Working Papers

(with Andrea Eisfeldt and Lei Zhang)

We develop a dynamic equilibrium model of complex asset markets with endogenous entry and exit in which the investment technology of investors with more expertise is subject to less asset-specific risk. The joint equilibrium distribution of financial expertise and wealth then determines this asset market’s risk bearing capacity. Higher expert demand lowers equilibrium required returns, reducing overall participation. In a dynamic industry equilibrium, investor participation in more complex asset markets with more asset-specific risk is lower, despite higher market-level Sharpe ratios, as long as asset complexity and expertise are complements. We analyze how asset complexity affects the stationary wealth distribution of complex asset investors. Because of selection, increased complexity reduces expertise heterogeneity and wealth concentration, even though the wealth distribution for more expert investors has fatter tails.

(with Barney Hartman-Glaser and Mindy Zhang)

We develop a model in which firm-specific shocks have a first-order effect on the distribution of rents between shareholders and managers. In our model, firms optimally provide managers with contracts that do not expose them to risk. Consequently, larger and more productive firms return a larger share of rents to shareholders while less productive firms endogenously exit. An increase in firm-level risk lowers the threshold at which firms exit and increases the measure of firms in the right tail of the size distribution. As a result, such an increase always increases the aggregate capital share in the economy, but may lower the average firm's capital share. Moreover, the aggregate capital share reported in national income accounts produces a biased estimate of the ex-ante distribution of rents because the data only contain surviving firms. We confirm that the average firm's capital share has declined amongst publicly traded U.S. firms, even though the aggregate capital share has increased. We attribute the secular increase in the aggregate capital share amongst these firms to an increase in firm size inequality that results from an increase in firm-level risk. This effect is only partially mitigated by an increase in inter-firm labor compensation inequality.

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.

Equity is Cheap for Large Financial Institutions: The International Evidence 
(with Priyank Gandhi and Alberto Plazzi)

Equity is a cheap source of funding for a country's largest financial institutions. In a large panel of 31 countries, we find that the stocks of a country's largest financial companies earn returns that are significantly lower than stocks of non-financials with the same risk exposures. In developed countries, only the largest banks' stock earns negative risk-adjusted returns, but, in emerging market countries, other large non-bank financial firms do. Even though large banks have high betas, these risk-adjusted return spreads cannot be attributed to the risk anomaly. Instead, we find that the large-minus-small, financial-minus-nonfinancial, risk-adjusted spread varies across countries and over time in ways that are consistent with stock investors pricing in the implicit government guarantees that protect shareholders of the largest banks. The spread is significantly larger for the largest banks in countries with deposit insurance, backed by fiscally strong governments, and in common law countries that offer shareholders better protection from expropriation. Finally, the spread predicts large crashes in that country's stock market and output.

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']

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 Yi-Li Chien and Kanda Naknoi) 

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.

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.

(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.