Empirical evidence on risk aversion for individual romanian capital market investors
ABSTRACT Stock prices move as corporate earnings prospects change but they also move as investors change their aversion to risk. One of the central tenets of finance is that investors expect higher return for taking risk. They exchange some of their risk less securities for risky assets because they expect the total pay-off in the long run to be optimal in terms of the risk-return trade-off. The previous studies proved that expected return is linearly related to risk and if we further assume investors are risk averse, the alluded relation will have to be positive. Risk aversion is reflected on a risk premium, which consists of an expected extra return that investors require to be compensated for the risk of holding stocks. We intend to evaluate the situation of Romania in terms of risk aversion. This study is very useful for understanding the differences between the individual investment behaviours in EU and to understand the further European market evolution taking into consideration this important variable - risk aversion.
- SourceAvailable from: Héctor F. Calvo Pardo[Show abstract] [Hide abstract]
ABSTRACT: We explore empirically whether earnings uncertainty and borrowing constraints deter households from the stockmarket, consistent with the predictions of theoretical studies of portfolio choice in the presence of uninsurable earnings. Recent extensions highlight the importance of the correlation between earnings and financial risks. We use a self-assessed proxy for the correlation from the DELTA-TNS 2002 cross-sectional survey. While income risk does not deter from the stockmarket those households' reporting a negative correlation, it does for those who report a non-negative sign, consistent with economic theory predictions.PSE (Ecole normale sup�rieure), PSE Working Papers. 01/2007;
- Applied Economics - APPL ECON. 01/2000;
- [Show abstract] [Hide abstract]
ABSTRACT: In this study, 110 students responded to a series of gambling options described in terms of amount of initial investment, amount to be won, and probability of winning or losing. Half of the subjects were given the “chance of winning” each gamble, and half were given the “chance of losing” each gamble. Students' experience as gamblers was also recorded. Students generally responded more favorably to gambles when the probability information was phrased in positive terms than when it was phrased in negative terms. Males responded more favorably than females, and more experienced gamblers responded more favorably than less experienced gamblers. The magnitude of the framing effect was relatively invariant across levels of prior gambling experience.Journal of Psychology - J PSYCHOL. 01/1988; 122(2):173-181.
EMPIRICAL EVIDENCE ON RISK AVERSION FOR INDIVIDUAL
ROMANIAN CAPITAL MARKET INVESTORS
Cristian PĂUN1, Radu MUŞETESCU2, Iulian BRAŞOVEANU3, Alina DRĂGHICI4
Abstract. Stock prices move as corporate earnings prospects change but they also move
as investors change their aversion to risk. One of the central tenets of finance is that
investors expect higher return for taking risk. They exchange some of their risk less
securities for risky assets because they expect the total pay-off in the long run to be
optimal in terms of the risk-return trade-off. The previous studies proved that expected
return is linearly related to risk and if we further assume investors are risk averse, the
alluded relation will have to be positive. Risk aversion is reflected on a risk premium,
which consists of an expected extra return that investors require to be compensated for
the risk of holding stocks. We intend to evaluate the situation of Romania in terms of risk
aversion. This study is very useful for understanding the differences between the
individual investment behaviours in EU and to understand the further European market
evolution taking into consideration this important variable – risk aversion.
Key words: risk aversion, individual investor, Romanian capital market
JEL: D53, G11.
The whole financial theory is based on the fundamental hypothesis of rational agents
investing on the financial markets. This rationality is characterized by a continuous pursuit of
the investors to maximize their utility function (actually maximizing the return of the
investment for a given risk level or minimizing the risk for an expected return level). In spite
their rationality, investors have a different perception over risk, its bearing having an
important psychological dimension. Most investors show a motivated risk aversion, but we
can find on the financial markets, even if only in theory, investors indifferent or with
preference for risk.
