Asset Pricing.

The NBER's Program on Asset Pricing met at the University of Chicago on March 30. Program Director John H. Cochrane, NBER and University of Chicago, and Nicolae B. Garleanu, NBER and the Wharton School, organized this program:

Ravi Bansal, Duke University; Dana Kiku, University of Pennsylvania; and Amir Yaron, University of Pennsylvania and NBER, "Risks for the Long Run: Estimation and Inference"

Discussant: George M. Constantinides, University of Chicago and NBER

Wei Yang, University of Rochester, "Time-Varying Exposure to Long-Run Consumption Risk"

Discussant: Lars P. Hansen, University of Chicago and NBER

Dimitri Vayanos, London School of Economics and NBER, and Jean-Luc Vila, Merrill Lynch, "A Preferred-Habitat Model of the Term Structure of Interest Rates"

Discussant: Pierre Collin-Dufresne, University of California, Berkeley and NBER

Lorenzo Garlappi, University of Texas, and Hong Yan, University of South Carolina, "Financial Distress and the Cross-Section of Equity Returns"

Discussant: Joao Gomes, University of Pennsylvania

Xavier Gabaix, MIT and NBER, "Linearity-Generating Processes: A Modeling Tool Yielding Closed Forms for Asset Prices"

Discussant: Pietro Veronesi, University of Chicago and NBER

Lubos Pastor and Pietro Veronesi, University of Chicago and NBER, and Lucian Taylor, University of Chicago, "Entrepreneurial Learning, The IPO Decision and the Post-IPO Drop in Firm Profitability"(NBER Working Paper No. 12792)

Discussant: Markus K. Brunnermeier, Princeton University and NBER

Recent work by Bansal and Yaron (2004) on long-run risks suggests that they can account for key features of asset market data. In this paper, Bansal, Kiku, and Yaron develop methods for estimating their equilibrium model by exploiting the asset pricing Euler equations. Using an empirical estimate for the long-run risk component, they demonstrate that the Long-Run Risk Model can indeed capture a rich array of asset returns. The model, at plausible preference estimates, can account for the market as well as the "value" and "size" premium. The researchers show that time averaging effects, that is a mismatch in the sampling and the agent's decision interval, lead to significant biases in the estimates for risk aversion and the elasticity of intertemporal substitution. Their evidence suggests that accounting for these biases is important for interpreting the magnitudes of the preference parameters and the economic implications of the model for asset prices.

Yang develops a model of time-varying expected returns and shows that, when investors care about the long-run consumption risk, they also care about the persistence of an asset's exposure to this risk, and demand substantially higher compensation for more persistent exposure. The model also implies a negative sensitivity of price-dividend ratios to expected excess returns, and the magnitude of the sensitivity is substantially larger for more persistent exposure. In an application of the model, he specifics individual stocks' dividend growth as containing two time-varying components of exposure to the long-run consumption risk--a fast mean-reverting component whose shocks are positively correlated with the independent dividend growth shocks, and a slow mean-reverting component whose shocks are negatively correlated with the independent dividend growth shocks. Firm-level simulations from this model produce short-run momentum and long-run reversal quantitatively comparable to empirically documented patterns in the cross section as well as along the time dimension. The simulations also show that the value premium across price-dividend ratio sorted portfolios is driven by a spread in the slow mean-reverting risk exposure. Together, these results propose potential interpretations of the value and momentum factors as representing time-varying loadings of different persistence on the long-run consumption risk factor.

Vayanos and Vila develop a term-structure model in which investors with preferences for specific maturities trade with risk-averse arbitrageurs. Arbitrageurs integrate the markets for different maturities, incorporating information about expected short rates into bond prices. The researchers show that bond risk premia are related negatively to short rates and positively to term-structure slope. Moreover, forward rates under-react to expected short rates, especially for long maturities, while investor demand mainly affects long maturities. Thus, the short end of the term structure is driven mainly by short-rate expectations, while the long end is driven by demand. Despite the presence of two distinct economic factors, the first principal component explains about 90 percent of movement. These results are consistent with empirical evidence and generate novel testable implications.

Garlappi and Yan propose a new perspective for understanding cross-sectional properties of equity returns. They explicitly introduce financial leverage in a simple equity valuation model and consider the likelihood of a firm defaulting on its debt obligations as well as potential deviations from the absolute priority rule (APR) upon the resolution of financial distress. They show that financial leverage amplifies the magnitude of the book-to-market effect and hence provides an explanation for the empirical evidence that value premia are larger among firms with higher likelihood of financial distress. By further allowing for APR violations, this model generates two novel predictions about the cross section of equity returns: 1) the value premium (computed as the difference between expected returns on mature and growth firms), is hump-shaped with respect to default probability, and 2) firms with a higher likelihood of deviation from the APR upon financial distress generate stronger momentum profits. Both predictions are confirmed in empirical tests. These results emphasize the unique role of financial distress and the ensuing nonlinear relationship between expected return and risk in understanding cross-sectional properties of equity returns.

Gabaix proposes a new class of stochastic processes with appealing properties for theoretical or empirical work in finance and macrocconomics, the "linearity-generating" class. Its key property is that it yields simple exact closed-form expressions for stocks and bonds, with an arbitrary number of factors. It operates in discrete and continuous time. It has a number of economic modeling applications. These include macroeconomic situations with changing trend growth rates, or stochastic probability of disaster, asset pricing with stochastic risk premia or stochastic dividend growth rates, and yield curve analysis that allows flexibility and transparency. Many research questions may be addressed more simply and in closed form by using the linearity-generating class.

Pastor, Veronesi, and Taylor develop a model in which an entrepreneur learns about the average profitability of a private firm before deciding whether to take the firm public. In this decision, the entrepreneur trades off diversification benefits of going public against benefits of private control. The model predicts that firm profitability should decline after the IPO, on average, and that this decline should be larger for firms with more volatile profitability and firms with less uncertain average profitability. These predictions are supported empirically in a sample of 7,183 IPOs in the United States between 1975 and 2004.