Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies

This paper investigates the extreme dependence and risk spillovers between Bitcoin and the currencies of the BRICS and G7 economies. We find time-varying dependence between Bitcoin and all currencies. Moreover, when analysing risk spillovers from Bitcoin to currencies, we find that Bitcoin exercises significant power over most currencies, with the South African rand and Brazilian real holding both the highest downside and upside risk before and during the COVID-19 pandemic period, respectively. When considering risk spillovers from currencies towards Bitcoin, the Japanese yen exhibits the highest downside spillovers. Importantly, we find asymmetric spillovers between extreme upward and downward movements. • We study dependencies between Bitcoin and the currencies of the BRICS and G7 economies. • We find time-varying dependence between Bitcoin and all of the fiat currencies. • Bitcoin exercises significant power over most of the considered currencies. • We find asymmetric spillovers between extreme upward and downward movements. [ FROM AUTHOR] Copyright of Emerging Markets Review is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A new copula-based bivariate Gompertz–Makeham model and its application to COVID-19 mortality data

One of the useful distributions in modeling mortality (or failure) data is the univariate Gompertz–Makeham distribution. To examine the relationship between the two variables, the extended bivariate Gompertz–Makeham distribution is introduced, and its properties are provided. Also, some reliability indices, including aging intensity and stress-strength reliability, are calculated for the proposed model. Here, a new copula function is constructed based on the extended bivariate Gompertz–Makeham distribution. Some of its features including dependency properties, such as dependence structure, some measures of dependence, and tail dependence, are studied. The estimation of the parameters of new copula is presented, and at the end, a simulation study and a performance analysis based on the real data are presented. So, by analyzing the mortality data due to COVID-19, the appropriateness of the proposed model is examined. [ FROM AUTHOR] Copyright of Iranian Journal of Fuzzy Systems is the property of University of Sistan & Baluchestan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

The impacts of COVID-19 on the dependence structure of the stock market

This article uses Gaussian copula marginal regression and tail dependence estimation by copula to explore COVID-19's effects on the dependence structure of the US stock market. Specifically, we investigate the dependence between S&P 500 returns and returns in eleven sectors at the mean and the tails of the joint distribution prior to and during the pandemic. We uncover strong evidence of the pandemic's heterogeneous effects on dependence structures across sectors. Certain sectors, including information technology and health care, increase in importance as return determinants of the composite index during the pandemic. We also find that COVID-19 increases tail dependence, specifically lower tail dependence more than upper tail dependence. These findings will be useful to investors interested in managing risk, particularly during pandemics.

Sukuk and bond dynamics in relation to exchange rate

PurposeThis study aims to contribute by expanding the existing literature on Sukuk return and volatility and exploring the implications of the Sukuk-exchange rate interactions. Design/methodology/approachThis study examines the dynamic interactions of Sukuk with exchange rate in 15 countries, employing the Wavelet approach that considers both time and investment horizons. FindingsThe results reveal significant evolving coherence of Sukuk return and volatility with the underlying exchange rate. The relationship is more potent than what this study witnesses in their counterpart bond market. For Sukuk returns, the coherence is negative, whereas it is positive for volatility. Notably, the coherence is strong in the medium to long term and intensifies during extreme economic episodes, especially during the COVID-19 pandemic. These findings are further validated by comparing firm-level matched data for Sukuk and conventional bond. Originality/valueTo the best of the authors' knowledge, this is the first study that reports the dynamic relationship of Sukuk return and volatility with the underlying exchange rate in 15 countries. Collectively, this study unites valuable insights for faith-based active Islamic investors and cross-border portfolio managers.

