Predictable Downturns

45 Pages Posted: 21 Jul 2018

See all articles by Carter Davis

Carter Davis

University of Chicago Booth School of Business

Date Written: June 28, 2018


Eugene Fama stated in his Nobel Prize lecture that “there is no statistically reliable evidence that expected stock returns are sometimes negative” (2013). However, various theoretical models such as Barberis et al. (2015) and Barlevy and Veronesi (2003) imply that expected stock returns are sometimes negative. This paper provides evidence that expected excess aggregate stock market returns are sometimes negative, and that portfolios composed of the most liquid stocks have predictable downturns as well. This paper presents a forecasting model that relies exclusively on ex-ante information to predict stock market downturns only when the day-prior confidence of a downturn is relatively high, and shows that the average excess return on days which are predicted to be downturns by the forecasting model is -13.9 basis points. Volatility and classic factor return variables alone are sufficient to predict downturns in the sample and are the most powerful downturn predictors. A market timing portfolio using these ex-ante predictions generates a risk-adjusted return of 3.5 basis points per day, annualized to an average 8.8% risk-adjusted return.

Keywords: negative expected returns, predictable downturns, asset pricing, market timing, predictability, negative returns

JEL Classification: G11, G12, G14

Suggested Citation

Davis, Carter, Predictable Downturns (June 28, 2018). Available at SSRN: or

Carter Davis (Contact Author)

University of Chicago Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

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