The first trial of conceptualizing the investors’ risk aversion belongs to Milton
Friedman and Leonard Savage (Milton Friedman, Leonard Savage Utility Analysis of Choices
Involving Risk, JPE, 1948) who defined the risk aversion by using the following decisional
situation: an investor who can chose among comparable investments will always chose the
one with the lowest risk. Explaining the investment behaviour using the returns of risky
financial investments’ utility function brought a new perspective to the risk aversion theory.
Studies show that investors behave differently regarding the risks they have to take, the risk
aversion dominating these behaviours. In Friedman's and Savage's opinion the main factor
that changes, in time, the investor’s attitude towards risk is the size of their wealth. Further
studies showed that there are also other factors with direct impact over the attitude towards
risk (economic growth forecasts of a market, the level of training and the experience gained,
fluctuations of the exchange market, psychological factors etc.).
1 PhD Lecturer, Academy of Economic Studies, Bucharest, email@example.com.
2 PhD Lecturer, Academy of Economic Studies, Bucharest, firstname.lastname@example.org.
3 PhD Lecturer, Academy of Economic Studies, Bucharest.
4 Assistant Professor, PhD Candidate, Academy of Economic Studies, Bucharest, email@example.com.
92 CRISTIAN PĂUN, RADU MUŞETESCU, IULIAN BRAŞOVEANU, ALINA DRĂGHICI
Accepting the three main investment behaviours (aversion, neutrality and preference),
the specialists’ attention was directed towards measuring the investors’ degree of risk
aversion – the first step in setting the risk premium (the price an aversive investor is willing to
accept in exchange of the risks he has to take), expressed in wealth terms. The first notable
efforts in understanding the factors that influence the degree of risk aversion were made by
John W. Pratt5 and Kenneth J. Arrow (Aspects of the Theory of Risk-Bearing, 1965). Their
observation begun with the fact that an investor with high risk aversion is less willing to take
those risks, that is, for him the price of bearing it (the risk premium) is much higher. In their
approach, the main factor of risk aversion is the wealth of the investors (the capital going to
be risked, and higher returns being expected). The utility function concavity can thus be a
relevant measure of the investors' risk aversion degree.
The fact that investors evaluate differently the risky investment alternatives and that
the expected utility is different, is first due to psychological factors, thus the financial market
becomes the sum of unique behaviours, in which each individual investor is guided by its own
needs (primary or secondary). In these conditions, all the three investment behaviours (risk
aversion, neutrality and risk preference) may be considered rational behaviours and can be
explained only based on the different shape of the utility function associated to their
behaviours (in all three cases investors pursue, in their own way, the utility function
In this respect, the fact that the risk premium depends directly on the alternative
investment risk (measured by the variance), inversely on the amount invested initially and
directly on the investors’ absolute risk the aversion degree (measured by Arrow-Pratt index)
was concluded. In this case is obvious that two investors can have different risk premiums
when they decide to invest the same initial capital in the same financial titles, because the
different degree of risk aversion. The increase with one unit of the initial wealth for the
investors with risk preference calls forth an acceleration of the utility augmentation (the
second grade derivative of the utility function is strictly positive), a decrease of the absolute
risk aversion and implicitly a reduction of the risk premium. The increase with one unit of the
initial wealth for the risk aversive investors calls forth a decrease of the utility augmentation
(the second grade derivative of the utility function is strictly negative), an increase of the
absolute risk aversion and implicitly an increase of the risk premium.
The evaluation of risk premium for each investor is almost impracticable on an
important financial market (the more institutional investors the more complicated the situation
becomes). Selecting the most important financial portfolio managers in a market is
recommended in order to assess the value of the risk premium for the next period.
Currently the most applied model by analysts for determining the risk premium on a
market is the use of historic values. The simplicity of this method comes from the market
models based on the market portfolio as optimum risky portfolio. In order to measure the risk
premium in this way the mean return of the market portfolio has to be computed for the
chosen period (approximated with the market index) followed by computing the mean return
of free risk titles in a market for the chosen period (state bonds are assimilated to risk free
titles), calculating the historical risk premium as the difference between the mean return of
market portfolio and the risk free rate and extrapolation of the historical value to the next
period6. The discounted cash flow model is used for estimating the implicit risk premium
value in the financial titles current price. Subtracting the risk premium is made in this case
from the value of the expected return on a market and the risk free rate of the market
(assimilated to the return of state bond or titles).
