Safe-haven and hedge currencies for the US, UK, and Euro area stock markets: A copula-based approach

Abstract

This paper uses a copula-based approach to identify safe haven and hedge currencies for the US, UK, and Euro area stock markets over the period 1999-2016. We reveal similarities and differences in the determination of safe haven and hedge currencies across the three stock markets. First, UK and Euro area stock markets have had the same set of hedge currencies, among which the CHF has been the most indispensable hedge currency.Second, there has been no safe haven currency for the UK stock market, whereas the Euro area stock market had some safe haven currencies until 2012, reflecting its large volatility relative to the UK market. Third, for the US stock market, the JPY has become the most important currency both as a safe haven and as a hedge since the 2007 global financial crisis. This is probably because the Japanese economy was less affected directly by that crisis and the subsequent European debt crisis than the three economies.

Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets

“…We employ the cross-quantilogram method and the quantile connectedness approach to investigate the tail dependence between the analyzed variables and downside and upside spillover among the markets represented by the chosen volatility indices. The cross-quantilogram method provides some advantages over other methodologies that could be used to gauge the tail interdependence between assets, such as copulas (Tachibana 2018 ; Xia et al 2019 ), (Naeem et al 2021 , 2022 ; Ando et al 2022 ). Specifically, copula-based methodologies would require us to select an appropriate marginal distribution (Vuuren and de Jong 2017 ); however, instead of requiring an inherently subjective choice of a distribution, the cross-quantilogram method relies on objectively determined quantiles, without depending on any assumptions or conditions regarding the moments of the distribution.…”

Impact of Chinese Yuan Devaluation on the Dependence Structure: The Archimedean Copula Approach

“…The copula methods have been applied in a variety of context for analysing dependence in financial time series in the literature. Among others, these applications include the examination of portfolio risks by Hsu et al (2012) and Weiss (2013), dependence between exchange rates by Min and Czado (2014), the complex relationship between energy, stock and currency markets by Aloui and Aïssa (2016), the value-atrisk for the exchange rate of onshore renminbi and offshore renminbi against US dollar by Du and Lai (2017), the relationship between stock returns and foreign exchange rates by Han and Zhou (2017), the safe haven and hedge currencies for stock markets by Tachibana (2018), and the tail dependence of high and low interest rate currency baskets to understand the uncovered interest rate parity puzzle by Ames et al (2017). Patton (2012) provides a review on copula-based models for economic and financial time series.…”

Are gold, USD, and Bitcoin hedge or safe haven against stock? The implication for risk management

“…For dependence on average, the correlation measure given by Spearman's rho or Kendall's tau can be obtained from the dependence parameter of the copula. A positive value of this correlation parameter indicates that asset may not be appropriate as a strong hedge, while a negative or zero value suggests the potential of the asset as a strong or weak hedge, respectively (see Lai & Tseng, 2010;Liu et al, 2016;Mensi et al, 2015;Reboredo, 2013aReboredo, , 2013bTachibana, 2018).…”