Capitalism's renaissance? The potential of repositioning the financial ‘meta-economy’

This paper examines whether the prevailing model of capitalism with its hallmark financial markets is the most productive and stable investment system to underpin the global economy into the future. It returns to the creation of the stock market in 1602 to examine the stock market's origin without the presumption of its respectability. Often considered the genesis of modern corporations and contemporary financial markets, its venerable status is questioned. The instability of the system, established incidental to the Dutch East India Company's solution for financing East Indies voyages and never intended as a model for global capitalism, is found to be insurmountable. Rather than extrapolating the current trajectory of capitalism, an alternative future based on the expansion of productive primary economic activity, is considered. A movement that is evolving spontaneously around innovative lending to expand business enterprises in the primary economy offers the possibility of this alternative future with goals other than amassing capital, more akin to the economic model that originally funded the Renaissance.     

Return and volatility properties: Stylized facts from the universe of cryptocurrencies and NFTs

Stylized facts of returns and volatility are an important approximation tool for empirical finance studies, especially in the area of young and new assets. In this paper, we examine the return and volatility properties of four non-fungible tokens (NFTs) and four cryptocurrencies from 24th January 2018–2nd August 2022. The results show the following: Firstly, the returns of both NFTs and cryptocurrencies have fat tails, with evidence of tail exponents following the inverse cubic-law, along with clear persistence behavior. Secondly, all returns exhibit volatility clustering, albeit to varying degrees, and the detected absence of inverse volatility-asymmetry challenges the safe-haven property often documented for cryptocurrencies. Thirdly, return-based long-memory is slightly more intense than volatility-based long-memory, especially for NFTs, which demonstrate a predictability contesting market efficiency. These findings are generally consistent with previous findings on equities, implying that the return and volatility behavior of NFTs and cryptocurrencies is leaning towards that of traditional assets.     

The impact of central bank digital currency news on the stock and cryptocurrency markets: Evidence from the TVP-VAR model

This study employs a non-linear framework to investigate the impacts of central bank digital currency (CBDC) news on the financial and cryptocurrency markets. The time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005) is estimated based on weekly data from the first week of January 2015 to the last week of December 2021. The vector of endogenous variables in the VAR estimation contains the Central Bank Digital Currency uncertainty index (CBDCU), cryptocurrency policy uncertainty index, S&P 500 index, VIX, and Bitcoin price. The TVP-VAR model’s time-varying responses demonstrated that the reactions of the cryptocurrency market to central bank digital currency announcements vary remarkably over time. The impacts of the CBDC shocks on the financial market have been increasingly visible during the COVID-19 pandemic. According to the time-varying forecast error decompositions, CBDCU and VIX shocks have accounted for most of the variance in cryptocurrency uncertainty and Bitcoin return shocks, notably during the COVID-19 period.     

Investigating individual privacy within CBDC: A privacy calculus perspective

Central Bank Digital Currencies (CBDC) are a digital innovation based upon distributed ledger and smart contract technology. In this paper we examine how potential users of CBDC technology willingly disclose their personal information. The researchers conducted an online quantitative survey which investigates the privacy perceptions of consumers. Using the privacy calculus theory lens, this study looks at the potential benefits of CBDC and how these influence user perceptions towards privacy disclosure. While this research suggests that participants in the study had negative perceptions in relation to the disclosure of personal information, many were willing to offset these concerns if there are significant benefits in the usage of CBDC. Factors such as ease of use, convenience, availability, and credibility were viewed as key benefits in this scenario. Thus, future banking strategies and marketing approaches need to consider these components to foster CBDC adoption.     

代币发行融资研究——基于企业生存时间的视角

本文以中国境内所有的代币发行融资项目为研究对象,研究代币发行融资对初创企业生存时间的影响。研究发现,相比股权融资,代币发行融资会显著缩短初创企业的寿命。这一结论在增加控制变量和使用工具变量等方法后依然稳健。渠道检验的结果显示,代币发行融资阻碍了初创企业人力资本的进一步深化,从而缩短了企业的持续经营时间。从代币发行融资的宏观经济后果来看,代币发行融资所造成的不良影响恶化了地区的信用环境,从而显著提高了地区的融资成本。进一步研究表明,代币发行融资对初创企业的负面影响在信息披露水平较低、不受关注以及缺少媒体监督的样本中更加显著。本文揭示了代币发行融资带来的负面影响,为禁止代币发行融资等规范金融创新的政策提供了经验证据。     

The economics of Bitcoin and similar private digital currencies

Recent innovations have made it feasible to transfer private digital currency without the intervention of an organization such as a bank. Any currency must prevent users from spending their balances more than once, which is easier said than done with purely digital currencies. Current digital currencies such as Bitcoin use peer-to-peer networks and open source software to stop double spending and create finality of transactions. This paper explains how the use of these technologies and limitation of the quantity produced can create an equilibrium in which a digital currency has a positive value. This paper also summarizes the rise of 24/7 trading on computerized markets in Bitcoin in which there are no brokers or other agents. The average monthly volatility of returns on Bitcoin is higher than for gold or a set of foreign currencies in dollars, but the lowest monthly volatilities for Bitcoin are less than the highest monthly volatilities for gold and the foreign currencies.     

