Measuring the value of labor-market hires for stock prices, be it underwriters when firms go public (IPOs) or chief executive officers (CEOs), is difficult due to selection. Opaque firms with higher costs of capital benefit more from prestigious underwriters, while productive firms benefit more...

We estimate the response of stock prices to exogenous monetary policy shocks using a vector-autoregressive model with time-varying parameters. Our evidence points to protracted episodes in which, after a short-run decline, stock prices increase persistently in response to an exogenous tightening...

The extant literature predicts market returns with "simple" models that use only a few parameters. Contrary to conventional wisdom, we theoretically prove that simple models severely understate return predictability compared to "complex" models in which the number of parameters exceeds the...

This paper examines the time series properties of the price of a risky asset implied by a model in which competitive traders are heterogeneously informed about the underlying sources of uncertainty in the economy.Traders do not observe the shocks in the period they occur. However, traders are...

Volatility tests are an alternative to regression tests for evaluating the joint null hypothesis of market efficiency and risk neutrality. Acomparison of the power of the two kinds of tests depends on what the alternative hypothesis is taken to be. By considering tests based on conditional...

We show that outcomes (parameter estimates and R-squareds) of regressions of prices on fundamentals allow us to recover exact measures of the ability of asset prices to aggregate dispersed information. Formally, we show how to recover absolute and relative price informativeness in dynamic...

In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions...

We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure, where an option price is inverted into the unobservable volatility state, to an approximate likelihood...

We develop a jackknife estimator for the conditional variance of a minimum-tracking- error-variance portfolio constructed using estimated covariances. We empirically evaluate the performance of our estimator using an optimal portfolio of 200 stocks that has the lowest tracking error with respect...

Recent research based on variance ratios and multiperiod-return autocorrelations concludes that the stock market exhibits mean reversion in the sense that a return in excess of the average tends to be followed by partially offsetting returns in the opposite direction. Dividing history into...