An Introduction to Behavioral Finance

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An Introduction to Behavioral Finance

• SIP Course on Stock Market Anomalies and Asset
  Management
• Professors S.P. Kothari and Jon Lewellen
• March 15, 2004

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An Introduction to Behavioral Finance

• Efficient markets hypothesis
• Large number of market participants
• Incentives to gather and process information
  about securities and trade on the basis of their
  analysis until individual participants valuation
  is similar to the observed market price
• Prices in such markets reflect information
  available to the participants, which means
  opportunities to earn above-normal rates of
  return on a consistent basis are limited
• Prediction Stock returns are (almost) impossible
  to predict
• Except that riskier securities on average earn
  higher rates of returns compared to less risky
  firms

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An Introduction to Behavioral Finance

• Behavioral finance
• Widespread evidence of anomalies is inconsistent
  with the efficient markets theory
• Bad models, data mining, and results by chance
• Alternatively, invalid theory
• Anomalies as a pre-cursor to behavioral finance
• Challenge in developing a behavioral finance
  theory of markets
• Evidence of both over- and under-reaction to
  events
• Event-dependent over- and under-reaction, e.g.,
  IPOs, dividend initiations, seasoned equity
  issues, earnings announcements, accounting
  accruals
• Horizon dependent phenomenon short-term
  overreaction, medium-term momentum, and long-run
  overreaction

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An Introduction to Behavioral Finance

• Behavioral finance theory rests on the following
  three assumptions/characteristics
• Investors exhibit information processing biases
  that cause them to over- and under-react
• Individual investors errors/biases in processing
  information must be correlated across investors
  so that they are not averaged out
• Limited arbitrage Existence of rational
  investors should not be sufficient to make
  markets efficient

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Behavioral finance theories

• Human information processing biases
• Information processing biases are generally
  relative to the Bayes rule for updating our
  priors on the basis of new information
• Two biases are central to behavioral finance
  theories
• Representativeness bias (Kahneman and Tversky,
  1982)
• Conservatism bias (Edwards, 1968).
• Other biases Over confidence and biased
  self-attribution

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Behavioral finance theories

• Human information processing biases
• Representativeness bias causes people to
  over-weight recent information and deemphasize
  base rates or priors
• E.g., conclude too quickly that a yellow object
  found on the street is gold (i.e., ignore the low
  base rate of finding gold)
• People over-infer the properties of the
  underlying distribution on the basis of sample
  information
• For example, investors might extrapolate a firms
  recent high sales growth and thus overreact to
  news in sales growth
• Representativeness bias underlies many recent
  behavioral finance models of market inefficiency

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Behavioral finance theories

• Human information processing biases
• Conservatism bias Investors are slow to update
  their beliefs, i.e., they underweight sample
  information which contributes to investor
  under-reaction to news
• Conservatism bias implies investor underreaction
  to new information
• Conservatism bias can generate
• short-term momentum in stock returns
• The post-earnings announcement drift, i.e., the
  tendency of stock prices to drift in the
  direction of earnings news for three-to-twelve
  months following an earnings announcement also
  entails investor under-reaction

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Behavioral finance theories

• Human information processing biases
• Investor overconfidence
• Overconfident investors place too much faith in
  their ability to process information
• Investors overreact to their private information
  about the companys prospects
• Biased self-attribution
• Overreact to public information that confirms an
  investors private information
• Underreact to public signals that disconfirm an
  investors private information
• Contradictory evidence is viewed as due to chance
• Genrate underreaction to public signals

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Behavioral finance theories

• Human information processing biases
• Investor overconfidence and biased
  self-attribution
• In the short run, overconfidence and biased
  self-attribution together result in a continuing
  overreaction that induces momentum.
• Subsequent earnings outcomes eventually reveal
  the investor overconfidence, however, resulting
  in predictable price reversals over long
  horizons.
• Since biased self-attribution causes investors to
  down play the importance of some publicly
  disseminated information, information releases
  like earnings announcements generate incomplete
  price adjustments.

