Journal ArticleDOI
Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market
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In this paper, the authors use vine copula approaches to model the co-dependence and portfolio value-at-risk of six cryptocurrencies using data of daily periodicity from September 2015 to June 2018.About:
This article is published in International Economics.The article was published on 2019-08-01. It has received 21 citations till now. The article focuses on the topics: Portfolio & Vine copula.read more
Citations
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A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets
TL;DR: In this article, an integrated survey of GARCH methodologies applications on 67 empirical papers that focus on cryptocurrencies is presented, where the main characteristics and the optimal approaches for modeling returns and volatility of cryptocurrencies are under scrutiny.
Journal ArticleDOI
Optimizing the market-risk of major cryptocurrencies using CVaR measure and copula simulation
TL;DR: In this article, the conditional value at risk was used to quantify the risk exposure and generalized Pareto distribution copula technique to analyze extreme events which helps in finding out the cause of extreme events.
Journal ArticleDOI
Is Tether a safe haven of safe haven amid COVID-19? An assessment against Bitcoin and oil using improved measures of risk
Khreshnal I. A. Syuhada,Arief Rahman Hakim,Djoko Suprijanto,Intan Muchtadi-Alamsyah,Lukman Hanif Arbi +4 more
TL;DR: In this article , an improved version of Value-at-Risk (VaR) and Expected Shortfall (ES) was proposed to evaluate the safe-haven properties of Bitcoin and Tether.
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Dependence Structure across Equity Sectors: Evidence from Vine Copulas
TL;DR: In this article , the authors examined the sectoral dependence among 82 Pakistani companies using a vine copula approach and daily data from July 1, 2014, to December 17, 2019.
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Stablecoins as a tool to mitigate the downside risk of cryptocurrency portfolios
TL;DR: In this paper , the authors empirically assessed the ability of three putative stablecoins (two dollar-backed, Tether and USD Coin; and one goldbacked, Digix Gold) to mitigate the risk of facing severe losses (downside risk) of a traditional cryptocurrency portfolio.
References
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Book
An Introduction to Copulas
TL;DR: This book discusses the fundamental properties of copulas and some of their primary applications, which include the study of dependence and measures of association, and the construction of families of bivariate distributions.
Journal ArticleDOI
Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
TL;DR: In this article, the authors propose simple and directional likelihood-ratio tests for discriminating and choosing between two competing models whether the models are nonnested, overlapping or nested and whether both, one, or neither is misspecified.
Journal ArticleDOI
Pair-copula constructions of multiple dependence
TL;DR: This work uses the pair-copula decomposition of a general multivariate distribution and proposes a method for performing inference, which represents the first step towards the development of an unsupervised algorithm that explores the space of possible pair-Copula models, that also can be applied to huge data sets automatically.
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Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask
TL;DR: This paper presents an introduction to inference for copula models, based on rank methods, by working out in detail a small, fictitious numerical example, the various steps involved in investigating the dependence between two random variables and in modeling it using copulas.
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A semiparametric estimation procedure of dependence parameters in multivariate families of distributions
TL;DR: In this article, the authors investigated the properties of a semiparametric method for estimating the dependence parameters in a family of multivariate distributions and proposed an estimator, obtained as a solution of a pseudo-likelihood equation, which is consistent, asymptotically normal and fully efficient at independence.
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