Economics & Growth | FX | Global
Currency markets often confound investors. Unlike equities or bonds, they are a long-short market, so if you buy one currency – say the dollar – you also sell another currency – perhaps the euro. This leads many to believe that there are no recurring sources of investment returns to be made from currencies. Yet specialists know better. Several strategies have proven to deliver returns, whether that is the currency carry trade (buying high interest rate currencies and selling low interest rate ones) or simply following the trend and buying the currency with the most momentum. But even with these strategies, many struggle to find useful links between economic indicators and currencies.
This article is only available to Macro Hive subscribers. Sign-up to receive world-class macro analysis with a daily curated newsletter, podcast, original content from award-winning researchers, cross market strategy, equity insights, trade ideas, crypto flow frameworks, academic paper summaries, explanation and analysis of market-moving events, community investor chat room, and more.
Currency markets often confound investors. Unlike equities or bonds, they are a long-short market, so if you buy one currency – say the dollar – you also sell another currency – perhaps the euro. This leads many to believe that there are no recurring sources of investment returns to be made from currencies. Yet specialists know better. Several strategies have proven to deliver returns, whether that is the currency carry trade (buying high interest rate currencies and selling low interest rate ones) or simply following the trend and buying the currency with the most momentum. But even with these strategies, many struggle to find useful links between economic indicators and currencies.
This paper, Business Cycles and Currency Returns, by academics Riccardo Colacito, Steven Riddiough, and Lucio Sarno, finds a compelling relationship between growth and currencies. Importantly, it is also one that can deliver positive investment returns.
The Set Up
The authors exploit the fact that one of the most successful ways to trade currencies is to look at them cross-sectionally. That is, rather than picking one currency pair, it is better to select a range of currencies and then rank them against each other based on one indicator. This has worked for carry trades or trend-following strategies. The authors create a measure of growth and rank currencies based on that. They then have a rule that buys the high growth currencies and sells the low growth ones.
What Measure of Growth Do They Use?
They focus on the output gap. This is the difference between a country’s actual output and its potential output. They use monthly OECD industrial production data. The easy part is measuring actual output – it’s the reported value of industrial production. The tricky part is to measure potential output, which is more theoretical in nature. To get around this, they measure the underlying trend in industrial production by using four methods. These include the commonly used Hodrick-Prescott (HP) filter and more refined ones such as the linear projection of Hamilton. The choice of these does lead to some differences in investment performance, but broadly speaking the results are similar.
Which Currencies Did They Test and How Far Back?
The authors looked at 27 currencies – mainly developed markets including all the current G10 currencies. The emerging markets they included were Brazil, Czech Republic, Iceland, and Turkey. They looked at the period 1983 to 2016, and since some of these currencies were legacy euro currencies (e.g. Italian lira and Austrian schilling), nine get dropped in 1999 with the introduction of the euro. As industrial production gets revised, they also tested their trading models on the shorter period of December 1999 to January 2016 using real-time data available on the month of trading.
What Trading Rule Do They Use?
The main rule is to split the currencies into five groups based on the size of the output gaps relative to the US’s. They then buy the highest output gap group of currencies and sell the lowest. All the currencies are equally weighted within the groups. Each group has the same number of currencies against the dollar, so the resultant positions are dollar neutral. They call this the ‘cross-sectional’ strategy or GAP-CS. They also look at another strategy where this time they buy any currency that has an output gap greater than the US’s and they sell any currency that has a lower one. As the number of currencies on the long and short side could differ, the resultant positions could have a dollar position. They call this the ‘time series’ strategy or GAP-TS.
So What Were the Investment Returns?
GAP-CS delivered returns of 5% per year (using the linear projection trend filter). The Sharpe ratio or volatility-adjusted returns was 0.66. GAP-TS delivered returns of between 3.7% per year with a Sharpe ratio of 0.37
However, the above returns are based on revised data over the longer sample period (1983 to 2016). If we use data available in real-time and include transaction costs, but over a shorter time period (1999-2016), the returns fall to 3.5% per year with a Sharpe of 0.50 for GAP-CS and they fall to 2.1% per year with a Sharpe of 0.50 for GAP-TS. Combining both strategies delivers a return of 2.8% but improves the Sharpe ratio to 0.60.
How Does This Compare to Other Currency Strategies?
The four most widely used currency strategies are carry, dollar carry, value and momentum. Over 1999 to 2016, these delivered pre-transaction cost Sharpe ratios of 0.6, 0.3, 0.2, and 0, respectively. Already, the output gap returns look attractive relative to them. The pre-transaction cost Sharpe ratio of GAP-CS was 0.7. Importantly, the correlations of the output gap returns to these other strategies are low. They range from a 7% correlation with momentum to a 23% correlation with dollar carry. The output gap model also has a zero correlation with US equities. Therefore, the model provides attractive diversification benefits to any portfolio.