Follow blockchain research across journals, conferences, and preprint repositories.
2,329 results · page 86 of 98
Angelika Kokkinaki, Svetlana Sapuric, Ifigenia Georgiou
No abstract is available for this record.
Chen Feng, Nan Li, M.H. Franco Wong, Mingyue Zhang
No abstract is available for this record.
Sandip Mukherji
This paper studies 60 months of recent returns to examine relationships between bitcoin and 16 exchange- traded funds of currencies, bonds, stocks, commodities, and alternative assets. Bitcoin provides much higher returns, positive skewness, volatility and extreme returns, than all the other assets. Only stocks offer a better risk-return tradeoff than bitcoin. Bitcoin returns have very weak positive correlations with stocks, commodities, and alternatives. Only two funds of stocks and commodities have significant explanatory power of about 3% each for bitcoin returns. The full model of all the 16 funds explains only 15.09% of bitcoin returns. A partial model, with the six funds that are significant in the full model, explains 12.78% of bitcoin returns; 3 stock funds and 1 commodity fund have significant coefficients in this model. These findings indicate that bitcoin is a unique asset which is only weakly related to stocks and commodities. The results also show that small allocations to bitcoin improve the risk-return tradeoffs of stock and bond portfolios.
Jiatao Liu, Ian W. Marsh, Paolo Mazza, Mikaël Petitjean
No abstract is available for this record.
Serkan Çankaya, Elçin Aykaç, Mefule Findikci
No abstract is available for this record.
Siddharth M. Bhambhwani, Stefanos Delikouras, George M. Korniotis
No abstract is available for this record.
Stavros Stavroyiannis
The overall performance of a portfolio is the utmost measure of success for the skills of the portfolio manager. The Sharpe ratio and the modified Sharpe ratio have been some of the most referenced standards used in finance, to evaluate the efficiency of funds and hedge fund managers, however; such an ordering should be accompanied by proper statistical inference. In this work we examine whether Bitcoin can diversify significantly a reference portfolio composed from the five best performers of the Dow Jones industrial average in 2017 that is, Apple, Boeing, Caterpillar, Visa, and Walmart. The portfolios are constructed via analytical solutions in the mean-variance framework, constrained optimisation for the cases of long-only and risk-parity portfolios, and an equal weight strategy. The statistical significance of the Sharpe and modified Sharpe ratio differences is examined via a variety of tests. The results indicate that Bitcoin can significantly improve only the Sharpe and modified Sharpe ratios of the minimum variance and risk-parity portfolios. On the efficient frontier, the tangent portfolios are dominated by the traditional stocks.
Alexander Brauneis, Roland Mestel, Ryan Riordan, Erik Theissen
No abstract is available for this record.
Rüdiger Fahlenbrach, Marc Frattaroli
We conduct a detailed analysis of investors in successful initial coin offerings (ICOs). The average ICO has 4700 contributors. The median participant contributes small amounts and many investors sell their tokens before the underlying product is developed. Large presale investors obtain tokens at a discount and flip part of their allocation shortly after the ICO. ICO contributors lack the protections traditionally afforded to investors in early-stage financing. Nevertheless, returns 9 months after the ICO are positive on average, driven mostly by an increase in the value of the Ethereum cryptocurrency.
Niranjan Sapkota, Klaus Grobys
This paper explores whether asset market equilibria in cryptocurrency markets do exist. In doing so, it distinguishes between privacy and non-privacy coins. Most recently, privacy coins have attracted increasing attention in the public debate as non-privacy cryptocurrencies, such as Bitcoin, do not satisfy some users’ demands for anonymity. Analyzing ten cryptocurrencies with the highest market capitalization in each submarket in the 2016–2018 periods, we find that privacy coins exhibit a distinct market equilibrium. Contributing to the current debate on the market efficiency of cryptocurrency markets, our findings provide evidence of market inefficiency. Moreover, the asset market equilibrium of privacy coins appears to originate from non-privacy coins with highest market capitalizations. We argue that the reason for this finding could be that non-privacy coins may be the first choice for criminals who might prefer cryptocurrencies exhibiting both a high level of anonymity and liquidity.
Amélie Charles, Olivier Darné
In this paper we study the daily volatility of four cryptocurrencies (BitCoin, Dash, LiteCoin, and Ripple) from June 2014 to November 2018. We first show that the cryptocurrency returns are strongly characterized by the presence of jumps as well as structural breaks (except Dash). Then, we estimate four GARCH-type models that capture short memory (GARCH), asymmetry (APARCH), strong persistence (IGARCH), and long memory (FIGARCH) from (i) original returns, (ii) jump-filtered returns, and (iii) jump-filtered returns with structural breaks. Results indicate the importance to take into account the jumps and structural breaks in modelling volatility of the cryptocurrencies. It appears that the cryptocurrency returns are well modelled by infinite persistence (BitCoin, Dash, and LiteCoin) or long memory (Ripple) with a Student-t distribution.
