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Several procedures to forecast daily risk measures in cryptocurrency markets have been recently implemented in the literature. Among them, long‐memory processes, procedures taking into account the presence of extreme observations, procedures that include more than a single regime, and quantile regression‐based models have performed substantially better than standard methods in terms of forecasting risk measures. Those procedures are revisited in this paper, and their value at risk and expected shortfall forecasting performance are evaluated using recent Bitcoin and Ethereum data that include periods of turbulence due to the COVID‐19 pandemic, the third halving of Bitcoin, and the Lexia class action. Additionally, in order to mitigate the influence of model misspecification and enhance the forecasting performance obtained by individual models, we evaluate the use of several forecast combining strategies. Our results, based on a comprehensive backtesting exercise, reveal that, for Bitcoin, there is no single procedure outperforming all other models, but for Ethereum, there is evidence showing that the GAS model is a suitable alternative for forecasting both risk measures. We found that the combining methods were not able to outperform the better of the individual models.
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Covid-19 salgınının ortaya çıkmasından sonra dünya çapında ekonomik çalkantılar ve şiddetli piyasa düşüşlerinin ortaya çıktığı görülmüştür. Bu dönemde hisse senedi piyasalarına yatırım yapmış ajanlar için hedge ve/veya güvenli liman araçları arayışları artmıştır. Kripto paralar ve altın özellikle gelişmekte olan ülke piyasalarındaki yatırımcılar için hedge ve/veya güvenli liman olma konusunda iyi potansiyellere sahiptir. Bu çalışmada, Borsa Ístanbul için Bitcoin, Etherium, Ripple, Litecoin ve altın piyasalarının hedge ve/veya güvenli liman piyasalar olup olmadığı, GARCH(1,1) hata terimleri varsayımı altında modellenmiş regresyon sistemi yardımı ile araştırılmıştır. Analizlerde örneklem olarak 4 Eylül 2017 – 30 Mart 2022 tarihleri arasındaki günlük frekanslı verilerden faydalanılmıştır. Ayrıca, Covid-19 salgın dönemi etkilerini ayrıştırmak için örneklem iki alt gruba ayrılmış ve tahminler Covid-19 öncesi dönem (31 Aralık 2019 öncesi) ve Covid-19 dönemi (31 Aralık 2019 ve sonrası) için ayrı ayrı analiz edilmiştir.A.B.D. doları cinsinden elde edilmiş kripto para (BTC, ETH, XRP, LTC), altın ve BÍST100 endeks getirileri kullanılarak bulunan tahmin sonuçlarına göre, tüm örneklem için Litecoin zayıf güvenli liman olarak ortaya çıkarken, Covid-19 öncesi dönemde Bitcoin ve Etherium zayıf hedge, Covid-19 salgın döneminde de Etherium zayıf güvenli liman olma özellikleri göstermektedir. Tüm örneklem ve salgın öncesi dönem verileri söz konusu olduğunda, BÍST100 endeks getiri dağılımının %10 çeyrek değerinden az olduğu durumlarda Bitcoin, Etherium ve Ripple güvenli liman piyasalar olarak gözlemlenirken, salgın döneminde altın, BÍST100 endeks getiri dağılımının %1 çeyrek değerinden az olduğu durumlarda güvenli bir liman olarak ortaya çıkmıştır. Fakat tüm analizlere dayanarak, altının genel görünümüyle BÍST100 endeksi için hedge veya güvenli limandan çok bir çeşitlendirici varlık olarak öne çıktığı söylenebilir.Alternate :After the Covid-19 outbreak, economic turmoil and severe market crashes have been observed around the world. During this crisis period, cyriptocurrencies and gold have become potentially good hedge and/or safe haven assets for especially the stock investors in emerging markets. This study investigates whether or not Bitcoin, Etherium, Ripple, Litecoin and gold markets have hedge and/or safe-haven properties for Borsa Ístanbul through a regression system modeled under the assumption of GARCH(1,1) error terms. Daily frequency data covering the period September 4, 2017 through March 30, 2022 is used in the sample analysis. In addition, to separate out the effects of the Covid-19 pandemic on the analysis, full sample is divided into two subgroups and the estimations are made separately for the pre-Covid-19 period (before 31 December 2019) and the Covid-19 period (31 December 2019 and later).According to the estimation results, Litecoin emerges as a weak safe haven for Borsa Ístanbul over the entire sample period, while Bitcoin and Etherium appear to be weak hedges in the pre-pandemic period. During the Covid-19 pandemic period, Etherium is shown to be a weak safe haven for the BÍST100 index. Full sample and pre-pandemic data analysis reveal that, Bitcoin, Etherium and Ripple act as safe-haven markets in some cases when the BÍST100 index returns hit lower than their 10% quantile value. After the outburst of the Covid-19 however, gold seems to act as a safe haven asset for Borsa Ístanbul when the BÍST100 index returns hit lower than their 1% quantile value. Based on the overall estimation results, gold stands out as a diversifier rather than a hedge and/or a safe haven asset for the BÍST100 index.