Currently this kind of studies was performed in very many countries (especially in the
developed ones), their conclusions being very interesting and important for understanding the
5 J.W. Pratt, Risk Aversion in the Small and in the Large, Econometrica, Vol. 32, p.122-36, 1964
6 A. Damodaran in his paper Understanding Risk, 2004, made such a complete study on the American capital
market presenting the dynamics of the risk premium in the period 1928-2001
Empirical evidence on risk aversion for individual Romanian Capital Market investors 93
investors psychology (in Asian countries, for example, the risk aversion is higher than in the
European countries, these having a higher risk aversion than the American market). By these
studies important information related to the factors influencing the investors’ risk attitude on a
local market can be obtained and also a series of interesting conclusions can be drawn
concerning the interest for financial investment, the propensity for investments/consume or
saving and the mode they can be influenced one way or the other. Measuring the risk
premium comparatively for a group of countries can provide further information regarding
their diversity and different integration degree.
Beginning with the first conclusions of the Arrow and Pratt's hypothesis regarding the
influence of earnings over the investment behaviour, a series of empirical studies testing the
factors that influence this complex variable were conducted. The first studies were concerned
with the differences between men and women in accepting the risks of financial investments:
an empirical study was performed in 1975 by Levin, Snyder and Chapman7 on a group of 110
students using a questionnaire regarding lotteries, the results indicating that women are more
risk aversive than men; in 1997, Powell and Ansic8 questioned a small group regarding
property insurance and the exchange market and again found that women are more aversive
than men (this study was among the first which analyzed individual aversion towards
speculative and pure risks); using information regarding the weight of the funds invested in
risky assets Jianakoplos and Bernasek9 concluded that unmarried women are more risk
aversive than unmarried men (the results proved invariant with age or educational level,
having children or social status of individual but still indirectly affecting investors risk
tolerance); a similar study was performed by Sunden and Surette10 who observed the direct
effect of individuals’ family status on their risk aversion (married individuals are less risk
aversive than the unmarried ones).
Several other studies went further in determining other demographic factors
influencing the degree of risk aversion involved in financial investments. Riley and Chow11
examined the individual investors capital allocation decision and found that the risk aversion
reduces with the earnings, education and age, until the age of 65 when the aversion rises.
They also discovered women’s risk aversion is higher than men's and that the coloured people
risk aversion is higher than that of white people.
Using a psychological questionnaire Zuckerman12 discovered relevant differences in
aversion related to age, sex, nationality, race, socio-economic status or family status. Using a
similar methodology, Hersch13 analyzed the individuals’ aversion towards non-financial risks
(smoking, usage of the safety belt, preventing illness, preventing dental aches) discovering
that white women with a high level of education have a higher aversion regarding these risks.
Barsky14 carried out for the first time an estimation of the minimum and maximum limits of
7 Levin Irwin P., Mary A. Snyder and Daniel P. Chapman, The Interaction of Experiential and Situational
Factors and Gender in a Simulated Risky Decision-Making Task, Journal of Psychology, 1988, 122(2),pp. 173-
8 Powell Melanie, and David Ansic, Gender Differences in Risk Behaviour in Financial Decision-Making: An
Experimental Analysis, Journal of Economic Psychology, 18(6), 1998, pp. 605-628
9 Jianakoplos, Nancy Ammon, and Alexandra Bernasek, Are Women More Risk Averse?, Economic Inquiry
36(4), 1998, pp. 620-630
10 Sunden, Annika E., and Brian J. Surette, Gender Differences in the Allocation of Assets in Retirement Savings
Plans, American Economic Review, Papers and Proceedings, 88(2), 1998, pp. 207-211
11 Riley, William B., Jr., and K. Victor Chow, 1992, Asset Allocation and Individual Risk Aversion, Financial
Analysts Journal, November-December, 1992, pp. 32-37
12 Zuckerman, Marvin, „Behavioral Expressions and Biosocial Bases of Sensation Seeking, Cambridge
University Press, 1994
13 Hersch, Joni, Smoking, Seat Belts, and Other Risky Consumer Decisions: Differences by Gender and Race,
Managerial and Decision Economics, 1996, 17(5), pp. 471-481
14 Barsky, Robert B., F. Thomas Juster, Miles S. Kimball, and Matthew D. Shapiro, Preference Parameters and
Behavioral Heterogeneity: An Experimental Approach in the Health and Retirement Study, Quarterly Journal of
Economics, 1997, 112(2), pp. 537-579
94 CRISTIAN PĂUN, RADU MUŞETESCU, IULIAN BRAŞOVEANU, ALINA DRĂGHICI
the investors risk aversion and defined the concept of risk tolerance as being the inverse of
risk aversion. He applied his model over returns and other demographic factors and
discovered that risk aversion varies between 0.7 and 15.8 with significant differences related
to age, sex, race, religion or nationality.
