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2,329 results · page 87 of 98
Cathy Yi‐Hsuan Chen, Romeo Despres, Li Guo, Thomas Renault
No abstract is available for this record.
Marko Ogorevc
This paper is motivated by a hypothesis that the long term value of a cryptocurrency is determined by its future use as money. For a cryptocurrency to be used as a medium of payment, it has to fulfill three independent functions: medium of exchange, a unit of account, and store of value. Currently, cryptocurrencies are held for investment purposes rather than being used for transactions and thus as a medium of exchange. For cryptocurrency to become widely adopted as a means of payment, it first needs to go through a very volatile period because speculative traders see long-run future value in the cryptocurrency. In order to soften transition from speculative asset to medium of payment a trading strategy is proposed, which provides liquidity and reduces volatility. Similar to pairs trading strategy, the proposed solution is based on cointegration and performed in three steps. The main difference is that proposed solution does not include shorting, but holding cryptocurrencies, thus increasing the total available cash and adding to the equilibrium price. Results from an ongoing experiment suggest that the proposed trading strategy is appealing for about 40% of cryptocurrency investors, as the struggle against volatility problem is accompanied by significant financial gains.
Mario Larangeira, Mario Larangeira
No abstract is available for this record.
Moinak Maiti, Darko Vuković, Victor Krakovich, Maneesh Kumar Pandey
The present study focuses on five cryptocurrencies co-movements physiognomies both in time and frequency domain. The present study highlighted several interesting facts related to cryptocurrencies co-movements both in time and frequency domain that have high policy and investment implications. Overall wavelet coherence diagrams clearly indicate about the very short and long contagion effect among the cryptocurrency pairs for the whole study period. The contagion effect is different at different time scales. Finally wavelet clustering diagram indicates that by investing only in XBP and BitCoin cryptocurrencies investors are not going to get any benefit from diversification. This predictable co-movements pattern among the cryptocurrencies could be the basic investment strategies to gain maximum profit by diversifying the risk in cryptocurrency investments.
Daniel Cahill, Dirk G. Baur, Zhangxin Liu, Joey Yang
We investigate the price reaction of listed companies in response to blockchain-related announcements. The average abnormal return based on a global sample of 713 firm announcements is approximately 5% on the announcement day, with significantly higher returns for U.S. firms, smaller firms and announcements in late 2017 and early 2018. We show that abnormal returns are linked to the performance of bitcoin. Additionally, speculative announcements exhibit higher returns than non-speculative announcements, and blockchain- related Form 8-K disclosures have negligible difference in performance compared to their U.S. peers. Whilst we acknowledge the possibility of a latent variable that affects both the abnormal returns and the performance of bitcoin, we hypothesise that investors have confused bitcoin and blockchain, and used the performance of bitcoin as an indicator of the expected success of the blockchain technology.
Dominique Lammer, Tobin Hanspal, Andreas Hackethal
No abstract is available for this record.
Julián Andrada Félix, Adrián Fernández-Pérez, Simón Sosvilla‐Rivero
No abstract is available for this record.
Klaus Grobys, Niranjan Sapkota
We examine all available 146 Proof-of-Work-based cryptocurrencies that started trading prior to the end of 2014 and track their performance until December 2018. We find that about 60% of those cryptocurrencies were eventually in default. The substantial sums of money involved mean those bankruptcies will have an enormous societal impact. Employing cryptocurrency-specific data, we estimate a model based on linear discriminant analysis to predict such defaults. Our model is capable of explaining 87% of cryptocurrency bankruptcies after only one month of trading and could serve as a screening tool for investors keen to boost overall portfolio performance and avoid investing in unreliable cryptocurrencies.
Arash Aloosh, Samuel Ouzan
No abstract is available for this record.