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This study provides an empirical analysis on the main univariate and multivariate stylized facts iin return series of the two of the largest cryptocurrencies, namely Ethereum and Bitcoin. A Markov-Switching Vector AutoRegression model is considered to further explore the dynamic relationships between cryptocurrencies and other financial assets. We estimate the presence of volatility clustering, a rapid decay of the autocorrelation function, an excess of kurtosis and multivariate little cross-correlation across the series, except for contemporaneous returns. The analysis covers the pandemic period and sheds lights on the behaviour of cryptocurrencies under unexpected extreme events.
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During the Covid-19 pandemic, there has been a rapid shift in global transaction patterns from offline to online digital payment models, along with a growing interest in the development of Central Bank Digital Currencies (CBDCs) in various countries. This article spotlights the unexamined issue of digital currency regulation by examining the practice and related regulatory rules of the pilot CBDC in China. Beginning with the global design choices of digital currencies, the article comparatively examines the technical design of China's CBDC, known as e-CNY. It further triggers a rethinking of conventional regulations for the protection of digital currency information by investigating the gap between the actual operation and design of e-CNY, as well as the gap between pilot policies and legal provisions such as the Cybersecurity Law, the Data Security Law, and the Personal Information Protection Law. This article argues that, on the one hand, the legislative balance between the protection of personal information and the regulation of illicit financial activities involved in the "loosely coupled account link” system of e-CNY should be reconsidered. On the other hand, the delineation of rights and responsibilities between dissemination institutions, payment service providers, and end-users needs to be further redefined and clarified.
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The aims of this research is to know the protection of float funds in the regulation of the payment system in Indonesia and how to optimize the protection of float funds in order to mitigate insolvency risk. This research will examine the regulation relating to float funds, which has seen tremendous expansion in recent years. However, until today, the float fund does not yet have an optimum protection to mitigate risk of insolvency. Therefore the urgency of the protection of float fund through an update of regulation should be of concern, that is the necessity of insured protection towards float fund, as well as regulation on the use of float funding investment returns. This research is descriptive analytic and uses normative juridical approach by prioritizing the analysis of secondary data in the form of primary source of law that is laws and regulations;secondary source of law such as journals and other previous research;and tertiary source of law. Next, the received data is analyzed qualitatively and juridical. The conclusion of this research are by regulation, the protection of float fund has not been conducted optimally, a concrete effort is needed from the regulator to optimize the protection of float fund to mitigate the risk of failure of payment due to insolvency by insurance protection, and regulation on the use of float fun investment returns.
