Behavioral Finance
Content
Behavioral Finance
Dr. Kumar Bijoy
Financial consultant
[email protected]
09810452266
Behavioral economics
• Behavioral economics: study the effects of
Social, cognitive, and emotional factors on
the economic decisions of
individuals
and
institutions and the consequences for market
prices, returns, and the resource allocation.
The fields are primarily concerned with
the bounds of rationality of economic agents.
• Behavioral
models: typically
integrate
insights from psychology with microeconomic
theory; in so doing, these behavioral models
cover a range of concepts, methods, and
fields.
Behavioral Finance
• According to Ritter (2002), the
foundation of the behavioral finance
is laid on two factors:
– ‘Cognitive Psychology’ (people’s way of
thinking)
– ‘limits to Arbitrage’ (effectiveness of
arbitrage in different circumstances)
Behavioral philosophy
• “Market in which security prices fully incorporate or
reflect any available information” …Fama (1970)
• “Foundation of Market Efficiency”… Andrei Shleifer
– Rationality: all investors are considered to be rational
and will adjust their estimates as soon as the new
information is released in an efficient and rational way
– Independent deviation from rationality: the excess
optimism or pessimism (i.e. irrationalities) of the investors
for some stocks that leads to offsetting the prices (due to
the assumption of “countervailing irrationalities”) and
hence produces market efficiency (Ross et al. 2008)
– Arbitrage: profit from mispricing
Classical Vs Behavioral
Finance
• Classical finance assumes full rationality,
thus cannot explain many price patterns
• Behavioral finance emerged in the 90s to
perfect the insights of mathematical finance.
• Using insights from all behavioral sciences
(cognitive neuroscience, psychology, sociol
ogy) on how real people depart from the
rational model — real people are boundedly
rational, behavioral finance can rationalize
hitherto-puzzling price patterns.
Behavioral Finance Definitions
Behavioral Finance, a study of investor market behavior that
derives from psychological principles of decision making, to explain
why people buy or sell the stocks they do.
The linkage of behavioral cognitive psychology, which studies
human decision making, and financial market economics.
Behavioral Finance focuses upon how investors interpret and act
on information to make informed investment decisions.
Investors do not always behave in a rational, predictable and an
unbiased manner indicated by the quantitative models. Behavioral
finance places an emphasis upon investor behavior leading to
various market anomalies.
Behavioral Finance Promise
Behavioral Finance promises to make economic models better
at explaining systematic (non-idiosyncratic) investor
decisions, taking into consideration their emotions and
cognitive errors and how these influence decision making.
Behavioral Finance is not a branch of standard finance; it is its
replacement, offering a better model of humanity.
Create a long term advantage by understanding the role of
investor psychology
Human flaws pointed out by the analysis of investor
psychology are consistent and predictable, and that they
offer investment opportunities.
Precursors to Behavioral Finance
Value investors proposed that markets over reacted to negative news.
Benjamin Graham and David Dodd in their classic book, Security Analysis,
asserted that over reaction was the basis for a value investing style.
David Dreman in 1978 argued that stocks with low P/E ratios were
undervalued, coining the phrase overreaction hypothesis to explain why
investors tend to be pessimistic about low P/E stocks.
Tversky and Daniel Kahneman published two articles in 1974 in Science.
They showed heuristic driven errors, and in 1979 in Econometrica, they
focused on representativeness heuristic and frame dependence.
Two Important Studies
•
Are equity valuation errors are systematic and therefore predictable?
–
–
–
•
Werner De Bondt and Richard Thaler 1985
–
–
•
Efficient markets view: prices follow a random walk, though prices fluctuate to
extremes, they are brought back (regression to the mean) to equilibrium in time.
Behavioral finance view: prices are pushed by investors to unsustainable levels
in both directions. Investor optimists are disappointed and pessimists are
surprised. Stock prices are future estimates, a forecast of what investors expect
tomorrow’s price to be, rather than an estimate of the present value of future
payments streams.
Early studies focused on relative strength strategies that buy past winners and
sell past losers
Investor Overreaction Hypothesis opposes Efficient Markets Hypothesis
Rejection of Regression to the Mean which says prices operating in the context of
extreme highs and lows balance each other
Shefrin and Statman 1985
–
–
Disposition Effect suggests investors relate to past winners differently (they keep
winners in their portfolio) than past losers (they sell past losers)
Odean applied the Disposition Effect in vivo context
Werner De Bondt and Richard Thaler 1985
study
De Bondt and Thaler extended Dreman’s reasoning to
predict a new anomaly.
They refer to representativeness, that investors become
overly optimistic about recent winners and overly
pessimistic about recent losers.
• They applied Tversky and Kahneman’s
representativeness to market pricing
– Overweight salient information such as recent
news
– Underweight salient data about long term
averages
• Investors overreact to both bad news and good news.
