Psychology and Behavioral Finance

Outline

What is behavioral finance? A list of behavioral features/quirks Herding behavior Does this all explain bubbles?

Behavioral Finance

Acknowledges that investors are not perfectly rational

Allows for psychological factors of behavior Applies results from experiments on risk

taking

Behavioral Quirks

We all make mistakes Laboratory experiments indicate that these

can follow consistent patterns

Questions About Quirks

Do they apply in the real world (outside the laboratory)?

Do they aggregate?

Top Behavioral Issues for Finance

Overconfidence Loss aversion/house money Anchoring/representativeness Regret Mental accounting Probability mistakes Ambiguity Herd behavior

Overconfidence

Driving surveys: 82% say above average New businesses

Most fail Entrepreneurs believe 70% chance of success Believe others have 30% chance of success

Investors believe they will earn above average returns

Overconfidence and Investor Behavior

Conjecture: Overconfident investors trade more (higher turnover) Believe information more precise than is

Psychology: Men more overconfident than women

Data: Men trade more than women Data: High turnover traders have lower

returns (net transaction costs)

Overconfidence and Risk taking

Overconfident investors take more risk Higher beta portfolios Smaller firms

Loss Aversion/House Money

House money More willing to risk recent gains

Loss aversion More risk averse after a recent loss General heavier weight on losses

(not mean-variance)

Difficulty : Aggregation

Anchoring/Representativeness

Arbitrary value that impacts decision Information shortcut Quantitative anchor

Current stock price, or recent performance Price of other stocks Loss aversion

Representativeness/familiarity Story telling Qualities of good companies Own company/local phone companies/home bias

Status Quo Bias (401K matching funds)

Regret

Pain from realizing past decisions were wrong Disposition

Investors hold losers too long, and Sell winners too soon Evidence: Higher volume on recent winners, lower for

losers Real estate: Sellers with losses set higher initial bid prices/

wait longer to sell

Impact on bubbles?

Regret

“My intention was to minimize myfuture regret. So I split my contribution

50/50 between bonds and stocks.”

Harry Markowitz

Mental Accounting

You can go on vacation. Would you like to pay for it with $200 month for the 6 months before the vacation $200 month for the 6 months after the vacation

Probability

Difficult for humans Conditional probabilities harder

Information -> Decisions

Uncertainty/ambiguity

Probability Mistakes

Medical tests DNA evidence Sports Game shows (Monty Hall)

Linda is 31 years old, single, outspoken, and very bright.She majored in environmental studies. She is an avid hiker,and also participated in anti-nuclear rallies.

Which is more likely?A.) Linda is a bank teller.B.) Linda is a bank teller and a member of Green Peace.

Gambler’s FallacyLaw of Small Numbers

Decisions made on short data sets Hot Hands Mutual funds

Patterns seen in short data sets Technical trading

Is this really irrational? Econometrics and regime changes “New Economy”

Ambiguity: Risk and Uncertainty

Risk: Know all probabilities Uncertainty: Probabilities are not known Knight/Ellsberg

"Knightian uncertainty"

Casinos versus stock markets Securitized debt markets

Donald Rumsfeld on Ambiguity

“Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns — the ones we don't know we don't know.”

Herding

Group technologies News media Personal contacts Telephones (20’s) Internet (90’s) Investment clubs

Investors watch what others our doing and investing in more than fundamentals

Internet Stocks and Herding

eToys versus Toys R Us Toys-R-Us

Market value $6 billion Earnings $376 million

eToys Market value $8 billion Earnings -$28 million, sales $30 million

Experiments

Asch experiments: obvious wrong answers (repeated with out physical proximity)

Milgram and authority Candid camera elevators

Information Cascades

Restaurant A versus B Does the right restaurant survive?

Epidemics and information Infection rate, removal rate Logistic curve Messy in finance and social systems (doesn’t work like a

disease) Theory of mind

Lot’s of hypotheses Narrow down to those others have

Summary

Humans often behave in somewhat irrational fashions Especially when uncertainty is involved

Key questions remain Aggregation Bubbles Investment strategies

Keep in mind: The real world is very complex