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PurposeThis paper aims to analyse COVID-19 indices and blockchain features on Bitcoin and Ethereum returns, respectively. The authors focus on the most used and owned cryptocurrencies that cover Europe, the US and Asian countries.Design/methodology/approachAn autoregressive distributed lag panel (pooled mean group and mean group) is utilized, and a robustness check is incorporated by using a Random Effect Model and Generalized Method of Moments (GMM).FindingsFour new findings were discovered, including (1) the vaccine confidence index (VCI) pushes economic recovery and increased demand for the Bitcoin market, but the opposite result was interestingly observed from Ethereum;(2) the blockchain features were revealed to be essential to Bitcoin, while they were irrelevant to Ethereum for short-run country-specific results;(3) the hash rate and network difficulty moved inversely during the pandemic;and (4) the government played a significant role in taking action during uncertain times and regarding cryptocurrency policies.Research limitations/implicationsVCI is constructed by the most used vaccine type in our sample countries (i.e. Pfizer), as the data for a specific classification by each type is still unavailable.Practical implicationsProviding an evenly distributed vaccination program primary vaccination series against COVID-19 to the citizens is an essential duty of the government. Bitcoin policymakers and investors should watch the COVID-19 vaccine distributions closely as it will affect its return. Ethereum is emphasized to keep developing its smart contract which appeared to outplay other blockchain features. Cryptocurrency investors should be wise in their investment decisions by analysing the news thoroughly.Social implicationsThis research emphasizes that the success in the roll-out of COVID-19 vaccination requires citizens' willingness to participate and their trust in the vaccine's efficacy. Such self-awareness and self-discipline in society can ultimately empower individuals and stabilise the economy. Nevertheless, the implementation of health protocols is still highly required to prevent the spread of new variants of COVID-19.Originality/valueThis is the first study that attempts to construct a VCI which denotes the confidence derived from the administration of full-dose COVID-19 vaccines (an initial vaccine and a second vaccine). The authors further find the impact on cryptocurrency returns. Next, blockchain size is utilized as a new determinant of cryptocurrencies.
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PurposeSmart contracts are self-executing computer programmes that have the potential to be used in several applications instead of traditional written contracts. With the recent rise of smart systems (e.g. Internet of things) and digital platforms (e.g. blockchain), smart contracts are gaining high interest in both business and academia. In this work, a framework for smart contracts was proposed with using reputation as the system currency, and conducts currency mining through fulfilling the physical commitments that are agreed upon.Design/methodology/approachA game theory model is developed to represent the proposed system, and then a system dynamics simulator is used to check the response of the blockchain with different sizes.FindingsThe numerical results showed that the proposed system could identify the takeover attacks and protect the blockchain from being controlled by an outsider. Another important finding is that careful setting of the maximum currency amount can improve the scalability of the blockchain and prevent the currency inflation.Research limitations/implicationsThis work is proposed as a conceptual framework for supply chain 4.0. Future work will be dedicated to implement and experiment the proposed framework for other characteristics that may be encountered in the context of supply chain 4.0, such as different suppliers' tiers, different customer typologies and smart logistics applications, which may reveal other challenges and provide additional interesting insights.Practical implicationsBy using the proposed framework, smart contracts and blockchains can be implemented to handle many issues in the context of operations and supply chain 4.0, especially in times of turbulence such as the COVID-19 global pandemic crisis.Originality/valueThis work emphasizes that smart contracts are not too smart to be applied in the context of supply chain 4.0. The proposed framework of smart contracts is expected to serve supply chain 4.0 by automating the knowledge work and enabling scenario planning through the game theory model. It will also improve online transparency and order processing in real-time through secured multitier connectivity. This can be applied in global supply chain functions backed with digitization, notably during the time of the pandemic, in which e-commerce and online shopping have changed the rules of the game.
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This paper performs the asymmetric multifractal cross-correlation analysis to examine the COVID-19 effects on three relevant high-frequency fiat currencies, namely euro (EUR), yen (YEN) and the Great Britain pound (GBP), and two cryptocurrencies with the highest market capitalization and traded volume (Bitcoin and Ethereum) considering two periods (Pre-COVID-19 and during COVID-19). For both periods, we find that all pairs of these financial assets are characterized by overall persistent cross-correlation behavior (αxy(0) > 0.5). Moreover, COVID-19 promoted an increase in the multifractal spectrum's width, which implies an increase in the complexity for all pairs considered here. We also studied the Generalized Cross-correlation Exponent, which allows us to verify that there is no asymmetric behavior between Bitcoin and fiat currencies and between Ethereum and fiat currencies. We conclude that investing simultaneously in major fiat currencies and leading cryptocurrencies can reduce the portfolio risk, leading to improvement in the investment results.
