nature nurture and financial decision making why do individuals exhibit investment biases n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Nature, Nurture, and Financial Decision-Making Why Do Individuals Exhibit Investment Biases? PowerPoint Presentation
Download Presentation
Nature, Nurture, and Financial Decision-Making Why Do Individuals Exhibit Investment Biases?

Loading in 2 Seconds...

play fullscreen
1 / 30

Nature, Nurture, and Financial Decision-Making Why Do Individuals Exhibit Investment Biases? - PowerPoint PPT Presentation


  • 132 Views
  • Uploaded on

Nature, Nurture, and Financial Decision-Making Why Do Individuals Exhibit Investment Biases?. University of Michigan-Dearborn Betty F. Elliott Initiative for Academic Excellence: Financial Literacy April 9, 2012. Henrik Cronqvist Claremont McKenna College Stephan Siegel

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Nature, Nurture, and Financial Decision-Making Why Do Individuals Exhibit Investment Biases?' - alpha


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
nature nurture and financial decision making why do individuals exhibit investment biases

Nature, Nurture, and Financial Decision-MakingWhy Do Individuals Exhibit Investment Biases?

University of

Michigan-Dearborn

Betty F. Elliott Initiative for Academic Excellence: Financial Literacy

April 9, 2012

Henrik Cronqvist

Claremont McKenna College

Stephan Siegel

University of Washington

Arizona State University

nature nurture and financial decision making
Nature, Nurture, and Financial Decision-Making

“Economics is a branch of biology broadly interpreted.”

  • Alfred Marshall (1920)
  • The Origins and Remediation of Human Inequality

(James Heckman)

    • This research is rooted in economics but goes well outside of traditional analyses to integrate research in psychology, demography, neuroscience and biology.
  • A complete theory of human behavior(Andy Lo (2010))
    • Can we develop a complete theory of human behavior that is predictive in all contexts?
  • Effectiveness of policy initiatives (Doug Bernheim (2009))

“The discovery of a patience gene could shed light on the extent to which correlations between the wealth of parents and their children reflect predispositions rather than environmental factors that are presumably more amenable to policy intervention”

genoeconomics
Genoeconomics*
  • Study the sources of variation in economic behaviors and outcomes
    • Understand how institutions or environments moderate or amplify genetic differences
        • Education lowers genetic variation of health outcomes
        • Teacher quality increases genetic variation of reading skills
    • Identify specific genes that predict behaviors/outcomes. Design interventions for those at “genetic” risk
    • Reduce omitted variable bias by including genetic markers

* Benjamin, Chabris, Glaeser, Gudnason, Harris, Laibson, Launer, and Purcell (2007)

research methods
Research Methods

Sample Studies

  • Twin and Adoption Studies
  • Behrman and Taubman (1976)
  • Ashenfelter and Krueger (1994)
  • Sacerdote (2002)
  • Bjoerklundet al. (2006)
  • Cesarini et al. (2009, 2010)
  • Molecular Genetics Studies
    • Candidate gene studies
    • Genome-wide association studies (GWAS)
      • Rotterdam Study
      • Framingham Heart Study
      • AGES/Reykjavik Study
  • Kuhnen and Chiao (2009)
  • Dreber et al. (2009)
  • Beauchamp et al. (2011)
  • Glaeser, Laibson, et al. (ongoing)
our contributions so far
Our Contributions, so far . . .
  • Large Scale Twin Studies using Swedish Data (1999 – 2007)
    • Risk Aversion and Financial Risk Taking
      • (Barnea, Cronqvist, and Siegel (2010))
    • Discount Rates, Impatience, and Wealth Accumulation
      • (Cronqvist and Siegel (2011))
    • Preferences over Homeownership and Home Location
      • (Cronqvist, Muenkel, and Siegel (2012))
investment biases
Investment Biases

The investor’s chief problem and even his worst enemy is likely to be himself.

Benjamin Graham

investment biases1
Investment Biases
  • Long list of investment behaviors that cannot be explained by standard preferences and belief formation
    • Underdiversify
    • Prefer local securities
    • Avoid realizing losses
    • Chase past performance
    • Trade a lot
    • Prefer lottery-type stocks
  • Behaviors have been shown to be:
    • Wide-spread, even present among professional traders/investors
    • Potentially costly
    • Generally linked to fundamental psychology construct
  • But, degrees vary across investors
why do individuals exhibit investment biases
Born with biases

Preferences and belief formation as outcome of natural selection

Jack Hirshleifer (1977), Becker (1976)

Robson (1996, 2001), Netzer (2009), Robson and Samuelson (2009)

Nature selects behaviors that maximize fitness

Depending on environment, biases can emerge

Loss Aversion: McDermott, Fowler, Smirnov (2008) [in biology: e.g. Caraco (1980)]

Over-confidence: Johnson and Fowler (2011)

Probability Matching: Brennan and Lo (2009)

Environmental conditions

Parenting

Information and education

Institutions

Incentives

Why Do Individuals Exhibit Investment Biases?
objectives
Quantify the importance of different sources

