Abstract
Long-range dependency of the volatility of exchange-rate time series plays a crucial role in the evaluation of exchange-rate risks, in particular for the commodity currencies. The Australian dollar is currently holding the fifth rank in the global top 10 most frequently traded currencies. The popularity of the Aussie dollar among currency traders belongs to the so-called three G’s—Geology, Geography and Government policy. The Australian economy is largely driven by commodities. The strength of the Australian dollar is counter-cyclical relative to other currencies and ties proximately to the geographical, commercial linkage with Asia and the commodity cycle. As such, we consider that the Australian dollar presents strong characteristics of the commodity currency. In this study, we provide an examination of the Australian dollar–US dollar rates. For the period from 18:05, 7th August 2019 to 9:25, 16th September 2019 with a total of 8481 observations, a wavelet-based approach that allows for modelling long-memory characteristics of this currency pair at different trading horizons is used in our analysis. Findings from our analysis indicate that long-range dependence in volatility is observed and it is persistent across horizons. However, this long-range dependence in volatility is most prominent at the horizon longer than daily. Policy implications have emerged based on the findings of this paper in relation to the important determinant of volatility dynamics, which can be incorporated in optimal trading strategies and policy implications.
Highlights
In his seminal work advocating for a system of flexible exchange rates, (Friedman 1953) envisaged that speculative forces would have stabilising effects that cause exchange rates to adjust smoothly over time, moving from one equilibrium to another
(Friedman 1953)’s prediction is not without merit, as exchange rates are shown to be less volatile over the longer term, and tend to revert to an equilibrium value that is in close association with relative prices (Lothian 2016); (Marsh et al 2012)
Existing literature indicates that the choice of an appropriate statistical tool for analysing exchange-rate dynamics should be made based on the long-memory properties of the underlying data generating process, which varies across different trading horizons
Summary
In his seminal work advocating for a system of flexible exchange rates, (Friedman 1953) envisaged that speculative forces would have stabilising effects that cause exchange rates to adjust smoothly over time, moving from one equilibrium to another. (Friedman 1953)’s prediction is not without merit, as exchange rates are shown to be less volatile over the longer term, and tend to revert to an equilibrium value that is in close association with relative prices (Lothian 2016); (Marsh et al 2012). 70% of the annual absolute changes of the AUD were greater than 3%, whereas the corresponding number for large relative price changes (Australian price level relative to that of the US) was only. Risks 2020, 8, 89 absolute changes of the AUD were greater than 3%, whereas the corresponding number for large relative price changes (Australian price level relative to that of the US) was only approximately approximately.
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