Among the most complex studies in this respect is the one performed in Holland
between 1993-2000 by a team of researchers, from the University of Amsterdam leaded by
Joop Hartog15, who questioned different socio-professional categories in order to quantify
their degree of risk aversion using three local publications Brabant Survey (2800 individuals
were questioned), Accountants Survey (3000 individuals, all chartered accountants, were
questioned by mail in 1996, out of which 1599 answered) and GPD Newspaper (a local
newspaper from Brabant area which included in its January 1998 Sunday issue a
questionnaire with six questions regarding the price investors would be willing to pay for a
lottery in different conditions; the questionnaire was a little more complex in this case than
the one published in the first two magazines and was concerned with other correlations – the
level of earnings, religious orientation, social status, level of education thus a series of very
interesting conclusions were drawn). Moreover it must be mentioned that the questionnaire
published in Brabant Survey the maximum accepted price was 500 guldens, in the case of
Accountants Survey the lotteries maximum accepted price was 1000 guldens while for the
questionnaire published in GPD Newspaper the lotteries maximum price was set at 200
guldens. The number of respondents and the answers’ distribution ensured the relevance of
this study, its conclusions being worthwhile.
Another study carried out in 1993 by C. Hawley and E. Fujii16 with the help of Survey
of Consumer Finances on American working persons, aged from 25 to 62, the results
indicating that the level of education, earnings and the debt degree are positively correlated
with the investors's risk tolerance and the married couples dominated by men are more risk
tolerant than the married couples dominated by women. This study showed that age is not
statistically representative for the investors risk tolerance.
Hawley and Fujii study was confirmed afterwards by the studies of Warner and
Cramer (1995) and of the J. Sung and S. Hanna (1996). The last two researches used the data
obtained by „Survey of Consumer Finances” and made a distribution of risk tolerance of
different demographic groups (out of 2691 respondents more than 60% percent were willing
to take the financial market specific risks). In the case of Sung and Hanna study the risk
tolerance was almost identical up to the age of 55 and then begun to directly decrease with
The race or the investor’s ethnic group is another influencing factor considered by
experts. A study conducted by Sung and Hannna17 analyzed the risk tolerance corresponding
to four ethnic groups: Caucasian, Hispanic, Black and others.
