Returns synchronization and daily correlation dynamics between international stock markets

By M. Martens, Ser-Huang Poon. 2001

241 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/b3509ebaffec607d55a18d7ca74b3ffdac5baa2b

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Citations in the corpus

A Practical Guide to Forecasting Financial Market Volatility (2005, methodology): “Nelson (1992) shows that such ARCH models may misspecify both the conditional mean and the dynamic of the conditional variance; in fact the misspecification may be so severe that the models make no sense as datagenerating processes, they could still produce consistent one-step-ahead conditional vari”
Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications (2004, methodology): “It has been widely documented elsewhere that the US market has, by far, the greatest influence on all the other stock markets (see Martens and Poon (2001) for example).”
Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model (2009, unknown): “Martens and Poon (2001) discussed the problem of distinguishing contemporaneous correlation from a spillover effect and provided evidence of downward bias in estimated correlations in the presence of nonsynchronous markets.”
Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns (2006, background): “Martens and Poon (2001) have shown that using non-synchronous data results in a significant downward bias in correlation, as compared to pseudo-closes.”
The Euro and European Financial Market Dependence (2007, background): “As shown in Martens and Poon (2001), it is essential to have time-synchronized prices when studying equity market co-movements.”
Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets (2011, unknown): “Indeed, a study by Martens and Poon (2001) shows that the daily stock market correlations are affected by the use of non-synchronous data.”
Global stock market reactions to scheduled U.S. macroeconomic news announcements (2006, background): “While the existing literature such as Bracker and Koch (1999) and Martens and Poon (2001) examine correlation structures across international equity markets and Booth, Martikainen, and Tse (1977) investigate the spillover phenomenon, the issue of integration with respect to scheduled announcements…”
Regime Switching Vine Copula Models for Global Equity and Volatility Indices (2016, unknown): “[43] for a comparison of various approaches).”
Asymmetric Volatility, Correlation and Returns Dynamics between the U.S. and U.K. Securitized Real Estate Markets (2006, unknown): “Also, and in contrast to the property data analyzed in this study, Martens and Poon (2001) indicate that the greatest volatility shock is caused when a large negative local return coincides with a large positive foreign return.”
Systemic Risk in Europe (2013, unknown): “…rW,t+1) = 0.03, indicating that there is no information in the world index return at t+1 useful for predicting the Europe index return at t. Martens and Poon (2001) describe the issue of asynchronization and show that instantaneous correlation between international stock markets…”
Interconnectedness in the global financial market (2017, unknown): “The dependencies are biased downwards because the time series are asynchronous (see also Martens and Poon, 2001).”