De Bondt and Thaler Study
Robert Shiller proposed prices show excess volatility.
That is, dividends do not vary enough to rationally justify
observed aggregate price movements
In spite of dividends, investors seem to attach
disproportionate importance to short run economic
developments.
Two Hypotheses: Each a violation of weak form market
efficiency.
1. Extreme movements in stock prices will be followed by
subsequent price movements in the opposite direction.
2. The more extreme the initial price movement, the
greater will be the subsequent adjustment.
De Bondt and Thaler 1985 study (cont)
Overreaction leads past losers to become
under priced and past winners to become
overpriced.
De Bondt and Thaler propose a strategy of
buying recent losers and selling recent
winners. Investors become too pessimistic
about past losers and overly optimistic
about past winners.
De Bondt and Thaler 1985 study (cont)
De Bondt and Thaler studied two portfolios of 35 stocks
One consisting of past extreme winners over the prior three years
One consisting of past extreme losers over the prior three years
Past losers subsequently outperformed winners over the next four
years.
Past losers were up 19.6 percent relative to the market in general.
Past winners were down five percent relative to the market in
general.
A difference of 24.6 percent between the two portfolios.
Study suggests that investors cause market prices to deviate from
fundamental values creating inefficient markets:
due to
representativeness heuristic markets’ treatment of past winners
and losers is not efficient.
De Bondt and Thaler study
Other Findings:
1. The overreaction effect is asymmetric: it
is much larger for losers than winners.
2. Most of the excess returns are realized in
January. (16.6% of the 24.6%)
3. The overreaction phenomenon mostly
occurs during the second and third year of
the test period. (By the end of the first year
the difference in the two portfolios is a
mere 5.4%)
Critics of De Bondt and Thaler 1985 study
Reversion to the mean explanation offered by Malkeil
consistent with efficient markets hypothesis
Zsuzsanna Fluck, Richard Quandt, and Malkeil study
Simulated an investment strategy of buying stocks
which had poor recent two or three year
performance.
They found: in the 1980s, 1990s, those stocks did
enjoy improved returns in the next period of time,
but they recovered only to the average stock
market performance.
It was a statistical pattern of return reversal, but to
appropriate levels (they did not overshoot levels).
More Critics
Two alternative Hypotheses: to overreaction.
1. Risk Change Hypothesis: overreaction is rational
response to risk changes (short term earnings outlook
changes) as measured by Betas
2. Firm size: past loser portfolio made up of small firms
Disturbing factors
1. Seasonal pattern of returns (January “turn of the
year” effect)
2. The characteristics of the firms in the portfolios
(Small size)
3. Co-relation is asymmetric
De Bondt and Thaler’s response
The data do not support either of these explanations. It
is emotional shifts in mood of investors—biased
expectations of the future, not rational shifts in
economic conditions
But what about?
Jegadeesh demonstrated shorter term reversals:
one week or one month
though these results are “transaction intense”
Grinblatt and Titman 1989, 1991 relative strength
strategies: they showed a tendency to buy stocks
that have increased in price over the previous
quarter, based on past relative strength
Integrating results
Contrarian strategies work with
1. Very short periods (one week, one month)
2. Very long periods (3 to 5 years)
Growth (relative strength strategies) work with three to 12 months
Jegadeesh and Titman (1993) studied period 1965-89 found:
three to 12 months earned average of 9.5% (six months earned
12%)
then reversals, 12-24 months lost 4.5%
for earnings announcements:
past winners earned positive returns for the first seven months
past losers earned positive returns for 13 month period
assessment
Dreman’s research
•
•
•
•
Sample of 1500 largest stocks, each over a billion in capitalization
Develop a portfolio of stocks with low P/E ratio
Portfolio established in 1970
By 1997 portfolio grew from $10,000 to $909,000 while the market
benchmark was $326,000.
Contrarian portfolios did better in down markets
During down quarters over the years, market averaged down 7.5%;
Contrarian portfolio down 4%
Dreman emphasized the importance of reinforcing events and “event
triggers” creating perceptual change
• Positive Surprises are very favorable for unpopular stocks (not so
for popular stocks)
• Negative Surprises are very consequential for popular stocks (not
so for unpopular stocks)
What it means?
