Asset Pricing Program Meeting

November 4, 2011
Andrew Ang and and Tano Santos of Columbia's Graduate School of Business, Organizers

Lars-Alexander Kuehn, Carnegie Mellon University, and Lukas Schmid, Duke University
Investment Based Corporate Bond Pricing

Kuehn and Schmid document the importance of accounting for investment options in models of credit risk. In the presence of financing and investment frictions, firm-level variables that proxy for asset composition carry explanatory power for credit spreads beyond leverage. As a result, cross-sectional studies of credit spreads that fail to control for the interdependence of leverage and investment decisions are unlikely to be very informative. Such frictions also give rise to a realistic term structure of credit spreads in a production economy.

Dirk Hackbarth, University of Illinois at Urbana-Champaign, and Timothy Johnson, London Business School
Real Options and Risk Dynamics: Implications for the Cross-Section and Time-Series of Expected Returns

Hackbarth and Johnson identify and test several new predictions about expected stock returns when real option values differ over time and across firms. The model implies an S-shaped relation between expected returns and profitability (or market-to-book) ratios. This relation generates a novel time-series pattern: return autocorrelations should display a U-shape, conditional on lagged operating variables. In cross-sections of homogeneous firms, the model does not generally imply a value premium. Instead the average relation between book-to-market and expected stock returns depends crucially on the degree of reversibility of the firm's production technology. Firms with the ability to scale down operations (liquidate capital) actually become safer as profitability decreases and book-to-market rises. In cross-sections of heterogeneous firms, the value premium is driven by differences in asset risk. Conditional on this, residual expected stock returns are positively related to lagged returns. The model thus presents a coherent account of the coexistence of value and momentum effects. Empirical tests provide evidence in support of each of the model's predictions.

Gara Afonso, Federal Reserve Bank of NY, and Ricardo Lagos, New York University and NBER
Trade Dynamics in the Market for Federal Funds

Afonso and Lagos develop a model of the market for federal funds that explicitly accounts for its two distinctive features: banks have to search for a suitable counter party; and, once they have met, both parties negotiate the size of the loan and the repayment. They use this theory to answer a number of positive and normative questions, including: What are the determinants of the fed funds rate? How does the market reallocate funds? Is the market able to achieve an efficient reallocation of funds? They also use the model for theoretical and quantitative analyses of policy issues facing modern central banks.

Tim Bollerslev, Duke University and NBER, and Natalia M. Sizova and George Tauchen, Duke University
Volatility in Equilibrium: Asymmetries and Dynamic Dependencies

Stock market volatility: clusters in time, appears fractionally integrated, carries a risk premium, and exhibits asymmetric leverage effects. At the same time, the volatility risk premium, defined by the difference between the risk-neutral and objective expectations of the volatility, appears short-memory. Bollerslev, Sizova, and Tauchen develop a first internally consistent equilibrium based explanation for all of these empirical facts. Using newly available high-frequency intra-day data for the S&P 500 and the VIX volatility index, they show that the qualitative implications from the new theoretical continuous-time model match remarkably well with the distinct shapes and patterns in the sample autocorrelations and the dynamic cross-correlations actually observed in the data.

Bryan T. Kelly, University of Chicago; Hanno Lustig, University of California at Los Angeles and NBER; and Stijn Van Nieuwerburgh, New York University and NBER

Too-Systemic-To-Fail: What Option Markets Imply About Sector-wide Government Guarantees (NBER Working Paper No. 17149)

A conspicuous amount of aggregate tail risk is missing from the price of financial sector crash insurance during the 2007-9 crisis. The difference in costs of out-of-the-money put options for individual banks, and puts on the financial sector index, increases four-fold 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. Kelly, Lustig, and Van Nieuwerburgh 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, they 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, they can closely replicate observed put spread dynamics. During the crisis, the spread responds acutely to government intervention announcements.

Manuel Adelino, Dartmouth College; Antoinette Schoar, MIT and NBER; and Felipe Severino, MIT
Credit Supply and House Prices: Evidence from Mortgage Market Segmentation

Adelino, Schoar, and Severino show that easier access to mortgage credit significantly increases house prices. By using exogenous changes in the conforming loan limit as an instrument for easier credit supply and cheaper cost of credit, they find that houses that become eligible for financing with a conforming loan show an increase in value of 1.1 dollars per square foot (for an average price per square foot of 224 dollars) and higher prices overall, controlling for a rich set of house characteristics. These coefficients are consistent with a local elasticity of house prices-to-interest rates between 1 and 6. In addition, loan-to-value ratios around the conforming loan limit deviate significantly from the common 80 percent norm, confirming that it is important in the financing choices of home buyers. In line with the interpretation here, the results are stronger in the first half of the sample (1998-2001) when the conforming loan limit was more important, given that other forms of financing were less common and substantially more expensive.

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