Is the Potential for International Diversification Disappearing? A Dynamic Copula Approach

By Peter F. Christoffersen, Vihang Errunza, Kris Jacobs, Hugues Langlois. 2012

436 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/515571b2555dc825130cc64cc2df6abc14357623

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Citations in the corpus

Copulas in Econometrics (2014, neutral): “3 Inference The expressions in (9), (21), and (20) share one common feature, i.”
Tail Co-Movement in Inflation Expectations as an Indicator of Anchoring (2017, methodology): “9A similar approach is adopted by Christoffersen et al. (2012) to capture dynamic dependence across equity markets.”
Conditional Euro Area Sovereign Default Risk (2014, neutral): “…strand of literature on modeling dependence in high dimensions, see, for example, Demarta and McNeil (2005), Chen, Härdle, and Spokoiny (2010), Christoffersen et al. (2012), Patton and Oh (2012, 2013), Smith, Gan, and Kohn (2012), and Engle and Kelly (2012), as well as to a growing…”
Time-Varying Systemic Risk: Evidence From a Dynamic Copula Model of CDS Spreads (2018, positive): “A similar model, though with an alternative skew t specification and with Engle’s (2002) DCC dynamics, is used by Christoffersen et al. (2012, 2013).”
Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models (2020, background): “(Christoffersen et al., 2012); a dynamic tail dependence exhibited in crude oil prices (Avdulaj and Barunik, 2015); a dynamic dependence between the oil market and stock markets before”
Regime Switching Vine Copula Models for Global Equity and Volatility Indices (2016, neutral): “We are aware that recent work on market integration like [72,73] shows that equity tail dependencies have increased over the last decades which would imply a strengthening tendency towards the “abnormal” regime.”
Emerging Equity Markets in a Globalizing World (2017, positive): “This result is consistent with recent results on non-linear dependence in emerging market returns by Christoffersen, Errunza, Jacobs and Langlois (2012) and with recent work on contagion during the global crisis (see Bekaert, Ehrmann, Fratzscher and Mehl, 2013).”
Maximum likelihood estimation of skew-t copulas with its applications to stock returns (2018, neutral): “[23] use empirical quantiles with K=100,000 to specify the GH skew-t copula because there is no closed-form quantile function for the univariate skew-t distribution.”