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.     

Estimating the reaction of Bitcoin prices to the uncertainty of fiat currency

Recent studies have found that investors move from fiat currencies to Bitcoin cryptocurrency in environments with low trust and high uncertainty. This paper investigates the reaction of Bitcoin prices to uncertainty concerning fiat currencies by introducing a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-based event analysis approach. The 2013 Cyprus bailout is used as an event over the uncertainty of fiat currencies. With the proposed approach, the original Bitcoin price series is decomposed into high-frequency, low-frequency, and trend components, thus disentangling the short-, medium-, and long-term effects of the events on Bitcoin prices, respectively. We find that the low-frequency component is dominant and increased because of the event. In addition, the announcement significantly increased the intensity of short-term fluctuations in Bitcoin prices. However, there was no structural change in Bitcoin prices in the long-term trend. This paper provides a way to show the reaction of Bitcoin prices to the uncertainty of fiat currencies at different time scales and suggests that the reaction is mainly captured by the medium-term trend.     

Currency Hedging Using the Mean-Gini Framework

The mean-Gini framework has been suggested as a robust alternative to the portfolio approach to futures hedging given its optimality under general distributional conditions. However, calculation of the Gini hedge ratio requires estimation of the underlying price distribution. We estimate minimum-Gini hedge ratios using two widely-used estimation procedures, the empirical distribution function method and the kernel method, for three emerging market and three developed market currencies. We find that these methods yield different Gini hedge ratios. These differences increase with risk aversion and are statistically significant for all developed market currencies but only one emerging market currency. In-sample analyses show that the empirical distribution function method is more effective at risk reduction than the kernel method for developed market currencies, whereas the kernel method is superior for emerging market currencies. Post-sample analyses strengthen the superiority of the empirical distribution function method for developed market and, in several cases, for emerging market currencies.JEL Classification: F31, G15     

把握历史机遇 承担做市使命

国际金融危机以来,央行抓住历史机遇适时启动人民币国际化进程,推出跨境贸易人民币结算试点及新兴市场货币挂牌工作。在央行指引下,中国银行全行统一部署,充分发挥各项优势,两项业务均取得可喜成果。同时,中国银行俄罗斯子行在莫斯科银行间货币交易所也应邀成为卢布兑人民币市场的做市商,实现了国内海外的同时做市。未来中国银行将一如既往地积极参与人民币国际化进程,脚踏实地地推动新兴市场货币做市业务发展,承担历史赋予的使命。     

Accounting for digital currencies

The purpose of this paper is twofold: (i) to investigate some of the main issues surrounding the classification of digital currencies, and (ii) to identify the accounting practices and standards tied to digital currencies. This paper discusses two different types of digital currencies, including: central bank digital currencies (CBDCs) and privately issued cryptocurrencies such as Bitcoin. The findings of this study suggest that current accounting standards do not precisely cover the accounting treatment of digital currencies, even though the estimated value of market capitalisation of cryptocurrency in 2022 was USD 200 billion. This conceptual paper identifies the imminent need for an accounting standard to provide guidance on the identification, classification, measurement, and presentation of digital currencies. In the interim, existing accounting standards can be amended to incorporate digital currencies to avoid inconsistent global accounting approaches.     

A Model Forecasting Risk for Emerging Market Currencies

In this paper, we propose a risk forecasting model for emerging market currencies. Our model is based on the Markov regime switch which is constructed by exploiting daily equity market information, and we show that our model outperforms the existing model using macroeconomic information. We evaluate it by the performance measures, the goodness-of-fit and the Wilcoxon rank-sum test.     

Capture the contagion network of bitcoin – Evidence from pre and mid COVID-19

COVID-19 is the first global scale crisis since the inception of Bitcoin. We compare the contagion phenomenon of Bitcoin and other financial markets or assets pre and during the COVID-19 shock in both contemporaneous and non-contemporaneous manner. This paper uses the directed acyclic graph (DAG), spillover index, and network topology to provide strong evidence on the directional contagion outcomes of Bitcoin and other assets. The empirical results show that the contagion effect between Bitcoin and developed markets is strengthened during the COVID-19 crisis. Particularly, European market has a dominant role. Excluding Bitcoin’s own shocks, United State and European markets are the main contagion sources to Bitcoin. European market also works as a intermediary to deliver infectious from United State and market fear. The findings show that gold always has contagion effect with Bitcoin, while gold, US dollar and bond market are the contagion receivers of Bitcoin under the shock of COVID-19. The empirical results further proved the safe haven, hedge and diversifier potential of Bitcoin in economic stable time, but also shows that the sustainability of these properties is undermined during the market turmoil.     

