We construct a no-arbitrage term structure model with jumps in the entire state vector at deterministic times but of random magnitudes. Jump risk premia are allowed for. We show that the model implies a closed-form representation of yields as a time-inhomogeneous affine function of the state...

We study the effects of belief dispersion on stock trading volume. Unlike most of the existing work on the subject, our paper focuses on how household investors' disagreements on macroeconomic variables influence market-wide trading volume. We show that greater belief dispersion among household...

We document a robust positive relationship between the belief dispersion about macroeconomic conditions among household investors and the stock market trading volume, using more than 30 years of household survey data and a novel approach to measuring belief dispersions. Notably, such a...

We study the fragility of discretionary liquidity provision by major financial intermediaries during systemic events. The laboratory of our study is the recent collapse of the auction rate securities (ARS) market. Using a comprehensive dataset constructed from auction reports and intraday...

We investigate the uncertainty dynamics surrounding extreme weather events through the lens of option and stock markets by identifying market responses to the uncertainty regarding both potential hurricane landfall and subsequent economic impact. Stock options on firms with establishments...

Stylized facts on U.S. output and interest rates have so far proved hard to match with DSGE models. But model predictions hinge on the joint specification of economic structure and a set of driving processes. In a model, different shocks often induce different comovements, such that the overall...

No, not really, since spectral estimators suffer from small sample and misspecification biases just as VARs do. Spectral estimators are no panacea for implementing long-run restrictions. In addition, when combining VAR coefficients with non-parametric estimates of the spectral density, care...

This paper describes the E-Newton and E-QNewton algorithms for solving rational expectations (RE) models. Both algorithms treat a model's RE terms as exogenous variables whose values are iteratively updated until they (hopefully) satisfy the RE requirement. In E-Newton, the updates are based on...

We construct new estimates of potential output and the output gap using a multivariate approach that allows for an explicit role for measurement errors in the decomposition of real output. Because we include data on hours, output, employment, and the labor force, we are able to decompose our...

This paper advances the theory and methodology of signal extraction by introducing asymptotic and finite sample formulas for optimal estimators of signals in nonstationary multivariate time series. Previous literature has considered only univariate or stationary models. However, in current...