A contemporary study of safe haven currencies

2016

This thesis provides contemporary insight into the safe haven phenomenon. We separately examine

three characteristic periods; the years 2001 to 2007, 2007 to 2010, and 2010 to 2016. Our focus is

to examine currency portfolio rebalancing in times of increased risk aversion and identify any

periodical changes in behavior pre and post financial crisis.

Using an autoregressive distributed lag (ADL) model, we study the high-frequency movements of

eight nominal effective exchange rates against three measures of risk aversion. The purpose of the

ADL model is to examine the safe haven behavior on an average basis. We later expand this

baseline model to an interactive dummy model, which allows us to explore the more conditional

behavior during crisis episodes. To the best of our knowledge, the literature has yet to explore this

topic in a similar fashion, especially for the recent years 2010 to 2016.

We document that the Japanese Yen (JPY), Swiss Franc (CHF) and U.S. Dollar (USD) tend to

appreciate when there is an increase in i) stock volatility; ii) forex volatility; iii) composite financial

volatility. In recent years, the JPY shows significantly stronger safe haven tendencies, whereas the

CHF portrays weaker properties post financial crisis. The USD has experienced a noteworthy shift

in status, and shows strong signs of being a safe haven currency post financial crisis compared to

the years 2001 to 2007, where it behaved more pro-cyclically with financial markets.

The New Zealand Dollar (NZD) and Australian Dollar (AUD) tend to depreciate when risk

aversion increases. Here, the AUD shows stronger non safe haven tendencies than the NZD.

Interestingly, the Norwegian Krone (NOK) shows relatively stronger non safe haven tendencies

for the recent period 2010 to 2016. On the other hand, results for the Euro (EUR) and British Pound

(GBP) are overall inconclusive.

We also identify a tendency of stronger quantitative impacts of the JPY during risk episodes

compared to ordinary days. The safe haven phenomenon is however not contingent upon these

specific episodes. On average, the quantitative impacts and explanatory powers are at their highest

for all findings during the years of the financial crisis, 2007 to 2010. Furthermore, the years 2010

to 2016 show far more powerful safe haven flows than 2001 to 2007.