Does Bitcoin still own the dominant power? An intraday analysis

The study investigates the intraday dynamics and price patterns of the primary cryptocurrencies. The Granger Mackey-Glass (M-G) model is employed to examine the asymmetric and nonlinear dynamic interactions in the first moment using positive and negative returns. The bivariate BEKK-GARCH model is applied to identify cross-market volatility shocks and volatility transmissions in the cryptocurrency market. The intra-cryptocurrency market analysis reveals that Bitcoin contains predictive information that can nonlinearly forecast the performance of other digital currencies when cryptocurrency prices either are rising or declining. The dominant power of Bitcoin is not dismissed using the intraday data. Further, Bitcoin's intraday lagged shocks and volatility induces more rapid and destabilizing effects on the conditional volatility of other currencies than each of the other currencies does on BTC's conditional volatility. The virtual currency markets are dynamically correlated and integrated through first and second-moment spillovers.     

On the investment credentials of Bitcoin: A cross-currency perspective

We examine diversification capabilities of Bitcoin for a global portfolio spread across six asset classes from the standpoint of investors dealing in five major fiat currencies namely US Dollar, Great Britain Pound, Euro, Japanese Yen and Chinese Yuan. Considering the period of prolonged decline in Bitcoin’s value throughout 2018, we employ modified conditional value-at-risk and standard deviation as measures of risk to perform portfolio optimisations across three asset allocation strategies. Results show that portfolios denominated in Japanese Yen, Chinese Yuan and US Dollar account for greater proportion of optimal investment in Bitcoin and exhibit higher improvement in risk-adjusted returns due to investment in Bitcoin. We also perform a comprehensive risk-adjusted evaluation of portfolios with and without Bitcoin to reinforce striking variation in degree of diversification benefits of Bitcoin in a cross-currency context. Taken together, our findings provide insights into sharp disparity in Bitcoin trading volumes across national currencies from a portfolio theory perspective.     

The Return Performance of Cubic Market Model: An Application to Emerging Markets

This article studies the performance of the high-order moment capital asset pricing model (CAPM) market models in emerging markets. We apply the cubic market model (4-moment CAPM) to 16 emerging market stock indices ranging from January 2010 to September 2015. Performance of the model is evaluated through the Fama and MacBeth’s two-step regression and through different corrections proposed in the literature, as well as generalized method of moments (GMM) estimation. According to Fama–MacBeth’s procedure, CAPM, the quadratic and cubic market models seem to be insignificant for the analyzed sample; however, the GMM estimation shows that quadratic model is valid for Indian, Polish, and Thai country indices, whereas cubic market model is accurate for Indian country index.     

Changes in the market structure and risk management of Bitcoin and its forked coins

Inconsistency of consensus results in blockchain forks, which create a new financial risk. After filtering out Bitcoin’s linear, nonlinear, and lag impacts on forked coins, this study employs a bottom-up hierarchical clustering algorithm to examine the logarithmic return series for Bitcoin and its 14 forked coins from 2018 to 2021. The results indicate that the market for forked coins can be divided into three clusters: SegWit-supported forked coins, mature forked coins, and the latest forked coins. Bitcoin and the mature forked coins form a cluster, and its performance is superior to others. Although Bitcoin’s return significantly affects that of its forked coins, it does not affect the market structure. Furthermore, this study provides references for risk aversion among investors in forked coins and presents macro-level information for cryptocurrency market authorities.     

News sentiment in the cryptocurrency market: An empirical comparison with Forex

We use high frequency intra-day data to investigate the influence of unscheduled currency and Bitcoin news on the returns, volume and volatility of the cryptocurrency Bitcoin and traditional currencies over the period from January 2012 to November 2018. Results show that Bitcoin behaves differently to traditional currencies. Traditional currencies typically experience a decrease in returns after negative news arrivals and an increase in returns following positive news whereas Bitcoin reacts positively to both positive and negative news. This suggests investor enthusiasm for Bitcoin irrespective of the sentiment of the news. This phenomenon is exacerbated during bubble periods. Conversely, cryptocurrency cyber-attack news and fraud news dampen this effect, decreasing Bitcoin returns and volatility. Our results contribute to the discussion on the nature of Bitcoin as a currency or an asset. They further inform practitioners about the characteristics of cryptocurrencies as a financial asset and inform regulators about the influence of news on Bitcoin volatility, particularly during bubble periods.     

Performance of Currency Trading Strategies in Developed and Emerging Markets: Some Striking Differences

Expanding the currency investment universe makes a lot of sense from a diversification point of view. Nevertheless, 60% of the total foreign exchange turnover is still only traded in three currency pairs (USD/EUR, USD/JPY and USD/GBP). The share of trading in local currencies in emerging markets is only around 5%. This can be explained by the fact that some currency managers fear investing in emerging market currencies. Many believe that political risk is the most dominant driver in these markets and that traditional investment rules do not work. In this paper, I apply four technical trading strategies for the developed market currencies and for the most traded emerging market currencies. The empirical results show some striking differences. They suggest that trend-following rules work better for emerging market currencies, while carry trading strategies perform better across developed market currencies. Nevertheless, it seems that conventional techniques could be successfully applied to both developed and emerging market currencies. I conclude that currency managers should not be afraid to diversify into emerging market currencies. They should, however, adjust their trading style accordingly.     

