Text-based Fiscal News and the Cross-section of Stock Returns

68 Pages Posted: 27 Dec 2022 Last revised: 30 May 2023

See all articles by My T. Nguyen

My T. Nguyen

Washington University in St Louis, John M. Olin Business School

Date Written: December 24, 2022

Abstract

Using 9,524 speeches by U.S. presidents over the last century, this paper implements textual analysis to construct long time-series index for fiscal policy. The Fiscal News Index is a strong predictor in the cross-section of stock returns. Investors demand higher expected returns for holding stocks with high exposure to Fiscal News Index. The pricing implications of the Fiscal News Index are mainly through the discount rate news channel. Empirical results suggest that the Fiscal News Index outperforms other business cycle indicators in terms of pricing the cross-section of stock returns. The pricing implication of the Fiscal News Index is also reflected in currency returns.

Keywords: fiscal news, cross-sectional stock returns, textual analysis, big data

JEL Classification: G18, G12

Suggested Citation

T. Nguyen, My, Text-based Fiscal News and the Cross-section of Stock Returns (December 24, 2022). Available at SSRN: https://ssrn.com/abstract=4311379 or http://dx.doi.org/10.2139/ssrn.4311379

My T. Nguyen (Contact Author)

Washington University in St Louis, John M. Olin Business School ( email )

Room 274 Simon Hall
Washington University in St. Louis
St. Louis, MO 63130
United States
6188183228 (Phone)

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