Does COVID-19 pandemic event alter the dependence structure breaks between crude oil and stock markets in Europe and America

This article attempts to investigate the influence of novel coronavirus (COVID-19) pandemic on the dependence structure break between crude oil and stock markets in Europe and America using ARMA-GARCH and R-vine copula methods. The empirical results demonstrate that international crude oil and European (American) stock markets have significant asymmetric and symmetric dependence structure, rapid outbreak of COVID-19 pandemic triggers their dependence structure break. The results of Kendall correlation confirms that COVID-19 pandemic amplifies the dependence risks between European Brent crude oil and France (German and Spain) stock markets and reduces the dependence risk between Brent crude oil and UK (Italy) stock markets after February 20, 2020. The COVID-19 pandemic may amplify the dependence risk between West Texas Intermediate (WTI) crude oil and Canada stock markets after March 23, 2020, it first quickly reduces the dependence risks between WTI crude oil and US (Brazil and Mexico) stock markets after March 23, 2020 and then enlarges their dependence risks after June 30, 2020. European and American crude oil and stock markets have induced different ranges of their dependence risks in different time scales and their dependence structure breaks have good robustness.

Dependence between Chinese stock market and Vietnamese stock market during the Covid-19 pandemic.

The study aims to investigate the tail dependence between Chinese stock market and Vietnamese stock market in the context of the Covid-19 pandemic. Using the data on the Ho Chi Minh City Stock Exchange (VNI) and the Shanghai Stock Exchange (SSEC) representing for Vietnam and China stock markets, the study reveals the tail dependence across three periods including: pre-pandemic, during the chaos of the pandemic, and the period of adaptation to the pandemic. Using the copula method including Normal, Clayton, Plackett, Frank, Student, Symmetrised Joe-Clayton copulas, the research results confirm that there is no dependent relationship between the stock market between the two countries in the pre-pandemic. During the pandemic, the Vietnamese stock market is heavily dependent on Chinese stock market, especially the upper tail dependence. During the period of adaptation to the pandemic, this dependence relationship still exists but less than that in the pandemic.

Conditional dependence structure and risk spillovers between Bitcoin and fiat currencies

This paper investigates the extreme dependence and risk spillovers between Bitcoin and the currencies of the BRICS and G7 economies. We find time-varying dependence between Bitcoin and all currencies. Moreover, when analysing risk spillovers from Bitcoin to currencies, we find that Bitcoin exercises significant power over most currencies, with the South African rand and Brazilian real holding both the highest downside and upside risk before and during the COVID-19 pandemic period, respectively. When considering risk spillovers from currencies towards Bitcoin, the Japanese yen exhibits the highest downside spillovers. Importantly, we find asymmetric spillovers between extreme upward and downward movements.

Modeling Dependent Structure Among Micro-Economics Variables Through COPAR (1)-Model in Pakistan.

A great fluctuations in oil price due to COVID-19 has been observed worldwide. Expertise of complicated relationships among economic indicators has considerable significance for consumers, specialists and strategy producers the same. This exploration work is devoted to investigating the impact of oil price fluctuations due to corona virus pandemic on inflation rate, interest rate and industrial production during lock-down using recent monthly data of Pakistan economic system starting from 2008-01 to 2020-04. At analysis stage, we generally tend to contemplate a novel autoregressive model approach to model non-linear dependence structure amongst a couple of time series. Having gain from the flexibleness of R-vine copulas, the copula autoregression with efficiency investigates the have an impact on of one-time series onto some other: it really is, one-time arrangement normally plays a vital role. Through these qualities of the model, we tend to investigate fuel price effects on industrial production, expansion rate and interest rate in my homeland. One in every of the key finding of this analysis is that there's a weak tail asymmetry, however some tail dependence, that COPAR-model with efficiency absorbs to account. Furthermore, the fashions monitor lagged reactions of interest rate and industrial production on adjustments in fuel prices inside Pakistan. The oil price result on the inflation rate; on the other hand, is quite rapid.

Dynamic asymmetric dependence and portfolio management in cryptocurrency markets

As a new form of digital assets based on blockchain technology, the cryptocurrency has received increasing attention from researchers and practitioners. However, less attention has been paid to their joint dynamics from the perspective of portfolio management. This paper investigates the dependence dynamics across four major cryptocurrencies and their economic importance in portfolio management using the data from January 2014 to June 2020. Our empirical analysis shows that significant economic gains can be obtained from modelling dynamic asymmetric dependence among cryptocurrencies. We show that our results are robust to the period of the recent market fluctuations caused by COVID-19.