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“Traditional finance is more concerned with checking that two 8 oz. bottles of ketchup is close to the price of one 16 oz bottle, than in understanding the price of the 16 oz bottle.” –Larry Summers

EMH adherents scream NO!!! to behavioral jumbo-mumbo Prices are right → no free lunch Two basic assumptions

• People make rational decisions

• People unbiased in predictions of the future Any inefficiencies will be arbitraged away quickly Based on risk and return

Traditional Finance – What is it?

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Should be low trading – Why is volume so high?• “The stock market is the best investment for long term

holders, who can just buy and hold through the ups and downs of the market.” – 76% strongly agree & 26% somewhat agree

Trade only on new info should mean low volatility Dividends shouldn’t matter Equity premium of 7% too high for just risk Short term momentum and long term reversion

shouldn’t exist

What do we observe?

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Positive news boosts depressed stocks more than “up” stocks

IPOs initially underpriced & underperform longer term WB, Legg Mason, et.al. are just 6-sigma flukes “Bubbles” happen frequently

• Cries of a “new paradigm”

• Book printed: Dow 35,000

• “We are in a new era. ____ has ushered in a new type of economy.

What do we observe?

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Predictability strongest in small, less liquid Liquidity can also make easier to arb away efficent Volume high in “up” markets and low in “down” Lowest decile based on B/M earns less than Rf

• Cries of a “new paradigm”

• Book printed: Dow 35,000

• “We are in a new era. ____ has ushered in a new type of economy.

Yes, even more observations

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Dow in 1896 = 40, 1998 = 9181. What would it have been if dividends were reinvested?

Piece of paper is folded in half, then half again. After 100 folds how thick will it be?

Compared with what you see on the street, how many are above average drivers?

A fair coin has come up “tails” four times in a row. What do you bet on next?

Equal chance win $19 vs. lose $20. Bet? Does it change if you are already up $200?

Time out for games

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You buy basketball tickets for $40. If it snows will you go? Now what if the tickets had been given to you?

Mary is librarian, Mary is librarian and member of Sierra, Mary works in banking.

More likely? Killed by falling airplane parts or by a shark?

Mean IQ of population of 5000 people is known to be 100. A sample of 50 is selected. The first IQ = 150. What is mean of sample?

Time out for games – the sequel

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Markets always efficient?• “…I’d be a bum on the street with a tin cup.”

Two features – limits to arbitrage and psychology Is it so hard to believe participant psychology

enters the transaction of financial assets? Yields insight into investments and how market

participants function Risk & return → Fear & Greed → Pride & Regret Prices reflect rational and irrational

Behavioral Finance – What is it?

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Not a sure-fire way to beat the market• “The market can stay irrational longer than you can stay

solvent” – JM Keynes

Does it mean anything in the aggregate? Does it matter or is it just wealth transfer from

stupid to smart? Isn’t a unified theory, just a collection of tools

Behavioral Finance – What isn’t it?

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Markets usually efficient Water seeks it own level = oceans are flat

• “…I’d be a bum on the street with a tin cup.”

Investors are basically bad Bayesians

Reconcile the two?

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Based on “Bounded rationality” Biases in heuristics

• Self Deception

• Reference points

• Representativeness

• Conservatism

• Cognitive dissonance

Kahneman & Tversky – Prospect Theory

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Overconfidence – belief personal knowledge (or illusion of it) is more accurate

Biased self-attribution – Good outcomes are ability, bad outcomes are someone else’s fault

= ex-post rationalization – Odean 1998• Individuals trade too much

• Buys do worse than sells and reluctant to sell losers

• Sold names returned 2.6% vs. .11% for replacements

• Men trade more than women and do worse

Self Deception

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Compare present to some point in past Purchase price Strike price of options Feeling of loss if down and elation if up Analyst forecast revisions – under reaction to new

information This oversimplification is why Buffett doesn’t look

at short term

Reference Points

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“ Law of small numbers” – heuristics problem Investors may let too little information drive their

decisions = beliefs change too quickly Overweight recent history→

• trend chasing or over-reaction to “hot hands”

• Like lemmings to the sea – ebay PE 3300 in 1999 or etoys mkt cap $8B vs. toys-r-us at $6B

• Could explain value outperforming growth

• Confuse good company with good investment

• Previous mention of short term focus in bubbles

Representativeness

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Flip side of the representativeness coin In face of new evidence, beliefs don’t change as

much as should Over-weight strength of signal, under-weight the

weight of signal E.g. a positive earnings surprise may take up to 60

days to fully incorporate

Conservatism

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Bad experiences are painful – try to ignore the pain rather than incorporate

Seek to reduce pain by adjusting beliefs about past successes

Cognitive Dissonance

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How Normal distribution is actually realized• Extreme tails underestimated.