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PurposeThe COVID-19 pandemic is known to have affected the logistics and supply chains;however, there is no adequate empirical evidence to prove in which way it has affected the relationship between the stocks related to this field with the corresponding cryptocurrencies. This paper aims to test the dynamic relationship of cryptocurrencies with supply chain and logistics stocks.Design/methodology/approachIn this paper, the author tests the causal and long-run relationship between logistics and supply chain stocks with the corresponding cryptocurrencies related to these fields, or those that are known to exhibit characteristics that can be utilized by these fields, testing also whether the COVID-19 pandemic affected this relationship. To do so, the author performs the variable-lag causality to test the causal relationship, and examines if this relationship changed due to COVID-19. The author then implements the multifractal detrended cross-correlation analysis to investigate the characteristics of a possible long-run relationship, testing also whether they changed due to COVID-19.FindingsThe results indicate that there is a positive long-run relationship between each logistics and supply chain stocks and the corresponding cryptocurrencies, before and also during COVID-19, but during COVID-19 this relationship becomes weaker, in most cases. Moreover, before COVID-19, the majority of the cases indicate a causal direction from cryptocurrencies to the stocks, while during COVID-19, the causal relationships decrease in multitude, and most cases unveil a causal direction from the stocks to cryptocurrencies.Originality/valueThe causal pattern changed during COVID-19, and the long-run relationship became weaker, showing a change in the dynamics in the relationship between logistics and supply chain stocks with cryptocurrencies.
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PurposeThe purpose of this paper is to explore the relationship between Dow Jones Islamic Market World Index, Islamic gold-backed cryptocurrencies and halal chain in the presence of state (regime) dynamics.Design/methodology/approachThe authors have used the Markov-switching model to identify bull and bear market regimes. Moreover, the dynamic conditional correlation, the Baba, Engle, Kraft and Kroner- generalized autoregressive conditional heteroskedasticity and the wavelet coherence models are applied to detect the presence of spillover and contagion effects.FindingsThe findings indicate various patterns of spillover between halal chain, Dow Jones Islamic Market World Index and Islamic gold-backed cryptocurrencies in high and low volatility regimes, especially during the COVID-19 pandemic. Indeed, the contagion dynamics depend on the bull or bear periods of markets.Practical implicationsThese present empirical findings are important for current and potential traders in gold-backed cryptocurrencies in that they facilitate a better understanding of this new type of assets. Indeed, halal chain is a safe haven asset that should be combined with Islamic gold-backed cryptocurrencies for better performance in portfolio optimization and hedging, mainly during the COVID-19 period.Originality/valueTo the best of the authors' knowledge, this paper is the first research on the impact of the halal chain on the Dow Jones Islamic Market World Index return, Islamic gold-backed cryptocurrencies returns in the bear and bull markets around the global crisis caused by the COVID-19 pandemic.
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Interest in leveraging blockchain technology to boost healthcare and e-health solutions has lately increased. Blockchain has proven to have enormous promise in a range of e-health industries because of its decentralized and reliable nature, including the secure exchange of electronic health records (EHRs) and database access management among numerous medical entities. A unique paradigm known as the "patient-centric approach” places the patient at the center of the healthcare system and gives them complete control over who has access to and can share their personal health information. Strong confidentiality and safety requirements are necessary for health information. Additionally, other concerns must be resolved, such as secrecy, interoperability, scalability, cost-effectiveness, and timeliness. This paper offers a patient-centric privacy-preserving framework for an efficient and safe medical record to address these problems. Based on three parameters transaction cost, execution time, and gas cost. Three blockchain platforms are compared by using the smart contract to find out the suitable platform for the implementation of this framework. Blockchain platforms served as a benchmark for the performance assessment of a designed framework. Although blockchain will not fix every issue in healthcare organizations, it will undoubtedly assist in dramatically reducing some of the most critical ones.
