How Hunger Affects our Financial Risk Taking‘Metabolic State Alters Economic Decision Making under Risk in Humans’

Symmonds et al. (2010)

Written by: Joanne McGuire, Mair Roberts, Nancy Singh, Simon Stevens & Joe Bell

Introduction

•Financial decisions are made everyday…

•… But have you ever thought about how hunger might affect your financial decision making???

Overview• Aim: To asses whether human financial decision

making is affected by hunger and metabolic state.

• Hypothesis: Changes in metabolic state would modulate decision-making and financial risk-taking in humans.

• Prediction: Likely to be more risk-averse after eating a high-calorie meal and more risk-neutral when satiated.

Method• 19 out of a potential 24 male volunteers

• Mean age: 25±7

• Healthy BMI: 22.6±1.7 kg/m²

• Tests carried out over 3 sessions, each one week apart

Method Continued…• Each week the lottery task was carried at

different times, pre/post meal

Figure 1

Method Continued…• Each participant was tested on a sequence of

200 paired lotteries; see Figure 2 below.

• . Figure 2.

Dependant Variables

•Visual Analogue Scores (VAS)

•Prandial suppression of Acyl-ghrelin

•Circulating Leptin levels

Results

p = 0.022, r²= 0.22 (n=18)

Graphs

Background research

•Extending research on animal foraging behaviours and instinctive reactions of humans.

•Is this study question relevant?

•Utility theory

Prospect theory

•People are more risk averse over gains

• Symmonds el at., 2010 ▫Decisions are more risk averse above a metabolic

reference point

Figure S1

Did the study methods address the most important potential sources of bias?•Systematic bias•Confirmatory bias/ overconfidence?

Bias leads us to seek out information that supports existing instincts or points of view while avoiding contradictory information.

•Sample Size Neglect When results have been generalised to a

population from a less than representative number of data points.

Was the study performed according to the original protocol?

•Yes – the study protocol was followed apart from the number of participants

•Not all original 25 participants were included in the experiment

•This reduces the potential to generalise findings to real-world situations

Strengths • Controlled changes in cognition

• Kept all the conditions constant

• Mixed the tests up over 3 weeks so there was no conditioning to tests

• VAS

• Randomized trials to stop habituation

• 14 hour fast is realistic

Critiques of method•BMI vs. WHR

•Gender

•Providing a 2066 calorie meal isn’t very realistic straight after a fast

•No feedback is given on the results of the lotteries which is not realistic in real life financial risks

Confounding variables• Whether hunger

affects other variables (eg. mood, emotion, other hormones)

• Boredom

• Stress

• Income

• Occupation

• Age

• Education

Other Literature•Genetics: Cesarini et al. (2010) have found

that genetic variation accounts for 25% of an individuals risk portfolio

•Gender: It has been found that women are more risk-averse than men (Johnson & Powell, 1994)

•Culture: Hens & Weng (2007) found that there are cultural differences in risk taking

Other Literature (cont)…• Emotion: Emotional effects can have a large

impact on risky decision-making as Zhao (2006) found.

• Age: Older people tend to take less financial risks than younger people (Jianakoplos & Bernasek, 2006)

• All of these effects show that Symmond’s study cannot be generalised to a population and may lack internal validity as none of these other variables were controlled for.

How we would investigate this within a student environment

•Bigger sample

•Mixed sample

•Mixed BMIs

•Use an incentive

•Different cultures

•Account for obesity and anorexia

•Take into account losses

How can it be applied to real life•Dieting and obesity•Are dieters more vulnerable to risky

decision making?

How can it be applied to real life•Casinos•Snacks vs. meals

How can it be applied to real life•The importance of breakfast

Conclusions •Symmonds et al’s experiment showed that

metabolic states affect financial risk-taking

•Addressing a new line of research and extending previous studies on animal behaviours.

•However, the experimental method is flawed and results appear slightly ambiguous

References

• Byrnes, J. P., Miller, D. C., Schafer, w. D. (1999). Gender differences in risk taking: A meta-analysis. Psychological Bulletin, 125(3), 367-383.

• Cesarini, D., Johannesson, M., Lichtenstein, P., Sandewall, O., & Wallace, B. (2010). Genetic variation in financial decision making. Journal of Finance, 65(5), 1725-1754.

• Comings, D,E., Rosenthal, R,J., Lesieur ,H,R., Rugle, L,J., Muhleman, D., Chiu, C., Dietz,G., & Gade, R. (1996). A study of the dopamine D2 receptor gene in pathological gambling. Pharmacogenetics ,6(3), 223-34

• Dwyer ,p., Gilkeson, J., & List, J. (2001). Gender differences in revealed risk taking: evidence from mutual fund investors. Economics Letters 76, 151-158

• Eckel, C. C., & Grossman, P. J. (2002). Sex differences and statistical stereotyping in attitudes towards financial risk. Evolution and Human Behavior, 23(4), 281-295.

• Hens, T., & Weng, M. (2007). Does Finance have a cultural Dimension? FINRISK Working Paper, 377.

References Cont…• Hill, A,J., Weaver, C,F., & Blundell, J,E. (1991). Food craving, dietary restraint

and mood. Appetite ,17(3), 187-97.

• Hunton, J., Hall, T., & Price, K (1998). The value of voice in participative decision making. Journal of Applied Psychology, 83 (5), 788-797

• Johnson, J., & Powell, P. (1994). Decision Making, Risk and Gender: Are managers different? British Journal of Management, 5(2), 123-138.

• Kahneman, D., & Tversky, A. (1979) "Prospect Theory: An Analysis of Decision under Risk", Econometrica, XLVII, 263-291.

• Powell, M., & Ansic, D. (1997). Gender differences in risk behaviour in financial decision-making: An experimental analysis. Journal of Economic Psychology, 18, 605-628.

• Schubert, R., Brown, M., Gysler, M., & Brachinger, H. (1999). Financial Decision-Making: Are Women Really More Risk-Averse? An American Economic Review, 89(2), 381-385.

References Cont…• Symmonds, M., Emmanuel, J. J., Drew, M. E., Batterham, R. L., & Dolan, R. J.

(2010). Metabolic State Alters Economic Decision Making under Risk in Humans. PLoS One, 5(6), e11090.

• Vroom, V, H., & Pahl, B. (1971). Relationship between age and risk taking among managers. Journal of Applied Psychology, 55 (5), 399-405.

• http://www.alexwhittaker.org/?p=26