• Intermediate tails overestimated

• Skewed right Diminishing sensitivity (will see graphically)

• Loss is convex, gains concave (double return/loss is not twice as good/bad)

• Losses hurt more in absolute than gains (steeper slope for losses)

• Kink at reference point

• Considered in isolation – no covariance Disposition effect – hold losers, sell gainers (see later)

Other parts of K & T theory(non-normal distribution & kink in utility curve)

How do the pieces fit? Pt.II

A large enough sample drawn from a normal distribution looks like a bell-shaped curve.

A large enough sample drawn from a normal distribution looks like a bell-shaped curve.

Probability

Return onlarge company commonstocks

99.74%

– 3 – 49.3%

– 2 – 28.8%

– 1 – 8.3%

Mean12.2%

+ 1 32.7%

+ 2 53.2%

+ 3 73.7%

The probability that a yearly return will fall within ± 1 standard deviation (± 20.5%) of the mean is approximately 68%.

68.26%

95.44%

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How do the pieces fit together?

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Gambler’s Fallacy Confirmation bias Mental Accounting Self deception

Other tools

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“Bad Bayesian” to the extreme A fair die had rolled 4 fours in a row. What’s the

chance of another 4? Mean reversion Confirmation Bias

• Side with opinions that support own view, ignore information contrary to that view

Gambler’s Fallacy & Confirmation Bias

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Kind of like a bunch of file folders in a file cabinet Transactions assigned to specific accounts then

evaluated in isolation (no covariance) Misperception of risk of adding another security to

portfolio Not just individuals. E.g. pension fund restrictions Sunk costs still seem to matter Dividends – don’t touch the principal

Mental Accounting – Thaler 1985

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House money – Investor factors in previous independent outcomes into current risky decision• Previous winner is willing to take on more risk

• Could partially explain bubbles

• “snake-bite” or “once-bitten” is the flip side (some investors from the 90s still haven’t returned)

In the extreme may take on “double or nothing” attitude to get to reference point• CBT Treasury futures traders if lose in morning, increase

risk in afternoon to get back

Mental Accounting – Thaler 1985

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Better than a poke in the eye with a sharp stick Disposition effect – Avoid losses, seek gains

• Exact opposite of tax code

• Ferris 88 – low volume for decliners, high for gainers

Chicago Merc – best futures traders sold losers and rode winners

Reference points – saw previously Want something to brag to friends about

Pride & Regret = Pain & Pleasure

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Averse to ambiguity Weather = mood –

• sunny days outperform miserable days by 24%

• Returns lower if less daylight – fall months, worse further north (England and Sweden) and reversed for southern hemisphere

• Important b/c price of stock usually set by optimists

• Disposition effect = avoid realizing paper losses and seek realizing paper gains (remember Odean)

Emotion, self-control and Decision

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Finance assumes “law of one price” holds Risks and Limits

• Arbitrage isn’t costless – may have to cover when misvaluations greatest = implementation costs

• Fundamental risk – may be a reason (private info) for pricing

• Noise trader risk worsens in short run – Royal Dutch/Shell

• Lots of investors can’t and others don’t want risk

• May not be able to identify peaks and troughs

• No good substitute – Palm/3com

• Closed end funds example

Limits to Arbitrage

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Is psychology even more important here? Assume managers will act in self interest, but they

may not be able to identify appropriate if biased. Are managers rational & unbiased Limited number → greater impact of bias Two ways to look at it: (probably a combo of both)

• Smart managers and dumb markets or

• Smart markets and dumb managers

Firm managers are people, too!

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Take advantage of investors? (rational manager)• IPO clusters or equity when overvalued – issue equity when

overvalued. Investors may not be able to short.

• CEOs judged on longer time frame – Managers can “spin” one bad quarter

• Dividend policy – catering viewpoint = Investors may interpret as good sign

• “Dot.com” – 1999 =74% announcement effect and 2001 70% for the reversal

• Earnings management

• Sticky dividends

Managers smart, markets dumb

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Reference points & mental accounting• IPO under pricing• Throw good money after bad

Bounded rationality• <10% of firms use NPV

Optimism and overconfidence• All CEOs are above average• mergers may not realize synergies (hubris)• capital budgeting projects may be overvalued• Too much cash leads to bad decisions

Biased self-attribution• Success is skill and failure is bad luck

Markets smart, managers dumb

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Be aware of predispositions and don’t fall prey Know your competition. (Incorporate their actions

into your plan) Understand how your firm’s managers might

perform

So what does it all mean for you?