Richard K. Lyons, Ganesh Viswanath-Natraj
We take this question to be isomorphic to, "What Keeps Fixed Exchange Rates Fixed?" and address it with analysis familiar in exchange-rate economics. Stablecoins solve the volatility problem by pegging to a national currency, typically the US dollar, and are used as vehicles for exchanging national currencies into non-stable cryptocurrencies, with some stablecoins having a ratio of trading volume to outstanding supply exceeding one daily. Using a rich dataset of signed trades and order books on multiple exchanges, we examine how peg-sustaining arbitrage stabilizes the price of the largest stablecoin, Tether. We find that stablecoin issuance, the closest analogue to central-bank intervention, plays only a limited role in stabilization, pointing instead to stabilizing forces on the demand side. Following Tether's introduction to the Ethereum blockchain in 2019, we find increased investor access to arbitrage trades, and a decline in arbitrage spreads from 70 to 30 basis points. We also pin down which fundamentals drive the two-sided distribution of peg-price deviations: Premiums are due to stablecoins' role as a safe haven, exhibiting, for example, premiums greater than 100 basis points during the COVID-19 crisis of March 2020; discounts derive from liquidity effects and collateral concerns.
Stefano Bistarelli, Alessandra Cretarola, Gianna Figà‐Talamanca, Ivan Mercanti · 5 authors
No abstract is available for this record.
Alexander Brauneis, Roland Mestel, Ryan Riordan, Erik Theissen
No abstract is available for this record.
Lennart Ante
No abstract is available for this record.
Niranjan Sapkota, Klaus Grobys
Cryptocurrencies employ different consensus protocols to verify transactions. While the Proof-of-Work consensus protocol is the most energy consuming protocol, Proof-of-Stake and Hybrid consensus protocols have been introduced which consume considerably less energy. We employ portfolio analysis to explore whether energy is a fundamental economic factor affecting cryptocurrency prices. Surprisingly, our results suggest that, on average, cryptocurrencies employing Proof-of-Work consensus protocols do not generate returns that are significantly different from those that incorporate Proof-of-Stake consensus protocols. Even more surprising is that our results show that cryptocurrencies that incorporate Hybrid consensus protocols generated significantly higher average return than the other groups. A possible explanation for that phenomenon may be that investors’ demand for cryptocurrencies that they perceive as offering more trust is larger than for those that carry potential risks of blockchain manipulation.
Gülüzar Kurt Gümüş, Yusuf Gümüş, Ayşegül Çimen
No abstract is available for this record.
Tobias Burggraf
No abstract is available for this record.
Jun Deng, Huifeng Pan, Shuyu Zhang, Bin Zou
No abstract is available for this record.
Roberto Frota Décourt, Usman W. Chohan, Maria Letizia Perugini
No abstract is available for this record.
Zura Kakushadze, Willie Yu
We give an algorithm and source code for a cryptoasset statistical arbitrage alpha based on a mean-reversion effect driven by the leading momentum factor in cryptoasset returns discussed in https://ssrn.com/abstract=3245641. Using empirical data, we identify the cross-section of cryptoassets for which this altcoin-Bitcoin arbitrage alpha is significant and discuss it in the context of liquidity considerations as well as its implications for cryptoasset trading.
Simon Mayer
No abstract is available for this record.
Guglielmo Maria Caporale, Alex Plastun
Abstract This paper examines whether there exists a momentum effect after one-day abnormal returns in the cryptocurrency market. For this purpose, a number of hypotheses of interest are tested for the Bitcoin, Ethereum and Litecoin exchange rates vis-à-vis the US dollar over the period 01.01.2015–01.09.2019, specifically whether or not: (H1) the intraday behavior of hourly returns is different on abnormal days compared to normal days; (H2) there is a momentum effect on days with abnormal returns, and (H3) after one-day abnormal returns. The methods used for the analysis include various statistical methods as well as a trading simulation approach. The results suggest that hourly returns during the day of positive/negative abnormal returns are significantly higher/lower than those during the average positive/negative day. The presence of abnormal returns can usually be detected before the day ends by estimating specific timing parameters. Prices tend to move in the direction of the abnormal returns till the end of the day when it occurs, which implies the existence of a momentum effect on that day giving rise to exploitable profit opportunities. This effect (together with profit opportunities) is also observed on the following day. In two cases (BTCUSD positive abnormal returns and ETHUSD negative abnormal returns), a contrarian effect is detected instead.
Savva Shanaev, Satish Kumar Sharma, Subhakara Valluri, Arina Shuraeva
No abstract is available for this record.