A. Can Inci, Rachel Lagasse
Purpose - This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period covering not only the large value increases but also the dramatic declines during the beginning of 2018, the purpose of this paper is to provide a more complete analysis of the dynamic nature of cryptocurrencies as individual investment opportunities, and as components of optimal portfolios. Design/methodology/approach - The mean-variance optimization technique of Merton (1990) is applied to develop the risk and return characteristics of the efficient portfolios, along with the optimal weights of the asset class components in the portfolios. Findings - The authors provide evidence that as a single investment, the best cryptocurrency is Ripple, followed by Bitcoin and Litecoin. Furthermore, cryptocurrencies have a useful role in the optimal portfolio construction and in investments, in addition to their original purposes for which they were created. Bitcoin is the best cryptocurrency enhancing the characteristics of the optimal portfolio. Ripple and Litecoin follow in terms of their usefulness in an optimal portfolio as single cryptocurrencies. Including all these cryptocurrencies in a portfolio generates the best (most optimal) results. Contributions of the cryptocurrencies to the optimal portfolio evolve over time. Therefore, the results and conclusions of this study have no guarantee for continuation in an exact manner in the future. However, the increasing popularity and the unique characteristics of cryptocurrencies will assist their future presence in investment portfolios. Originality/value - This is one of the first studies that examine the role of popular cryptocurrencies in enhancing a portfolio composed of traditional asset classes. The sample period is the largest that has been used in this strand of the literature, and allows to compare optimal portfolios in early/recent subsamples, and during the pre-/post-cryptocurrency crisis periods.
Cathy Yi‐Hsuan Chen, Christian Hafner
Cryptocurrencies lack clear measures of fundamental values and are often associated with speculative bubbles. This paper introduces a new way of testing for speculative bubbles based on StockTwits sentiment, which is used as the transition variable in a smooth transition autoregression. The model allows for conditional heteroskedasticity and fat tails of the conditional distribution of the error term, and volatility may depend on the constructed sentiment index. We apply the model to the CRIX index, for which several bubble periods are identified. The detected locally explosive price dynamics, given the specified bubble regime controlled by a smooth transition function, are more akin to the notion of speculative bubble that is driven by exuberant sentiment. Furthermore, we find that volatility increases as the sentiment index decreases, which is analogous to the commonly called leverage effect.
Shaen Corbet, Veysel Eraslan, Brian M. Lucey, Ahmet Şensoy
No abstract is available for this record.
Nicola Borri, Kirill Shakhnov
No abstract is available for this record.
Yukun Liu, Aleh Tsyvinski, Xi Wu
ABSTRACT We find that three factors—cryptocurrency market, size, and momentum—capture the cross‐sectional expected cryptocurrency returns. We consider a comprehensive list of price‐ and market‐related return predictors in the stock market and construct their cryptocurrency counterparts. Ten cryptocurrency characteristics form successful long‐short strategies that generate sizable and statistically significant excess returns, and we show that all of these strategies are accounted for by the cryptocurrency three‐factor model. Lastly, we examine potential underlying mechanisms of the cryptocurrency size and momentum effects.
Weiyi Liu, Xuan Liang, Guowei Cui
No abstract is available for this record.
Wolfgang Karl Härdle, Campbell R. Harvey, Raphael Constantin Georg Reule
Abstract Cryptocurrency refers to a type of digital asset that uses distributed ledger, or blockchain, technology to enable a secure transaction. Although the technology is widely misunderstood, many central banks are considering launching their own national cryptocurrency. In contrast to most data in financial economics, detailed data on the history of every transaction in the cryptocurrency complex are freely available. Furthermore, empirically oriented research is only now beginning, presenting an extraordinary research opportunity for academia. We provide some insights into the mechanics of cryptocurrencies, describing summary statistics and focusing on potential future research avenues in financial economics.