Given the substantial differences among risk tolerance capacities of these groups (the
Caucasians have the highest risk tolerance and the Blacks the lowest) we may assert that this
factor has a direct impact on the way investors accept and perceive the risk attached to
financial investments. Education also has a direct influence on risk tolerance, as several
studies prove a direct link between higher education and the acceptance of higher risk related
to investments. This might be explained by a superior understanding of risk of those with
higher education and a better capacity to predict future developments. The analysis was
conducted on four education levels: primary school, high school, college and postgraduate
studies. The results demonstrate an intense and direct impact on accepting financial risk: the
15 Joop Hartog, On a Simple Measure of Individual Risk Aversion, Timbergen Institute Discussion Paper, 2000,
16 Hawley, Clifford B. and E. Fujii., An empirical analysis of preferences for financial risk: further evidence on
the Friedman-Savage Model, Journal of Post Keynesian Economics, Nr. 16, vol. 2, 1993, pp. 20 – 24
17 Jaimie Sung, Sherman Hanna, Factors related to risk tolerance, Financial Counseling and Planning, Vol. 7,
1996, pag. 14
Empirical evidence on risk aversion for individual Romanian Capital Market investors 95
higher the subject’s education, the higher his tolerance to risk. Closely connected to
education, the study also evaluated the risk tolerance for different professions: management,
technical personnel/salesmen/ administrators, service-related occupations, high technology-
related occupations, or productive professions in agriculture or fishing. The study revealed no
special connection of these professions with the capacity to accept financial risk. However,
the study revealed a significant difference between men and women tolerance to risk, as the
mean tolerance for the entire group was 60.4. Other factors, as the size of the family, the
possessions or number of years till retirement, proved to be irrelevant. As the authors of the
study pointed out, only part of these factors could objectively explain different risk tolerance
levels (age, education, and income) while others are pure subjective factors (race, sex, social
statute, and occupation).
M. Halek si J. Eisenhauer18 came to relatively same conclusions after conducting a
similar study. They discovered that factors like age, sex, race, religion (Catholicism,
Protestantism and Judaism were analyzed), unemployment and economic crises directly affect
investor’s risk aversion. Other factors like education, the number of children or the social
statute (married or unmarried) are less relevant to pure risk. Based on regression, the model
claimed that Hispanics and Blacks are consistently less adverse to pure risk and that Judaism
is the only religion with significant effect on risk aversion. The study conducted by the two
above mentioned made a distinction between pure and speculative risk, so that the nationality,
sex, age and education became more relevant for speculative risk.
All these studies prove the complexity of risk aversion and its subjective dimension, as
the estimates are difficult to obtain accurately. Investors have ultimately a unique behaviour
which results in an balanced price, no matter how adverse they are to risk. Understanding risk
aversion offers another perspective for constructing and optimizing risky financial portfolios.
METHODOLOGY USED FOR MEASURING RISK TOLERANCE AND RISK AVERSION
The questionnaire for the individual investors was posted on Internet at the following
link www.rei.cercetare.ase.ro/aversiune, during 15th September – 15th October, 2007.
The questionnaire was promoted on specialized web sites (www.asigurări.ro,
www.finantare.ro, www.finint.ase.ro) and the results of our study will also be published on
these web sites.
During 15th September – 15th October, 2007 we had 494 respondents, the
questionnaire remaining open for further research (we intend to use it a few consecutive years
to improve the research).
The current number of respondents ensures the relevancy of this study for the
Romanian Capital Market:
a) Confidentiality level: 95%
b) Error: 4.41%;
c) Population: 22,000,000 inhabitants.
We have used the following methodology for interpreting the questionnaire:
‐ Each answer received a number of points.
a=4; b=3; c=2; d=1
a=1; b=2; c=3; d=4
a=1; b=2; c=3; d=4
a=1; b=2; c=3
a=1; b=2; c=3
a=1; b=2; c=3; d=4
a=1; b=2; c=3; d=4
a=1; b=2; c=3; d=4
18 Martin Halek, Joseph G. Eisenhauer, Demography of risk aversion, The Journal of Risk and Insurance, 2001,
Vol. 68, No. 1, 1-24, pp. 10 – 15
96 CRISTIAN PĂUN, RADU MUŞETESCU, IULIAN BRAŞOVEANU, ALINA DRĂGHICI
a=1; b=2; c=3; d=4
a=1; b=2; c=3
a=1; b=2; c=3; d=4
‐ Each questionnaire was evaluated and each respondent received a total number of points
reflecting he/she risk tolerance
‐ For interpreting the number of points received by each respondent we have used the
• Number of points between 0 and 18: Low risk tolerance
• Number of points between 19 – 22: Below average risk tolerance
• Number of points between 23 – 28: Average risk tolerance
• Number of points between 29 – 32: Above average (high) risk tolerance
• Number of points between 33 – 47: Very high risk tolerance
‐ For computing the risk aversion we have used the following formula:
‐ We gave the following interpretation to this indicator
• Aversion higher than 5.6: Very high risk aversion
• Aversion between 4.5 and 5.3: High risk aversion;
• Aversion between 4.4 and 3.6: Average risk aversion;
• Aversion between 3.5 and 3.1: Low risk aversion;
• Aversion below 3.0: Very low risk aversion.
