The profits of carry
Over the past decade, currency management has progressively shifted from being viewed as a source of risk to what many absolute investors have always believed - a source of sustainable and uncorrelated returns. As a result, institutional investors, as well as private individuals, are increasingly considering currency as an asset class in its own right. In response, the universe of currency managers has grown and so has the distinction between the classifications of their investment styles.
One of the more commonly known investment styles within the currency industry, and certainly one of the most debated, is the carry trade (also known as forward bias). In fact, such is its popularity over the past few years that various forms of foreign exchange instruments were created and made available to the general public via exchange-traded funds and structured notes. The aim of this article is to discuss the persistence of carry and offer some forward-looking guidance on the likely outlook for currency investment styles in general.
A carry investment style in the currency market involves going long high-yielding currencies and shorting lower-yielding currencies. One of the more popular rationales for discussing the returns on currency trades is from the perspective of the efficient market hypothesis (Burnside et al, 2006). This implies the return gained from the interest rate component of buying a high-yielding versus low-yielding currency should be exactly offset by the subsequent moves in the spot price in the opposite direction.
Contrary to the efficient market hypothesis, the carry investment style has been found to be empirically profitable (Galati, Heath & McGuire, 2007). A number of theories have been proposed to explain this apparent inefficiency. The persistence of any returns in the currency investment universe is indeed inefficient, but only if currencies are viewed as a closed system with rational investors who have similar time horizons, are indifferent to risk and have perfect access to information (Remolona & Schrijvers, 2003). However, as has been proven historically, currency investments are far removed from such an idealised simple scenario.
Let us consider carry from the perspective of a purely rational investor. The purchase of any asset involves the balance between return and risk. In the case of equities, the return on a stock purchase is related to the dividend payout, assuming the price of the stock is unchanged. By analogy, the return on a purchase of a high-yielding versus low-yielding currency is related to the interest rate differential between the two, so long as the spot rate remains unchanged. The carry trade, therefore, involves the balance of risk between the risk-free return and downside volatility risk over a given time horizon, be it for a systematic or discretionary currency investor.
A simple strategy of buying the three highest-yielding and selling the three lowest-yielding currencies within the G-101 universe, rebalanced monthly, and measured over the past 20 years shows that the greatest proportion of returns over the past two decades can be attributed to the interest rate component. From a purely investment perspective, therefore, the interest rate differential can be viewed as a risk premium associated with the downside risk of significantly negative spot returns. This downside risk can be characterised by two components - financial market volatility and liquidity.
Historically, and as has been seen since the credit crisis from the third quarter of 2007, carry trades have tended to underperform in periods of heightened financial market volatility, precisely because the returns gained from the interest rate component become negligible as a result of the potential losses through movements in the spot price. Over the past two decades, a considerable amount of research has been conducted to account for and predict both the level and the likely change of volatility (Bank for International Settlements, 2006). The relative surprise with which the recent market events affected many financial institutions, however, indicates that accurate volatility prediction still presents a challenge.
One of the more popular methods of volatility estimation, in part adopted by systematic investment styles, uses historical returns, option implied volatilities or any other price indicators to extrapolate into the future. At Principal Global Investors (PGI), we use a proprietary indicator called the Base Volatility Index, which differs from the traditional approaches. Rather than forecasting financial market volatility itself, it is an indicator of various fundamental-based preconditions for a rise in financial market volatility, and hence is forward looking. The overall indicator, shown in figure 1, is made up of a series of sub-indexes aimed at analysing the fundamental preconditions separately.
The choice of sub-indexes reflects our understanding of what causes financial market volatility (including foreign exchange volatility) to rise and fall. Higher values correspond to conditions likely to generate higher uncertainty of returns, with a historical threshold of -0.2 and above (grey shaded area in figure 1) indicating preconditions for a significant increase. As can be seen from the graph, the composite index tracks G-3 currency volatility reasonably well and, as early as the start of 2007, was signalling a less favourable volatility environment.
When viewed in the context of sub-indexes, the recent rise in financial market volatility can mainly be attributed to the deviation of the valuation component, driven until recently by the excessively tight credit spreads, flat yield curves and a combination of abnormally polarised exchange rates and current account deficits. The rise since the third quarter of 2007 is related to the component linked to global monetary policy uncertainty.
Simultaneously, however, macroeconomic volatility is still relatively low. Having spiked during the Asian crisis in 1997/98 and then climbed again during the global recession in 2001/02, macroeconomic volatility has decreased significantly and remains low by historical standards.
In this context, our outlook for the next phase in financial market volatility is a likely rise in macroeconomic volatility arising from unsteady growth, inflation and unemployment - not just in the US, but globally. Figure 2 shows the index level plotted against the annualised three-year average information ratio of the simple carry trade. There is a direct relationship historically, and given the current level of the index, we expect the interest rate return as compensation for the level of spot volatility to diminish further in the months to come.
The information ratio analysis assumes that when volatility rises, currency spot returns follow a simplified normal distribution. However, the non-normality of most financial instrument returns, including currency, is an empirically observed fact. This relative non-normality (or tail risk) of price-return series of various currencies presents additional downside risk, which goes beyond the simple carry-to-risk ratio. A recent study analysed these risks in target currencies in Asia-Pacific (Gyntelberg & Remolona, 2007). In this article, we analyse the risks across the G-10 currencies and show this non-normality presents a further risk premium that is embedded in the interest rate differentials.
