Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market

doi:10.1016/J.INTECO.2019.03.002

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Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market

Journal Article•DOI•

Vine copula-based dependence and portfolio value-at-risk analysis of the cryptocurrency market

Gideon Boako¹, Aviral Kumar Tiwari, David Roubaud•Institutions (1)

Kwame Nkrumah University of Science and Technology¹

01 Aug 2019-International Economics (Elsevier)-Vol. 158, Iss: 158, pp 77-90

TL;DR: 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.

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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.

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Journal Article•DOI•

Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying.

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Laura Garcia-Jorcano¹, Sonia Benito²•Institutions (2)

University of Castilla–La Mancha¹, National University of Distance Education²

01 Aug 2020-Research in International Business and Finance

TL;DR: In a time-varying copula analysis, given by the Student-t copula, it is found that even under normal market conditions, for some markets, the role of Bitcoin as a hedge asset might fail on a high number of days.

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41 citations

Cites background or methods or result from "Vine copula-based dependence and po..."

...2018 and Bouri et al. 2017c), but other studies did not detect a significant leverage effect (Dyhrberg, 2016; Tiwari et al. 2019a; Katsiampa, 2017; Takaishi, 2018). Regarding this, Klein et al. (2018) argue that their results are because they use the Student-t distribution to account for heavy tails present in the distribution of the returns. When they assume a normal distribution, they confirm and replicate the results of Dyhrberg (2016). The sensitivity of the results regarding the underlying distribution is also discussed in Baur et al....
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...7 The time-varying nature of the Bitcoin’s properties as a diversifier and hedge has also been studied by Tiwari et al. (2019b) and Boako et al. (2019)....
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...2018 and Bouri et al. 2017c), but other studies did not detect a significant leverage effect (Dyhrberg, 2016; Tiwari et al. 2019a; Katsiampa, 2017; Takaishi, 2018). Regarding this, Klein et al. (2018) argue that their results are because they use the Student-t distribution to account for heavy tails present in the distribution of the returns....
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Journal Article•DOI•

Return equicorrelation in the cryptocurrency market: Analysis and determinants

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Elie Bouri¹, Elie Bouri², Xuan Vinh Vo², Tareq Saeed³•Institutions (3)

Holy Spirit University of Kaslik¹, University of Economics, Ho Chi Minh City², King Abdulaziz University³

01 Jan 2021-Finance Research Letters

TL;DR: In this paper, the authors examined market integration among 12 leading cryptocurrencies from August 8, 2015 to February 28, 2019 using the dynamic equicorrelation (DECO) model, and found that market integration is a continuing and persistent phenomenon.

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40 citations

Journal Article•DOI•

Cyber attacks, spillovers and contagion in the cryptocurrency markets

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Guglielmo Maria Caporale¹, Woo-Young Kang¹, Fabio Spagnolo¹, Nicola Spagnolo¹•Institutions (1)

Brunel University London¹

18 Jan 2021-Journal of International Financial Markets, Institutions and Money

TL;DR: In this article, mean and volatility spillovers between three major cryptocurrencies (Bitcoin, Litecoin and Ethereum) and the role played by cyber-attacks are examined, with Bitcoin appearing to be the dominant cryptocurrency.

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26 citations

Cites methods from "Vine copula-based dependence and po..."

...For instance, Boako et al. (2019) apply vine copula methods to analyse both the co-dependence and portfolio valueat-risk (VaR) of six cryptocurrencies and find evidence of strong dependencies and a changing dependency structure. By contrast, the findings in Borro (2019) concerning the conditional correlation between cryptocurrencies and other assets appear to be robust to the introduction of time variation into the empirical model. Ji et al. (2019) examine network connectedness in both the returns and volatility of six major cryptocurrencies (Bitcoin, Ethereum, Ripple, Litecoin, Stellar and Dash) using daily data over the period 7 August 2015 – 22 February 2018 and computing a set of measures developed by Diebold and Yilmaz (2012, 2016)....
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...For instance, Boako et al. (2019) apply vine copula methods to analyse both the co-dependence and portfolio valueat-risk (VaR) of six cryptocurrencies and find evidence of strong dependencies and a changing dependency structure. By contrast, the findings in Borro (2019) concerning the conditional correlation between cryptocurrencies and other assets appear to be robust to the introduction of time variation into the empirical model....
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...For instance, Boako et al. (2019) apply vine copula methods to analyse both the co-dependence and portfolio valueat-risk (VaR) of six cryptocurrencies and find evidence of strong dependencies and a changing dependency structure....
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Journal Article•DOI•

Connectedness between cryptocurrencies and foreign exchange markets: Implication for risk management

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Rahma Chemkha¹, Ahmed BenSaïda², Ahmed Ghorbel¹•Institutions (2)

University of Sfax¹, Effat University²

01 Mar 2021-Journal of Multinational Financial Management

TL;DR: In this article, the authors examined the connectedness between cryptocurrencies and major fiat currencies in a multivariate framework using vine copulas and found that the dependence, measured conditionally or unconditionally, is positive and higher for the pairs of the same market than those across markets.

