This article takes a shrinkage approach to examine the empirical implications of aversion to model uncertainty. The shrinkage approach explicitly shows how predictive distributions incorporate data and prior beliefs. It enables us to solve the optimal portfolios for uncertainty-averse investors. Aversion to uncertainty about the capital asset pricing model leads investors to hold a portfolio that is not mean-variance efficient for any predictive distribution. However, mean-variance efficient portfolios corresponding to extremely strong beliefs in the Fama--French model are approximately optimal for uncertainty-averse investors. The empirical Bayes approach does not result in optimal portfolios for investors who are averse to model uncertainty.

The stochastic discount factor (SDF) method provides a unified general framework for econometric analysis of asset‐pricing models. There have been concerns that, compared to the classical beta method, the generality of the SDF method comes at the cost of efficiency in parameter estimation and power in specification tests. We establish the correct framework for comparing the two methods and show that the SDF method is as efficient as the beta method for estimating risk premiums. Also, the specification test based on the SDF method is as powerful as the one based on the beta method.

Without the assumption of conditional homoskedasticity, a general asymptotic distribution theory for the two‐stage cross‐sectional regression method shows that the standard errors produced by the Fama–MacBeth procedure do not necessarily overstate the precision of the risk premium estimates. When factors are misspecified, estimators for risk premiums can be biased, and the t ‐value of a premium may converge to infinity in probability even when the true premium is zero. However, when a beta‐pricing model is misspecified, the t ‐values for firm characteristics generally converge to infinity in probability, which supports the use of firm characteristics in cross‐sectional regressions for detecting model misspecification.

Most empirical studies of the static CAPM assume that betas remain constant over time and that the return on the value-weighted portfolio of all stocks is a proxy for the return on aggregate wealth. The general consensus is that the static CAPM is unable to explain satisfactorily the cross-section of average returns on stocks. We assume that the CAPM holds in a conditional sense, i.e., betas and the market risk premium vary over time. We include the return on human capital when measuring the return on aggregate wealth. Our specification performs well in explaining the cross-section of average returns.

Financial institutions around the world expected the millennium date change (Y2K) to cause an aggregate liquidity shortage. Responding to the concern, the Federal Reserve Bank of New York auctioned Y2K options to primary dealers. The options gave the dealers the right to borrow from the Fed at a predetermined interest rate. Using the implied volatilities of Y2K options and the on-off-the-run spread, we demonstrate that the Fed's action eased the fears of bond dealers, contributing to a drop in the liquidity premium of Treasury securities. Our analysis shows the link between the microstructure of government debt markets and the central bank's provision of liquidity. We argue that Y2K options and their effects on liquidity premium broadly conform to the economic theory on public provision of private liquidity. The Author 2008. Published by Oxford University Press on behalf of the Society for Financial Studies. All rights reserved. For permissions, please e-mail: [email protected]., Oxford University Press.

Contingent capital (CC), which aims to internalize the costs of too‐big‐to‐fail in the capital structure of large banks, has been under intense debate by policy makers and academics. We show that CC with a market trigger, in which direct stakeholders are unable to choose optimal conversion policies, does not lead to a unique competitive equilibrium unless value transfer at conversion is not expected ex ante. The “no value transfer” restriction precludes penalizing bank managers for taking excessive risk. Multiplicity or absence of equilibrium introduces the potential for price uncertainty, market manipulation, inefficient capital allocation, and frequent conversion errors.

The Term Auction Facility (TAF), the first auction-based liquidity initiative by the Federal Reserve during the global financial crisis, was aimed at improving conditions in the dollar money market and bringing down the significantly elevated London interbank offered rate (Libor). The effectiveness of this innovative policy tool is crucial for understanding the role of the central bank in financial stability, but academic studies disagree on the empirical evidence of the TAF effect on Libor. We show that the disagreement arises from mis-specifications of econometric models. Regressions using the daily level of the Libor-OIS spread as the dependent variable miss either the permanent or temporary TAF effect, depending on whether the dummy variable indicates the events of the TAF or the regimes before and after an TAF event. Those regressions also suffer from the unit-root problem and produce unreliable test statistics. By contrast, regressions using the daily change in the Libor-OIS spread are robust to the persistence of the TAF effect and the unit-root problem, consistently producing reliable evidence that the downward shifts of the Libor-OIS spread were associated with the TAF. The evidence indicates the efficacy of the TAF in helping the interbank market to relieve liquidity strains.

A growing literature suggests that, even in the absence of any ability to predict returns, holding options on the benchmarks or trading frequently can generate positive alpha. The ratio of alpha to its tracking error appraises a fund's performance. This paper derives the performance-maximizing strategy, which turns out to be a variant of a buy-write strategy, and the least upper bound on such performance enhancement. If common equity indices are used as benchmarks, the potential alpha generated from trading frequently can be substantial in magnitude, but it carries considerable risk. The statistical significance in estimated alpha is low, and the probability of a negative alpha is high. The performance enhancement from holding options can be significant - both economically and statistically - if the options' implied volatilities are higher than the volatilities of the benchmark returns. The performance-maximizing strategy derived in this paper is different from the strategies that switch portfolio exposure to the benchmarks. The exposure-switching strategies are not promising unless the switching is based on superior information.