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Behavioral finance theories

• In addition to exhibiting information-processing
  biases, the biases must be correlated across
  investors so that they are not averaged out
• People share similar heuristics
• Focus on those that worked well in our
  evolutionary past
• Therefore, people are subject to similar biases
• Experimental psychology literature confirms
  systematic biases among people

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Behavioral finance theories

• Limited arbitrage
• Efficient markets theory is predicated on the
  assumption that market participants with
  incentives to gather, process, and trade on
  information will arbitrage away systematic
  mispricing of securities caused by investors
  information processing biases
• Arbitrageurs will earn only a normal rate of
  return on their information-gathering activities
• Market efficiency and arbitrage EMH assumes
  arbitrage forces are constantly at work
• Economic incentive to arbitrageurs exists only if
  there is mispricing, i.e., mispricing exists in
  equilibrium

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Behavioral finance theories

• Behavioral finance assumes arbitrage is limited.
  What would cause limited arbitrage?
• Economic incentive to arbitrageurs exists only if
  there is mispricing
• Therefore, mispricing must exist in equilibrium
• Existence of rational investors must not be
  sufficient
• Notwithstanding arbitrageurs, inefficiency can
  persist for long periods because arbitrage is
  costly
• Trading costs Brokerage, B-A spreads, price
  impact/slippage
• Holding costs Duration of the arbitrage and cost
  of short selling
• Information costs Information acquisition,
  analysis and monitoring

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Behavioral finance theories

• Why cant large firms end limited arbitrage?
• Arbitrage requires gathering of information about
  a firms prospects, spotting of mispriced
  securities, and trading in the securities until
  the mispricing is eliminated
• Analysts with the information typically do not
  have the capital needed for trading
• Firms (principals) supply the capital, but they
  must also delegate decision making (i.e.,
  trading) authority to those who possess the
  information (agents)
• Agents cannot transfer their information to the
  principal, so decisions must be made by those who
  possess information
• Agents are compensated on the basis of outcomes,
  but the principal sets limits on the amount of
  capital at the agents disposal (the book)
• Limited capital means arbitrage can be limited

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Behavioral finance theories

• Like the efficient markets theory, behavioral
  finance makes predictions about pricing behavior
  that must be tested
• Need for additional careful work in this respect
• Only then can we embrace behavioral finance as an
  adequate descriptor of the stock market behavior
• Recent research in finance is in this spirit just
  as the anomalies literature documents
  inconsistencies with the efficient markets
  hypothesis

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Stock Returns, Aggregate Earnings Surprises, and
Behavioral Finance
 S.P. Kothari, Jonathan Lewellen, Jerold B.
Warner     SIP Course on Stock Market Anomalies
and Asset Management March 15, 2004
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Objective of the study

• We study the relation between market index
  returns and aggregate earnings surprises
• We focus on concurrent and lagged surprises
• Do prices react slowly?
• Is there discount rate information in aggregate
  earnings changes?

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Motivation

• At the firm level, post-earnings announcement
  drift is well-known
• The slow adjustment to public information is
  inconsistent with market efficiency
• Slow adjustment is consistent with behavioral
  finance
• Barberis/Shleifer/Vishny (BSV, 1998)
• Daniel/Hirshleifer/Subrahmanyam (DHS, 1998)
• Hong/Stein (HS, 1999)
• Aggregate return-earnings relation serves as an
  out-of-sample test of the behavioral hypothesis
  of investor underreaction
• Literature concentrates on cross-sectional return
  predictability
• We provide time-series evidence

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Main findings

• Aggregate relation does not mimic the firm-level
  relation
• Market returns do not depend on past earnings
  surprises
• Inconsistent with underreaction (or overreaction)
• Market returns are negatively (not positively)
  related to concurrent earnings news
• s seem economically significant
• Earnings and interest/ discount rate shocks are
  positively correlated
• Good aggregate earnings news can be bad news
• Decomposing earnings changes does not fully
  eliminate the negative correlation between
  earnings news and returns, a troubling result

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Firm level drift and behavioral models

• Drift could occur if investors systematically
  ignore the time-series properties of earnings.
• Bernard/Thomas (1990) show that quarterly
  earnings changes have positive serial dependence
  (.34,.19,.06 at the first 3 lags)
• If investors underestimate the dependence, prices
  will respond slowly and they will be surprised by
  predictable changes in earnings.
• Consistent with this, the pattern of trading
  profits at subsequent earnings announcements
  matches the autocorrelation pattern.