Consistent with “positive feedback traders” hypothesis on market
price
Market under reacts to information about the short term prospects
of firms but overreacts to information about their long term
prospects
This is plausible given that the nature of the information
available about a firm’s short term prospects, such as earnings
forecasts, is different form the nature of the more ambiguous
information that is used by investors to assess a firm’s longer
term prospects
David Dreman: Contrarian strategies do better than the market
over time
Importance of earnings surprises on popular and unpopular
stocks reveals a market sentiment is significant
Specific over and under market reactions
Markets over react to IPOs
Markets under react to: earnings announcements,
dividend announcements, open market share
repurchases, brokerage recommendations
Investors systematically under weight
(conservative):
abstract, statistical, and highly relevant
information,
while they over weight (representativeness
heuristic)
salient, anecdotal, and extreme information
Explanations/Theories for Under and Over
reaction
Kent Daniel, David Hirshleifer and
Avanidhar Subrahmanyam:
“Investor Overconfidence and biased self
attribution”
Variations in investor confidence which is an
over estimation of ability to value stocks
and predict future prices arising from biased
self attribution
which is confirming information in the public
arena
encourages
but
disconfirming
information does not discourage, (blames
Daniel, Hirshleifer and Subrahmanyan (cont)
• Shifts in investors’ confidence cause
– Negative long lag auto correlations (Contrarian
strategies)
– Excess volatility relative to fundamentals
(variance)
– Predictability about future prices
• Shifts in investors’ self attribution cause
– Short lag autocorrelation (momentum
strategies)
– Short run earnings drift in the direction of
earnings surprise
– Abnormal stock performance in the opposite
direction of long term earnings changes.
(Negative correlation between future returns
Daniel, Hirshleifer and Subrahmanyan (cont)
Theory is based on investor overconfidence, and on
changes in confidence resulting from biased self
attribution of investment outcomes
– Investors will overreact to private information
signals creates momentum in price (either
absent public information to support price, or
assuming public information confirm private
signals, or….
• Investors will under react to public information
signals (avoids correction in stock price until it
goes to extreme)
Unlike noise trader approach, this theory posits that
investors misinterpret genuine new private
information.
Explanations/Theories (cont)
Barberis, Shlieifer and Vishny 1998 : Learning model
explanation
Actual earnings follow a random walk, but individuals believe
that earnings follow either a steady growth trend, or else
earnings are mean reverting.
Representativeness heuristic (finds patterns in data too readily,
tends to over react to information) and conservatism (clings to
prior beliefs, under reacts to information).
Interaction of representativeness heuristic and conservatism:
explains short term under reaction and long term over reaction
Investor’s reaction to current information condition on past
information. Investor tends to under react to information that is
preceded by a small quantity of similar information and to over
react to information that is preceded by a large quantity of
similar information.
Explanations/Theories (cont)
Hong and Stein 1997
Under and Over reactions arise from the
interaction of momentum traders and
news watchers
Momentum traders make partial use of the
information continued in recent price
trends, and ignore fundamental news
Fundamental
traders
rationally
use
fundamental news but ignore prices.
Explanations/Theories (cont)
Bloomfiled, Libby and Nelson
Traders
in
experimental
markets
undervalue the information of others
People with evidence that is favorable but
unrealizable
tend
to
overreact
to
information, whereas people with evidence
that is somewhat favorable but reliable
under react
Optimism, Overconfidence, and Odean’s
Research
People are overly optimistic
• People believe that they are less likely to get hit by a bus
or be robbed than their neighbors
People are overconfident in their own abilities
• Driving skills and social skills are better
• New business owners believe their business has a 70%
chance of success, but only 30% succeed
• Helps soldiers cope with war
Overconfidence and the stock market
• Overconfidence can lead to substantial losses when
investors overestimate their ability to identify the next
Microsoft or Amazon
• Securities that investors purchase under perform those
they sell
Benartzi, Kahneman and Thaler survey on
Overconfidence
Survey of Morningstar 1053 subscribers
• 84% male, average age is 45, annual in come $93,000
• Average allocation to stocks is 79%
• Optimism question:
– Thinking about financial decisions, do you spend more time
thinking about the potential return or the possible loss?
– What do you think is the likelihood of stocks outperforming
bonds in the long run?
• Overconfidence and Optimism decided by
– Answer to the question about likelihood of stocks
outperforming bonds
– Asset allocation of retirement contributions of stocks vs.
bonds
Odean’s study of overconfidence in the
marketplace
What happens in financial markets when people are
overconfident?
• Trading volume increases: overconfidence generates trading.
Those who trade more frequently fare worse than those who
trade less
• Overconfident traders hold under-diversified portfolios; riskier
portfolios though they have the same degree of risk aversion
• Overconfident insiders improve price quality; overconfident
noise traders worsen it
• Men are more overconfident than women; men trade more
frequently (45% more) than women, men earn less returns
than women (one percent less).
