Jessica Wachter

Education

Phd, Harvard University, 2000; AB, Harvard College, 1996

Academic Positions Held

Wharton: 2003present. Previous appointments: Stern School of Business, New York University

Jessica Wachter serves on the board of directors of the American Finance Association.  She is currently an associate editor at the Review of Financial Studies, the Journal of Economic Theory, and Mathematics and Financial Economics. She has been a Research Associate of the National Bureau of Economic Research since 2008.  Her research interests include asset pricing models that incorporate rare events, models of portfolio allocation, and financial econometrics.

Jerry Tsai and Jessica Wachter (Working), Pricing longlived securities in dynamic endowment economies.

Mete Kilic and Jessica Wachter (Working), Risk, unemployment, and the stock market: A rareeventbased explanation of labor market volatility.

Abstract: What is the driving force behind the cyclical behavior of unemployment and vacancies? What is the relation between jobcreation incentives of firms and stock market valuations? We answer these questions in a model with  timevarying risk, modeled as a small and variable probability of an economic disaster. A high probability implies greater risk and lower future growth, lowering the incentives of firms to invest in hiring.  During periods of high risk, stock market valuations are low and  unemployment rises.  The model thus explains volatility in equity and labor markets, and the relation between the two.  

Joao F. Gomes, Marco Grotteria, Jessica Wachter (Working), Cyclical Dispersion in Expected Defaults.

Sang Byung Seo and Jessica Wachter (Working), Do rare events explain CDX tranche spreads?.

Sang Byung Seo and Jessica Wachter (Working), Option Prices in a Model with Stochastic Disaster Risk.

Abstract: Contrary to wellknown asset pricing models, volatilities implied by equity index options exceed realized stock market volatility and exhibit a pattern known as the volatility skew.  We explain both facts using a model that can also account for the mean and volatility of  equity returns.   Our model assumes a small risk of economic disaster that is calibrated based on  international data on large consumption declines.   We allow the disaster probability to be stochastic, which turns out to be crucial to the model's ability both to match equity volatility and to reconcile option prices with macroeconomic data on disasters.    

Efstathios Avdis and Jessica Wachter (Forthcoming), Maximum likelihood estimation of the equity premium.

Abstract: The equity premium, namely the expected return on the aggregate stock market less the government bill rate, is of central importance to the portfolio allocation of individuals, to the investment decisions of firms, and to model calibration and testing. This quantity is usually estimated from the sample average excess return. We propose an alternative esti mator, based on maximum likelihood, that takes into account informa tion contained in dividends and prices. Applied to the postwar sample, our method leads to an economically significant reduction from 6.4% to 5.1%. Simulation results show that our method produces more reliable estimates under a wide range of specifications.   

Jerry Tsai and Jessica Wachter (2016), Rare booms and disasters in a multisector endowment economy, Review of Financial Studies , 29 (5), pp. 11131169.

Jerry Tsai and Jessica Wachter (2015), Disaster risk and its implications for asset pricing, Annual Review of Financial Economics, 7, pp. 219252.

Jerry Tsai and Jessica Wachter, Disaster risk and asset pricing in VOX EU,June, 11, 2015.

Jessica Wachter and Missaka Warusawitharana (2015), What is the chance that the equity premium varies over time? Evidence from regressions on the dividendprice ratio, Journal of Econometrics, 186, pp. 7493.

Abstract: We examine the evidence on excess stock return predictability in a Bayesian setting in which the investor faces uncertainty about both the existence and strength of predictability. When we apply our methods to the dividendprice ratio, we find that even investors who are quite skeptical about the existence of predictability sharply modify their views in favor of predictability when confronted by the historical time series of returns and predictor variables. Correctly taking into account the stochastic properties of the regressor has a dramatic impact on inference, particularly over the 20002005 period.   

Past Courses

FNCE100 CORPORATE FINANCE

This course provides an introduction to the theory, the methods, and the concerns of corporate finance. The concepts developed in FNCE 100 form the foundation for all elective finance courses. The main topics include: 1) the time value of money and capital budgeting techniques; 2) uncertainty and the tradeoff between risk and return; 3) security market efficiency; 4) optimal capital structure, and 5) dividend policy decisions. During the fall semester there are honors sections of FNCE 100 offered. The seats in the honors sections are awarded through an application process. Please go to https://fnce.wharton.upenn.edu/programs/courseapplications/ for additional information.

FNCE911 FINANCIAL ECONOMICS

The objective of this course is to undertake a rigorous study of the theoretical foundations of modern financial economics. The course will cover the central themes of modern finance including individual investment decisions under uncertainty, stochastic dominance, mean variance theory, capital market equilibrium and asset valuation, arbitrage pricing theory, option pricing, and incomplete markets, and the potential application of these themes. Upon completion of this course, students should acquire a clear understanding of the major theoretical results concerning individuals' consumption and portfolio decisions under uncertainty and their implications for the valuation of securities.

Knowledge @ Wharton

• How Disaster Risk Is Priced into the Stock Market, Knowledge @ Wharton 06/29/2015
• A Premature Eulogy for Public Companies?, Knowledge @ Wharton 10/10/2012
• Apple Turnover, Knowledge @ Wharton 04/18/2012
• U, V or W: What Kind of Recovery Can We Expect, and When?, Knowledge @ Wharton 02/03/2010
• Can Fund Managers Pick Good Stocks? Yes, They Can, But…, Knowledge @ Wharton 02/23/2005
• A Fresh Look At Mutual Funds’ Performance Data, Knowledge @ Wharton 03/28/2001
• The 6% Factor: Which Fund Managers Will Outperform Index Funds?, Knowledge @ Wharton 03/21/2000