We develop a model of pandemic risk management and firm valuation. We introduce aggregate transmission shocks into an epidemic model and link valuations to infections via an asset-pricing framework with vaccines. Infections lower earnings growth but firms can mitigate damages. We estimate a...

This paper studies the pricing of volatility risk using the first-order conditions of a long-term equity investor who is content to hold the aggregate equity market rather than tilting towards value stocks and other equity portfolios that are attractive to short-term investors. We show that a...

We develop a new methodology that allows conditional performance to be a function of information available at the start of the performance period but does not make assumptions about the behavior of the conditional betas. We use econometric techniques developed by Lynch and Wachter (2011) that...

quot;Risk managementquot; in securities markets refers to the oversight of portfolio managers and professional traders when they trade on behalf of investors in security markets. Monitoring of their trading performance, profit and loss, and risk-taking behavior, is measured by principals using...

Existing literature continues to be unable to offer a convincing explanation for the volatility of the stochastic discount factor in real world data. Our work provides such an explanation. We do not rely on frictions, market in completeness or transactions costs of any kind. Instead, we modify a...

We extend Kyle's (1985) model of insider trading to the case where liquidity provided by noise traders follows a general stochastic process. Even though the level of noise trading volatility is observable, in equilibrium, measured price impact is stochastic. If noise trading volatility is...

We propose a novel method to estimate dynamic equilibrium models with stochastic volatility. First, we characterize the properties of the solution to this class of models. Second, we take advantage of the results about the structure of the solution to build a sequential Monte Carlo algorithm to...

The long term discount rate is critically dependent upon projections of future growth rates that are fuzzier in proportion to the remoteness of the time horizon. This paper models such increasing fuzziness as an evolving hidden-state stochastic process. The underlying trend growth rate is an...

We develop a new parametric estimation procedure for option panels observed with error which relies on asymptotic approximations assuming an ever increasing set of observed option prices in the moneyness- maturity (cross-sectional) dimension, but with a fixed time span. We develop consistent...