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Evidence

• Time-series properties of earnings
• Stock returns and aggregate earnings surprises
• Returns, earnings, and discount rates

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Earnings series

• Compustat Quarterly database, 1970 2000
• NYSE, Amex, and NASDAQ stocks with
• Earnings before ext. items, quarter t and t 4
• Price, quarter t 4
• Book value, quarter t 4
•  Plus
• December fiscal year end
• Price gt 1
• Exclude top and bottom 0.5 based on dE/P

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Sample
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E/P, 1970 2000
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Firms w/ positive earnings, 1970 2000
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Quarterly earnings changes (), 1970 2000
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Aggregate earnings growth, 1970 2000
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dE scaled by lagged price, 1970 2000
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Autocorrelations

• Seasonally-differenced earnings (dE Et Et-4)
• Estimation 
• dE/St ?0 ?k dE/St-k ?t 
• dE/St ?0 ?1 dE/St-1 ?2 dE/St-2 ..
  ?5 dE/St-5 ?t
• Market Time-series regressions
• Firms Fama-MacBeth cross-sectional regressions

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Autocorrelations, dE/P, 1970 2000
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Implications

• Basic message
• Pattern similar for firms and market
• Persistence stronger for market good for tests
• Specifics
• Transitory, idiosyncratic component in firm
  earnings
• Aggregate earnings changes are permanent
• Earnings changes predictable but volatile (?
  18.6)
• AR1 similar to AR5

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Returns and earnings surprises

• Rtk ? ? dE/Pt etk
•  k 0, , 4
•  Changes and surprises
•  Market Time-series regressions
•  Firms Fama-MacBeth cross-sectional regressions

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Returns and earnings, 1970 2000
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Contemporaneous relation

• Explanatory power 4 8 
• Fitted values dE/P-vw
• Std. dev. of earnings surprises 0.25
• Slope 10.10
• Two std. deviation shock ? 5 drop in prices
•  Historical
• Earnings change in top 25 return ? 1 (s.e.
  1.7)
• Earnings change in bottom 25 return ? 7 (s.e.
  1.6)

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Contemporaneous relation

• Early overreaction
• No theory
• Not in firm returns 
• Movements in discount rates 
• Rt ?d,t ?r,t
• Cash flow news vs. expected-return news

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Returns and past earnings

• Zero to negative
• No evidence of under-reaction
• Inconsistent with behavioral theories
• Results are robust
• Alternative definitions of earnings
• Subperiods
• Annual returns and earnings
• Subsets of stocks (size, B/M terciles)

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Summary observations

• Large portfolio
• Earnings more persistent
• Initial market reaction more negative
• Puzzling from a cashflow-news perspective
• Small portfolio
• Reversal at lag 4
• Negatively related to CRSP, but not own returns

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Earnings and discount rates

• Rt ?d,t ?r,t
• ?d,t cashflow news
• ?r,t expected-return news discount-rate news
• Returns and earnings
• cov(dEt, Rt) cov(dEt, ?d,t) cov(dEt, ?r,t)
• cov(dEt, ?r,t)?
• inflation and interest rates ()
• consumption smoothing ()
• changes in aggregate risk aversion ()

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Earnings and the macroeconomy, 1970 2000
Correlations
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Earnings and the macroeconomy, 1970 2000
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Controlling for discount rates

• Two-stage approach
• dEt ? ? ?TBILLt ? ?TERMt
• ? ?DEFt ? dEt-1 ?
• Rtk ? ? Fitted(dEt) ? Residual(dEt) etk
• Timing?
• Rt Rt1 Rt2 Rt3 Rt4
• dEt

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Returns and earnings, 1970 2000
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Annual dE/P, 1970 2000
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How big are the effects?

