What Makes Investors Optimistic? What Makes Them Afraid?

40 Pages·2011·0.36 MB·English

What Makes Investors Optimistic? What Makes Them Afraid?

Arvid O. I. Hoffmann*
Maastricht University and Netspar
Thomas Post
Maastricht University and Netspar

This version: March 30, 2012

First version: December 10, 2011

Abstract: Based on a combination of monthly survey data and matching trading records, we identify the drivers
of individual investors’ optimism, as expressed by their return expectations, and fear, as expressed by their risk
tolerance and risk perceptions. We find that past returns positively impact investors’ return expectations and risk
tolerance, and negatively impact their risk perceptions. The risk associated with these past returns, however,
does not effectuate changes in investors’ return expectations, risk tolerance, or risk perception. The tendency to
look primarily at past returns is especially pronounced among less experienced and sophisticated, and more
overconfident, investors. These investors seem to find it difficult to evaluate and interpret portfolio risk, and use
portfolio returns as a more easily available and salient performance metric.

JEL Classification: D14, D81, G01, G11, G24
Keywords: Individual Investors, Return Expectation, Risk Tolerance, Risk Perception

* Corresponding author: Arvid O. I. Hoffmann, Maastricht University, School of Business and Economics, Department of
Finance, P.O. Box 616, 6200 MD, The Netherlands. Tel.: [phone]. E-mail: [email protected].

This research would not have been possible without the help of a large brokerage firm. The authors thank this broker and its
employees. For their comments on earlier drafts of this paper, the authors thank Brad Barber and seminar participants at the
University of New South Wales, Maastricht University, and University of Amsterdam.
1. Introduction
Individual investor behavior influences asset prices (Lee, Shleifer, and Thaler 1991;
Hirshleifer 2001; Kumar and Lee 2006), return volatility (Foucault, Sraer, and Thesmar
2011), and even the macro economy (Korniotis and Kumar 2011a). Central determinants of
investor behavior, such as choices of when and how to invest, are return expectations, risk
tolerance, and risk perceptions (Nosic and Weber 2010; Dominitz and Manski 2011).
Changes in these variables drive key aspects of trading and risk-taking behavior, such as
trading frequency, turnover, and the buy-sell ratio (Hoffmann, Post, and Pennings 2010).
Debated, however, is how individual investors form their return expectations, risk tolerance,
and risk perceptions. In particular, the evidence on the directional impact that individual-level
risk and return experiences have on the formation process of these variables is mixed.
Using a combination of monthly survey data and matching brokerage records, we
resolve this controversy in the existing literature. We provide a comprehensive study of the
determinants of changes in individual investors’ optimism, as expressed by their return
expectations, and fear, as expressed by their risk tolerance and risk perceptions. The results
show that in a real decision context past returns are a powerful driver of investor optimism as
well as fear: past returns positively impact return expectations and risk tolerance, and
negatively impact risk perceptions. The risk associated with these past returns, however, does
not effectuate changes in investors’ return expectations, risk tolerance, or risk perception. The
tendency to look primarily at past returns is especially pronounced among less experienced
and sophisticated, and more overconfident, investors. These investors seem to find it difficult
to evaluate and interpret portfolio risk, and use portfolio returns as a more easily available
and salient performance metric.
This paper makes several contributions to the literature. First, we examine the impact of
past portfolio returns as well as past portfolio risk on subsequent changes in investors’ return
2
expectations, risk tolerance, and risk perceptions. Much prior work focuses on the impact of
past returns (Dominitz and Manski 2011; Hurd, van Rooij, and Winter 2011), but does not
study the effect of the riskiness of these returns. Yet, according to standard finance theory,
risk should be as important as returns in investor decision making (Markowitz 1952; Sharpe
1964). Second, prior research typically studies return expectations, risk tolerance, and risk
perceptions in isolation. For example, Dominitz and Manski (2011) and Hurd, van Rooij, and
Winter (2011) study the impact of past returns on changes in return expectations. Glaser and
Weber (2005) examine the effect of past returns on changes in risk perceptions. Malmendier
and Nagel (2011) show the influence of past returns on changes in risk tolerance. In contrast,
we study return expectations, risk tolerance, and risk perceptions together. Doing so is
important, as these variables affect different aspects of investor trading and risk-taking
behavior (Hoffmann, Post, and Pennings 2010). Third, we study the impact of individual
investors’ personally experienced returns and risks. Previous research focuses on how
aggregate market returns influence return expectations, risk tolerance, and risk perceptions.
In so doing so, however, these studies do not examine the effects of the underlying
heterogeneity in investors’ individual-level risk and return experience. Fourth, we study how
investors’ return expectations, risk tolerance, and risk perceptions adapt in a real investment
decision context as opposed to examining these variables within a general sample of
household survey or experiment participants who may or may not invest in the stock market.
The remainder of this paper is organized as follows. Section 2 presents related literature
and develops the hypotheses. Section 3 describes the data. Section 4 sets out descriptive
results. Section 5 tests the hypotheses. Section 6 presents robustness checks and evaluates
alternative explanations. Section 7 concludes the paper and discusses its implications.