Yunus Kılıç, İbrahim Çütçü
Kripto para olarak da adlandırılan dijital para fiyatlarındaki değişimler son yıllarda yatırımcıların oldukça ilgisini çekmiştir. Hızlı fiyat değişimlerinden getiri elde etmek isteyen yatırımcılar yeni bir varlık olan dijital paralara yönelmişlerdir. Bu doğrultuda, dijital paraların geleneksel menkul kıymetlerine alternatif olma ihtimalleri tartışılmaya başlanmıştır. Çalışmada, Bitcoin fiyatları ile Borsa İstanbul arasındaki eşbütünleşme ve nedensellik ilişkisini tespit etmek amaçlanmıştır. Bu kapsamda, Engle-Granger ve Gregory-Hansen eşbütünleşme testleri ile Toda-Yamamoto ve Hacker-Hatemi-J nedensellik testlerinden faydalanılmıştır. Bulgular, her iki eşbütünleşme testine göre Bitcoin fiyatları ile Borsa İstanbul endeks değeri arasında orta ve uzun vadede bir eşbütünleşme ilişkisinin olmadığını; nedensellik testlerinden sadece Toda-Yamamoto nedensellik testine göre Borsa İstanbul’dan Bitcoin fiyatlarına doğru tek yönlü nedensellik ilişkisi olduğunu göstermiştir.
Natalia Jerdack, Akmaral Dauletbek, Meredith Divine, Michael Hult · 5 authors
Cryptocurrencies have gained tremendous popularity over the past few years. The purpose of this study is to try to understand the factors that are driving cryptocurrency-related trading activities. Focusing on the well-established cryptocurrency called Bitcoin, we find that online search popularity and the volume of trade in unrelated stock markets positively and negatively, respectively, influence Bitcoin trading volume. We also find no statistical evidence that the underlying sentiment behind relevant financial news influence Bitcoin trading volume. We believe these results might be of great value to investors interested in cryptocurrencies and might instigate further research on this topic.
Sashikanta Khuntia, J. K. Pattanayak
No abstract is available for this record.
Mustafa Çıkrıkçı, Mustafa Özyeşil
In this study, we investigated whether bitcoin crypto money is an alternative to the stock exchange as an investment tool. For this purpose, the relationship between bitcoin and the stock market was examined in terms of the returns and liquidity. In the analysis, daily returns of the 9 Far East countries and Turkey's stock markets and daily returns of the bitcoin were used for the period of 22.02.2012-15.08.2018. According to the results of the model, an increase of the Bitcoin's returns has reduced the return on the stock market in Turkey and Far East countries. From point of this, it can be seen that the as an investment tool, bitcoin cryptocurrency has been becoming the substitute for the country stock exchanges included in the sample. The highest impact of bitcoin on the stock exchange was observed in Turkey and Indonesia while the least effect was seen on the Malaysia, Singapore and Korea respectively.
Pavel Ciaian, d’Artis Kancs, Miroslava Rajčániová
This is the first paper that estimates the price determinants of BitCoin in a Generalised Autoregressive Conditional Heteroscedasticity framework using high frequency data. Derived from a theoretical model, we estimate BitCoin transaction demand and speculative demand equations in a GARCH framework using hourly data for the period 2013-2018. In line with the theoretical model, our empirical results confirm that both the BitCoin transaction demand and speculative demand have a statistically significant impact on the BitCoin price formation. The BitCoin price responds negatively to the BitCoin velocity, whereas positive shocks to the BitCoin stock, interest rate and the size of the BitCoin economy exercise an upward pressure on the BitCoin price.
Karl Weinmayer, S. Gasser, Alexander Eisl
No abstract is available for this record.
David Y. Aharon, Mahmoud Qadan
No abstract is available for this record.
Au Vo, Christopher Yost-Bremm
Cryptocurrency such as Bitcoin is a rapidly developing phenomenon in financial technology with considerable research interest but is understudied. In this research article, we use a Design Science Research paradigm to create a high-frequency trading strategy at the minute level for Bitcoin using six exchanges as our Information Technology artifact. We created financial indicators and utilized a machine learning (ML) algorithm to create our strategy. We provided two sets of evaluation. First, we evaluated this strategy against another popular ML algorithm and found our algorithm performed better on the average. Second, we analyzed the economic benefits using the strategy against out-of-sample trading in foreign exchange currency. We presented both descriptive and prescriptive contributions to Design Science Research via the development and testing of our artifacts.