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A rule-based model to that goes long USD-EM in the month (t+1) when economic policy uncertainty shows a large gain in the month (t) provides favourable returns over time. For the US and European uncertainty indices, all of the positive performance is the result of identifying two major risk events over the past decade – September 2008 and August 2011 – when the currencies we analysed sold off by an average 13.4% and 10.4% respectively during those months.
While the China index-based trading rule was only able to identify the large EM FX sell-off in October 2008, it shows the best cumulative returns over time.
The hit ratio is the greatest for the China index (57%) and the lowest for the US and Europe (36%-38%). Nonetheless, being able to adjust portfolios accordingly to sidestep major drawdowns for a long EM FX portfolio is critical in improving the return profile of carry trades over time.
The trading crux for US based EM FX baskets: Using large increases in the US economic policy uncertainty index as the signal for when to get long USD-EM, shows very good results for the MXN, BRL, KRW, TRY, and ZAR. Not surprisingly, currencies with closer geographic proximity to the US and higher beta currencies within EM tend to be most sensitive. The signal is quite poor for the other Asian currencies outside the KRW.
The trading crux for Europe-based EM FX basket: For the European index-based trading rule, long USD against MXN and CLP performed well as does the CEE bloc (PLN, CZK, HUF). The signal from the European economic policy uncertainty index provides a poor signal for Asian currencies, with the exception of the KRW.
The trading rule for China-based EM basket: The ZAR has been the most negatively impacted by large increases in China’s economic policy uncertainty index, with long USD-ZAR producing an average positive return of 2.27% for each month the signal is activated. The LATAM currency complex is the next most affected, and within Asia, the INR and KRW have been most affected.
The trading rule results indicate that there is some momentum in risk aversion caused by policy uncertainty and the ability to capture tail events makes it a useful metric to monitor going forward.