3
2. Related Literature and Hypotheses
In this section we review the related literature we use to develop hypotheses regarding the
expected impact of past returns and past risk on subsequent changes in investors’ optimism,
as expressed by their return expectations, and fear, as expressed by their risk tolerance and
risk perceptions.

2.1 Investor Optimism
Research in behavioral finance demonstrates a persistent effect of investor psychology on
trading and risk-taking behavior (Barber and Odean 2001; Bailey, Kumar, and Ng 2011). In
particular, previous work in cognitive psychology (Gilovich, Vallone, and Tversky 1985) and
studies on how individuals form forecasts (De Bondt 1993) suggest that investors’ past
returns can impact their future expectations in two major ways. On the one hand, individual
investors might be susceptible to the gambler’s fallacy effect, that is, misinterpreting the law
of averages (Tversky and Kahneman 1971). Because of representativeness (Kahneman and
Tversky 1972), individuals belief that the law of large numbers applies to small as well as to
large samples. In an investment context, this implies that after a run-up in stock prices,
investors tend to expect below-average returns (Shefrin 2002). On the other hand, when
making investment choices, individual investors often bet on what they perceive as trends in
prices and believe in “hot” (“cold”) hands after observing positive (negative) outcomes, that
is, they expect “trends” to continue (Gilovich, Vallone, and Tversky 1985; De Bondt 1993;
Johnson, Tellis, and Macinnis 2005). Accordingly, we formulate the following competing
hypotheses about the impact of past returns on investors’ subsequent optimism as expressed
by their return expectations:

4
H : Past returns are negatively related to investors’ subsequent return expectations.
1a
H : Past returns are positively related to investors’ subsequent return expectations.
1b

Regarding the impact of individual investors’ past risk on their return expectations, we build
on and extend prior literature on the representativeness and affect heuristics (Kahneman and
Tversky 1972; Finucane et al. 2000). Shefrin (2001), for example, argues that because of
individuals’ reliance on representativeness, they expect high returns from safe stocks and low
returns from risky stocks. In particular, investors judge that “good” stocks are those issued by
“good” companies and associate these with both safety and high future returns. This tendency
to rely on representativeness when making investment decisions causes investors to use the
affective associations they have of a company when forming expectations about the risk-
return attributes of this company’s stock (Finucane, Alhakami, Slovic, and Johnson 2000;
Statman, Fisher, and Anginer 2008). The resulting cross-sectional negative correlation
between investors’ expected risk and returns is robust, as confirmed by Ganzach (2000). We
extend this relationship to an intertemporal setting. That is, to draw inferences about the
expected returns of various assets, investors are expected to use available information on
those assets’ past risk, just like they use past return information to form their expectations
about future returns. We develop the following hypothesis about the impact of past risk on
investors’ subsequent optimism as expressed by their return expectations:

