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Carry funding and safe haven currencies: A threshold regression approach

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  • Hossfeld, Oliver
  • MacDonald, Ronald

Abstract

In this paper, we analyze which currencies can be regarded as safe haven currencies. Our empirical approach allows us to distinguish between a low- and high stress regime, and to control for the impact of carry trade reversals and other fundamental determinants. We therefore address the question of whether a supposed safe haven currency only appreciates in times of crises because carry trades are unwound, in which the corresponding currency has served as funding currency, or whether it possesses 'true' safe haven qualities; i.e. it provides a hedge against global stock market losses in stressful times even after controlling for the impact of carry trade reversals. The latter issue has largely been brushed aside in the extant literature but has important policy implications for the justification of central bank FX interventions in times of crises. According to the estimation results, two currencies, the Swiss franc and (to a lesser extent) the US dollar qualify as safe haven currencies, and the euro serves as a hedge currency. Results for the yen support its role as a carry funding vehicle, but not necessarily that of a safe haven currency. While the focus is on effective exchange rates, the paper also contains a separate analysis of bilateral euro-based exchange rates, given the euro's prominent role during the euro area sovereign debt crisis.

Suggested Citation

  • Hossfeld, Oliver & MacDonald, Ronald, 2014. "Carry funding and safe haven currencies: A threshold regression approach," Discussion Papers 34/2014, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdps:342014
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    References listed on IDEAS

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    Cited by:

    1. repec:eee:jimfin:v:79:y:2017:i:c:p:189-202 is not listed on IDEAS
    2. Pınar Yeşin, 2017. "Capital Flows and the Swiss Franc," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 153(4), pages 403-436, October.
    3. Thomas Nitschka, 2014. "Have investors been looking for exposure to specific countries since the global financial crisis? - Insights from the Swiss franc bond market," Working Papers 2014-13, Swiss National Bank.
    4. Matthieu Bussiere & Menzie D. Chinn & Laurent Ferrara & Jonas Heipertz, 2018. "The New Fama Puzzle," NBER Working Papers 24342, National Bureau of Economic Research, Inc.
    5. repec:eee:jimfin:v:74:y:2017:i:c:p:283-300 is not listed on IDEAS
    6. repec:eee:glofin:v:35:y:2018:i:c:p:82-96 is not listed on IDEAS
    7. Fatum, Rasmus & Yamamoto, Yohei & Zhu, Guozhong, 2017. "Is the Renminbi a safe haven?," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 189-202.
    8. Eraslan, Sercan, 2016. "Safe-haven demand for housing in London," Economic Modelling, Elsevier, vol. 58(C), pages 482-493.
    9. repec:eee:jimfin:v:78:y:2017:i:c:p:1-20 is not listed on IDEAS
    10. Rasmus Fatum & Yohei Yamamoto & Guozhong Zhu, "undated". "Is the Renminbi a Safe Haven?," Working Papers e109, Tokyo Center for Economic Research.
    11. repec:spr:sjecst:v:154:y:2018:i:1:d:10.1186_s41937-017-0014-7 is not listed on IDEAS
    12. Beckmann, Joscha & Czudaj, Robert, 2017. "Exchange rate expectations since the financial crisis: Performance evaluation and the role of monetary policy and safe haven," Journal of International Money and Finance, Elsevier, vol. 74(C), pages 283-300.

    More about this item

    Keywords

    Nonlinear Regression; Threshold Model; Safe Haven; Carry Trade;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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