For the risk aversion factorial analysis we chose the following socio-professional
profile for individual investors: age, sex, educational level, income, occupation, social status.
For the factor age we choose five representative levels: under 30 years old, between
31–44 years old, between 45–54 years old, between 55–64 years old and over 65 years old.
Our expectations are a higher risk aversion for the extremes (persons too young or too
old) and a slight increase of the risk aversion for the respondents with ages in the middle
of the range.
Considering the educational level we have used four categories: high-school, faculty,
master, doctoral and the expectation was that the risk aversion will decrease as the
educational level increases.
For the social status factor we used five categories: unmarried, married without
children, married with children, divorced, widow. The expectation was that as the social
responsibilities increase, the risk aversion decreases, individuals being more willing to
take investment risks.
Referring to the net income, we used five income levels correlated to the medium
income: under €150, between €150-€350, between €350-€650, between €650-€850 and over
€850. We expected that the risk aversion will decrease as the income increases.
For the occupational categories we used seven degrees of involvement in economic
activities: unemployed, student, employee in the budgetary sector, employee in the private
sector, entrepreneur, liberal professions and retired. The expectation was that the risk aversion
will be proportional to the risks taken in each individual’s profession.
For each socio-demographic category we computed the tolerance and average risk
Empirical evidence on risk aversion for individual Romanian Capital Market investors 97
RESULTS OF THE STUDY
A. Sample Structure Analysis
Referring to the sample structure we have an important disequilibrium relative to sex
(Table no. 1), if take in consideration the Romanian population structure (that in July 2004
was 51% women and 49% men).
Comparing the structure of the sample (Table no. 2) with the Romanian population age
structure we observe that our sample is too large for the “Under 30 years old” dimension
(21% for the Romanian population as to 52% in our data), extremely small for “Over 65 years
old” (19% for the Romanian population as to 0.2% in the sample) and too small for “Between
55-64 years old” (13% for the Romanian population as compared to 5.26% in our data).
So the sample is representative for the young and adult population. Also women in the
sample are younger than the men.
No. respondents (%)
Under 30 years old
Between 31 – 44 years old
Between 45 – 54 years old
Between 55 – 64 years old
Over 65 years old
The education level of the sample is slightly above the average (Table no. 3), which is
relevant if we consider the average capital market graduate investors. A relevant number of
investors are at the extremes: they have a PhD and graduated high-school. Considering the
structure of the Romanian population on the level of education, we may consider the
responses relevant only for the higher education segment.
No. respondents (%)
Considering the social status dimension (Table no. 4) our sample is very different than
the structure of the Romanian population on this dimension. We consider that this is not a
defining criterion for the sample, so a different structure than the Romanian population
wouldn’t have a negative impact on the representative capacity of the study. In behavioural
finance literature this criterion is not considered very important.
No. respondents (%)
Married without children
Married with children
No. respondents (%)
98 CRISTIAN PĂUN, RADU MUŞETESCU, IULIAN BRAŞOVEANU, ALINA DRĂGHICI
According to data available for the average salary in Romania in august 2007, only
32.59% of the respondents have an income close to the average salary or lower than the
national average, all the other ones being above this level (Table no. 5). This could be
explained by the fact the access to Internet is not equally available to the entire population.
The propensity to investment is being influenced by the level of income and Romania being a
country with a relative low level of prosperity, we consider the sample to be representative for
the population with propensity to invest on the capital market.