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Unlike the 2007–2009 economic meltdown, the COVID-19 pandemic was not caused by problematic market situation or reckless financial policy;it was, in fact, completely unpredicted (Hsu and Tang 2022). [...]it contrasted from other earlier dramatic events caused by economic and financial circumstances, including the Asian financial crisis in 1997–1998 or the European debt crisis in 2010–2013 (Dong et al. 2022). [...]the similarity of these downturns is that they commenced in one nation or area and spread rapidly to other markets, prompting considerable disruption in the worldwide financial system (Zhang et al. 2022). [...]COVID-19 has been regarded as an "exogenous shock” or potentially a "black swan”, as it was such a rare occurrence that has major repercussions for stock markets without any reasonable anticipation (Costola et al. 2023). According to Yu and Xiao (2023), the pessimistic news from COVID-19 government restriction policies generated more instability in stock markets than the optimistic news. [...]Conlon and McGee (2020) raised suspicions on Bitcoin's potential to provide protection from volatility in conventional markets. [...]the publications featured in this Special Issue expanded our comprehension surrounding the effect of the COVID-19 pandemic on financial markets and the real economy, and they proposed appealing future research avenues.
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PurposeThe purpose of this research is to analyze the Bitcoin (BTC) and Ether (ETH) long memory and conditional volatility.Design/methodology/approachThe empirical approach includes ARFIMA-HYGARCH and ARFIMA-FIGARCH, both models under Student‘s t-distribution, during the period (ETH: November 9, 2017 to November 25, 2021 and BTC: September 17, 2014 to November 25, 2021).FindingsFindings suggest that ARFIMA-HYGARCH is the best model to analyze BTC volatility, and ARFIMA-FIGARCH is the best approach to model ETH volatility. Empirical evidence also confirms the existence of long memory on returns and on BTC volatility parameters. Results evidence that the models proposed are not as suitable for modeling ETH volatility as they are for the BTC.Originality/valueFindings allow to confirm the fractal market hypothesis in BTC market. The data confirm that, despite the impact of the Covid-19 crisis, the dynamics of BTC returns, and volatility maintained their patterns, i.e. the way in which they evolve, in relation to the prepandemic era, did not change, but it is rather reaffirmed. Yet, ETH conditional volatility was more affected, as it is apparently higher during Covid-19. The originality of the research lies in the focus of the analysis, the proposed methodology and the variables and periods of study.
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This study examines the volatility changes of 20 cryptocurrencies from January 2018 to May 2021 using sparse VHAR-MGARCH model. Our proposed model incorporates the high-dimensionality and time-varying conditional heterogeneity of cryptocurrency markets. We examined the time-varying spillover index, dynamic correlation structure, and connectivity between cryptocurrencies. Our empirical analysis clearly shows that there was a volatility shift on 13 March 2020, due to a market crash caused by COVID-19. This naturally divides the data into three periods: pre-crisis, during the crisis, and post-crisis regimes. The pre-crisis regime exhibited long-term cyclic fluctuations in the spillover index. However, after the market crash, the spillover index remained at a very high level with almost no interconnections between cryptocurrencies. The post-crisis regime showed quite a few irregular and sharp spikes in the spillover index, together with record-breaking prices and volumes.
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Our investigation strives to unearth the best portfolio hedging strategy for the G7 stock indices through Bitcoin and gold using daily data relevant to the period 2 January 2016 to 5 January 2023. This study uses the DVECH-GARCH model to model dynamic correlation and then compute optimal hedge ratios and hedging effectiveness. The empirical findings show that Bitcoin and gold were rather effective hedge assets before COVID-19 and diversifiers during the pandemic and Russia–Ukraine war. From hedging effectiveness perspectives, gold and Bitcoin are safe-haven assets, and the investment risk of G7 stock indices could be hedged by taking a short position during thepandemic period and war except for the pair Nikkei/Gold. Additionally, gold beats Bitcoin in terms of hedging efficiency. We thus demonstrate the central role of Bitcoin and gold as financial market participants, particularly during market turmoil and downward movements. Our findings can be of interest to investors, regulators, and governments to take into consideration the role of Bitcoin in financial markets.