The decade-long cryptocurrencies and the blockchain rollercoaster: Mapping the intellectual structure and charting future directions

Recent advances in science mapping allowed to analyze the entire intellectual structure of blockchain and cryptocurrencies in business-related disciplines to identify 174 academic articles as well as 1482 practitioner-oriented articles published since the inception of cryptocurrencies in 2008 to highlight key trends of the published outputs. The results demonstrate academic research done by 389 authors in 296 organizations based in 50 countries that only just initiated the conversation on four major streams of the literature—Bitcoin and cryptocurrencies; blockchain adoption; cryptocurrency and blockchain environment; and business model innovations. When comparing academic scholarship to practitioner-oriented literature, the results demonstrate that practitioners discussed investor-related themes, cryptocurrency intrinsic value, political-economic sphere, and the impact of cryptocurrency and blockchain technologies on the wider society in greater detail. As a result, a number of themes are identified and discussed that could align academic and practitioner interests and provide guidance for further research in this important field.     

Liquidity in the cryptocurrency market and commonalities across anomalies

We examine how liquidity affects cryptocurrency market efficiency and study commonalities in anomaly performance in cryptocurrency markets. Based on the unique features of cryptocurrencies, we build a model with anonymous traders valuing cryptocurrencies as payments for goods and investment assets, and find that decreases in funding liquidity translate into lower asset liquidity in the cryptocurrency market. Empirically, we observe that many widely recognized stock market anomalies also exist in the cryptocurrency market, although some have opposite long and short legs. We also find evidence that a decrease in cryptocurrency liquidity enhances anomalous returns while preventing the cryptocurrency market from achieving efficiency.     

The illusion of managerial control

The design and implementation of organizational control systems based on a cybernetic model stand in need of revision. The revision is required by increasing numbers of reports of system ineffectiveness and, in some cases, failure. The paper suggests that a major reason for current difficulties resides in the “illusion of control” implied by theory and implemented in practice. An alternative definition of organizational control based in the concept of “multirationality” is proposed.     

中国网络平台运营法治化路径探微

数字经济促进经济快速发展的同时,也滋长了市场支配地位滥用,垄断市场或进行不正当竞争,侵害消费者权益,甚至危及一国经济或金融安全。中国网络平台运营法治化路径是：以明确平台责任为基础,将大型在线平台作为主要监管对象,对大型在线平台的垄断问题进行法律规制,营造公平竞争的市场环境;以消费者权益保护作为网络平台运营法治化的目标;规定平台等级区分与责任承担相一致原则;进一步明确违法惩戒的法律措施。     

Good volatility,bad volatility,and the cross section of cryptocurrency returns

This paper examines the predictability of realized volatility measures (RVM), especially the realized signed jumps (RSJ), on future volatility and returns. We confirm the existence of volatility persistence and future volatility is more strongly related to the volatility of past positive returns than to that of negative returns in the cryptocurrency market. RSJ-sorted cryptocurrency portfolios yield statistically and economically significant differences in the subsequent portfolio returns. After controlling for cryptocurrency market characteristics and existing risk factors, the differences remain significant. The investor attention explains the predictability of realized jump risk in future cryptocurrency returns.     

The entry and exit dynamics of the cryptocurrency market

This paper presents an analysis of the entry and exit dynamics of the cryptocurrency market that focuses on the growth of initial coin offerings during 2015–2020. We used two different datasets: one includes long-lived cryptocurrencies, while the other includes the whole cryptocurrency system at our disposal–that is, it considers the entering and exiting cryptocurrencies. Comparing the dynamics between both datasets with the index cohesive force approach, we assessed how the growth of the initial coin offerings and the exiting cryptocurrencies affected the connectedness of the market. Our results show that the expansion of the cryptocurrency system gave rise to a strong collective movement during 2018–2019. Afterwards, the group pressure, due to the bubble of the initial coin offerings, decreased in favour of the largest cryptocurrencies. Lastly, we observed changes in the hierarchical order of the most influential cryptocurrencies. In particular, Ethereum became the most influential cryptocurrency, at the detriment of Bitcoin.     

