Blockchain Papers

Yosef Bonaparte

No abstract is available for this record.

Serkan Samut, Rahmi Yamak

In this study, it was investigated whether the Covid-19 pandemic, which started to affect the world in early 2020, influenced the relationship between return volatility and trading volume in the cryptocurrency market. In the empirical part of the study, 40 cryptocurrencies were included in the analysis. The data were divided into two separate periods as before and during the pandemic. Two alternative estimators developed by Garman and Klass (1980) and by Rogers and Satchell (1991) were used to measure the return volatility of cryptocurrencies. With causality and simultaneous correlation analyses, it was determined that the sequential information arrival hypothesis was valid in the cryptocurrency market in the pre-pandemic period. In the pandemic period, the sequential information arrival hypothesis lost its effect and left its place to the mixture of distribution hypothesis.

Nam You Sang, Kang Sang Hoon

No abstract is available for this record.

Triasesiarta Nur, Narendra Dewangkara

Cryptocurrency works on a system that admits people to make payments all over the world without the requirement for any intermediary. Most digital currencies experience frequent periods of intense volatility. This paper examines the day of the week effects in return and volatility on Bitcoin, Ethereum, Ripple, Litecoin, and Tether currencies. To estimate volatile variance, this research uses five ARCH family models: ARCH, GARCH, EGARCH, TARCH and PARCH Models. The best models are derived based on Akaike Info Criterion and Schwarz Criterion. The sample periods vary based on the date of the initial release of each currency up to 31 December 2019. Results indicate the Power ARCH (PARCH) is the best model for Bitcoin and Litecoin, Threshold ARCH (TARCH) model is the best for Ethereum, Ripple, and Litecoin, and the EGARCH model is for Tether. Each model shows a different day of the week effects on each currency.

Weihao Han, David Newton, Emmanouil Platanakis, Charles Sutcliffe · 5 authors

Cryptocurrency returns are highly non-normal, casting doubt on the standard performance metrics. We apply almost stochastic dominance (ASD), which does not require any assumption about the return distribution or degree of risk aversion. From 29 long-short cryptocurrency factor portfolios, we find eight that dominate our four benchmarks. Their returns cannot be fully explained by the three-factor coin model of Liu et al. (2022). So we develop a new three-factor model where momentum is replaced by a mispricing factor based on size and risk-adjusted momentum, which significantly improves pricing performance.

Mark Schaub

On January 4, 2021 the Office of the Comptroller of the Currency (OCC), a major regulator of financial institutions in the United States, announced that federally chartered banks and thrifts were now allowed to utilize stablecoins as payment instruments. Much research and many discussions have revolved around policies of governments worldwide in how to handle the new cryptocurrency phenomenon. The purpose of this short study was to observe the valuation impact of that announcement on the three largest cryptocurrencies and two others. Research findings show the altcoins with valuations not tied to the dollar had substantial increases in value while the stablecoins, which the announcement specified are now allowed to be used by banks, changed very little. Specifically, Bitcoin and Etherium increased over 20% in value within 5 days of the announcement while the stablecoins Tether and USDCoin changed in value by no more than 0.10% for the same event window. This shows that stablecoins lived up to their name even though they were promoted as an acceptable payment system in the US.

David Häfner

This dissertation is dedicated to the analysis of three superordinate economic principles in varying market environments: market efficiency, the behavior of market participants and information asymmetry. Sustainability and social responsibility have gained importance as investment criteria in recent years. However, responsible investing can lead to conflicting goals with respect to utility-maximizing behavior and portfolio diversification in efficient markets. Conducting a meta-analysis, this thesis presents evidence that positive (non-monetary) side effects of responsible investing can overcome this burden. Next, the impact of the EU-wide regulation of investment research on the interplay between information asymmetry, idiosyncratic risk, liquidity and the role of financial analysts in stock markets is investigated. An empirical analysis of the emerging primary and secondary market for cryptocurrencies yields further insights about the effects of information asymmetry between investors, issuers and traders. The efficient allocation of resources is dependent on the market microstructure, the behavior of market participants, as well as exogenous shocks. Against this background, this thesis is dedicated to the empirical analysis of limit order books, the rationality of traders and the impact of COVID-19. Due to its young history, the market for cryptocurrencies yields a suitable research subject to test classical financial theories. This doctoral thesis reveals parallels between the microstructure of cryptocurrency and stock markets and uncovers some previously unknown statistical properties of the cryptocurrency market microstructure. An initial examination of the impact of COVID-19 further shows that cryptocurrencies with a high market capitalization seem to react to macroeconomic shocks similar to stock markets. This cumulative dissertation comprises six stand-alone papers, of which three papers have already been published.

Muhammad Umar

No abstract is available for this record.

John Silberholz, Di Wu

No abstract is available for this record.

