Rodney White Conference on Financial Decisions and Asset Markets

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Rodney White Conference on Financial Decisions and Asset Markets Molecular Genetics, Risk Aversion, Return Perceptions, and Stock Market Participation Rick Sias Laura Starks Harry Turtle University of Arizona University of Texas Colorado State University Rodney White Conference on Financial Decisions and Asset Markets March 2019

Motivation – Do genetic factors impact: Importance of genetic factors Risk aversion? Beliefs regarding the distribution of equity returns? Stock market participation? Importance of genetic factors Linking risk aversion and beliefs to stock ownership Linking other factors (e.g., wealth, trust) to stock ownership, risk aversion, and beliefs

Molecular genetics Genome – genetic information needed to build and maintain a human Contained in 23 pairs of chromosomes within every* cell in your body

Molecular genetics Each chromosome is one long DNA molecule Genes are the parts of the DNA that “code” for protein 99% of DNA is non-coding “Rungs” of the DNA ladder consist of four nitrogenous bases A (adenine) T (thymine) C (cytosine) G (guanine) 37T cells

Molecular genetics Complementary base pairing (A&T; C&G) Human genome (i.e., the 23 chromosomes) have 3.2B “rungs” (base pairs)

Molecular genetics Nucleotide is the side of the ladder + the associated Nitrogenous base (e.g., highlighted nucleotide is C) Of 3.2B base pairs, <1% vary across individuals which accounts for why we are not identical*

Molecular genetics Places where two individuals differ are Single Nucleotide Variation If <1% of population differs, SNV=mutation If >1% of population differs, Single Nucleotide Polymorphism (SNP) ~10M SNPs

Molecular genetics Once human genome mapped, look for relations between SNPs (places where the “rungs” differ) and characteristics -- physical, disease, behavioral Few characteristics are due to a single (or even few) SNPs Sickle cell anemia due to a single SNP (Mendelian trait) Most characteristics are impacted by many SNPs E.g., hundreds or thousands of SNPs make very small contributions to height Mendelian trait = monogenetic trait Multiple SNPs ==> polygenic trait

Molecular genetics Standard approach: Genome Wide Association Studies (GWAS) Search the entire genome (~all 10M SNPs in 23 chromosomes) Because #potential independent variables >>observations regress phenotype on each SNP individually (and controls), e.g., 10M regressions Weight SNPs by effect size to form a single measure known as PolyGenic Score (PGS) Polygenic score == risk factor for a phenotype == likelihood of a particular trait

Data Health Retirement Study (SSA and National Institute on Aging) Adults ages 50-80 Our sample Surveys for 2010, 2012, 2014, & 2016 >6k individuals and >13k individual-year observations

Data Genetics Outcomes Traditional explanatory variables Controls Educational Attainment PGS Myocardial Infarction PGS General Cognition PGS Coronary Artery Disease PGS Neuroticism PGS BMI PGS Depressive Symptoms PGS Height PGS Outcomes Self-rated risk aversion P(RM<-20%) Chance market up (>0) Hold any stocks P(RM>20%) Traditional explanatory variables Wealth Trust Height Income Sociability BMI Education Optimism Health Cognition Early life poverty Panel C of Appendix A provides a summary of studies describing links between traditional explanatory variables and outcomes Controls Gender Retired Age Married HRS Wave Genetic PCs

Genetics, holding stocks, risk aversion, and beliefs Q1 - Do genetic endowments help explain variation in risk aversion, beliefs regarding stock returns, and stock market participation? Regress outcomes on controls and each PGS

Genetics and likelihood of holding any stock

Genetics and beliefs regarding stock returns ~4% in std dev terms Std dev of chance up is 26.5%  0.927/26.5 = 3.5% Std dev of crash is 23.198  1.021/23.2 = 4.4%

Genetics and risk aversion

Genetics, holding stocks, risk aversion, and beliefs Q1 - Do genetic endowments help explain variation in risk aversion, beliefs regarding stock returns, and stock market participation? Yes

Genetics, holding stocks, risk aversion, and beliefs Q2 – Can genetics help explain the relation between risk aversion, beliefs, and stock market participation? And, if so, how much? Step 1: Remove variation in participation, risk aversion, and beliefs related to control variables (e.g., age, gender, married, retired, HRS waves, & genetic PCs) “Orthogonalized” participation, risk aversion, beliefs Step 2: Regress orthogonalized RA (or beliefs) on the eight PGSs fitted value is “genetic component” residual is “non-genetic component” Step 3: Regress orthogonalized participation on genetic and non-genetic components and partition R2

Stock market participation, risk aversion, and beliefs

Stock market participation, risk aversion, and beliefs

Traditional explanatory variables and genetics Q2 – Can genetics help explain the relation between risk aversion, beliefs, and stock market participation? And, if so, how much? Yes Best estimate: 30% genetic/70% non-genetic

Traditional explanatory variables and genetics Q3a – Can genetics help explain the relation between “traditional” explanatory variables stock market participation, risk aversion, and beliefs? Step 1: Confirm relation between traditional variables (e.g., trust) and stock market participation Higher trustlower risk aversion, more bullish beliefs, and greater equity market participation Step 2: Test if genetics help explain variation in traditional variables

Genetics and trust

Traditional explanatory variables and genetics Q3b – How much of the relation between outcomes and traditional variables is due to genetic variation in traditional variable versus non-genetic variation? Step 1: Remove variation in outcomes and traditional variables attributed to the control variables: “Orthogonalized” participation, risk aversion, beliefs, trust Step 2: Regress orthogonalized trust on the eight PGSs fitted value is “genetic component” residual is “non-genetic component” Step 3: Regress orthogonalized participation on genetic and non-genetic components of trust and partition R2.

Genetics and trust

Traditional explanatory variables and genetics Q3 – Can genetics help explain the relation between “traditional” explanatory variables stock market participation, risk aversion, and beliefs? And if so, how much? Yes Across 11 variables ~ 40% genetic/60% non-genetic

Summing up… Genetic endowments associated with cognition, personality, health and body shape help explain variation in: Risk aversion Beliefs re the distribution of stock returns Owning stock About 30% of the relation between stock ownership and risk aversion and beliefs arises from the portion of risk aversion and beliefs explained by these eight genetic endowments About 40% of the relation between stock ownership and traditional explanatory variables arises from the “genetic” component (across the 11 variables)

Thank You!