How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets

Dyhrberg, Anne Haubo; Foley, Sean; Švec, Jiří

doi:10.1016/j.econlet.2018.07.032

Cited by 200 publications

(106 citation statements)

References 23 publications

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“…We find an average bid-ask spread of 0.97 bp with a distribution skewed towards lower bid-ask spreads (median spread of 0.16 bp, skewness ≈ 17). For a similar time period but different exchanges, Dyhrberg et al (2018) find comparable average quoted bid-ask spreads ranging from 0.54 bp to 7.8 bp and point out that these are "significantly lower than the average quoted (effective) spread [...] of stocks on the NYSE" (Dyhrberg et al 2018, p. 141). However, taking into account liquidity deeper into the order book, we find that liquidity costs rise fast for larger volumes ω: Two-sided VWAP spreads for 1 BTC are on average twice as high as the bid-ask spread, and rise by roughly one order of magnitude (8.37 bp) for a volume of 10 5 USD, which still is a relatively small amount for traditional institutional investors.…”

Section: Distribution Of Volume At the (Best) Bid And Askmentioning

confidence: 96%

“…Donier and Bonart (2015) use trade data to reconstruct "metaorders" and investigate the price impact of these orders. Other works focus on stylized facts of price time series (Bariviera et al 2017;Brandvold et al 2015;Chan et al 2017;Chu et al 2017;Easwaran et al 2015;Zargar and Kumar 2019;Zhang et al 2018) or the liquidity at the best bid and best ask-see Dimpfl (2017) and Dyhrberg et al (2018).…”

Section: Introductionmentioning

confidence: 99%

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Testing Stylized Facts of Bitcoin Limit Order Books

Schnaubelt

Rende

Krauß

2019

JRFM

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The majority of electronic markets worldwide employ limit order books, and the recently emerging exchanges for cryptocurrencies pose no exception. With this work, we empirically analyze whether commonly observed empirical properties from established limit order exchanges transfer to the cryptocurrency domain. Based on the literature, we establish a structured methodological framework to conduct analyses in a systematic and comprehensive way. We then present results from a unique and extensive limit order data set acquired from major cryptocurrency exchanges for the currency pair Bitcoin to US Dollar. We recover many observations from mature markets, such as a symmetry between the average ask and the average bid side of the order book, autocorrelation in returns on the smallest time scales only, volatility clustering and the timing of large trades. We also observe some idiosyncrasies: The distributions of trade size and limit order prices deviate from commonly observed patterns. Also, we find limit order books to be relatively shallow and liquidity costs to be relatively high when compared to established markets.

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Section: Distribution Of Volume At the (Best) Bid And Askmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Testing Stylized Facts of Bitcoin Limit Order Books

Schnaubelt

Rende

Krauß

2019

JRFM

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“…Giá Bitcoin có đặc điểm là chịu sự tác động của giá trong quá khứ và biến động rất lớn qua thời gian [2][3][4][5] . Với những đặc trưng như vậy, Bitcoin được xem như là tài sản đầu cơ [6][7][8] . Xét về tính hiệu quả thì bằng chứng về các nghiên cứu còn khá mâu thuẫn với nhau.…”

Section: Giới Thiệuunclassified

“…Việc hiểu các đặc trưng của tiền ảo giúp nhà đầu tư đánh giá tốt hơn và đưa ra quyết định chính xác hơn. Bitcoin được xem như là một loại tài sản tài chính có thể được sử dụng để đầu cơ chứ không phải phương tiện trao đổi [6][7][8][24][25][26][27] . Hiệu quả thị trường Bitcoin được đánh giá dựa trên giả thuyết thị trường hiệu quả [28][29][30][31][32] và bước ngẫu nhiên [33][34][35][36] .…”

Section: Cơ Sở Lý Thuyếtunclassified

Does Bitcoin share the same characteristics as a financial asset? Empirical evidence through the monetary policy

Thư

Dương

2020

Sci. Tech. Dev. J. Econ. Law. Manag.

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The cryptocurrency market, especially Bitcoin, has been received much attention from investors in the market. They often pay attention to which factors determine Bitcoin prices in order to make an investment decision more correctly. Therefore, the research focuses on the determinants of Bitcoin prices in the market based on previous studies relevant to stocks. In addition, to control variables including stock prices, gold prices, and exchange rates, the study also emphasizes on the monetary policy of the two great countries considered to have a strong influence on the volatility of the cryptocurrency market, the US and China. Data in the research are collected from reliable sources (coinmarketcap.com for Bitcoin data and Euromonitor for data on interest rates of the monetary policy). The study collects daily data for Bitcoin prices and monthly data for macroeconomic variables in the period of 2010 – 2018. With regard to the time series data, the research applies two econometric methods, GARCH and EGARCH, to evaluate the difference between positive and negative shocks of the monetary policy towards Bitcoin prices. The results indicate that interest rates of the Chinese and American monetary policy have a converse relationship with Bitcoin prices. Besides, control variables show a statistically significant association with Bitcoin prices. In conclusion, the research suggests that Bitcoin has the characteristics of a financial asset based on its similarities over determinants between stocks and Bitcoin.

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“…Interestingly, there are some researches that have evaluated the microscopic structure in the Bitcoin market. In more detail, while Dyhrberg et al (2018) initially examined the transaction costs as well as liquidity from market structures, Li and Wang (2017) conducted an empirical study to examine the technological and economic determinants of cryptocurrency exchange rates. These studies provided insights of large factors such as news public interest (Google search, Wiki views, Twitter, Facebook, and Forum), user volume trading (volume and frequency), Bitcoin amount, hash rate, difficulty in other markets (Gold and stocks), financial stress, and economy fundamentals.…”

Section: Bitcoin and Cryptocurrency Marketsmentioning

confidence: 99%

Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas

Huynh

2019

JRFM

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This paper contributes a shred of quantitative evidence to the embryonic literature as well as existing empirical evidence regarding spillover risks among cryptocurrency markets. By using VAR (Vector Autoregressive Model)-SVAR (Structural Vector Autoregressive Model) Granger causality and Student’s-t Copulas, we find that Ethereum is likely to be the independent coin in this market, while Bitcoin tends to be the spillover effect recipient. Our study sheds further light on investigating the contagion risks among cryptocurrencies by employing Student’s-t Copulas for joint distribution. This result suggests that all coins negatively change in terms of extreme value. The investors are advised to pay more attention to ‘bad news’ and moving patterns in order to make timely decisions on three types (buy, hold, and sell).

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How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets

Cited by 200 publications

References 23 publications

Testing Stylized Facts of Bitcoin Limit Order Books

Testing Stylized Facts of Bitcoin Limit Order Books

Does Bitcoin share the same characteristics as a financial asset? Empirical evidence through the monetary policy

Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas

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