Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets

Baykar Silahli; Kemal Dincer Dingec; Atilla Cifter; Nezir Aydin

doi:10.1016/j.frl.2019.101425

Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets

Baykar Silahli^*
, Kemal Dincer Dingec
, Atilla Cifter
, Nezir Aydin

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

30 Citations (Scopus)

Abstract

This paper extends the univariate two-sided Weibull distribution to a multivariate case for portfolio-value-at-risk estimation. This method allows to capture the stylized facts of the time series of cryptocurrencies, such as extreme volatility, volatility clustering, very heavy tails, and skewness. This new portfolio risk model is applied to a cryptocurrency portfolio consisting of four major coins: Bitcoin, Litecoin, Ripple, and Dash. The predictive performance of the proposed model is compared with several widely used models. We find that the portfolio value-at-risk with two-sided Weibull distribution outperforms the other models.

Original language	English
Article number	101425
Journal	Finance Research Letters
Volume	38
DOIs	https://doi.org/10.1016/j.frl.2019.101425
Publication status	Published - Jan 2021
Externally published	Yes

Keywords

Cryptocurrency markets
Portfolio Value-at-Risk
Two-sided Weibull distribution
Volatility

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10.1016/j.frl.2019.101425

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title = "Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets",

abstract = "This paper extends the univariate two-sided Weibull distribution to a multivariate case for portfolio-value-at-risk estimation. This method allows to capture the stylized facts of the time series of cryptocurrencies, such as extreme volatility, volatility clustering, very heavy tails, and skewness. This new portfolio risk model is applied to a cryptocurrency portfolio consisting of four major coins: Bitcoin, Litecoin, Ripple, and Dash. The predictive performance of the proposed model is compared with several widely used models. We find that the portfolio value-at-risk with two-sided Weibull distribution outperforms the other models.",

keywords = "Cryptocurrency markets, Portfolio Value-at-Risk, Two-sided Weibull distribution, Volatility",

author = "Baykar Silahli and Dingec, \{Kemal Dincer\} and Atilla Cifter and Nezir Aydin",

note = "Publisher Copyright: {\textcopyright} 2019 Elsevier Inc.",

year = "2021",

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language = "English",

volume = "38",

journal = "Finance Research Letters",

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AU - Silahli, Baykar

AU - Dingec, Kemal Dincer

AU - Cifter, Atilla

AU - Aydin, Nezir

PY - 2021/1

Y1 - 2021/1

N2 - This paper extends the univariate two-sided Weibull distribution to a multivariate case for portfolio-value-at-risk estimation. This method allows to capture the stylized facts of the time series of cryptocurrencies, such as extreme volatility, volatility clustering, very heavy tails, and skewness. This new portfolio risk model is applied to a cryptocurrency portfolio consisting of four major coins: Bitcoin, Litecoin, Ripple, and Dash. The predictive performance of the proposed model is compared with several widely used models. We find that the portfolio value-at-risk with two-sided Weibull distribution outperforms the other models.

AB - This paper extends the univariate two-sided Weibull distribution to a multivariate case for portfolio-value-at-risk estimation. This method allows to capture the stylized facts of the time series of cryptocurrencies, such as extreme volatility, volatility clustering, very heavy tails, and skewness. This new portfolio risk model is applied to a cryptocurrency portfolio consisting of four major coins: Bitcoin, Litecoin, Ripple, and Dash. The predictive performance of the proposed model is compared with several widely used models. We find that the portfolio value-at-risk with two-sided Weibull distribution outperforms the other models.

KW - Cryptocurrency markets

KW - Portfolio Value-at-Risk

KW - Two-sided Weibull distribution

KW - Volatility

UR - https://www.scopus.com/pages/publications/85077700847

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VL - 38

JO - Finance Research Letters

JF - Finance Research Letters

M1 - 101425

ER -

Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets

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Keywords

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