Follow blockchain research across journals, conferences, and preprint repositories.
2,329 results · page 25 of 98
Hubert Dichtl, Wolfgang Drobetz, Tizian Otto
No abstract is available for this record.
Andrea Andolfatto, Siddharth Naik, Lorenzo Schönleber
No abstract is available for this record.
Camilla Yen
No abstract is available for this record.
Ziyue Su
In recent years, with the rapid development of science and technology today (especially blockchain techniques), a special currency cryptocurrency (also relatively known as digital currencies) was born in 2008 and has received a lot of attention. On account of its special nature and intrinsic, a large amount of investors often combine digital currencies and quantitative trading to make profits and earn extra returns based on the concepts. With this in mind, this study mainly describes the definition of digital currency and its development process and compares digital currency with ordinary currency to highlight its advantages and disadvantages. Subsequently, this research introduces the combined application of digital currency and quantitative transaction in general with some of the backtesting results. According to the analysis, this paper puts forward suggestions on the existing problems of digital currency and promotes its further development in the future. Overall, these results shed light on guiding further exploration of quantitative strategy designs for cryptocurrency.
Mehak Younus, Muhammad Abubakr Naeem
No abstract is available for this record.
Yakun Liu, Yan Chen
No abstract is available for this record.
Suwan Long, Ying Xie, Zhengyuan Zhou, Brian M. Lucey · 5 authors
No abstract is available for this record.
Daphne Sobolev, Vasileios Kallinterakis
Despite regulators’ warnings that investing in cryptoassets is highly risky, cryptocurrency investments are prevalent. To explore investors’ engagement with regulatory risk advice, we conducted two surveys. Cryptocurrency investors residing in the UK and the US were asked about their interpretation of the notion of risk, awareness of regulatory risk advice, and attitudes towards the advice and the regulators. Investors were also asked whether they followed the advice. Qualitative content analysis of their answers suggests that people often invest in cryptocurrencies although they understand the risks involved and are aware of the regulators’ advice. They do so due to their risk propensity, self-reliance, criticism of the informativeness of the advice, or attitudes towards regulators. Furthermore, negative attitudes towards regulators often stem from lack of trust and the perception that regulators are dated. This study suggests that regulators could benefit investors by providing them with more informative advice and addressing their attitudes.
Poodi Venkata Vijaya Durga, G. Anusha
No abstract is available for this record.
Tom J. Espel
No abstract is available for this record.
Chia‐Hsien Tang, Yen‐Hsien Lee, Ya‐Ling Huang, You-Xuan Liu
This study examines the relationship between E-mini S&P 500 futures' crash risk and Bitcoin futures' returns and volatility using data from 2017 to 2021. While E-mini S&P 500's crash risk doesn't significantly influence Bitcoin returns, it correlates with its volatility, especially during events like the COVID-19 pandemic and U.S. elections. Furthermore, as global and emerging market indices rise, Bitcoin futures volatility decreases, suggesting its role as a hedging tool. These findings are pivotal for investors aiming to construct informed trading strategies, leverage Bitcoin futures as a hedging asset during economic instability, and keep tabs on traditional market indicators like E-mini S&P 500 crash risk for anticipating fluctuations in Bitcoin futures.
Minhao Leong, Simon Kwok, Vitali Alexeev
No abstract is available for this record.
Stefan Gabriel, Robert M. Kunst
No abstract is available for this record.
Jeffrey R. Black, Jobaer Hossain, Shawn McFarland
No abstract is available for this record.
Daeyoung Jeon, Changeun Kim, Jongho Park, Bong‐Gyu Jang
No abstract is available for this record.
Gönül Çolak, Joshua Della Vedova, Sean Foley, Sinh Thoi
No abstract is available for this record.
Ryeomyung Kang, Soosung Hwang, Jin-Ho Shin
No abstract is available for this record.
Rebecca Abraham
This study presents the mathematical formulations of investor sentiment for investors in cryptocurrencies. We assume that bitcoin prices are driven by investor sentiment measured in terms of Google search volume and social media posts. The current generation of retail investors uses non-traditional methods such as social media posts and Google searches to obtain information so that an increase in posts and searches on ‘bitcoin,’ indicate positive or negative investor sentiment. Mathematical formulations describe investor sentiment separately for risk-averse, moderate risk, and risk-taking investors. Risk-averse investors are considered to be aberrant in their investment in cryptocurrencies as they are naturally resistant to high-risk investments such as cryptocurrencies. Only risk-taking investors capture the fullest extent of irrational exuberance that prevailed in the cryptocurrency markets. However, risk-takers with very high-risk tolerance, such as hedge funds, trade in investments with volatility to capitalize upon the highest market prices for cryptocurrencies. Their behavior is modeled in cryptocurrency futures and cryptocurrency call options, and cryptocurrency put options. The insight provided by this paper is that the history of cryptocurrency prices is stored in a Laplace transform so that investor sentiment is based on the trajectory of past prices for cryptocurrencies and cryptocurrency futures. For cryptocurrency options, the history of volatility of prices is embedded in the Laplace transform, with increasing volatility embedded in call option prices, and decreasing volatility embedded in put option prices.
Riccardo Cosenza, Simon Stalder
No abstract is available for this record.
Daniel Tut
No abstract is available for this record.
Tasnim Khalid, Mujeeb Saif Mohsen Al-Absy, Mohammad Omar Farooq
No abstract is available for this record.
Xudong Wang, Xiaofeng Hui
Bitcoin futures exchange‐traded funds (ETFs) are recent innovations in cryptocurrency investment. This article studies the price‐volume relationship in this market from an information perspective. We first propose effective mutual information which has better estimation accuracy to analyze the contemporaneous relationship. Using half‐hourly trading data of the world’s largest Bitcoin futures ETF, we find that trading volume changes and returns contain information about each other and are contemporaneously dependent. Then, we employ effective transfer entropy to examine the intertemporal relationship. The results show that there exists information transfer from volume changes to returns in most of our sample period, suggesting the presence of return predictability and market inefficiency. However, information transfer in the opposite direction occurs much less frequently, and the amount is typically smaller.
Lars Kuerzinger, Christoph J. Börner
No abstract is available for this record.
Alexia Anastasopoulos, Nikola Gradojević, Fred Liu, Alex Maynard · 5 authors
We assess the information content of order flow for the cross-section of cryptocurrency returns. Our analysis is based on a set of international order flows denominated in 11 major currencies that reflect world order flow. We find that world order flow has strong explanatory and predictive power for cryptocurrency returns. Order flow tends to dominate economic fundamentals for out-of-sample prediction, especially in the context of non-linear machine learning models, and its performance cannot be explained by limits to arbitrage. Overall, our findings indicate that order flow has a permanent effect on cryptocurrency returns.