• Over the last 30 years, CRSP VWT portfolio
• Increased 6.5 in value in the quarters with
  negative earnings growth
• Increased 1.9 in value in quarters with positive
  earnings growth

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Conclusions

• Markets reaction to earnings surprises much
  different at the aggregate level
• Negative reaction to good earnings news
• Past earnings contain little (inconsistent)
  information about future returns
• Investment strategy Long in quarters when
  aggregate earnings changes are negative
• Open questions
• Do earnings proxy for discount rates?
• Is there a coherent behavioral story for the
  patterns?

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Richardson and Sloan (2003) External Financing
and Future Stock Returns

• Prior evidence Market is sluggish in rationally
  incorporating information in managers market
  timing motivation for external financing
• Market timing Raise funds when the firm is
  overvalued and repurchase shares when the firm is
  undervalued.
• Slow assimilation of the information can be
  because of investors information processing
  biases
• Sluggish reaction means opportunities for
  abnormal returns
• How large are the returns to a trading strategy?
• What is the source of the abnormal returns? Is
  it related to the use of proceeds from external
  financing?
• Richardson and Sloan Examine returns to a
  trading rule based on net external financing (not
  individual decisions like share repurchasing)

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Returns following external financing

• Prior evidence
• Low returns following equity offerings, debt
  offerings, and bank borrowings
• High returns following share repurchases
• Managers seem to time external financing
  transactions to exploit mispricing
• Markets immediate reaction to the financing
  decisions is incomplete (underreaction to public
  announcements of voluntary decisions)
• Market gradually reacts over the following
  one-to-three years inconsistent with market
  efficiency and consistent with some of the
  information-processing biases

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Returns following external financing

• Richardson and Sloan show that
• Net external financing generates a 12-month
  abnormal return of about 16 (Table 5)
• The return is on long-minus-short position that
  has a zero initial investment
• Long position is in firms that raise the least
  external financing (i.e., repurchase shares or
  retire debt)
• Short position is in firms that raise the most
  external financing issue equity or debt or
  borrow from a bank

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Returns following external financing

• Richardson and Sloan show that
• Use of the proceeds from external financing
  matters (Table 6)
• Investment in operating assets generates highest
  return on the zero-investment portfolio
• Suggests managers over-invest in assets
• Market fails to fully assimilate information in
  accruals
• What are accruals?
• Earnings (X) CF Accruals (A)
• When you sell on credit, earnings increase, cash
  flow does not, but accruals in the form of
  accounts receivables increase
• Investment in operating assets is a form of
  accrual

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Returns following external financing
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Returns following external financing

• External financing decisions as well as
  exceptional corporate performance (high sales
  growth or extreme decline) are all associated
  with large accruals
• A large increase in sales translates into a large
  increase in receivables, so an accrual increase
  is associated with increased sales
• Accruals also present opportunities to the
  management to manipulate them and/or create them
  fictitiously
• A fictitious dollar of sales and receivables
  accruals contributes dollar for dollar to
  earnings before taxes and also enhances profit
  margin (because the cost of goods sold is not
  increased with fictitious sales)

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Returns following external financing

• Since extreme performance or financing activities
  or fictitious sales are typically not
  sustainable, accruals revert
• If investors suffer from information processing
  biases, do they recognize the time-series
  properties of accruals and its implications for
  future earnings?
• In particular, does the market recognize that
  The persistence of current earnings is
  decreasing in the magnitude of accruals and
  increasing in cash flows?
• Market overvalues accruals (i.e., fails to
  recognize that accruals-based earnings are not
  permanent)
• Trading strategy implication Long in low accrual
  stocks and short in high accrual stocks to
  generate above-normal performance.
• Trading strategy based on external financing is
  based on accruals raise capital means high
  accruals means go short

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Conclusions

• Investors exhibit many behavioral biases
• If the biases are similar across individuals and
  arbitrage forces are limited, then the behavioral
  biases can cause prices to deviate systematically
  from economic fundamentals
• Recent attempts to test the effects of behavioral
  biases in stock price data
• Aggregate earnings data and stock returns
• Individual firms financial data and stock
  returns
• Stock returns associated with external financing
  decisions
• Stock returns due to investors alleged inability
  to process information in accounting accruals
• Next set of issues
• How large is the mispricing? Can it be exploited?
  What are the barriers to implementation and what
  are the implications for asset management?