H : Past risk is negatively related to investors’ subsequent return expectations.
2

2.2 Investor Fear
We define investor fear as consisting of two components: risk tolerance and risk perceptions.
That is, fear is comprised of an investor’s general predisposition toward taking risk (risk
5
tolerance) and his or her current interpretation of the riskiness of the stock market (risk
perception). We first develop hypotheses regarding the impact of past returns on risk
tolerance and risk perceptions and subsequently formulate hypotheses regarding the impact of
past risk.
Considering the impact of past returns on investors’ subsequent risk tolerance, we build
on the house-money effect as established by Thaler and Johnson (1990). Accordingly, we
expect individuals to become more risk tolerant after experiencing a gain (see also Barberis,
Huang, and Santos 2001).

H : Past returns are positively related to investors’ subsequent risk tolerance.
3

Concerning the impact of past returns on investors’ subsequent risk perceptions, there is
evidence in support of a negative as well as a positive relationship. In an experimental
setting, De Bondt (1993) finds that although individuals generally tend to expect price trends
to continue, their risk perceptions depend on prior performance in an opposite manner. De
Bondt notes that “the mere fact that a stock goes up in price increases its ‘downward
potential’” (1993: 369). Thus, risk perceptions can be expected to increase after investors
experience positive returns. However, Shefrin’s (2001) work on the role of representativeness
in investors’ cross-sectional assessments of the riskiness of stocks with good or bad returns
suggests a negative relationship between past returns and subsequent risk perceptions. That
is, when investors have experienced favorable returns, they apparently have bought “good”
stocks, which, in their opinion, are also safe stocks. Accordingly, we formulate the following
competing hypotheses about the impact of past returns on investors’ subsequent fear as
expressed by their risk perceptions:

6
H : Past returns are positively related to investors’ subsequent risk perceptions.
4a
H : Past returns are negatively related to investors’ subsequent risk perceptions.
4b

Regarding the impact of past risk on investors’ subsequent risk tolerance, Kahneman and
Lovallo (1993), find that individuals often expose themselves to risk because they misjudge
the odds. Thus, being confronted with the outcomes of previous risky choices in the form of
realized past risk should affect investors’ risk tolerance. It is unclear, however, in which
direction this effect will go. For some investors, awareness of the amount of risk they have
taken reaffirms their true willingness to take risks, while for others, the level of realized risk
comes as a surprise, increases fear, and leads them to reduce their risk tolerance. Hence, we
formulate the following unidirectional hypothesis regarding the impact of realized past risk
on investors’ subsequent fear as expressed by their risk tolerance:

H : Past risk is related to investors’ subsequent risk tolerance.
5

Considering the influence of past risk on investors’ subsequent risk perceptions, we expect a
positive relationship to the extent that individuals believe that market trends will continue, as
do a majority of households when asked about aggregate market returns (cf. Dominitz and
Manski 2011). Hence, we formulate the following hypothesis about the impact of past risk on
investors’ subsequent fear as expressed by their risk perceptions:

H : Past risk is positively related to investors’ subsequent risk perceptions.
6

7
3. Data
The data consist of the brokerage records of 1,510 clients of the largest discount broker in the
Netherlands, along with matching monthly survey data collected for these investors from
April 2008 through March 2009. Using discount brokerage data has two advantages. First,
discount brokerage is the dominant channel through which both U.S. and Dutch individuals
invest in the stock market (Barber and Odean 2000; Bauer, Cosemans, and Eichholtz 2009).
Second, as discount brokers do not offer advice, the investment transactions and survey
responses reflect investors’ own decisions and opinions. As the sample period corresponds to
a time of high market volatility, there is substantial variation in investors’ optimism and fear
as well as in their portfolio returns and risk, which is beneficial for estimating the effect of
investors’ past portfolio risk and returns on the formation of optimism and fear. Following
Hoffmann, Post, and Pennings (HPP) (2010), who use the same data set, we exclude accounts
of minors and of those with an average portfolio value of less than €250. To exclude
professional traders, we discard accounts in the top 1% of annual trading volume, transaction
frequency, or turnover distributions, leaving 1,376 accounts.