Models of natural selection require some genetic variation

Understand whether education, experience, or incentives affect the importance of different sources

In particular, what conditions moderate genetic predispositions

Improve policy design

Invest in gene and genome wide association studies

Objectives
existing evidence
Existing Evidence
  • 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))
  • Experimental and survey evidence

Twin Studies

    • Overconfidence: Cesarini et al. (2009)
    • Conflicting evidence for several biases: Cesarini et al. (2011) and Simonson and Sela (2011)

Gene Association Studies

    • Different genes associated with risk attitudes over gains and losses (Zhong et al. (2010))

Neuro-scientific Studies

    • Different brain activity for realized vs. unrealized gains (Frydman, Barberis, Camerer, Bossaerts, and Rangel (2011))
  • No empirical evidence based on “real world” financial decisions
our research methodology
Our Research Methodology

Identical Twins

Fraternal Twins

Mary Kate and Ashley

Olson

Elin and Josefin

Nordegren

intuition of methodology
Intuition of Methodology
  • Use identical & fraternal twins to decompose variation:
    • Identical twins have 100% of their genes in common
    • Fraternal twins on average have 50% of their genes in common
    • Twins who grew up in same family have a common environment
    • Each twin has his or her individual-specific environment

If genes matter, then identical twins should be more similar than fraternal twins in terms of their behavior.

methodology

MZ

DZ

Methodology
  • Random effect model with genetic effecta, common effectc and individual-specific effecte:
  • Covariance structure implied by genetic theory:
methodology cont d
Methodology, cont’d

Estimate parameters σ2a, σ2c, and σ2e via maximum likelihood estimation (MLE) with bootstrapped standard errors

Derive the variance components:

A-share – genetic component:

C-share – common environment

(parenting):

E-share – individual environment & measurement error:

slide15
Data
  • Twins from the Swedish Twin Registry.
  • Matched with annual financial data (including holdings of assets and sales transactions) and socioeconomic data from Statistics Sweden (1999 – 2007, no transactions in 2001/02)
  • Require:
    • 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
Measuring Investment Biases
  • Home Bias

Proportion of equity portfolio held in Swedish equity

  • Disposition Effect

Conceptually: PGR – PLR (Odean (1998), Dhar and Zhu (2006), Campbell et al. (2009)) Based raw return in years with at least one sales transaction

    • Turnover

Annual sales volume (SEK) divided by value of portfolio at beginning of year.

    • Performance Chasing

Fractions of stocks acquired with raw returns in top two deciles

    • Skewness Preference

Fraction of lottery stocks in portfolio (Kumar (2009))

slide21

Mutual Fund and Large Investors

  • Repeat analysis combining direct stockholdings and mutual fund investments
  • Results are essentially the same
  • Diversification measure (mutual fund / all risky financial assets) has A component of about 39%
  • Repeat analysis for investors that hold at least 20% of assets in risky financial assets
  •  Genetic component increases by typically 10 to 20% points
slide22

Robustness

  • Same sex twin only
  • Model Misspecification
    • Allowing for negative variance components
    • Nonlinear models
  • Communication between twins
    • 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 slightly reduced, but generally robust
moderating genetic predisposition
Moderating Genetic Predisposition
  • Evidence that experience, education, and wealth affect investment biases and trading behavior (e.g. Vissing-Jorgensen (2003), Dhar and Zhu (2006), Calvet et al. (2009), Graham et al. (2009))
  • Environment can enhance or constrain genetic predisposition
    • Heritability of reading ability increases with quality of teacher (Taylor et al. (2010))
    • Education seems to reduce genetic variation of health status (Johnson et al. (2009))
  • Examine (for a sub sample) how years of education interact with different sources of variation
  • We find no significant effect of years of education on size of genetic variance
slide25

Moderator: Years of Education

Turnover

Home Bias

Loss Aversion

Performance Chasing

slide27

Sources of Behavioral Consistency

  • Behavior across different domains is often correlated
  • If genetic factors matter, source of the correlation should be genetic
  • Correlate Home Bias with
    • Distance to birthplace
    • Indicator whether spouse is from same home state
slide28

Sources of Behavioral Consistency

  • Behavior across different domains is often correlated
  • If genetic factors matter, source of the correlation should be genetic
  • Correlate Home Bias with
    • Distance to birthplace
    • Indicator whether spouse is from same home state
conclusions
Conclusions
  • Why do investor exhibit investment biases? We show that to a large existent biases, such as Home Bias, Disposition Effect, Turnover, Performance Chasing, as well as Skewness Preference are innate
  • Our findings are consistent with recent theoretical models that argue that biases are the outcome of natural selection
  • While genetic effects are important, they are not destiny:
    • A large part of the cross-sectional variation appears to be related to individual experiences and circumstances
    • General educational achievement does not seem to moderate genetic predispositions
    • For twins with occupational experience in finance genetic factors seem to matter less