国家数字化战略的国际比较及启示

本文探讨了国家数字化战略对于驱动创新、促进改革和管理风险的意义。通过借 鉴美国、德国和英国的数字化战略的政策与实践,提出了我国推动数字化战略的四点启示：一 是加强基础设施与平台建设;二是发展数字技术和数字产业;三是加强人才培养和数字教育; 四是保护数据安全和个人隐私。     

Countering money laundering and terrorist financing: A case for bitcoin regulation

Bitcoin was created in 2008 to serve as an alternative payment mechanism for both the under-banked and un-banked, or those in regions where the formal financial system suffers from broad corruption and efficient regulation. However, criminals and terrorists quickly exploited Bitcoin's unique properties, namely its peer-to-peer nature and pseudo-anonymity, to facilitate extensive terrorist financing and money laundering schemes. Government reactions to safeguard national security interests have been extremely varied, ranging from outright bans to passive tolerance. This inconsistency stems from how to effectively classify Bitcoin. On one side are those who argue Bitcoin is a currency, and on the other are those who claim it is a type of asset. In the US alone, these discrepancies have led to a bureaucratic turf war between different regulatory bodies, namely the Financial Crimes Enforcement Network, the Commodity Futures Trading Association, the Securities and Exchange Commission, and the Internal Revenue Service. This study seeks to move beyond the existing legal frameworks, arguing that Bitcoin should be classified as a technology and regulation should rest with private sector technology companies.     

Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach

We construct the complete network of tail risk spillovers among major cryptocurrencies using the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression. We capture important features of the network, including major risk-driving and major risk-receiving currencies, and the evolution of the tail dependence among the currencies over time. Importantly, we reveal a striking finding that the right tail dependence among the cryptocurrencies is significantly stronger than the left tail counterpart. This unique characteristic may have contributed to the rise in popularity of cryptocurrencies over the last few years. Our portfolio analysis reveals that diversification in cryptocurrency investment can be accomplished simply by employing the naïve equal-weighted scheme even when transaction costs are taken into account.     

Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19

In this paper, we study the long memory behavior of the hourly cryptocurrency returns during the COVID-19 pandemic period. Initially, we apply different tests against the spurious long memory, with the results indicating the presence of true long memory for most cryptocurrencies. Yet, using the multivariate test, the series are found to be contaminated by level shifts or smooth trends. Then, we adopt the wavelet-based multivariate long memory approach suggested by Achard and Gannaz (2016) to model their long memory connectivity. The findings indicate a change in persistence for all series during the sample period. The fractal connectivity clustering indicates a similarity among Ethereum (ETH) and Litecoin (LTC), Monero (XMR), Bitcoin (BTC), and EOC token (EOS), while Stellar (XLM) is clustered away from the remaining series, indicating the absence of any interdependence with other crypto returns. Overall, shocks arising from COVID-19 crisis have led to changes in long-run correlation structure.     

On the drivers of technical analysis profits in cryptocurrency markets: A Distributed Lag approach

The cryptocurrency literature on technical analysis has largely ignored drivers of technical analysis return adjusted by transaction costs (i.e., adjusted returns). To that end, we propose a Heterogeneous Autoregressive Distributed Lag Model of Returns (HARDL-R) to examine the impact from EPU, VIX, and SP500 returns to adjusted returns. We provide evidence that these three drivers matter during bubble periods compared to non-bubble periods. When not differentiating bubble periods, we find that VIX is the only driver influencing the dynamics of adjusted returns from 2016 to 2021. These findings remain relatively stable after controlling for the volume of transactions.     

A comparative analysis of cryptocurrency returns and economic policy uncertainty pre- and post-Covid-19

This study analyzes the impact of economic policy uncertainty (EPU) on cryptocurrency returns for a sample of 100 highly capitalized cryptocurrencies from January 2016 to May 2021. The results of the panel data analysis and quantile regression show that increases in global EPU have a positive impact on cryptocurrency returns for lower cryptocurrency returns quantiles and an adverse impact for upper quantiles. In line with the existing literature, the Covid-19 pandemic resulted in higher returns for cryptocurrencies. Inclusion of a Covid-19 dummy in the models strengthened the impact of EPU on cryptocurrency returns. Furthermore, the relationship between the change in EPU and cryptocurrency returns was direct in the pre-Covid-19 period but inverse in the post-Covid-19 period. These results imply that cryptocurrencies act more like traditional financial assets in the post-Covid-19 era.     

Cryptocurrency,confirmatory bias and news readability – evidence from the largest Chinese cryptocurrency exchange

We investigate whether Chinese cryptocurrency investors show confirmatory bias when processing authority‐related news. Authority‐related news is defined as news that is related to government authority (including central bank) policies or talk. By using data from the largest cryptocurrency exchange in China, we find that investors’ response to authority‐related news is negative and significant in general. Moreover, we find that the abnormal trading volume and standard deviation of abnormal trading volume are significantly higher for authority‐related news with higher readability, suggesting investors respond to the more readable authority‐related news with more trading behaviour.