How Does Household Portfolio Diversification Vary with Financial Literacy and Financial Advice?

• DOI: http://doi.org/10.1111/jofi.12231
• Author: HANS‐MARTIN VON GAUDECKER
• Published date: 01 April 2015
• Date: 01 April 2015

THE JOURNAL OF FINANCE •VOL. LXX, NO. 2 •APRIL 2015

How Does Household Portfolio Diversification

Vary with Financial Literacy and Financial

Advice?

HANS-MARTIN VON GAUDECKER∗

ABSTRACT

Household investment mistakes are an important concern for researchers and poli-

cymakers alike. Portfolio underdiversification ranks among those mistakes that are

potentially most costly.However, its roots and empirical importance are poorly under-

stood. I estimate quantitatively meaningful diversification statistics and investigate

their relationship with key variables. Nearly all households that score high on finan-

cial literacy or rely on professionals or private contacts for advice achieve reasonable

investment outcomes. Compared to these groups, households with below-median fi-

nancial literacy that trust their own decision-making capabilities lose an expected

50 bps on average. All group differences stem from the top of the loss distribution.

ECONOMIC THEORY PREDICTS THAT households will hold their risky assets in the

form of a well-diversified portfolio. The extent to which this prediction holds

true has important implications for the regulation of consumer financial prod-

ucts, the design of retirement savings plans, and the distribution of consumer

well-being in general. It is especially significant to know the patterns of under-

diversification. If only those households that are particularly savvy in financial

matters invested their retirement wealth in a few highly correlated stocks,

most policymakers would conclude that this was a rational choice driven, for

example, by superior information (van Nieuwerburgh and Veldkamp (2010)). If

only the least financially literate households were doing the same thing, how-

ever, policy makers would likely conclude that these households were simply

making poor decisions. In a similar vein, a regulator’s strategy also depends on

∗Von Gaudecker is with Universit¨

at Bonn, Department of Economics. Several of the data ma-

nipulations and preliminary estimations were performed by Mark Prins as part of his MSc Thesis

at VU University Amsterdam and in a subsequent research assistantship to the author. Special

thanks to him for an excellent programming job and many fruitful discussions. Funding from

Netspar is gratefully acknowledged. I appreciate helpful comments received from seminar and

conference participants at the Universities of Frankfurt and Bonn, the 2nd SAVE conference in

Deidesheim, the 2011 Netspar Pension Workshop in Amsterdam, and the Federal Reserve Bank of

Chicago; in particular, TabeaBucher-Koenen, Armin Falk, Dimitris Georgarakos, Michael Halias-

sos, Rainer Haselmann, Olivia Mitchell, Karl Scholz, Stephen Zeldes, and Michael Ziegelmeyer.

Furthermore, I would like to thank CentERdata for help on numerous data questions; Mauro Mas-

trogiacomo for sharing code to prepare the DHS data; and Maarten van Rooij, Annamaria Lusardi,

and Rob Alessie for providing the data and code used to construct the financial literacy scores in

van Rooij, Lusardi, and Alessie (2011).

DOI: 10.1111/jofi.12231

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490 The Journal of Finance R

whether the underdiversified households rely on professional financial advisers

or make their investment choices autonomously.

Little guidance has come from empirical studies, which can be roughly di-

vided into two strands. One strand studies detailed diversification properties

using administrative data from Scandinavian countries (Calvet, Campbell, and

Sodini (2007,2009), Grinblatt, Keloharju, and Linnainmaa (2011)). These stud-

ies show that—when one accounts for mutual funds on top of stock portfolios—

most households reach reasonable investment outcomes, but some may expect

a very low rate of return given the amount of risk they take. However, the

lack of data on financial literacy and financial advice prevents one from go-

ing beyond unconditional distributions of diversification losses with respect

to the questions raised above. A second strand employs simple measures of

portfolio diversification drawn from household surveys (Bilias, Georgarakos,

and Haliassos (2009), Graham, Harvey, and Huang (2009), Guiso and Jappelli

(2009), Kimball and Shumway (2010)). In these studies, the data issues are

reversed: while covariates are abundant, the diversification properties do not

permit a quantitative analysis.

In this paper, I combine the strengths of both approaches and calculate

quantitatively meaningful diversification measures for the respondents to a

Dutch household survey. In addition to an abundance of background variables,

the survey includes detailed information on both financial literacy and the

most important source of financial advice. In my analysis, I employ the return

loss (Calvet, Campbell, and Sodini (2007)) as the diversification measure. The

return loss is the difference between the maximum expected return attainable

at a given standard deviation and the actual expected return for a particular

portfolio. The unconditional distribution of the annual return loss reveals that

it is limited to half a percentage point or less up to the fourth quintile. In its

top quintile, it averages 1.8 percentage points, which is large and comparable

to previous results.

My main analyses uncover an important interaction of financial literacy and

financial advice in the decision-making process. The return loss of households

that seek advice either in their private network or from professionals does not

vary with financial literacy. Among households making autonomous decisions,

the distribution of the return loss looks very similar only if they are endowed

with the maximum level of financial literacy. In this group, a decrease in finan-

cial literacy of one standard deviation is associated with an increase in return

loss by 0.7 percentage points on average. Using quantile regressions I show

that these effects stem entirely from very large effects at the upper end of the

return loss distribution.

Intrigued by the fact that the outcomes of households relying on profes-

sional financial advisers are so similar to those of households relying on rec-

ommendations from within their private network, I further investigate the

differences between these two groups. The use of professional financial ad-

vice is associated with an increase in fees paid across the portfolio of 0.3

percentage points. However, the higher fees do not translate into a significantly

higher return loss.