• Single men and single women the results are larger (67%
more trading, 1.4% less)
Trading Behavior and Returns
Individual investors who hold common stock directly pay a
tremendous performance penalty for active trading
• Odean study “trading can be hazardous to your wealth”
– Studied 66,465 households from 1991 to 1996
– Most frequent traders earn 11.4% (turn over 75% of
portfolio)
– Average household earned 16.4%
– Market benchmark was 17.9%
• Odean study on On line traders
– Studied 1607 traders on line, compared with 1607
telephone traders
– On line traders experienced strong performance prior to
going on line
– After on line, less profitable, lagging the market by three
points
– Explained by overconfidence, self attribution bias, illusion
Overconfidence and the Disposition Effect
Investors
weight
recent
observations
too
heavily
(representativeness heuristic)
Investors under weight prior information
Investors commit the gambler’s fallacy: expecting recent events
(downturns in stock prices) to reverse
Disposition effect: Investors hold on to losers in their portfolio
(because they can’t be wrong), and sell winners.
Investors judge their decision on the basis of the returns realized
not paper money returns, then holding losers will avoid
confronting their true abilities.
Investors won’t learn from mistakes, continue as overconfident.
Odean’s research confirms Disposition Effect
Odean looks at trading decisions of investors at discount
brokerage
Stocks traders buy under perform those that they sell
Level of Over-confidence changes
dynamically
Depending upon the success or failure, level
of overconfidence changes
• A trader is not overconfident when he
begins to trade
• Overconfidence increase over his first
several trading periods early in his career
– These overconfident traders survive the
threat of arbitrage, that is, they are not
the poorest traders
– Initial success increases overconfidence
• Overconfidence declines thereafter
two types of investors
• Irrational amateurs: that tend to
carry stock at prices different from
the efficient prices because of their
wrong notions of stocks to be under
or overvalued.
• Rational professionals: that
predicts the nature of the stocks
efficiently, clearly and come to some
conclusions
Factors….
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Age
Education
Experience
Wealth
Mood
Gender
Profession
Liability
Society
Availability
Economy
Behavioral Finance Models
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Rational behavior
Over and Under-reaction
Mental Compartments
Over Confidence
Disjunction Effect (Cognitive Psychology or
anomalies)
Prospect theory
Expected Utility Theories
Momentum
Technical analysis
Contrarian strategies
Cognitive Psychology
• Overconfidence:
– Too little Diversification… Ritter (2002)
– According to Ross (1987), “overconfidence can
be clearly related to some deep-set
psychological phenomena” or even to some
broader complexity like “incapability of making
adequate allowance for the uncertainty in
one’s own view”, “a more global difficulty tied
up with multiple mental processes”
– “representativeness heuristic”…Tversky and
Kahneman (1974)
Overreaction:
• The reason behind the low returns on Glamour stocks
{Stocks with high returns in the past (3-5 years) and
are more preferred by the investors} as compared to
the Value stocks {Stocks with low returns in the past
(3-5 years) and are not generally preferred by the
investors} in the future is because of the overreaction
of the investors…. DeBondt and Thaler (1985)
• Firms list their stocks to take advantage of the
market’s overreaction arises because of their recent
superior performance” (Dharan and Ikenberry (1995);
Fama (1993)
• “price-ratio”
hypothesis
.According
to
which
companies with high P/E are considered to be
“Overvalued”
• Volatility of stock: overreaction of the investors is
one of the possible reason behind the frequent
movement of security prices following stock splits
(Ohlson and Penman (1983), Jain (2011)) and
initial public offerings (Ibbotson and Ritter (1988)
and Ritter (1991)
• People/investors “Overreact to unexpected and
Dramatic news” which is in violation of Bayes’
rule (DeBondt and Thaler (1985)
Under reaction:
•
“Momentum effect”- This is because investors
think the earnings to be mean-reverting resulting in
under reaction whenever any change in earnings
occurred but when at a later stage, they prove to be
wrong then stock prices exhibit a slow response to
the earnings announced in the past (Barberis,
Shleifer and Vishny (1998)
• “Principle of Conservatism” (coined by Edwards
(1968)) . According to which if any change occurs,
individual tend to take time in order to adjust to that
change and hence underreacts (Ritter (2002)
Disjunction Effect:
• It can be defined as the propensity for the
people/investors to wait until they know everything
about the market or the subject whether or not the
information is of prime importance to oneself and if that
information will make any difference in the decision
making or not (Shiller (2001)).
• According to Savage (1954), “disjunction effect is a
contradiction to the sure-thing principle of rational
behavior”.
• Disjunction effect explains the volatility of
speculative stock prices after or before
announcement occurs (Shafir and Tversky (1992)
the
any
Mental Compartments
• Planning and Budgeting
• “people think naturally on the “safe” part of the
investment i.e. protected against the downside
risk and “risky “part of the investment is planned
to earn higher abnormal return to become rich”-Shefrin and Statman (1994)
• January effect: January is the month in which
maximum stock prices appreciation can be seen
as individual treats January to be the starting of
their new investments researched in as many as
15 countries (Gultekin and Gultekin (1983)
Expected Utility and Prospect
Theory
• “it offers economical representation of
truly rational behavior under uncertainty”
(Shiller (2001)
• it has “systematically mispredicted human
behavior” (Shiller (2001); Allais (1953)
• according to the prediction of the
Expected Utility Theory, this should not
happen and individuals were supposed to
stick to their preferences as the certainty
increases not the price.