Does Bitcoin behave as a currency?: A standard monetary model approach

We derive the Bitcoin exchange rate dynamics by solving the exchange rate equation of the standard flexible-price monetary model to investigate any characteristics of Bitcoin like a currency. The dynamics is driven by an asymmetric mean-reverting fundamental shock which can be attributed to a money demand shock. A crash occurs when the exchange rate with a weakened mean-reverting force breaches a lower boundary where a smooth-pasting condition is imposed. The empirical results show the exchange rate dynamics can be calibrated according to the model, in which the mean reversion of the dynamics is positively co-integrated with the Bitcoin transaction volume indicating demand for Bitcoin; and with the risk reversals of the commodity currencies (Australian dollar and Canadian dollar) in currency option markets. The analysis shows that the Bitcoin exchange rate shares some characteristics of commodity currencies with crash risk. This suggests that Bitcoin behaves as a currency between fiat money and a crypto-commodity used for trading and investment purposes.     

Trading activity and price discovery in Bitcoin futures markets

This study examines the impact of trading activities on price discovery in the Bitcoin futures markets. We find that trades of hedgers are positively correlated with the modified information shares in both CME and CBOE futures markets, suggesting that their trading promotes futures market efficiency. Retailers’ trading activity relates negatively to the price discovery of the CME Bitcoin futures and thus destabilizes the market. Speculators exert positive (negative) impact on the price discovery in the CME (CBOE) Bitcoin futures. Our finding that CME’s Bitcoin futures exhibit superior price discovery than CBOE’s provides plausible justification for CBOE’s decision in March 2019 to suspend further listings of Bitcoin futures contracts.     

International Equity Index and Currency Futures: Commodity Currencies or Emerging Versus Developed Markets?

Equity index futures in both emerging and developing markets that are net commodity exporters are strongly linked to their respective currency futures markets. Unconditional correlations among equity and currency futures are the highest for these net basic materials producers in both emerging and developed markets. Granger causality tests also indicate that stock market returns are more strongly related to currency futures returns for commodity-exporting countries. Additionally, conditional correlations among currency and equity futures returns are the strongest for commodity-producing countries in both emerging and developed economies. Volatility spillover analysis provides consistent results. The overall results indicate that the status of a country as a net importer or exporter of raw materials is more important to the relationship between equity and currency futures than whether it is an emerging or developed economy.     

Nonlinear tail dependence in cryptocurrency-stock market returns: The role of Bitcoin futures

We investigate the median and tail dependence between cryptocurrency and stock market returns of BRICS and Developed countries using a newly developed nonparametric cumulative measure of dependence over the period January 4, 2016 – December 31, 2019 as well as before and after the introduction of Bitcoin futures on December 17, 2017. The new measure is model-free and permits measuring tail risk. The results highlight the leading role of S&P500, Nasdaq and DAX 30 in predicting BRICS and developed countries’ stock market returns. Among BRICS countries, BVSP shows a starring role in predicting stock market returns. BSE 30 is the most predictor of cryptocurrencies, which have a little predictability on stock market returns. Ethereum has the leading role in predicting cryptocurrencies and stock market returns followed by Bitcoin. Tail dependence shows substantial role of S&P500, Nasdaq and BVSP in predicting stock market returns. Subsample analysis show the role of Bitcoin futures in reshaping the mean and tail dependence between cryptocurrency and stock market returns. Our results have important policy implications for portfolio managers, hedge funds and investors.     

Flight-to-quality and correlation between currency and stock returns

We document that capital flows in and out of emerging or developed markets are sensitive to global equity market conditions. Capital tends to move out of emerging into developed countries in global down markets, leading to depreciation (appreciation) of emerging (developed) currencies. This generates a positive (negative) correlation between currency and equity in emerging (developed) markets which is amplified by the magnitude of the capital movement. We also verify that hedging currency risks may undo the natural hedge and increase the total return volatility under negative correlation.     

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.     

Safehavenness of currencies

This study assesses the ‘safehavenness’ of a number of currencies with a view to providing a better understanding of how capital flow tends to react to a sharp increase in global risk aversion in turbulent times. It focuses on how the currencies are perceived by international investors or, more specifically, whether they are seen as safe-haven or risky currencies. To assess the safehavenness of the currency, we use risk reversal, which is the price difference between the call and put options of a currency, as it reflects how disproportionately market participants are willing to pay to hedge against its appreciation or depreciation. The relationship between the risk reversal of the currency and global risk aversion is estimated by means of parametric and non-parametric regressions that allow us to capture currency behaviour in times of extreme adversity, that is, the tail risk. Our empirical results found the Japanese yen and, to a lesser extent, the Hong Kong dollar to be the only safe havens under stressful conditions among the 34 currencies vis-à-vis the US dollar.