Currency premia and global imbalances

© 2016 The Author 2016. Published by Oxford University Press on behalf of The Society for Financial Studies. We show that a global imbalance risk factor that captures the spread in countries' external imbalances and their propensity to issue external liabilities in foreign currency explains the cross-sectional variation in currency excess returns. The economic intuition is simple: net debtor countries offer a currency risk premium to compensate investors willing to finance negative external imbalances because their currencies depreciate in bad times. This mechanism is consistent with exchange rate theory based on capital flows in imperfect financial markets. We also find that the global imbalance factor is priced in cross-sections of other major asset markets

Business cycles and currency returns

We find a strong link between currency excess returns and the relative strength of the business cycle. Buying currencies of strong economies and selling currencies of weak economies generates high returns both in the cross-section and time series of countries. These returns stem primarily from spot exchange rate predictability, are uncorrelated with common currency investment strategies, and cannot be understood using traditional currency risk factors in either unconditional or conditional asset pricing tests. We also show that a business cycle factor implied by our results is priced in a broad currency cross section.Steven Riddiough gratefully acknowledges financial support from the Faculty of Business and Economics, University of Melbourne

Foreign exchange volume

We investigate the information contained in foreign exchange (FX) volume using a novel dataset from the over-the-counter market. We find that volume helps predict next day currency returns and is economically valuable for currency investors. Predictability implies a stronger currency return reversal for currency pairs with abnormally low volume today, and is driven by the component of FX volume unrelated to volatility, illiquidity, and order flow. We rationalize these findings via a simple model of exchange rate determination, in which volume helps reveal the degree of asymmetric information in currency markets. Testing this prediction shows that asymmetric information is uniform across currency pairs but varies across instruments.We thank the Accounting & Finance Association of Australia and New Zealand for generous financial suppor

Nonstandard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-standard errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants