Commodity Trade and the Carry Trade: a Tale of Two Countries

Ready, Robert; Roussanov, Nikolai; Ward, Colin R.

doi:10.3386/w19371

Cited by 53 publications

(61 citation statements)

References 31 publications

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“…These are positive carry currencies (with high average interest rates) of countries that are commodity exporters. To the extent that high U.S. bond returns are associated with a run to quality in times of global economic stress, the depreciation of the Australian and New Zealand dollars is consistent with the model of Ready, Roussanov, and Ward (2013), which illustrates the relative riskiness of the currencies of commodity-producing countries. Table 3 report the regression coefficients for slopesorted and interest-rate-sorted currency portfolios, respectively.…”

Section: Testing Uncovered Bond Return Parity In the Time-seriessupporting

confidence: 56%

The Term Structure of Currency Carry Trade Risk Premia

2013

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We find that average returns to currency carry trades decrease significantly as the maturity of the foreign bonds increases, because investment currencies tend to have small local bond term premia. The downward term structure of carry trade risk premia is informative about the temporal nature of risks that investors face in currency markets. We show that long-maturity currency risk premia only depend on the domestic and foreign permanent components of the pricing kernels, since transitory currency risk is automatically hedged by interest rate risk for long-maturity bonds. Our findings imply that there is more cross-border sharing of permanent than transitory shocks.

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Section: Testing Uncovered Bond Return Parity In the Time-seriessupporting

confidence: 56%

The Term Structure of Currency Carry Trade Risk Premia

2013

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“…Daily spot and forward rates are from Barclays and Reuters . The sample period is 1988 to 2016 following Ready, Roussanov, and Ward (). Table lists the 39 countries and the dates of their corresponding data availability.…”

Section: Data and Empirical Trade Network Centralitymentioning

confidence: 99%

“…To illustrate the differences between centrality, size, and the trade composition measure of Ready, Roussanov, and Ward (), I present comparison plots in Figure . I abbreviate their measure as RRW.…”

Section: Data and Empirical Trade Network Centralitymentioning

confidence: 99%

Trade Network Centrality and Currency Risk Premia

Richmond¹

2019

The Journal of Finance

149

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I uncover an economic source of exposure to global risk that drives international asset prices. Countries that are more central in the global trade network have lower interest rates and currency risk premia. To explain these findings, I present a general equilibrium model in which central countries' consumption growth is more exposed to global consumption growth shocks. This causes the currencies of central countries to appreciate in bad times, resulting in lower interest rates and currency risk premia. Empirically, central countries' consumption growth covaries more with world consumption growth, further validating the proposed mechanism.

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“…Third, the focus on generating a negative covariance between currency risk premia and expected depreciations in these models may be less relevant empirically than previously thought. Papers that offer explicit models of either permanent or highly persistent asymmetries in currency risk premia include Martin (2012), Hassan (2013), Maggiori (2017), Richmond (2016), and Ready, Roussanov, and Ward (2017). 6 Another strand of the literature has connected persistent currency risk premia with shocks that are themselves persistent, as in Engel and West (2005), Croce (2011, 2013), Gourio, Siemer, and Verdelhan (2013), and Colacito et al (2017).…”

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confidence: 99%

Forward and Spot Exchange Rates in a Multi-currency World

Hassan

Mano

2014

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Separate literatures study violations of uncovered interest parity (UIP) using regression-based and portfolio-based methods. We propose a decomposition of these violations into a cross-currency, a between-time-and-currency, and a cross-time component that allows us to analytically relate regression-based and portfolio-based facts, and to estimate the joint restrictions they place on models of currency returns. Subject to standard assumptions on investors' information sets, we find that the forward premium puzzle (FPP) and the "dollar trade" anomaly are intimately linked: both are driven almost exclusively by the cross-time component. By contrast, the "carry trade" anomaly is driven largely by cross-sectional violations of UIP. The simplest model the data do not reject features a cross-sectional asymmetry that makes some currencies pay permanently higher expected returns than others, and larger time series variation in expected returns on the US dollar than on other currencies. Importantly, conventional estimates of the FPP are not directly informative about expected returns, because they do not correct for uncertainty about future mean interest rates. Once we correct for this uncertainty, we never reject the null that investors expect high-interest-rate currencies to depreciate, not appreciate.Throughout the main text, we use monthly observations of US dollar-based spot and forward exchange rates at the 1-, 6-and 12-month horizon. All rates are from Thomson Reuters Financial Datastream. The data range from October 1983 to June 2010. For robustness checks, we also use all UK pound-based data from the same source as well as forward premia calculated using covered interest parity from interbank interest rate data, which are available for longer time horizons for some currencies. Our dataset nests the data used in recent studies on currency returns, including Lustig et al. (2011) and. In additional robustness checks, we replicate our findings using only the subset of data used in these studies.Many of the decompositions we perform require balanced samples. However, currencies enter and exit the sample frequently, the most important example of which is the euro and the currencies it replaced. We deal with this issue in two ways. In our baseline sample ("1Rebalance"), we use the largest fully balanced sample we can construct from our data by selecting the 15 currencies with the longest coverage (the currencies

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Commodity Trade and the Carry Trade: a Tale of Two Countries

Abstract: NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Cited by 53 publications

References 31 publications

The Term Structure of Currency Carry Trade Risk Premia

The Term Structure of Currency Carry Trade Risk Premia

Trade Network Centrality and Currency Risk Premia

Forward and Spot Exchange Rates in a Multi-currency World

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