Why Do Individuals Exhibit Investment Biases?

National Taiwan UniversityInternational Conference on Finance

December 6, 2012

Henrik Cronqvist Claremont McKenna College

Stephan SiegelUniversity of Washington

Genes and Household FinanceResearch Agenda So Far

Save

Consume

Participate in stock market

Don’t participate in stock market

More risk

Less risk

Investment “biases”

We use twin study research design to examine, for each of the above choices, the effects of i) genetic and environmental influences, and ii) GxE moderators.

Parallel to molecular genetics and neuroscientific studies by Camerer, Bossaerts, Kuhnen, Laibson, Zak, and others.

Today:

Investment “styles” – value vs. growth

Investment “Biases”

Long list of investment behaviors that cannot be explained by standard preferences and belief formation:

Underdiversify Prefer local securities – home bias Avoid realizing losses Trade a lot Chase past performance Prefer lottery-type stocks

Some of these behaviors have been shown to be: Wide-spread; present also among professional investors Related to fundamental psychological mechanisms Costly

But, degrees of behavior vary across investors

Biological Basis for Investment Behaviors

Existing Evidence

Experimental evidence (previous slide)

Capuchin monkeys exhibit loss aversion Capuchin monkeys prefer gambles with good outcomes framed as bonuses

over identical pay-off gambles with bad outcomes framed as losses Loss aversion is part of “decision-making process that evolved before humans

and capuchins separated” (Chen et al. (2006), Lakshminarayanan et al. (2011))

But: No empirical evidence on the genetics of investment “biases” based on real world financial decisions and data

Josefin and ElinNordegren

Research Methodology: Twin Researc

Identical Twins

The Hodgson Twins

Fraternal Twins

Intuition of Methodology

Use identical & fraternal twins to decompose the variation in investment behaviors:

Identical (monozygotic, MZ) twins share 100% of their DNA

Fraternal (dizygotic, DZ) twins share on average 50% of their DNA

Twins who grew up in same family share a common environment

Each twin has his/her individual (non-shared) environment

If genes matter, then identical twins should be more similar than fraternal twins in terms of, e.g., their investment behaviors.

7

Methodology

Random effect model with genetic effect a, common effect c and individual-specific effect e:

Covariance structure implied by genetic theory: MZ

DZ

Methodology, cont’d

Estimate parameters σ2a, σ2

c, and σ2e via maximum likelihood

estimation (MLE) with bootstrapped standard errors

Derive the variance components:2

2 2 2a

a c

2

2 2 2c

a c

2

2 2 2a c

A-share – genetic component:

C-share – common environment(parenting):

E-share – individual environment & measurement error:

Data Swedish Twin Registry

Matched with annual financial data (including holdings of assets and sales transactions) and socioeconomic data from Statistics Sweden (1999 – 2007)

Filters: At least 18 years old Both twins hold some equities (directly or indirectly) in one year Average all variables over the years that individual is in sample

Measuring Investment “Biases”

DiversificationNumber of stocks in portfolio

Home Bias Proportion of equity portfolio in local (=Swedish) equities

Turnover Annual sales volume scaled by value of portfolio at beginning of year

Disposition Effect Proportion Gains Realized (PGR) – Proportion Losses Realized (PLR) (Odean (1998))

Performance Chasing Proportion of equities acquired with raw returns in top two deciles

Skewness Preference Proportion of “lottery” securities (Kumar (2009))

Evidence from Correlations

Variance Decomposition

Diver- sification

Home Bias Turnover

Disposition Effect

Performance Chasing

Skewness Preference

A Share 0.453 0.452 0.251 0.272 0.311 0.275

0.084 0.053 0.029 0.127 0.091 0.050

C Share 0.030 0.000 0.000 0.000 0.095 0.0000.052 0.028 0.007 0.045 0.065 0.028

E Share 0.516 0.548 0.749 0.728 0.594 0.7250.042 0.037 0.027 0.109 0.039 0.034

Variance Decomposition

D E T A I L

Robustness

Opposite-sex twins

Model misspecification Allowing for negative variance components

Communication Identical twins communicate more with one another Financial decisions are influenced by communication (e.g. Shiller and

Pound (1998), Hong, Kubik, and Stein (2004)) Sort pairs into 10 communication intensity bins and randomly drop

identical/fraternal pairs until both types are equally often present per bin. Estimate model across all 10 bins.

“A” component is somewhat reduced, but overall, results are robust.

Equal environments assumption

Two Additional Results

Moderators of genetic investment biases

Behavioral consistency: Investment biases and behaviors in other, non-investment, domains

Moderating Genetic Effects

Environment can enhance or reduce the effects of genetic predisposition

Example: Education seems to reduce genetic variation in health outcomes (Johnson et al. (2009))

Examine how years of education interact with the genetic effects

No significant evidence that years of education reduces genetic predispositions to investment biases

Moderator: Years of Education

0.00

0.50

1.00

1.50

2.00

2.50

8 10 12 14 16

Var(E) Var(C) Var(A)

Financial Experience

Does work experience in the financial industry or, e.g., in a corporate treasury department reduce genetic predispositions to investment biases?

Repeat analysis for individuals working with finance:

“A” components reduced (generally by >50%).

Experience in the finance industry seems to reduce the genetic predisposition to investment biases.

Behavior across different domains is often consistent If genetic factors matter, source of consistency should be genetic

Correlate Home Bias with Distance to birthplace Indicator whether spouse is from same home region

Behavioral Consistency

Behavioral Consistency

Conclusions

A long list of investment biases are “human” in the sense that investors are born with pre-dispositions

25-50% of variation explained by genetic variation

Provide empirical support for evolutionary models of investment biases (e.g., Brennan and Lo (2009))

Education does not reduce the genetic predisposition to investment biases. But finance industry experience reduces genetic effects.

Genetic factors influencing investment biases affect behaviors in other, non-investment, domains.