David Elferich

Research background: Since the financial crisis in 2008, numerous other cryptocurrencies have established themselves in the financial industry alongside Bitcoin. Although the validity of the user cases is still lacking, Bitcoin is already being used extensively in the institutional finance sector, among others. Here, the comparison of Bitcoin to other asset classes in mixed portfolio structures must be taken into account. According to the latter, far-reaching areas of investigation emerge by adding Bitcoin in the evaluation of risk-return ratios of mixed portfolio weightings. Purpose of the article: The objective of this paper is to examine, within the framework of Harry Markowitz’s efficiency theory, the impact of including Bitcoin as an investment asset for the risk-return ratios of mixed portfolio structures. Methods: The statistical analysis is based, among other things, on paired sample tests, where the return and volatility values are tested for significant differences in the selected test values. Findings & Value added: The statistical investigations show that the introduction of Bitcoin leads to advantageous return structures, but at the same time to significantly increased volatility values of the examined portfolio constellations. Setting a regional focus of the investment assets in the investigations led to a simplified evaluation basis and at the same time offers the scientific space for further investigations.

Imran Yousaf, Larisa Yarovaya

No abstract is available for this record.

Matthias Scharnowski, Stefan Scharnowski, Stefan Scharnowski, Lukas Zimmermann

No abstract is available for this record.

Ilja Kantorovitch, Janko Heineken

No abstract is available for this record.

Yunchuan Sun, Xiangyi Kong, Tongrui Chen, Hang Su · 6 authors

Compared with stock market, cryptocurrency market is more susceptible to investor sentiment at the lack of substantial asset support. This study develops a proxy to measure the investor sentiment of cryptocurrency market by using textual analytics on millions of posts in Chain Node, which is the most active online community for Chinese cryptocurrency investors. We investigate the correlation between the sentiment and the market return from Jan. 2018 to Aug. 2020. The study argues that the proposed proxy could well reflect the investor sentiment of the cryptocurrency.

Linus Wilson

We look at the association between the price of a cryptocurrency and the secondary market prices of the hardware used to mine it. We find the prices of the most efficient Graphical Processing Units (GPUs) for Ethereum mining are significantly positively correlated with the daily price returns to that cryptocurrency.

Raja Nabeel‐Ud‐Din Jalal, Simona Leonelli

No abstract is available for this record.

Ingolf Gunnar Anton Pernice, Anna Almosova, Hermann Elendner

No abstract is available for this record.

Mahdi Ghaemi Asl, Elie Bouri, Sahar Darehshiri, David Gabauer

No abstract is available for this record.

Simon Trimborn, Yang Li

No abstract is available for this record.

Victoria Dobrynskaya, Mikhail Dubrovskiy

The authors consider a variety of cryptocurrency and equity risk factors as potential forces that drive cryptocurrency returns and carry risk premiums. In a cross-section of 2,000 biggest cryptocurrencies during 2014–2020, only downside market risk, cryptocurrency size and cryptocurrency policy uncertainty factors are systematically priced with significant premiums. Cryptocurrencies, which have greater exposures to these factors, yield higher returns subsequently. Equity market risk, particularly equity downside market risk, appears to be more important than cryptocurrency market risk, suggesting greater linkages between cryptocurrency and equity markets than we used to think. Global and the US equity factors are more relevant for the cryptocurrency market than local factors from other markets. However, there is no evidence that exposure to momentum, volatility and Fama–French factors is compensated by higher returns.

N. Passalis, Solon Seficha, Avraam Tsantekidis, Anastasios Tefas

No abstract is available for this record.

Jianqin Hang, Xu Zhang

This study proposes a novel approach that incorporates rolling‐window estimation and a quantile causality test. Using this approach, Google Trends and Bitcoin price data are used to empirically investigate the time‐varying quantile causality between investor attention and Bitcoin returns. The results show that the parameters of the causality tests are unstable during the sample period. The results also show strong evidence of quantile‐ and time‐varying causality between investor attention and Bitcoin returns. Specifically, our results show that causality appears only in high volatility periods within the time domain, and causality presents various patterns across quantiles within the quantile domain.

Carol Alexander, Jun Deng, Bin Zou

We consider the hedging problem where a futures position can be automatically liquidated by the exchange without notice. We derive a semi-closed form for an optimal hedging strategy with dual objectives - to minimise both the variance of the hedged portfolio and the probability of liquidations due to insufficient collateral. The optimal solution depends on the statistical characteristics of the spot and futures extreme returns and parameters that characterise the hedger by loss aversion, choice of leverage and collateral management. An empirical analysis of bitcoin shows that the optimal strategy combines superior hedge effectiveness with a reduction in the probability of liquidation. We compare the performance of seven major direct and inverse hedging instruments traded on five different exchanges, based on minute-level data. We also link this performance to novel speculative trading metrics, which differ markedly between venues.

Cathy Yi‐Hsuan Chen, Dmitri Vinogradov

No abstract is available for this record.