Prospect Theory
• Prospect Theory can be defined as a
mathematically formulated theory that
substitutes
“weights”
instead
of
“probabilities” and “value function” instead
of “utility function” in expected utility theory.
• In Prospect Theory, individuals are working
to maximize the weighted sum of value
rather than utility whereby weights are not
equal to probabilities (Kahneman and
Tversky (1979); Shiller (2001)
• according to this theory, (in the previous example
given by Allais (1953)) people will assign very high
weight to event which is very certain and little
weight to event which is not very certain
irrespective of the price/constant to be the same
• “Human behavior towards risk” can also be studied
by replacing probabilities with weights in the
expected utility theory. For example “public
enthusiasm for high price lottery with low winning
probability and hence low expected payout”
(Kahneman and Tversky (1979)) or “overpaying for
airline flight insurance”
Limits to Arbitrage
• “A market with millions of small arbitrager taking large
number of tiny positions can make the market efficient
by making the price to drive towards the fundamental
value in different markets” (Fama (1965); Sharpe (1964)
and Ross (1976)
• According to “limits to Arbitrage” as there are some
investors that buys the overpriced and sell the
underpriced securities in turn disturbing the parity
condition in the short run and hence giving losses to the
arbitrager which restricts them to take small position
because of the risk perception (Ross et al. 2008)
• Arbitraging activities are also limited because of the
capital requirements, lack of perfect knowledge and the
risk involved to make the markets efficient and hence is
one of the anomalies of ‘Efficient Markets
Trading Strategies
• Momentum Trading Strategy: buying past
winners and selling past losers”),
• Technical Trading Strategy: buy when ‘buy
signal’ emits and sell to hold cash when ‘sell
signal’ emits
• Contrarian Trading Strategy: also known
as “Value strategies” which is opposite to
momentum strategy i.e. “buying past losers
and selling past winners” to avoid herding with
the other participants in the stock market
Why so desperate
CAD
Depreciating
INR
Falling GDP
Fiscal
deficit
Unemploy
ment
Inflation
Why so
desperate
THERE IS NO REASON TO BE DISAPPOINTED . INDIA WILL PROGRESS
VERY FAST AND THE SKILLS OF OUR YOUTH WILL TAKE INDIA AHEAD.
Cognitive bias..
• A cognitive bias refers to a systematic pattern of
deviation from norm or rationality in judgment,
whereby inferences about other people and situations
may be drawn in an illogical fashion.
• Individuals create their own "subjective social
reality" from their perception of the input and not
the objective input, may dictate their behavior in
the social world.
• Thus, cognitive biases may sometimes lead to
perceptual distortion, inaccurate judgment, illogical
interpretation, or what is broadly called irrationality.
From Wikipedia, the free encyclopedia
Neuro Finance: Inside the investor's brain
•
In Neuro finance:
– It examines experimentally the nature of the cognitive
processes engaged in acquiring and processing informa
tion in financial decision making.
– It further studies how people select action plans based
on the acquired representations of the values of poten
tial investment prospects.
•
Goals:
– to identify what kind of information the human brain can
process efficiently (and what kind it cannot), as well as
the environmental conditions facilitating or hampering
this information processing.
– to better understand how investment decisions are
tuned depending on the appreciation of distinct kinds of
uncertainty, such as risk, jump risk, and estimation
uncertainty
(ambiguity
and
model
uncertainty).
Neuro Finance
• The epistemology underlying neurofinance is dif
ferent and reflects recent advances in decision
neuroscience.
• We’re
initially
agnostic
(doubtful
or
noncommittal ) about the degree of rationality of
people, i.e, we do not take people to be limited in
their computational capabilities. Rather, we infer
their degree of sophistication experimentally,
from the observation of behavior and neural activ
ity during cognitive tasks performed in the lab.
• These cognitive tasks replicate challenges that
are routinely encountered in real world financial
decision-making.
Challenges…
• Learning asset distributions that jump over time (objec
tively very hard but in effect easier for people than
one would thought)
• Learning to avoid seemingly-glamorous but suboptimal
investments (not easy because we lack self-control)
• Properly perceiving financial market returns (not easy
either, owing to some ingrained biases that plague
human perception!)
• Making everyday predictions about key financial phe
nomena such as price changes, etc.
• One important aspect of this new paradigm is
to examine in the lab which environmental
conditions hamper the emergence of rational
ity, and which conditions help make people
smart.
