The authors find support for a negative relation between conditional expected monthly return and conditional variance of monthly return using a GARCH-M model modified by allowing (1) seasonal patterns in volatility, (2) positive and negative innovations to returns having different impacts on conditional volatility, and (3) nominal interest rates to predict conditional variance. Using the modified GARCH-M model, they also show that monthly conditional volatility may not be as persistent as was thought. Positive unanticipated returns appear to result in a downward revision of the conditional volatility, whereas negative unanticipated returns result in an upward revision of conditional volatility.

In this article we develop alternative ways to compare asset pricing models when it is understood that their implied stochastic discount factors do not price all portfolios correctly. Unlike comparisons based on χ 2 statistics associated with null hypotheses that models are correct, our measures of model performance do not reward variability of discount factor proxies. One of our measures is designed to exploit fully the implications of arbitrage-free pricing of derivative claims. We demonstrate empirically the usefulness of our methods in assessing some alternative stochastic factor models that have been proposed in asset pricing literature.

In this article we develop alternative ways to compare asset pricing models when it is understood that their implied stochastic discount factors do not price all portfolios correctly. Unlike comparisons based on statistics associated with null hypotheses that models are correct, our measures of model performance do not reward variability of discount factor proxies. One of our measures is designed to exploit fully the implications of arbitrage‐free pricing of derivative claims. We demonstrate empirically the usefulness of our methods in assessing some alternative stochastic factor models that have been proposed in asset pricing literature.

We provide a rationale for the presence of points in mortgage loan contracts. Our analysis builds on two key features. First, insurance markets are unavailable for labor income. Second, the “due‐on‐sale” clause allows banks to offer loan contracts which partially insure against fluctuations in labor income. If explicit prepayment penalties are prohibited by law, points serve effectively as prepayment penalties. We also examine environments where such penalties are not prohibited and show that points will be used if interest rates cannot depend on the size of the loan.

This paper shows that bank runs can be modeled as an equilibrium phenomenon. We demonstrate that some aspects of the intuitive “story” that bank runs start with fears of insolvency of banks can be rigorously modeled. If individuals observe long “lines” at the bank, they correctly infer that there is a possibility that the bank is about to fail and precipitate a bank run. However, bank runs occur even when no one has any adverse information. Extra market constraints such as suspension of convertibility can prevent bank runs and result in superior allocations.

The authors show how to use security market data to restrict the admissible region for means and standard deviations of intertemporal marginal rates of substitution of consumers. Their approach (1) is nonparametric and applies to a rich class of models of dynamic economics; (2) characterizes the duality between the mean-standard deviation frontier for intertemporal marginal rates of substitution and the familiar mean-standard deviation frontier for asset returns; and (3) exploits the restriction that intertemporal marginal rates of substitution are positive random variables. The region provides a convenient summary of the sense in which asset market data are anomalous from the vantage point of intertemporal asset pricing theory.

We argue that the empirical evidence against the capital asset pricing model (CAPM) based on stock returns does not invalidate its use for estimating the cost of capital for projects in making capital budgeting decisions. Because stocks are backed not only by projects in place, but also by the options to modify current projects and undertake new ones, the expected returns on stocks need not satisfy the CAPM even when expected returns of projects do. We provide empirical support for our arguments by developing a method for estimating firms' project CAPM betas and project returns. Our findings justify the continued use of the CAPM by firms in spite of the mounting evidence against it based on the cross section of stock returns.

V. V. Chari, Ravi Jagannathan, Larry Jones; Price Stability and Futures Trading in Commodities*, The Quarterly Journal of Economics, Volume 105, Issue 2, 1

We document a seasonal pattern in stock returns around quarterly earnings announcement dates: small firms show large positive abnormal returns and a sizable increase in the variability of returns around these dates. Only part of the large abnormal returns can be accounted for by the tendency of firms with good news to announce early. Large firms show no abnormal returns around announcement dates and a much smaller increase in variability.