Working Papers

Nominal Exchange Rate Stationarity and Long-Term Bond Returns
(with Adrien Verdelhan and Andreas Stathopoulos)

When markets are complete, exchange rates correspond to the ratio of domestic and foreign pricing kernels. When the martingale components of the pricing kernels are the same across countries and exchange rates are stationary, long-term bond returns, once converted in the same currency, should be the same across countries. In the data, we do not find significant differences in long-term government bond risk premia in dollars across G10 countries. Moreover, in 60% of our rolling windows, we cannot reject that realized foreign and domestic long-term bond returns expressed in dollars are the same, as if nominal exchange rates were stationary in levels, contrary to the academic consensus.

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..

(with Michael Katz and Lars Nielsen)

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.

Firm Volatility in Granular Networks 
(with Bryan Kelly and Stijn Van Nieuwerburgh)

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.

A conspicuous amount of aggregate tail risk is missing from the price of financial sector crash insurance during the 2007-2009 crisis. The difference in costs of out-of-the-money put options for individual banks, and puts on the financial sector index, increases fourfold from its pre-crisis level. At the same time, correlations among bank stocks surge, suggesting the high put spread cannot be attributed to a relative increase in idiosyncratic risk. We show that this phenomenon is unique to the financial sector, that it cannot be explained by observed risk dynamics (volatilities and correlations), and that illiquidity and no-arbitrage violations are unlikely culprits. Instead, we provide evidence that a collective government guarantee for the financial sector lowers index put prices far more than those of individual banks, explaining the divergence in the basket-index spread. By embedding a bailout in the standard one-factor option pricing model, we can closely replicate observed put spread dynamics. During the crisis, the spread responds acutely to government intervention announcements.

Deflation Risk
(with Francis Longstaff and Matthias Fleckenstein)

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.