the Bitcoin price suffered a loud
decrease from about 1,000 $/BTC to about 180 $/BTC. The aftermath of Mt. Gox bankruptcy
eroded the trust of customers on crystocurrencies. Bitfinex (owned by iFinex Inc.), an exchange
trading and currency-storage platform based out of Hong Kong, was established as the dominant
Bitcoin exchange platform. The main focus of Bitfinex was to improve informational security to
reduce risk of intruders. The subsequent price surge from levels of about 180 $/BTC to about 2,800
$/BTC by July 2017 motivated the surge of diverse exchange platforms (e.g., London-based
Spectrocoin and Cryptopay) specialized on crystocurrencies, with Bitcoin as the main security.
The absence of a regulatory agency and the relatively recent launching made Bitcoin a very
volatile and speculative currency. Since the functioning of the Bitcoin market does not rely on
policies from a central bank, the market is quite sensitive to real (e.g., economic, social and political) and fake (e.g., rumors) news. Also, the poorly defined liquidity conditions of the market
and the lack of certainty rules for investment realization add fragility to transactions, an effect that
is reflected as large price jumps and excessive volatility as compared to traditional currencies and
assets [2]. Still, many people have the belief that Bitcoin is a very risky currency for normal
transactions [3]. Besides, instigated by the Mt. Gox’s data leaking by late 2013, some doubts on the
informational efficiency of the Bitcoin market (of cryptocurrencies in general) have arisen in the
recent years. Bartos [4] reported that the Bitcoin returns follow the hypothesis of efficient markets
as it immediately adapts to publicly announced information. Urquhart [5] studied the period from
August 1st, 2010 to July 31st, 2016 and used automatic variance tests (AVR) to find that returns are
significantly inefficient over the scrutinized period. However, when the sample was splitted out into
two subsample periods, it was found that the Bitcoin market is efficient in the latter period (August
64 1st, 2013 to July 31st, 2016). Kurihara and Fukushima examined empirically whether or not
weekly price anomalies exist by checking the market efficiency of Bitcoin, finding that Bitcoin
transactions are becoming more efficient. Nadarajah and Chu [7] used power transformation of the
Bitcoin returns to show that that efficient market hypothesis is not fulfilled. Bariviera et al. used
detrended fluctuation analysis (DFA) over a sliding window to report that the Hurst exponent
changed significantly during the first years of existence of Bitcoin, tending to stabilize in recent
times, from early 2014 to date. Recently, Urquhart [9] found significant evidence of price clustering
at round numbers.
The aim of this work is to provide further results on the informational market efficiency of the
Bitcoin market. To this end, following the methodology by Bariviera et al. [9], the DFA
implemented over a sliding window was used to detect changes in long-range correlations of price
returns. For intraday data in the period from June 30, 2013 to June 3rd 75 , 2017, the results show that
the Bitcoin market is generally efficient within a confidence band of 95% after the Mt. Got’s
bankruptcy (February, 2014). However, some deviations from efficiency are observed for 2017,
coinciding with the huge price increase that led the price to about 2,500 $/BTC. Also, intraday datawith hourly frequency indicates important departures from the random behavior, with returns
showing anti-persistent dynamics over long periods.