__[slides]__

(with Robert Richmond)

Exchange rates strongly co-vary against their base currency. We uncover a gravity equation in this factor structure: the key determinant of a country’s exchange rate beta on the common base factor is the country’s distance from the base country. The farther the country, the larger the beta. For example, the beta of the CHF/USD exchange rate on the dollar factor is determined by the distance between Switzerland and the United States. Shared language, legal origin, shared border, resource similarity and colonial linkages also significantly lower the betas. On average, the exchange rates of peripheral countries tend to have high Rsquareds in factor regressions, while central countries have low Rsquareds. A no-arbitrage model of exchange rates replicates this distance-dependent factor structure when the exposure of pricing kernels to global risk factors is more similar for closer country pairs.

__Nominal Exchange Rate Stationarity and Long-Term Bond Returns__

**[slides]**(with Adrien Verdelhan and Andreas Stathopoulos)

We derive a novel test for nominal exchange rate stationarity that exploits the forward-looking information in long maturity bond prices. When nominal exchange rates are stationary, no arbitrage implies that the return on the foreign long bond expressed in dollars is identical to the return on the U.S. bond. In the data, we do not find significant differences in long-term government bond risk premia in dollars across G10 countries, contrary to the large differences in risk premia at short maturities documented in the FX carry trade literature. Moreover, in most of the cases examined, we cannot reject that realized foreign and domestic long-term bond returns in dollars are the same, as if nominal exchange rates were stationary in levels, contrary to the academic consensus. [This paper was formerly circulated under the title `The Term Structure of Carry Trade Risk Premia']

**Does Incomplete Spanning in International Financial Markets Help to Explain Exchange Rates?**

(with Adrien Verdelhan)

Exchange rates are puzzlingly smooth and only weakly correlated with macro-economic fundamentals compared to the predictions of exchange rate models with complete spanning. This paper derives an upper bound on the effects of incomplete spanning in international financial markets. We introduce stochastic wedges between log exchange rate changes and the difference in the countries' log pricing kernels without violating the foreign investors' Euler equations for the domestic risk-free assets. The wedges reconcile the volatility of no-arbitrage exchange rates with the data, provided that the volatility of the wedges is approximately as large as the maximum Sharpe ratio. But, when pricing kernels and wedges are conditionally lognormal, these same wedges cannot deliver exchange rates that simultaneously match currency risk premia and the exchange rates' correlation with fundamentals in the data..

Local stock markets adjust sluggishly to changes in local inflation. Nominal returns on a country's local stock market index do not respond to country-specific variation in the rate of inflation. When the local rate of inflation increases, local investors subsequently earn significantly lower real returns on local stocks, but not on local bonds or foreign stocks. We provide evidence that stock market investors use sticky long-run nominal discount rates. Small departures from rational inflation expectations that underweight current inflation in forecasts of future inflation suffice to match the real stock return predictability induced by inflation in the data.

Empirical work on asset prices suggests that pricing kernels have to be almost perfectly correlated across countries. If they are not, real exchange rates are too smooth to be consistent with high Sharpe ratios in asset markets. However, the cross-country correlation of macro fundamentals is far from perfect. We reconcile these empirical facts in a two-country stochastic growth model with segmented markets. A large fraction of households either do not participate in the equity market or hold few equities, and these households drive down the cross-country correlation in aggregate consumption. Only a small fraction of households participate in international risk sharing by frequently trading domestic and foreign equities. These active traders are the marginal investors, who impute the almost perfect correlation in pricing kernels. In our calibrated economy, we show that this mechanism can quantitatively account for the excess smoothness of exchange rates in the presence of highly volatile stochastic discount factors.

We propose a network model of firm volatility in which the customers’ growth rate shocks influence the growth rates of their suppliers, larger suppliers have more customers, and the strength of a customer-supplier link depends on the size of the customer firm. Even though all shocks are i.i.d., the network model produces firm-level volatility and size distribution dynamics that are consistent with the data. In the cross section, larger firms and firms with less concentrated customer networks display lower volatility. Over time, the volatilities of all firms co-move strongly, and their common factor is concentration of the economy-wide firm size distribution. Network effects are essential to explaining the joint evolution of the empirical firm size and firm volatility distributions.

We study the nature of deflation risk by extracting the objective distribution of inflation from the market prices of inflation swaps and options. We find that the market expects inflation to average about 2.5 percent over the next 30 years. Despite this, the market places substantial probability weight on deflation scenarios in which prices decline by more than 10 to 20 percent over extended horizons. We find that the market prices the economic tail risk of deflation very similarly to other types of tail risks such as catastrophic insurance losses. In contrast, inflation tail risk has only a relatively small premium. Deflation risk is also significantly linked to measures of financial tail risk such as swap spreads, corporate credit spreads, and the pricing of super senior tranches. These results indicate that systemic financial risk and deflation risk are closely related.

(with Ralph Koijen and Stijn Van Nieuwerburgh)

Value stocks have higher exposure to innovations in the nominal bond risk premium, which measures the markets' perception of cyclical variation in future output growth, than growth stocks. The ICAPM then predicts a value risk premium provided that good news about future output lowers the marginal utility of investors' wealth today. In support of the business cycle as a priced state variable, we show that low value minus growth returns, typically realized at the start of recessions when nominal bond risk premia are low and declining, are associated with lower future dividend growth rates on value minus growth and with lower future output growth in the short term. Because of this new nexus between stock and bond returns, a parsimonious three-factor model can jointly price the book-to-market stock and maturity-sorted bond portfolios and reproduce the time-series variation in expected bond returns. Structural dynamic asset pricing models need to impute a central role to the business cycle as a priced state variable to be quantitatively consistent with the observed value, equity, and nominal bond risk premia.