• Thus, Neuro finance affords a unique opportu
nity to:
– develop acute prediction of investors’ behavior
– identify environmental markers of behavioral
sophistication/irrationality in financial markets
– create nudges to aid decision making
Methodology…
• Methodology-wise, neurofinance lies at the inter
section of experimental economics and computa
tional neuroscience.
• It replicate in the lab core challenges faced by
finance practitioners, and examine how lab sub
jects (regular people as well as finance profession
als) solve these challenges.
• It does two things:
– Look at behavior
– Scan the brain of the subjects during the experi
ment
What for? Implications for the
industry
• Portfolio managers and traders have to process informa
tion on the spot in rapidly changing environments.
• Little is known about how to tailor organizational and
individual decision-making processes to help people
process information efficiently in such contexts.
• By identifying environmental factors improving efficient
information processing, it is hoped that research in neu
rofinance will produce practical results on how to
improve investment and trading decisions, at both indi
vidual
and
organizational
levels.
world's happiest man‘…Matthieu Ricard, a 69-year-old Tibetan Buddhist monk
Thank you
3/3/16
61
Dr. Kumar Bijoy
Financial consultant
[email protected]
09810452266
Behavioral economics
• Behavioral economics: study the effects of
Social, cognitive, and emotional factors on
the economic decisions of
individuals
and
institutions and the consequences for market
prices, returns, and the resource allocation.
The fields are primarily concerned with
the bounds of rationality of economic agents.
• Behavioral
models: typically
integrate
insights from psychology with microeconomic
theory; in so doing, these behavioral models
cover a range of concepts, methods, and
fields.
Behavioral Finance
• According to Ritter (2002), the
foundation of the behavioral finance
is laid on two factors:
– ‘Cognitive Psychology’ (people’s way of
thinking)
– ‘limits to Arbitrage’ (effectiveness of
arbitrage in different circumstances)
Behavioral philosophy
• “Market in which security prices fully incorporate or
reflect any available information” …Fama (1970)
• “Foundation of Market Efficiency”… Andrei Shleifer
– Rationality: all investors are considered to be rational
and will adjust their estimates as soon as the new
information is released in an efficient and rational way
– Independent deviation from rationality: the excess
optimism or pessimism (i.e. irrationalities) of the investors
for some stocks that leads to offsetting the prices (due to
the assumption of “countervailing irrationalities”) and
hence produces market efficiency (Ross et al. 2008)
– Arbitrage: profit from mispricing
Classical Vs Behavioral
Finance
• Classical finance assumes full rationality,
thus cannot explain many price patterns
• Behavioral finance emerged in the 90s to
perfect the insights of mathematical finance.
• Using insights from all behavioral sciences
(cognitive neuroscience, psychology, sociol
ogy) on how real people depart from the
rational model — real people are boundedly
rational, behavioral finance can rationalize
hitherto-puzzling price patterns.
Behavioral Finance Definitions
Behavioral Finance, a study of investor market behavior that
derives from psychological principles of decision making, to explain
why people buy or sell the stocks they do.
The linkage of behavioral cognitive psychology, which studies
human decision making, and financial market economics.
Behavioral Finance focuses upon how investors interpret and act
on information to make informed investment decisions.
Investors do not always behave in a rational, predictable and an
unbiased manner indicated by the quantitative models. Behavioral
finance places an emphasis upon investor behavior leading to
various market anomalies.
Behavioral Finance Promise
Behavioral Finance promises to make economic models better
at explaining systematic (non-idiosyncratic) investor
decisions, taking into consideration their emotions and
cognitive errors and how these influence decision making.
Behavioral Finance is not a branch of standard finance; it is its
replacement, offering a better model of humanity.
Create a long term advantage by understanding the role of
investor psychology
Human flaws pointed out by the analysis of investor
psychology are consistent and predictable, and that they
offer investment opportunities.
Precursors to Behavioral Finance
Value investors proposed that markets over reacted to negative news.
Benjamin Graham and David Dodd in their classic book, Security Analysis,
asserted that over reaction was the basis for a value investing style.
David Dreman in 1978 argued that stocks with low P/E ratios were
undervalued, coining the phrase overreaction hypothesis to explain why
investors tend to be pessimistic about low P/E stocks.
Tversky and Daniel Kahneman published two articles in 1974 in Science.
They showed heuristic driven errors, and in 1979 in Econometrica, they
focused on representativeness heuristic and frame dependence.
Two Important Studies
•
Are equity valuation errors are systematic and therefore predictable?
–
–
–
•
Werner De Bondt and Richard Thaler 1985
–
–
•
Efficient markets view: prices follow a random walk, though prices fluctuate to
extremes, they are brought back (regression to the mean) to equilibrium in time.
Behavioral finance view: prices are pushed by investors to unsustainable levels
in both directions. Investor optimists are disappointed and pessimists are
surprised. Stock prices are future estimates, a forecast of what investors expect
tomorrow’s price to be, rather than an estimate of the present value of future
payments streams.
