Real exchange rates can predict currency excess returns, and this predictive power
becomes stronger when expanded to include such country-specific factors as productivity,
export quality, net foreign assets, and output gaps.
How Is This Research Useful to Practitioners?
As investors and market practitioners evaluate various investments, assessing the value of
global currencies is a critical step. Global investors typically rely on such relative
measures as purchasing power parity and the underlying real exchange rate, because these
rates implicitly suggest expectations about future economic fundamentals. Real exchange
rates are assumed to be driven by expected excess returns, expected real interest rate
differentials, and long-run expected real exchange rates. Thus, having a superior
understanding of this implicit currency value, both current and forecasted, should enable an
investor to achieve superior investment returns.
The authors attempt to provide a more accurate currency valuation framework that affords a
better understanding of a currency’s true value. After being adjusted for macro
fundamentals, this framework can produce superior Sharpe ratios that are largely
attributable to lower return volatility. These higher Sharpe ratios should help investment
professionals achieve a superior risk–reward profile for their various portfolios.
How Did the Authors Conduct This Research?
Four factors are chosen to more accurately determine the value of a currency: productivity,
export quality, net foreign assets, and output gaps. The authors use productivity as a
variable because highly productive economies tend to persistently exhibit stronger exchange
rates. Export quality is used because quality variations can lead to prolonged differences
in price levels. Net foreign assets are included because these resources capture global
imbalances that require exchange rate adjustments. Output gaps, the final variable, are used
because they are an indicator of future expected interest rate differentials. The authors
use a panel of exchange rates and macro fundamentals covering 23 advanced and emerging
economies over 1970–2014 at a quarterly frequency. These data come mostly from the
Global Financial Database; the export quality data come from the International Monetary
Fund. These two sources also provide home-bias data. The authors then use Granger
causality–type tests to determine whether the macro variables relate to exchange rate
differentials by regressing these numbers on lagged fundamentals. Using regression analysis,
they determine whether home bias influences exchange rate differentials, finding that those
results are not statistically significant.
The results of this research suggest that investment professionals would benefit from
diversifying away from such conventional strategies as carry and momentum. Investment
professionals seeking to maximize returns for a given level of risk should consider this
research and its findings when constructing portfolios and evaluating strategies.
The authors provide critical insight regarding the valuation of currencies from an
asset-pricing standpoint. Market practitioners and research professionals should use these
findings to better evaluate multicurrency investments and strategies. Further research that
not only isolates instances in which a currency persistently deviates from its suggested
value but also determines the economic causes and effects of that environment is needed.