NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Asset Pricing

November 20-21, 2014
Nicolae Garleanu and Martin Lettau, University of California, Berkeley, Organizers

Rhys Bidder, Federal Reserve Bank of San Francisco, and Ian Dew-Becker, Northwestern University

Long-Run Risk is the Worst-Case Scenario

Bidder and Dew-Becker study an investor who is unsure of the dynamics of consumption growth. She estimates her consumption process non-parametrically to place minimal restrictions on dynamics. Treating the agent as ambiguity-averse yields a simple and tractable framework for analyzing her model uncertainty. The researchers analytically show that the worst-case model that she uses for pricing, given a penalty on deviations from the point estimate, is a model with long-run risks, even if consumption growth is actually white noise. With a single parameter determining risk preferences, the model generates high and volatile risk premia and matches R²s from return forecasting regressions, even though risk aversion is equal to 4.8 and the worst-case dynamics are statistically nearly indistinguishable from the true model.


Marianne Andries, Toulouse School of Economics; Thomas Eisenbach, Federal Reserve Bank of New York; and Martin Schmalz, University of Michigan,
Asset Pricing with Horizon-Dependent Risk Aversion

Andries, Eisenbach, and Schmalz study general equilibrium asset prices in a multi-period endowment economy when agents' risk aversion is allowed to depend on the maturity of the risk. The researchers find that horizon-dependent risk aversion preferences generate a decreasing term structure of risk premia if and only if volatility is stochastic. Therefore, under the horizon-dependent risk aversion model, recent empirical results on the term structure of risk premia are driven by a downward-sloping term structure of the price of volatility risk. The authors test this prediction using both index options data and by showing that the value premium is related to exposure to volatility risk.


Dongho Song, Boston College

Bond Market Exposures to Macroeconomic and Monetary Policy Risks

Song documents evidence of structural changes in key moments of the yield curve and the correlation between bond-stock returns and consumption growth-inflation. The researcher estimates an equilibrium model that features regime shifts in monetary policy aggressiveness and the conditional covariance of consumption and inflation that generate endogenous regime-switching inflation and bond price dynamics. The shifts in the conditional covariance process affect the dynamics of the yield curve and asset prices, while policy changes mostly influence their second moments. The model accounts for several bond market features, including the presence of unspanned macroeconomic factors and changes in the bond-stock return correlation.

Itamar Drechsler, New York University and NBER, and Qingyi Drechsler, WRDS

The Shorting Premium and Asset Pricing Anomalies (NBER Working Paper No. 20282)

Short-rebate fees are a strong predictor of the cross-section of stock returns, both gross and net of fees. Drechsler and Drechsler document a large "shorting premium": the cheap-minus-expensive-to-short (CME) portfolio of stocks has a monthly average gross return of 1.31%, a net-of-fees return of 0.78%, and a 1.44% four-factor alpha. The researchers show that short fees interact strongly with the returns to eight of the largest and most well-known, cross-sectional anomalies. The anomalies effectively disappear within the 80% of stocks that have low short fees, but are greatly amplified among those with high fees. The authors propose a joint explanation for these findings: the shorting premium is compensation for the concentrated short risk borne by the small fraction of investors who do most shorting. Because it is on the short side, it raises prices rather than lowers them. The researchers proxy for this short risk using the CME portfolio return and demonstrate that a Fama-French + CME factor model largely captures the anomaly returns among both high- and low-fee stocks.


Christopher Culp, Johns Hopkins Institute for Applied Economics; Yoshio Nozawa, Federal Reserve Board; and Pietro Veronesi, University of Chicago and NBER

The Empirical Merton Model

Although the Merton model of corporate debt as equivalent to safe debt minus a put option on the firm's assets fails to match observed credit spreads, Culp, Nozawa, and Veronesi show that portfolios of long Treasuries and short traded put options ("pseudo bonds") closely match the properties of traded corporate bonds. Pseudo bonds display a credit spread puzzle that is stronger at short horizons, unexplained by standard risk factors, and unlikely to be solely due to illiquidity. The researchers illustrate a novel, model-free benchmarking methodology to run data-based counterfactuals, with applications to credit spread biases, the impact of asset uncertainty, and bank-related rollover risk.


Alan Moreira, Yale University, and Alexi Savov, New York University and NBER

The Macroeconomics of Shadow Banking (NBER Working Paper No. 20335)

Moreira and Savov build a macroeconomic model that centers on liquidity transformation in the financial sector. Intermediaries maximize liquidity creation by issuing securities that are money-like in normal times but become illiquid in a crash when collateral is scarce. The researchers call this process shadow banking. A rise in uncertainty raises demand for crash-proof liquidity, forcing intermediaries to delever and substitute toward safe, collateral-intensive liabilities. Shadow banking shrinks, causing the liquidity supply to contract, discount rates and collateral premia to spike, and prices and investment to fall. The model produces slow recoveries, collateral runs, and flight to quality and it provides a framework for analyzing unconventional monetary policy and regulatory reform proposals.


 
Publications
Activities
Meetings
NBER Videos
Themes
Data
People
About

National Bureau of Economic Research, 1050 Massachusetts Ave., Cambridge, MA 02138; 617-868-3900; email: info@nber.org

Contact Us