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This paper contributes to the literature dedicated to the interlinkages between cryptocurrencies and currencies by investigating whether Bitcoin price movements affect the exchange rates of a sample of nine European countries with non-euro currencies. By resorting to the novel unconditional quantile regression, we show that there is a statistically significant link between Bitcoin price movements and changes in nominal exchange rates. In normal market conditions, an increase in the price of Bitcoin can be associated with an appreciation of the currencies from our sample, while during the COVID-19 pandemic, the relationship inversed. In addition, we find heterogeneities in this relationship, depending on the level of change in the nominal exchange rate. The results emphasize the relevance of Bitcoin price movements to the conduct of monetary policy through the exchange rate channel and that investors in cryptocurrencies and various financial assets denominated in the currencies from our sample can benefit from diversification by including both types of assets in their portfolios.
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Pugliese focuses on the year of internal audit. For the first time in three years, they begin a year with something other than COVID-19 as the undisputed main headline. To be clear, COVID remains one of the top issues, and it continues to have global implications on everything from supply chains to budgets. But, after years of dealing with the pandemic, businesses have mostly accounted for COVID-based disruptions and incorporated adjustments and accommodations into their business plans. Businesses are now beginning to return to operations that resemble pre-COVID "normalcy," and 2023 is a blank slate that presents internal auditors with a tremendous opportunity to reaffirm our value and claim our space in emerging areas. Top issues for the year once again include cybersecurity, ESG topics, and fraud, not to mention increased scrutiny on cryptocurrencies following the FTX collapse. With a spotlight on these issues, their profession is sure to remain front and center.
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This paper investigates the dynamic volatility spillover and connectedness among different sectors of the Indian stock market during the Covid-19 pandemic. The study considers 18 sectors listed on the National Stock Exchange. Diebold-Yilmaz Volatility spillover model and Baruník and Křehlík frequency connectedness methodology are used to investigate the time varying dynamics of the spillover during the turbulence period. Daily market prices of 18 sectors, from March 15, 2019, to February 28, 2022, are considered for the present study. The results reveal that the spillover from infra, commodities, services, MNC, oil and gas, financial services, private bank, energy, and PSE is more, and this clearly indicates that during the pandemic, these sectors mostly had a spillover effect on other sectors.
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PurposeThis paper aims to empirically investigate the extent to which interdependence in markets may be driven by COVID-19 effects.Design/methodology/approachThe current global COVID-19 pandemic is adversely affecting the oil market (West Texas Intermediate) and crypto-assets markets.FindingsThe authors find that the dependence structure changes significantly after the global pandemic, providing valuable information on how the COVID-19 crisis affects interdependencies. The results also prove that the performance of digital gold seems to be better compared to stablecoin.Originality/valueThe authors fit copulas to pairs of before and after returns, analyze the observed changes in the dependence structure and discuss asymmetries on propagation of crisis. The authors also use the findings to construct portfolios possessing desirable expected behavior.
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PurposeThis article examines the effects of credit to private sector on the business and trade activities. The effectiveness of rapid expansion in public and private borrowing through state's intervention after COVID-19 pandemic has been assessed in this study.Design/methodology/approachThe model to determine the role of credit expansion is based on four equations estimated through panel least square technique on 18 years data of 186 countries.FindingsIt is concluded that credit to private sector and external debt improve the investment in infrastructure, which is a significant determinant of gross domestic product growth. Empirical evidences corroborate that higher number of firms using banks to finance their investment and the volume of broad money determine the magnitude of credit to private sector.Originality/valueThis study explores some new evidences and aspects of the credit financing which have not been discussed in this way before.