Document Type
Working Paper
Date of this Version
6-2015
Abstract
We explore whether investors who are more financially knowledgeable earn more on their retirement plan investments compared to their less sophisticated counterparts, using a unique new dataset linking administrative data on investment performance and financial knowledge. Results show that the most financially knowledgeable investors: (a) held 18 percentage points more stock than their least knowledgeable counterparts; (b) could anticipate earning 8 basis points per month more in excess returns; (c) had 40% higher portfolio volatility; and (d) held portfolios with about 38% less idiosyncratic risk, as compared to their least savvy counterparts. Our results are qualitatively similar after controlling on observables as well as modeling sample selection. We also examine portfolio changes to assess the potential impact of the financial literacy intervention. Controlling on other factors, those who elected to take the Financial Literacy survey boosted their equity allocations by 66 basis points and their monthly expected excess returns rose by 2.3 basis points; no significant difference in volatility or nonsystematic risk was detected before versus after the survey. While these findings relate to only one firm, we anticipate that they may spur other efforts to enhance financial knowledge in the workplace.
Keywords
401(k), financial knowledge, investments
Working Paper Number
WP2015-10
Copyright/Permission Statement
All findings, interpretations, and conclusions of this paper represent the views of the authors and not those of the Wharton School or the Pension Research Council. © 2015 Pension Research Council of the Wharton School of the University of Pennsylvania. All rights reserved.
Acknowledgements
Research support for the work reported herein was provided by the Pension Research Council/Boettner Center at the Wharton School of the University of Pennsylvania, as well as the Office of Employee Benefits at the Federal Reserve System that provided the data for the study and partial funding for the project. Without implicating them, we are grateful for useful comments provided by William Clark, Pierre-Carl Michaud, Ryan Peters, Petra Todd, Ning Tang, and Steven Utkus. We are also appreciative of excellent programming assistance from Yong Yu.
Date Posted: 26 June 2019