We also observed that women in the sample have a lower level of income than men
(incomes higher that 650Euros have only 28.9% of the women compared to 48.85% for men),
which can be the result of hazard, lower income level jobs or the discrimination. Women in
the sample are in a higher proportion working in the private sector and students, unlike the
men that are in higher proportion entrepreneurs or having liberal professions (this could
explain the discrepancies in income).
No. respondents (%)
The sample for the “Occupation” dimension shows very high number of respondents
in “Student” and “Entrepreneur” and low levels for “Unemployed” and “Retired” (table no.
6); but the last two categories have the lowest propensity to invest. The entrepreneurs and
employees in the private sector are most important groups of investors.
No. respondents (%)
Employee in the budgetary sector
Employee in the private sector
No. respondents (%)
B. Risk aversion analysis
Individual investors in the Romanian capital market show a low (slightly below the
average) risk aversion (Table no. 7).
The analysis of the results showed a lower risk aversion of men as compared to
women (Table no. 8).
The small difference between the two categories doesn’t indicate a clear distinction,
both categories having a low risk aversion.
Empirical evidence on risk aversion for individual Romanian Capital Market investors 99
Referring to the age factor (Table no. 9) the analysis showed that the respondents
below 30 years old and the ones between 55-64 years old show the highest risk aversion. The
risk aversion is considerably lower for 31-44 and 45-54 years old groups. The results for the
group over 65 years old are not relevant, as we had only one respondent.
Over 65 years old
Between 31 - 44 years old
Between 45 - 54 years old
Under 30 years old
Between 55 - 64 years old
Similar empirical studies made for other markets showed that there are significant
differences in risk aversion for the different social categories. Normally the risk aversion
should be inversely proportional with the social responsibilities undertaken by the individual
(related to family, children). For the Romanian market our results show that the
widows/widowers have the lowest risk aversion, followed by the respondents married without
children, married with children, unmarried and the divorced (Table no.10).
Married without children
Married with children
Considering the educational level, for the Romanian market the results indicate that the
risk aversion decreases with the increase of the education level – the respondents that finished
high-school showing the highest risk aversion, followed by the ones with a bachelor degree and
a master degree (Table no. 11). The exception is the doctoral level – an explanation could be
that 61% of respondents with a PhD are employees in the budgetary sector.
Empirical studies for other markets showed that risk aversion is inversely proportional
to the income level: as the individual investors’ incomes increase their risk aversion
decreases. The results for the Romanian market indicate that the highest degree of risk
aversion is showed by the respondents with the lowest income level, the risk aversion
decreasing proportionally as the income level increases (respondents with incomes over €850
showing a risk aversion with 0.6 points lower than the one recorded for the lowest income
level) – Table no. 12.
100 CRISTIAN PĂUN, RADU MUŞETESCU, IULIAN BRAŞOVEANU, ALINA DRĂGHICI
Normally individual investors having a lower degree of risk aversion are the ones
taking risks in their daily activity; thus entrepreneurs, liberal professions should have the
lowest risk aversion while the students and the employees in the budgetary sector would show
higher levels of risk aversion). Such a result validates the method of measuring the risk
aversion by questionnaire and the results obtained. For the Romanian capital market the
results showed that the occupational factor is relevant for measuring risk aversion: the lowest
degree of risk aversion is shown by occupational categories that take risks on day-by-day
basis – entrepreneurs and liberal professions; students and retired respondents have the
highest risk aversion (Table no. 13). It is interesting that the unemployed respondents have a
risk aversion degree lower that the one showed by the employees in the budgetary sector.
Employee private sector
Employee budgetary sector
The study on tolerance and risk aversion of individual investors for the Romanian
capital market highlights the following aspects:
Individual investors risk aversion, for the Romanian capital market in 2007, is low (below the
average), thus the Romanian investors are willing to take a lot more risks for their investments,
expecting a higher return;
Women have a relatively higher risk aversion than the men when considering investments on the
Age is a relevant factor for the individual investors’ risk aversion. Respondents under 30 years
old and the ones over 55 years old show a high risk aversion. For the ones over 65 years old the
results are not relevant, as we didn’t have enough respondents.
