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A New Tail-Based Correlation Measure and Its Application in Global Equity Markets

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  • Liu,Jinjing

Abstract

The co-dependence between assets tends to increase when the market declines. This paper develops a correlation measure focusing on market declines using the expected shortfall (ES), referred to as the ES-implied correlation, to improve the existing value at risk (VaR)-implied correlation. Simulations which define period-by-period true correlations show that the ES-implied correlation is much closer to true correlations than is the VaR-implied correlation with respect to average bias and root-mean-square error. More importantly, this paper develops a series of test statistics to measure and test correlation asymmetries, as well as to evaluate the impact of weights on the VaR-implied correlation and the ES-implied correlation. The test statistics indicate that the linear correlation significantly underestimates correlations between the US and the other G7 countries during market downturns, and the choice of weights does not have significant impact on the VaR-implied correlation or the ES-implied correlation.

Suggested Citation

  • Liu,Jinjing, 2019. "A New Tail-Based Correlation Measure and Its Application in Global Equity Markets," Policy Research Working Paper Series 8709, The World Bank.
    • Handle: RePEc:wbk:wbrwps:8709
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    File URL: http://documents.worldbank.org/curated/en/641081547753593928/pdf/WPS8709.pdf
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    Cited by:

    1. Małgorzata Just & Aleksandra Łuczak, 2020. "Assessment of Conditional Dependence Structures in Commodity Futures Markets Using Copula-GARCH Models and Fuzzy Clustering Methods," Sustainability, MDPI, vol. 12(6), pages 1-22, March.

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    Keywords

    Capital Markets and Capital Flows; Securities Markets Policy&Regulation; Capital Flows;
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