Early studies focused on relative strength strategies that buy past winners and
sell past losers
Investor Overreaction Hypothesis opposes Efficient Markets Hypothesis
Rejection of Regression to the Mean which says prices operating in the context of
extreme highs and lows balance each other
Shefrin and Statman 1985
–
–
Disposition Effect suggests investors relate to past winners differently (they keep
winners in their portfolio) than past losers (they sell past losers)
Odean applied the Disposition Effect in vivo context
Werner De Bondt and Richard Thaler 1985
study
De Bondt and Thaler extended Dreman’s reasoning to
predict a new anomaly.
They refer to representativeness, that investors become
overly optimistic about recent winners and overly
pessimistic about recent losers.
• They applied Tversky and Kahneman’s
representativeness to market pricing
– Overweight salient information such as recent
news
– Underweight salient data about long term
averages
• Investors overreact to both bad news and good news.
De Bondt and Thaler Study
Robert Shiller proposed prices show excess volatility.
That is, dividends do not vary enough to rationally justify
observed aggregate price movements
In spite of dividends, investors seem to attach
disproportionate importance to short run economic
developments.
Two Hypotheses: Each a violation of weak form market
efficiency.
1. Extreme movements in stock prices will be followed by
subsequent price movements in the opposite direction.
2. The more extreme the initial price movement, the
greater will be the subsequent adjustment.
De Bondt and Thaler 1985 study (cont)
Overreaction leads past losers to become
under priced and past winners to become
overpriced.
De Bondt and Thaler propose a strategy of
buying recent losers and selling recent
winners. Investors become too pessimistic
about past losers and overly optimistic
about past winners.
De Bondt and Thaler 1985 study (cont)
De Bondt and Thaler studied two portfolios of 35 stocks
One consisting of past extreme winners over the prior three years
One consisting of past extreme losers over the prior three years
Past losers subsequently outperformed winners over the next four
years.
Past losers were up 19.6 percent relative to the market in general.
Past winners were down five percent relative to the market in
general.
A difference of 24.6 percent between the two portfolios.
Study suggests that investors cause market prices to deviate from
fundamental values creating inefficient markets:
due to
representativeness heuristic markets’ treatment of past winners
and losers is not efficient.
De Bondt and Thaler study
Other Findings:
1. The overreaction effect is asymmetric: it
is much larger for losers than winners.
2. Most of the excess returns are realized in
January. (16.6% of the 24.6%)
3. The overreaction phenomenon mostly
occurs during the second and third year of
the test period. (By the end of the first year
the difference in the two portfolios is a
mere 5.4%)
Critics of De Bondt and Thaler 1985 study
Reversion to the mean explanation offered by Malkeil
consistent with efficient markets hypothesis
Zsuzsanna Fluck, Richard Quandt, and Malkeil study
Simulated an investment strategy of buying stocks
which had poor recent two or three year
performance.
They found: in the 1980s, 1990s, those stocks did
enjoy improved returns in the next period of time,
but they recovered only to the average stock
market performance.
It was a statistical pattern of return reversal, but to
appropriate levels (they did not overshoot levels).
More Critics
Two alternative Hypotheses: to overreaction.
1. Risk Change Hypothesis: overreaction is rational
response to risk changes (short term earnings outlook
changes) as measured by Betas
2. Firm size: past loser portfolio made up of small firms
Disturbing factors
1. Seasonal pattern of returns (January “turn of the
year” effect)
2. The characteristics of the firms in the portfolios
(Small size)
3. Co-relation is asymmetric
De Bondt and Thaler’s response
The data do not support either of these explanations. It
is emotional shifts in mood of investors—biased
expectations of the future, not rational shifts in
economic conditions
But what about?
Jegadeesh demonstrated shorter term reversals:
one week or one month
though these results are “transaction intense”
Grinblatt and Titman 1989, 1991 relative strength
strategies: they showed a tendency to buy stocks
that have increased in price over the previous
quarter, based on past relative strength
Integrating results
Contrarian strategies work with
1. Very short periods (one week, one month)
2. Very long periods (3 to 5 years)
Growth (relative strength strategies) work with three to 12 months
Jegadeesh and Titman (1993) studied period 1965-89 found:
three to 12 months earned average of 9.5% (six months earned
12%)
then reversals, 12-24 months lost 4.5%
for earnings announcements:
past winners earned positive returns for the first seven months
past losers earned positive returns for 13 month period
assessment
Dreman’s research
•
•
•
•
Sample of 1500 largest stocks, each over a billion in capitalization
Develop a portfolio of stocks with low P/E ratio
Portfolio established in 1970
By 1997 portfolio grew from $10,000 to $909,000 while the market
benchmark was $326,000.
