Common Risk Factors in Currency Markets

The starting claim is that currency risk premia are a robust feature of the data, survive transaction costs, and are determined by exposure to a single global risk factor for which the interest rate itself is the measure of exposure. (The figures below come from the freely available NBER working-paper version of June 2008, which is the full text this summary was built from; the published version appeared in the Review of Financial Studies in 2011.) The empirical design is a cross-sectional sort rather than the usual time-series test: at the end of each month all currencies for which forward contracts trade are allocated to six portfolios by their forward discount – which equals the interest differential when covered interest parity holds – so portfolio 1 holds the lowest interest rate currencies and portfolio 6 the highest, and portfolios are rebalanced monthly. This matters for interpretation, because the classic UIP failure documented by Hansen-Hodrick and Fama concerns currencies whose rates are higher than usual, whereas here “our investment strategy only considers whether the currency’s interest rate is currently high.” The sample is 37 currencies from end-1983 to early 2008, growing from 9 countries to 26 with a maximum of 34, with a 15-country developed subsample as a robustness check; returns are computed from spot and one-month forward contracts net of bid-ask spreads. The basic magnitudes: portfolio 1 currencies trade at an average forward discount of -390 basis points but appreciate by only about 100 basis points, giving a log excess return of -290 basis points; portfolio 6 currencies trade at a discount of 778 basis points but depreciate only 188, giving +590 basis points. Net of transaction costs the spread between the first and last portfolio is 483 basis points a year with a Sharpe ratio of 0.54 – against 7.11 percent and a Sharpe ratio of 0.48 for the Fama-French US market excess return over the same period, which does not net out any transaction costs. In the developed-country subsample the long-short Sharpe ratio is 0.39. A principal component analysis of the six portfolio returns yields two factors explaining more than 80 percent of return variation: a level factor (70 percent of common variation, all portfolios loading equally) that is essentially the average portfolio return, labelled the dollar factor RX, and a slope factor (over 12 percent) with monotonically increasing loadings, essentially portfolio 6 minus portfolio 1, labelled HML_FX. Cross-sectional asset pricing on the six portfolios gives an adjusted R-squared of 69 percent with a root mean squared error around 95 basis points and no rejection of the null that pricing errors are zero. The estimated market price of HML_FX risk is 546 basis points per annum against a sample factor mean of 537 – a nine-basis-point gap, which is what linear factor pricing requires since the factor is itself a traded return. HML_FX betas rise monotonically from -0.39 for portfolio 1 to 0.61 for portfolio 6, so low interest rate currencies insure US investors against this risk while high interest rate currencies expose them to it. The dollar factor’s price (135 basis points, mean 136) prices the average level of returns but none of the cross-section. Three further results tie the pieces together: sorting currencies instead on their estimated HML_FX betas recovers monotonically increasing forward discounts and excess returns, so the interest rate really is measuring exposure; the carry factor also prices momentum portfolios, which supports a risk-based rather than characteristic-based reading; and the average forward discount across portfolios predicts returns better than portfolio-specific discounts, with forecast excess returns on medium-to-high interest portfolios moving counter-cyclically against US industrial production, payrolls and help-wanted indices and positively with term and default premia and the VIX. A no-arbitrage exponentially-affine model with a country-specific and a common SDF factor reproduces this, but only under two conditions: a common factor must exist, since it is “the only source of cross-sectional variation in currency risk premia,” and low interest rate currencies must load more on the common factor when the price of common risk is high. Heterogeneity in country-specific loadings alone cannot do the job.

Taper Tantrums: Quantitative Easing, Its Aftermath, and Emerging Market Capital Flows

Identifying US monetary policy shocks from daily moves in five-year Treasury futures around FOMC announcements, this paper shows that during the unconventional-policy years those shocks largely represent revisions to required risk compensation rather than to the expected short-rate path, and that their effects on emerging market portfolio positions run mainly through valuations rather than physical flows – with by far the largest effects during the taper period. The shock measure follows Rogers, Scotti and Wright (2014): the daily change in the implied yield of the five-year Treasury futures contract on FOMC announcement dates, plus the additional policy events in Gagnon et al. (2011) and the taper-tantrum date of 22 May 2013. Its average value is a fall of 2.0 basis points during the QE period and a rise of 1.6 basis points during the taper period, against minus 0.6 for the full sample and minus 0.5 pre-crisis, with the period differences statistically significant. Feeding the shock through the Kim and Wright (2005) affine term structure decomposition shows it moves both the expected short rate and the term premium in the conventional period, but that in the unconventional periods the largest effects are on term premia and those effects rise monotonically with maturity – a one-standard-deviation shock raises the ten-year yield by 4.7 basis points pre-crisis but 12.2 basis points during QE, against unconditional daily ten-year standard deviations of 5.8 and 7.1 basis points respectively. The capital-flow analysis uses Bertaut-Tryon and Bertaut-Judson monthly estimates built from US Treasury International Capital data, covering 15 emerging markets monthly from 1994 to 2014, with positions, flows and valuation changes for debt and equity separately scaled by annual GDP, estimated in a random-effects panel with lagged dependent variables, an extensive set of lagged push and pull controls, and country-clustered robust standard errors. Three kinds of heterogeneity emerge. Flows versus prices: “in nearly every specification, the effect of monetary policy shocks on asset returns is larger than that for physical flows,” which the authors read as consistent with the shocks capturing revisions in required risk compensation. Debt versus equity: during QE the coefficient on equity valuations is ten times that on debt valuations, and during the taper period equity effects are double or triple debt effects. QE versus tapering: during QE the significant responses are confined to debt and equity valuations and equity positions, whereas after tapering was first mentioned the coefficients are inversely signed and significant at the 1 percent level across essentially every variable, and an order of magnitude larger than pre-crisis for debt positions, debt valuations and equity flows. Because the shock has a magnitude, the paper can price these effects: a mean-sized QE shock corresponds to roughly a $153.5 million monthly increase in US emerging market equity positions per country, a mean-sized taper shock to a $144.1 million monthly outflow, with one-standard-deviation ranges of roughly minus $672 million to plus $979 million during QE. The paper is explicit that its estimates are associations from a controlled panel regression rather than structural effects: coefficients are described throughout as correlations, the shock’s channel is inferred from coefficient signs rather than separately identified, and the exchange rate results, while statistically significant, are reported as economically modest against an unconditional monthly bilateral exchange rate standard deviation of 3.57 percent.

Review of Financial Studies | Macro Paper Warehouse

Common Risk Factors in Currency Markets

Taper Tantrums: Quantitative Easing, Its Aftermath, and Emerging Market Capital Flows