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Flight-to-quality in the stock–bond return relation: a regime-switching copula approach

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Abstract

This paper examines the existence, intensity and international dependence of flight-to-quality from stocks to government bonds. To this end, we develop a two-state regime-switching bivariate copula model and apply it to the domestic and cross-country stock–bond return pairs of six developed countries (France, Germany, Japan, Switzerland, the UK and the US) over the period 1999–2019. We find that US and UK government bonds have played a primary role of safe-haven assets during stock market downturns. The remaining government bond markets show the evidence of flight-to-quality, but its intensity is relatively weak. Further, we find that although flight-to-quality tends to occur simultaneously in multiple countries, the frequency of the joint occurrence varies across government bond markets.

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Notes

  1. Early studies that introduce a RS framework into copulas are Chollete et al. (2009), Jondeau and Rockinger (2006), Okimoto (2008) and Rodriguez (2007) in which the dependence structure of international stock markets is investigated.

  2. Garcia and Tsafack (2011) analyze the dependence structure between four variables (stock and government bond returns of two countries). Extending our bivariate model to multivariate distributions requires substantial computational burden, and thus, we leave it to future work.

  3. Durand et al. (2010) derive a copula function that combines Frank and Gumbel copulas to capture both a normal situation of positive correlation and a rare event of flight-to-quality between stock and bond markets. This is a very flexible model, but our RS copula model is more flexible in that asymmetric copulas other than Gumbel (Clayton and Joe in this paper) can be used for describing an asymmetric regime.

  4. Hartmann et al. (2004) find that stock–bond contagion is approximately as frequent as flight-to-quality from stocks to bonds in G-5 countries over the period 1987–1999. However, our earlier analysis presents no evidence on the contagion over the period 1999–2019, and hence, this paper only studies flight-to-quality phenomena.

  5. Note, however, that the differences between the unconditional means of the two returns do not affect the estimation result of the dependence structure because they are removed in the copula approach by filtering the conditional mean and variance of marginal distributions.

  6. We do not report the standard errors and significance of the exceedance correlation estimates in the table because the t-test using the standard errors leads to the same result as the Wald test for \(H_0: \rho = \rho ^{\mathrm{{asy}}}_{\mathrm{{nor}}} = 0\).

  7. See Appendix 1 in Longin and Solnik (2001) for the method to compute the optimal threshold values.

  8. See Joe (1997, (2015) and Nelsen (2006) for a comprehensive exposition of copulas.

  9. The starting value \(\xi _{1|0}\) is set equal to the vector of unconditional probabilities for two states, that is, \([(1-p_{22})/(2-p_{11}-p_{22}), (1-p_{11})/(2-p_{11}-p_{22})]'\).

  10. To save space, we do not report the estimated coefficients on the ARMA and GARCH terms as they are relatively less informative. These results are available from the authors upon request.

  11. The delta method is used to compute standard errors for the estimates of Kendall’s \(\tau \) and LU tail dependence.

  12. There are two exceptions, UK–JP and US–JP (Table 10), for which incorrect estimates are obtained (bounded estimates of 0.5 for the transition probabilities and very large standard errors). Thus, for the two pairs, we regard the normal–asymmetric RS copula model reported in Panel A as the most appropriate model, but its normal regime, rather than the asymmetric one, as a regime to describe flight-to-quality events.

  13. There are two slight differences, which are explained in the subsequent two footnotes. The whole of the results with a threshold value of 0.15 is available from the authors upon request.

  14. When relying on the different definition of flight-to-quality with a threshold value of 0.15, there are three cases where domestic flight-to-quality simultaneously occurs in all countries.

  15. For the different definition of flight-to-quality with a threshold value of 0.15, the ratio for Switzerland is low compared to the other three European countries. This suggests some degree of independence of Swiss financial markets from the three European countries.

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Acknowledgements

I am grateful to an anonymous referee for valuable comments and suggestions. I also acknowledge financial support from JSPS KAKENHI (Grant No.: 16K03746).

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  1. Graduate School of Economics, Osaka Prefecture University, Sakai, Osaka, Japan

    Minoru Tachibana

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Tachibana, M. Flight-to-quality in the stock–bond return relation: a regime-switching copula approach. Financ Mark Portf Manag 34, 429–470 (2020). https://doi.org/10.1007/s11408-020-00361-5

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