The Euro and European Financial Market Dependence

By Söhnke M. Bartram, Stephen J. Taylor, Yaw‐Huei Wang. 2007

254 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/78655fbe083cd2e525c24dead43538bdd7d947e7

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Citations in the corpus

Copula-GARCH versus dynamic conditional correlation: an empirical study on VaR and ES forecasting accuracy (2013, background): “Several recent studies indicate that the dependence structures inherent in asset returns are time-dependent (e.g. Markwat et al. 2009; Bartram et al. 2007).”
Dynamic European stock market convergence: Evidence from rolling cointegration analysis in the first euro-decade (2010, methodology): “…Hardouvelis et al. (2006) find full integration among the euro-area stock markets by the end of the 1990s, Morana and Beltratti (2002), Fratzscher (2002), Kim et al. (2005) and Bartram et al. (2007) report more modest evidence in favour of integration around the introduction of the single currency.”
The economic value of co-movement between oil price and exchange rate using copula-based GARCH models (2011, background): “In addition, we follow the concept of Patton (2006) and Bartram et al. (2007) by assuming that the dependence parameters rely on past dependence and historical information (uo,t−1−0.5)(ue,t−1−0.5).”
Volatility spillovers across global asset classes: Evidence from time and frequency domains (2018, background): “, 2016), patterns of market integration and market efficiency (Bekaert and Harvey, 2003; Bartram et al., 2007; Forte and Peña, 2009), degree of contagion or spillovers (Bae et al.”
World market risk, country-specific risk and expected returns in international stock markets (2010, unknown): “3 For the significance of time-varying cross-correlations in international markets, see Bartram et al. (2007), Cai et al. (2009), Markwat et al. (2009), and You and Daigler (2010).”
A review of copula models for economic time series (2012, methodology): “[9] use a time-varying conditional copula model to study financial market integration between seventeen European stock market indices; Heinen and Rengifo [88] use copulas to model multivariate time series of counts; Rodriguez [127] uses copulas to study financial contagion; Dearden et al.”
Long Memory Dynamics for Multivariate Dependence under Heavy Tails (2014, unknown): “Time-varying copulas have been introduced by Patton (2002, 2006) and applied and extended by Dias and Embrechts (2004, 2010), Jondeau and Rockinger (2006), Bartram, Taylor, and Wang (2007) and Ausin and Lopes (2010).”
Dynamic hedging with futures: A copula‐based GARCH model (2008, methodology): “In order to effectively solve this problem, we follow the two-stage estimation procedure proposed by Joe (1997)9 and then adopted by Patton (2006b) and Bartram et al. (2007).”