A Simple Out-of-Sample Test of Predictability against the Random Walk Benchmark

We show that a straightforward modification of a trading-based test for predictability displays interesting advantages over the Excess Profitability (EP) test proposed by Anatolyev and Gerco when testing the Driftless Random Walk Hypothesis. Our statistic is called the Straightforward Excess Profitability (SEP) test, and it avoids the calculation of a term that under the null of no predictability should be zero but in practice may be sizable. In addition, our test does not require the strong assumption of independence used to derive the EP test. We claim that dependence is the rule and not the exception. We show via Monte Carlo simulations that the SEP test outperforms the EP test in terms of size and power. Finally, we illustrate the use of our test in an empirical application within the context of the commodity-currencies literature.

Modelling Australian Dollar Volatility at Multiple Horizons with High-Frequency Data

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.

New financial markets and their impact on raw material prices

<p>The purpose of the study was to determine the impact of the Chinese financial market, which is a new market, on the exchange rates of commodity currencies and, thus, the prices of raw materials. For this purpose, an autoregressive distributed lag model (ARDL) was used. The results indicate that the Chinese stock market and futures market for the yuan (the Chinese Yuan Non-Deliverable Forward Transactions; CNY NDF market) had a significant impact on commodity currencies before the global financial crisis in 2008/09, then the effect widened to include more commodity currencies in the post-crisis period. Further evidence suggests that the CNY NDF market had a greater impact on commodity currencies than the Chinese stock market. Despite the significant position of the Chinese economy, research also indicates that the impact of Chinese financial markets on commodity currencies (raw material prices) is weaker than the impact of the US stock market and US dollar market.</p>