On financial risk and the safe haven characteristics of Swiss franc exchange rates

Grisse, Christian; Nitschka, Thomas

doi:10.1016/j.jempfin.2015.03.006

Cited by 94 publications

(70 citation statements)

References 42 publications

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“…Therefore, the JPY is "safer" than the CHF and thus during the global financial crisis period the JPY appears to be the "safest" of the possible safe haven currencies considered. 10 To find that the JPY as well as the CHF both appreciate against the USD as uncertainty increases is broadly consistent with the results of Ranaldo and 10 See Botman, Carvalho Filho, and Lam (2013) for a discussion of why the JPY tends to appreciate during episodes of increased market uncertainty and Grisse and Nitschka (2013) for details on the CHF as a safe haven currency.…”

Section: Resultssupporting

confidence: 59%

Intra-safe haven currency behavior during the global financial crisis

Fatum

Yamamoto

2016

Journal of International Money and Finance

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We investigate intra-safe haven currency behavior during the recent global financial crisis. The currencies we consider are the USD, the JPY, the CHF, the EUR, the GBP, the SEK, and the CAD. We first assess which safe haven currency appreciates the most as market uncertainty increases, i.e. we assess which safe haven currency is the "safest". We then use non-temporal threshold analysis to investigate whether intra-safe haven currency behavior changes, e.g. accelerates or decelerates, as market uncertainty increases. We find that the JPY is the "safest" of safe haven currencies and that only the JPY appreciates as market uncertainty increases regardless of the prevailing level of uncertainty. For all other currencies under study we find significant market uncertainty threshold effects. We extend our analysis to also consider intra-safe haven currency behavior before and after the global financial crisis. JEL codes: F31, G15

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Section: Resultssupporting

confidence: 59%

Intra-safe haven currency behavior during the global financial crisis

Fatum

Yamamoto

2016

Journal of International Money and Finance

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“…In other words, the predictive power of the assessments may be affected by the presence of safe haven currencies in the sample. Five currencies, namely, the US dollar, euro, British pound, Swiss franc, and Japanese yen can be considered as safe haven currencies in the current sample according to the previous literature; see, for example, Ranaldo and Söderlind (2010), Habib and Stracca (2012), Grisse and Nitschka (2015), and de Bock and de Carvalho Filho (2015), among others.…”

Section: Robustness Check With Safe Haven Currenciesmentioning

confidence: 99%

Exchange Rate Predictability and State-of-the-Art Models

Yeșin

2015

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This discussion paper series represents research work-in-progress and is distributed with the intention to foster discussion. The views herein solely represent those of the authors. No research paper in this series implies agreement by the Study Center Gerzensee and the Swiss National Bank, nor does it imply the policy views, nor potential policy of those institutions. to 2011, and were based on three state-of-the-art exchange rate models with a medium-term focus which were developed by the IMF. The empirical analysis using 26 advanced and emerging market economy currencies reveals that the 'diagnosis' of undervalued or overvalued currencies based on these models has significant predictive power with respect to future exchange rate movements, with one model outperforming the other two. The models are better at predicting future exchange rate movements in advanced and open economies. Controlling for the exchange rate regime does not increase the predictive power of the assessments. Terms of use: Documents in Exchange Rate PredictabilityFurthermore, the directional accuracy of the IMF assessments is found to be higher than market expectations.

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“…Swiss National Bank, 2013). It was also directly affected by the banking crisis in 2008/2009 and is still affected by the on-going euro area crisis since Swiss assets (including the exchange rate) are typically perceived as "safe haven" assets (Kugler and Weder, 2005;Grisse and Nitschka, 2013;Hoffmann and Suter, 2010;Ranaldo and Söderlind, 2010) by global investors.…”

Section: Introductionmentioning

confidence: 99%

What news drive variation in Swiss and US bond and stock excess returns?

Nitschka

2014

Swiss J Economics Statistics

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Summary Based on a vector autoregressive model (VAR), this paper shows that time variation in monthly excess returns on Swiss government bonds and stocks is predominantly driven by news of inflation and dividends, respectively. This finding is in marked contrast to US evidence which points to a more prominent role of excess return news. Variance decompositions based on estimates from threshold VARs show that US stock market evidence is consistent with the view that market participants put more weight on news of macroeconomic, i.e. cash-flow, risks in periods of exceptionally low real interest rates than in normal times.

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On financial risk and the safe haven characteristics of Swiss franc exchange rates

Cited by 94 publications

References 42 publications

Intra-safe haven currency behavior during the global financial crisis

Intra-safe haven currency behavior during the global financial crisis

Exchange Rate Predictability and State-of-the-Art Models

What news drive variation in Swiss and US bond and stock excess returns?

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