Is Hard and Soft Information Substitutable? Evidence from the Lockdowns

35 Pages Posted: 11 Feb 2021

See all articles by Jennie Bai

Jennie Bai

Georgetown University - Department of Finance; National Bureau of Economic Research (NBER)

Massimo Massa

INSEAD - Finance

Date Written: February 1, 2021


We study the degree of information substitutability in the financial markets; in particular, we focus on the COVID pandemic that has made people’s interaction far more difficult. Exploiting both the cross-sectional and time-series variations induced by lockdowns in the United States, we investigate how the difficulty/inability to use soft information has prompted a switch to hard information, and further the implication of such a switch on fund performance. We show that lockdowns reduce fund investment in proximate stocks and generate a portfolio rebalancing towards distant stocks. The rebalancing has negative implications on fund performance by reducing fund raw (excess) return of 0.76% (0.29%) per month during the lockdown, suggesting that soft and hard information is not easily substitutable. Soft information originates with geographic proximity and human interactions, mostly in caf´e, restaurants, bars, and fitness centers. The most affected funds are those more likely to rely on soft information which use a larger management team or sub-advisors. Our findings not only document the nature of soft information and its degree of substitutability with hard information, but also show that soft information requires “person-to-person” meetings and thus diminishes when such meetings are discontinued or hampered. This suggests that the “New World” based on Zoom/Skype/Team and remote connections will have direct negative implications in terms of the ability of collecting soft information and therefore to affect fund performance.

JEL Classification: G12, G2, G3

Suggested Citation

Bai, Jennie and Massa, Massimo, Is Hard and Soft Information Substitutable? Evidence from the Lockdowns (February 1, 2021). CEPR Discussion Paper No. DP15744, Available at SSRN:

Jennie Bai (Contact Author)

Georgetown University - Department of Finance ( email )

3700 O Street, NW
Washington, DC 20057
United States


National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Massimo Massa

INSEAD - Finance ( email )

Boulevard de Constance
F-77305 Fontainebleau Cedex
+33 1 6072 4481 (Phone)
+33 1 6072 4045 (Fax)

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