Bitcoin as a Complement to Emerging Market Currencies

Bitcoin is a digital currency that has gained significant traction as an economic instrument. Despite its rise, it has received little attention from the scholarly community. This study is one of the first studies to examine Bitcoin’s use as a complement to emerging markets currencies; more specifically, I analyze the value and volatility of Bitcoin relative to emerging market currencies and explore ways in which Bitcoin can complement emerging market currencies. The results suggest that Bitcoin has characteristics that make it well-suited to work as a complement to emerging market currencies and that there are ways to minimize Bitcoin’s risks.     

Evaluation by the Aumann and Serrano performance index and Sharpe ratio: Bitcoin performance

We compare Bitcoin performance based on the Aumann and Serrano performance index and Sharpe ratio assuming that asset returns follow the class of discrete normal mixture distributions. The Aumann and Serrano performance index can take into account higher moments of the underlying distribution of assets and is relevant for risk-averse investors. We evaluate Bitcoin performance based on the Aumann and Serrano index relative to the performance of other assets. Our evaluation shows that Bitcoin is rated highly by the Sharpe ratio but rated very poorly by the Aumann and Serrano index. We also find some stock assets can beat Bitcoin by the Sharpe ratio when an investment horizon is monthly.     

Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard‐to‐value fundamentals

What predicts returns on assets with “hard‐to‐value” fundamentals such as Bitcoin and stocks in new industries? We are the first to propose an equilibrium model that shows how technical analysis can arise endogenously via rational learning, providing a theoretical foundation for using technical analysis in practice. We document that ratios of prices to their moving averages forecast daily Bitcoin returns in and out of sample. Trading strategies based on these ratios generate an economically significant alpha and Sharpe ratio gains relative to a buy‐and‐hold position. Similar results hold for small‐cap, young‐firm, and low analyst‐coverage stocks as well as NASDAQ stocks during the dotcom era.     

Is blockchain technology a watershed for tourism development?

ABSTRACT

The rise of blockchain technology could radically disrupt the global economy. As an emergent technology, blockchain is of broad and current interest in the tourism industry. Small island economies are at the forefront of adopting this digital asset and technology. For instance, the Caribbean economies are launching their first digital legal tender, and Aruba is developing a blockchain platform to boost tourism revenue. Given the velocity of adoption, blockchain technology holds significant implications for tourism development. This research letter provides a discourse on the adoption of blockchain technology among small island economies concerning the opportunities and potential challenges faced and offers practical implications for tourism stakeholders.     

美、欧央行监管比特币的做法及其对我国的启示

2015年12月5日,中国人民银行、银监会、证监会等五部委联合印发了《关于防范比特币风险的通知》,这对于保护社会公众的财产权益,保障人民币的法定货币地位,防范洗钱风险,维护金融稳定,具有重要的现实意义。美、欧央行对比特币的监管已先行一步,对我国具有一定的启示和借鉴。本文简要介绍了我国比特币交易情况及监管现状,归纳总结了美、欧央行监管比特币做法,提出我国应借鉴美、欧央行做法制定应急预案,防范比特币风险。     

新型货币“比特币”:产生、原理与发展

2013年4月10日,随着与美元兑换率达到1:266美元,使比特币这一电子虚拟货币一下子引起了现实世界的关注。本文梳理了比特币的由来和设计,深入分析了比特币的特点和属性;比特币经过几年的发展,对社会产生了明显的影响;但是当前其法律地位以及发展前景社会各界是见仁见智。在互联网飞速发展的当下,比特币凭借其创新的理念和可靠的技术吸引众多人的目光,它将对我们的生活产生何种影响,值得我们深入的研究和思考。     

Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models

This study extends the examination of the Efficient-Market Hypothesis in Bitcoin market during a five-year fluctuation period, from September 1 2017 to September 1 2022, by analyzing 28,739,514 qualified tweets containing the targeted topic “Bitcoin”. Unlike previous studies, we extracted fundamental keywords as an informative proxy for carrying out the study of the EMH in the Bitcoin market rather than focusing on sentiment analysis, information volume, or price data. We tested market efficiency in hourly, 4-hourly, and daily time periods to understand the speed and accuracy of market reactions towards the information within different thresholds. A sequence of machine learning methods and textual analyses were used, including measurements of distances of semantic vector spaces of information, keywords extraction and encoding model, and Light Gradient Boosting Machine (LGBM) classifiers. Our results suggest that 78.06% (83.08%), 84.63% (87.77%), and 94.03% (94.60%) of hourly, 4-hourly, and daily bullish (bearish) market movements can be attributed to public information within organic tweets.     

Does bitcoin co-move and share risk with Sukuk and world and regional Islamic stock markets? Evidence using a time-frequency approach

This paper examines the co-movements between Bitcoin (BTC) and the Dow Jones World Stock Market Index, regional Islamic stock markets, and Sukuk markets. We apply cross wavelet transform and wavelet coherence analysis with a wavelet-based measure of value at risk. The co-movement is stronger and in the same direction at lower frequencies, suggesting the benefits from diversification with BTC are relatively less for long-term investors compared to short-term investors. Co-movement in the opposite direction at high frequencies implies better benefits of hedging in the short run through diversification in BTC and Islamic equity markets. Robustness tests show that the correlations increase as we increase from an investment horizon of two days to one of 64 days. The frequency-domain causality test shows significant causality flow from BTC to the Islamic market of Asia-Pacific, Japan, and Sukuk markets in the short term. Additionally, BTC is found to lead Asia-Pacific Islamic stock markets in the long term. Finally, we note that the benefits of portfolio diversification with BTC and Islamic assets vary across time and frequencies.