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20 citations

Journal Article•DOI•

Modeling risk dependence and portfolio VaR forecast through vine copula for cryptocurrencies

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Khreshna Syuhada¹, Arief Hakim¹•Institutions (1)

Bandung Institute of Technology¹

23 Dec 2020-PLOS ONE

TL;DR: In this paper, a dependence model for financial risks and a portfolio risk of cryptocurrencies is presented through vine copula, where the marginal risk model is assumed to follow a heteroscedastic process of GARCH(1,1) model.

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Abstract: Risk in finance may come from (negative) asset returns whilst payment loss is a typical risk in insurance. It is often that we encounter several risks, in practice, instead of single risk. In this paper, we construct a dependence modeling for financial risks and form a portfolio risk of cryptocurrencies. The marginal risk model is assumed to follow a heteroscedastic process of GARCH(1,1) model. The dependence structure is presented through vine copula. We carry out numerical analysis of cryptocurrencies returns and compute Value-at-Risk (VaR) forecast along with its accuracy assessed through different backtesting methods. It is found that the VaR forecast of returns, by considering vine copula-based dependence among different returns, has higher forecast accuracy than that of returns under prefect dependence assumption as benchmark. In addition, through vine copula, the aggregate VaR forecast has not only lower value but also higher accuracy than the simple sum of individual VaR forecasts. This shows that vine copula-based forecasting procedure not only performs better but also provides a well-diversified portfolio.

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9 citations

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References

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Book•

An Introduction to Copulas

[...]

Roger B. Nelsen

01 Jan 1999

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.

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Abstract: The study of copulas and their role in statistics is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the construction of families of bivariate distributions. This book is suitable as a text or for self-study.

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8,626 citations

Journal Article•DOI•

Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses

[...]

Quang Vuong

01 Mar 1989-Econometrica

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.

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Abstract: In this paper, we propose a classical approach to model selection. Using the Kullback-Leibler Information measure, we 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. As a prerequisite, we fully characterize the asymptotic distribution of the likelihood ratio statistic under the most general conditions.

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5,661 citations

Journal Article•DOI•

Pair-copula constructions of multiple dependence

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Kjersti Aas, Claudia Czado¹, Arnoldo Frigessi², Henrik Bakken³•Institutions (3)

Technische Universität München¹, University of Oslo², Norwegian University of Science and Technology³

01 Apr 2009-Insurance Mathematics & Economics

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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Abstract: Building on the work of Bedford, Cooke and Joe, we show how multivariate data, which exhibit complex patterns of dependence in the tails, can be modelled using a cascade of pair-copulae, acting on two variables at a time. We use the pair-copula decomposition of a general multivariate distribution and propose a method for performing inference. The model construction is hierarchical in nature, the various levels corresponding to the incorporation of more variables in the conditioning sets, using pair-copulae as simple building blocks. Pair-copula decomposed models also represent a very flexible way to construct higher-dimensional copulae. We apply the methodology to a financial data set. Our approach 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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1,744 citations

Journal Article•DOI•

Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask

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Christian Genest¹, Anne-Catherine Favre¹•Institutions (1)

Institut national de la recherche scientifique¹

01 Jul 2007-Journal of Hydrologic Engineering

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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Abstract: 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 writers exhibit the various steps involved in investigating the dependence between two random variables and in modeling it using copulas. Simple graphical tools and numerical techniques are presented for selecting an appropriate model, estimating its parameters, and checking its goodness-of-fit. A larger, realistic application of the methodology to hydrological data is then presented.

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1,414 citations

Journal Article•DOI•

A semiparametric estimation procedure of dependence parameters in multivariate families of distributions

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Christian Genest¹, Kilani Ghoudi¹, Louis-Paul Rivest¹•Institutions (1)

Laval University¹

01 Sep 1995-Biometrika

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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Abstract: SUMMARY This paper investigates the properties of a semiparametric method for estimating the dependence parameters in a family of multivariate distributions. The proposed estimator, obtained as a solution of a pseudo-likelihood equation, is shown to be consistent, asymptotically normal and fully efficient at independence. A natural estimator of its asymptotic variance is proved to be consistent. Comparisons are made with alternative semiparametric estimators in the special case of Clayton's model for association in bivariate data.

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1,280 citations