3.1 Brokerage Records
Brokerage records are available for investors who completed at least one survey during the
sample period. A “record” consists of an identification number, a transaction date and time, a
buy/sell indicator, the type of asset traded, the gross transaction value, and transaction
commissions. The records also contain information on investors’ daily account balances,
demographics such as age and gender, and their six-digit postal code. Based on this postal
code, which is unique to each street (or parts of a street) in the Netherlands, and data
retrieved from Statistics Netherlands (Central Bureau of Statistics), we assign income and
8
residential house value to each investor.1 Table 1 defines all variables. Table 2 shows
descriptive statistics of all brokerage accounts available, and those for the subset of accounts
belonging to clients who completed the survey in each particular month of the sample period.

[Tables 1 and 2 here]

A comparison with samples used in other studies of individual investor behavior in the
United States (Barber and Odean 2000), Germany (Dorn and Huberman 2005), and the
Netherlands (Bauer, Cosemans, and Eichholtz 2009) shows that this study’s sample of
investors is similar in terms of age and gender, portfolio size, and turnover. Moreover, the
account values comprise the major share of investors’ total self-managed wealth. Due to the
Dutch tax code, tax-loss-selling motivated trading does not affect the results.

3.2 Survey Design and Data Collection
At the end of each month between April 2008 and March 2009, we conducted an online
survey among a panel of the broker’s clients. To develop the panel, an email invitation was
sent to 20,000 randomly selected clients in March 2008. Six months later, a re-invitation was
sent to these clients to maintain a sufficient response rate. The response rate of 4.28% (for
April 2008) is in line with comparable large-scale surveys (cf. Dorn and Sengmueller 2009).
A possible concern is that monthly variation of non-response (Table 2) might not be random.
For example, investment success could be related to propensity to respond. Robustness
checks in HPP (2010) show that the sample is not subject to non-random response problems
and, in addition, indicate that the results are unaffected by the timing of responses.

1 Home ownership rates in the Netherlands are high (67.5%, as of 2008 (Eurostat 2011), as well as skewed
toward wealthier households (Rouwendal 2007). Thus, it is likely, that the house values assigned correspond
closely to the value of the houses actually owned by the investors in the sample.
9
The survey elicited information on investors’ expectations of stock-market returns, their
risk tolerance, and their risk perceptions for each upcoming month (see Table 3). We use
simple subjective measures, as they typically have higher explanatory power for individuals’
financial decision-making than do more complex types of measurement, which are often
misunderstood by respondents (Wärneryd 1996; Kapteyn and Teppa 2011). Return
expectations measure investors’ optimism about the returns of their investment portfolio and
are measured as in Weber, Weber, and Nosic (2010). Risk tolerance reflects investors’
general predisposition toward financial risk (like or dislike of risky situations) and is
measured following Pennings and Smidts (2000). Risk perception reflects investors’
interpretation of the riskiness of the stock market and is measured according to Pennings and
Wansink (2004).
To ensure a reliable measurement instrument, we used multiple items per variable,
included these items in the questionnaire in a random order (Netemeyer, Bearden, and
Sharma 2003), and used a mixture of regular and reverse-scored items (Nunnally and
Bernstein 1994). Reliability is high; Cronbach’s alpha is between 0.71 and 0.89 for the
different survey variables (Hair et al. 1998). The survey variables are computed by equally
weighting and averaging their respective item scores. Such variables perform at least as well
as those using “optimally” weighted factor scores, but have the advantage of a readily
interpretable absolute modal meaning (Dillon and McDonald 2001).

[Table 3 here]

4. Descriptive Results
Figures 1 and 2 show investors’ portfolio returns and the volatility of theses returns during
the sample period, as well as the corresponding returns and volatilities of the Dutch stock
market index (AEX). Investors’ returns (calculated as the product of the daily relative
changes in the value of their investment portfolio, taking into account transaction costs and
10