Social status is also a relevant factor for individual investors’ risk aversion; the study showed that
for the Romanian market we have an inversely proportional relation between the social
responsibilities taken by the individuals and their risk aversion;
Except for the PhD persons, for whom the results are not relevant for the sample, Romanian
individual investors’ risk aversion decreases as their education level increases;
Risk aversion decreases as the Romanian individual investors’ incomes increase, thus income is
an important factor for the investment behaviour;
The occupational criterion is also relevant for our study and shows that another factor
determining the risk aversion is individual investors’ involvement in economic activities. This
criterion validates and confirms the results of the study and the methodology used.
Empirical evidence on risk aversion for individual Romanian Capital Market investors 101
1. Arrondel L., Calvo H., Oliver X. (2005), ‘Portfolio Choice and Background Risk:
Evidence from France’, Paris-Jourdan Sciences Economiques;
2. Barsky, Robert B., F. Thomas Juster, Miles S. Kimball, and Matthew D. Shapiro, (1997),
‘Preference Parameters and Behavioral Heterogeneity: An Experimental Approach in the
Health and Retirement Study’, Quarterly Journal of Economics, 112(2), pp. 537-579;
3. Bertoni, A. (2005), ‘Investors’ Self-confidence in Financial Choices: the Italian Case’,
Financial Management Association International Working Paper.
4. Hawley, Clifford B. and E. Fujii. (1993), ‘An empirical analysis of preferences for
financial risk: further evidence on the Friedman-Savage Model’, Journal of Post
Keynesian Economics, Nr. 16, vol. 2: 20 – 24;
5. Hersch, Joni, (1996), ‘Smoking, Seat Belts, and Other Risky Consumer Decisions:
Differences by Gender and Race’, Managerial and Decision Economics 17(5): pp. 471-
6. J.W. Pratt (1964), ‘Risk Aversion in the Small and in the Large’, Econometrica Vol. 32:
7. Jianakoplos, Nancy Ammon, and Alexandra Bernasek, (1998), ‘Are Women More Risk
Averse?’, Economic Inquiry 36(4), pp. 620-630
8. Joop Hartog (2000), ‘On a Simple Measure of Individual Risk Aversion’, Timbergen
Institute Discussion Paper: pp. 8;
9. Kapteyn, A, Teppa, F. (2002), ‘Subjective Measures of Risk Aversion and Portfolio
Choice’, CentER, Tilburg University, February 18;
10. Levin Irwin P., Mary A. Snyder and Daniel P. Chapman, (1988), ‘The Interaction of
Experiential and Situational Factors and Gender in a Simulated Risky Decision-Making
Task’, Journal of Psychology, 122(2),pp. 173-181
11. Martin Halek, Joseph G. Eisenhauer, (2001), ‘Demography of risk aversion’, The Journal
of Risk and Insurance, Vol. 68, No. 1, 1-24: 10 – 15
12. Powell Melanie, and David Ansic, (1998), ‘Gender Differences in Risk Behaviour in
Financial Decision-Making: An Experimental Analysis’, Journal of Economic
Psychology, 18(6): pp. 605-628
13. Riley, William B., Jr., and K. Victor Chow, (1992), ‘Asset Allocation and Individual Risk
Aversion’, Financial Analysts Journal, November-December, pp. 32-37;
14. Scheicher, M. (2003) ‘What drives investor risk aversion? Daily evidence from the
German equity market’, BIS Quarterly Review;
15. Sunden, Annika E., and Brian J. Surette, (1998), ‘Gender Differences in the Allocation of
Assets in Retirement Savings Plans’, American Economic Review, Papers and
Proceedings, 88(2): pp. 207-211;
16. Sung, J., Hanna, S., (1996) “Factors related to risk tolerance”, Financial Counseling and
Planning, 7, 11-20;
17. Zuckerman, Marvin, (1994), ‘Behavioral Expressions and Biosocial Bases of Sensation
Seeking’, Cambridge University Press