Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach

Abstract

We construct the complete network of tail risk spillovers among major cryptocurrencies using the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression. We capture important features of the network, including major risk-driving and major risk-receiving currencies, and the evolution of the tail dependence among the currencies over time. Importantly, we reveal a striking finding that the right tail dependence among the cryptocurrencies is significantly stronger than the left tail counterpart. This unique characteristic may have contributed to the rise in popularity of cryptocurrencies over the last few years. Our portfolio analysis reveals that diversification in cryptocurrency investment can be accomplished simply by employing the naïve equal-weighted scheme even when transaction costs are taken into account.

Gold or Bitcoin, which is the safe haven during the COVID-19 pandemic?

“… Corbet, Katsiampa and Lau, 2020a , Corbet, Katsiampa and Lau, 2020b suggest that Bitcoin is a strong safe haven for oil and a weak safe haven for the stock market. Hedging strategies involving Bitcoin could also lower the portfolio's risk and improve the portfolio performance ( Guesmi, Saadi, Abid, et al, 2019 ; Kajtazi & Moro, 2019 ; Nguyen, Chevapatrakul, & Yao, 2020 ). Differently, Bouri, Jalkh, Molnár, et al (2017) find that Bitcoin is a poor hedging instrument, suited only for diversification.…”

Dynamic large financial networks via conditional expected shortfalls

“…In other words, in the same spirit as Borri (2019) and Nguyen et al (2020), who focused on cryptocurrencies and tail-relationships, we present herein a generalization of the approach by Hautsch et al (2014), with estimations of financial networks focusing on dynamic ES. Indeed, Hautsch et al (2014), when estimating the impact of other companies on the VaR of targeted companies, made use of a penalized quantile regression, thus not fully dealing with potential dynamic evolutions in the conditional quantiles.…”

Research on the Invulnerability of Chinese Banking System

“…Hautsch et al [6] constructed a risk spillover network by the interdependence between firms' tail risk exposures of more than 100 financial firms of the United States, and found that risk contagion among financial firms was the main cause of market systemic risks. Nguyen et al [8] map the entire network of tail risk dependence among 21 major cryptocurrencies and find that Bitcoin and Litecoin are the major drivers of tail risk when markets are bullish, and Ethereum and Ethereum Classic are major drivers of tail risk when markets are bearish. Li et al [9] use the sample of 19 international financial markets to analyze the tail risk contagion between international financial market during the COVID-19 epidemic.…”