Before we embark on a statistical analysis, let us focus briefly on assessing foreign exchange market liquidity. Although currencies are by far the most actively traded instrument globally, the liquidity of currencies in general is difficult to measure directly due to the fact that foreign exchange transactions are mostly traded directly between counterparties rather than on a registered exchange. One of the commonly used references is the triennial report published by the Bank for International Settlements (BIS). According to the latest BIS report, published in 2007, daily foreign exchange turnover is estimated as $3.2 trillion (Triennial Central Bank Survey of Foreign Exchange and Derivatives Market Activity, 2007). Given such a high turnover, it is interesting to compare the relative liquidity, measured by traded volume, across different countries.
Table A shows the relationship between the total traded volume, GDP and the average cash interest rate for the corresponding countries over the past two decades. There is a general trend for less liquid currencies, with lower GDP, to exhibit a higher average interest rate historically.
Given the BIS measure, it is instructive to check whether currencies with lower liquidity according to the BIS also exhibit greater downside risk. There are various statistical methods that can be applied to test for the empirical tail risk of financial return distributions. One of the more recent popular methods proposed for measuring the non-normality of financial assets is the use of the omega function (Shadwick & Keating, 2002). Using variance as the sole measure of risk implicitly assumes asset prices are normally distributed. However, the omega function samples all moments of the distribution simultaneously and hence can be intuitively interpreted in financial terms. The omega measure is not parametric, but is calculated directly from the observed distribution and requires no estimates, and hence measures the downside risk directly.
Omega is simply defined as the ratio of the probability-weighted cumulative returns above a certain threshold. A higher value of omega is therefore a direct measure of a higher ratio of probability of returns below a certain threshold to that above a certain threshold. When the threshold is set sufficiently low (that is, equal to the mean return minus the 99% of the normal distribution), a value of omega above 1/99 = 1.01% is a signature of additional downside risk compared with the simple normal distribution estimate.
To compare the downside risk of a simple carry strategy, we calculated the omega values using daily currency spot return data from September 1993 to December 2007 for all the G-10 currencies versus the yen. The yen was chosen as the base currency due to the fact it exhibited the lowest average yield over this period, and is the most commonly used funding currency for carry trades in general.
The average daily standard deviation of spot returns was in the range of 0.6% (for Swiss franc/yen) to 0.8% (for New Zealand dollar/yen). The threshold of return was therefore set at a value significantly greater than the standard deviation, at -1.2% daily, in the direction of appreciating yen - that is, in the opposite direction to the carry trade.
Figure 3 shows the plot of the measured omega values versus the average interest rate differential with yen as a base currency. On average, there exists a general trend in which currencies with higher interest rate differentials also exhibit a greater probability-weighted drawdown.
Figure 4 shows the relationship between the measured downside risk (in this instance divided by the daily standard deviation) and the inverse of the percentage of traded volume as reported by the BIS. Currencies with lower overall traded volume (and hence liquidity) exhibit higher downside return risk for the same underlying level of realised standard deviation.
This relationship between the interest rate differential, liquidity and the corresponding downside risk suggests currency investment in smaller economies within the developed world provides a higher general interest rate return, partly as a form of compensation for the lower relative liquidity and corresponding downside risk of owning them.
Furthermore, this downside currency risk has an increasingly important effect at elevated volatility levels. To see this, we can compare the contribution of excess downside risk (measured as the downside risk beyond the ninety-ninth percentile estimated by the normal distribution) and the average daily standard deviation. Figure 5 shows this relationship for the most polarised carry pair of the three in the G-10 universe (highest versus lowest yielding), using a one-year rolling window.
At lower overall volatility levels, when the standard deviation of returns to carry is low and a simple carry-to-risk ratio is attractive, the non-normal exhibited downside risks are very low. On the other hand, when the average volatility is elevated, the probability of returning less than the ninety-ninth percentile implied by the standard deviation becomes significantly higher than 1%. At low volatility levels, therefore, the interest rate differential is generally the most important factor in picking the currency pairs, whereas when volatility is elevated, liquidity becomes a more significant issue.
From our current perspective, in line with the rise in our Base Volatility Index and the likely impact on downside risk for carry trades, we forecast a decreasing attractiveness of the interest rate return component in comparison with the low volatility environment that characterised the four years leading up to August 2007, particularly for currencies with lower relative liquidity. With volatility rising, timing becomes an increasingly important component for successful currency management, and a forward-looking style is generally complementary to the type of market conditions where historical financial market volatility becomes an ever-decreasing prediction of the future realised.
Ivan Petej is a currency analyst at Principal Global Investors. Email: Petej.Ivan@principal.com
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact email@example.com or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact firstname.lastname@example.org to find out more.
You are currently unable to copy this content. Please contact email@example.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email firstname.lastname@example.org
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email email@example.com
More on Foreign exchange
Power-reverse to the future: falling yen revs up PRDCs again
Pressure on Japanese unit sparks revival in power-reverse dual currency notes
Credit Suisse and Commerz latest banks to ditch hold times
Mizuho also confirms zero last look add-on but MUFG’s policy unclear on the controversial FX practice
Has Covid stopped the clocks on FX timestamp efforts?
Budget reallocation may not be the only factor stalling standardisation progress, say participants
EU benchmark drama set for cliffhanger end
Access to key FX rates due to be decided six months before potential cut-off
Banks rent ready-made algos for FX trading
NatWest, XTX Markets and others develop new outsourcing model for tech
Who killed FX volatility?
Beyond central bank policy, traders see a range of hidden structural factors at work
Harnessing the benefits of more automated fx trade lifecycle operations
FX markets are unique not only in their scale but also in their complexity. There are multiple trading paradigms, and also multiple venues where trades may be executed. The FX ecosystem is highly fragmented and the case for more automation – more…
Smarter trading in a fragmented world
FX Week recently hosted a webinar in partnership with Refinitiv to ask foreign exchange industry leaders to discuss geopolitical challenges, market changes and developments, and evolving technologies, and how they have shaped forex markets in Asia