Contrarian portfolios did better in down markets
During down quarters over the years, market averaged down 7.5%;
Contrarian portfolio down 4%
Dreman emphasized the importance of reinforcing events and “event
triggers” creating perceptual change
• Positive Surprises are very favorable for unpopular stocks (not so
for popular stocks)
• Negative Surprises are very consequential for popular stocks (not
so for unpopular stocks)
What it means?
Consistent with “positive feedback traders” hypothesis on market
price
Market under reacts to information about the short term prospects
of firms but overreacts to information about their long term
prospects
This is plausible given that the nature of the information
available about a firm’s short term prospects, such as earnings
forecasts, is different form the nature of the more ambiguous
information that is used by investors to assess a firm’s longer
term prospects
David Dreman: Contrarian strategies do better than the market
over time
Importance of earnings surprises on popular and unpopular
stocks reveals a market sentiment is significant
Specific over and under market reactions
Markets over react to IPOs
Markets under react to: earnings announcements,
dividend announcements, open market share
repurchases, brokerage recommendations
Investors systematically under weight
(conservative):
abstract, statistical, and highly relevant
information,
while they over weight (representativeness
heuristic)
salient, anecdotal, and extreme information
Explanations/Theories for Under and Over
reaction
Kent Daniel, David Hirshleifer and
Avanidhar Subrahmanyam:
“Investor Overconfidence and biased self
attribution”
Variations in investor confidence which is an
over estimation of ability to value stocks
and predict future prices arising from biased
self attribution
which is confirming information in the public
arena
encourages
but
disconfirming
information does not discourage, (blames
Daniel, Hirshleifer and Subrahmanyan (cont)
• Shifts in investors’ confidence cause
– Negative long lag auto correlations (Contrarian
strategies)
– Excess volatility relative to fundamentals
(variance)
– Predictability about future prices
• Shifts in investors’ self attribution cause
– Short lag autocorrelation (momentum
strategies)
– Short run earnings drift in the direction of
earnings surprise
– Abnormal stock performance in the opposite
direction of long term earnings changes.
(Negative correlation between future returns
Daniel, Hirshleifer and Subrahmanyan (cont)
Theory is based on investor overconfidence, and on
changes in confidence resulting from biased self
attribution of investment outcomes
– Investors will overreact to private information
signals creates momentum in price (either
absent public information to support price, or
assuming public information confirm private
signals, or….
• Investors will under react to public information
signals (avoids correction in stock price until it
goes to extreme)
Unlike noise trader approach, this theory posits that
investors misinterpret genuine new private
information.
Explanations/Theories (cont)
Barberis, Shlieifer and Vishny 1998 : Learning model
explanation
Actual earnings follow a random walk, but individuals believe
that earnings follow either a steady growth trend, or else
earnings are mean reverting.
Representativeness heuristic (finds patterns in data too readily,
tends to over react to information) and conservatism (clings to
prior beliefs, under reacts to information).
Interaction of representativeness heuristic and conservatism:
explains short term under reaction and long term over reaction
Investor’s reaction to current information condition on past
information. Investor tends to under react to information that is
preceded by a small quantity of similar information and to over
react to information that is preceded by a large quantity of
similar information.
Explanations/Theories (cont)
Hong and Stein 1997
Under and Over reactions arise from the
interaction of momentum traders and
news watchers
Momentum traders make partial use of the
information continued in recent price
trends, and ignore fundamental news
Fundamental
traders
rationally
use
fundamental news but ignore prices.
Explanations/Theories (cont)
Bloomfiled, Libby and Nelson
Traders
in
experimental
markets
undervalue the information of others
People with evidence that is favorable but
unrealizable
tend
to
overreact
to
information, whereas people with evidence
that is somewhat favorable but reliable
under react
Optimism, Overconfidence, and Odean’s
Research
People are overly optimistic
• People believe that they are less likely to get hit by a bus
or be robbed than their neighbors
People are overconfident in their own abilities
• Driving skills and social skills are better
• New business owners believe their business has a 70%
chance of success, but only 30% succeed
• Helps soldiers cope with war
Overconfidence and the stock market
• Overconfidence can lead to substantial losses when
investors overestimate their ability to identify the next
Microsoft or Amazon
• Securities that investors purchase under perform those
they sell
Benartzi, Kahneman and Thaler survey on
Overconfidence
Survey of Morningstar 1053 subscribers
• 84% male, average age is 45, annual in come $93,000
• Average allocation to stocks is 79%
• Optimism question:
– Thinking about financial decisions, do you spend more time
thinking about the potential return or the possible loss?
– What do you think is the likelihood of stocks outperforming
bonds in the long run?
• Overconfidence and Optimism decided by
– Answer to the question about likelihood of stocks
outperforming bonds
– Asset allocation of retirement contributions of stocks vs.
bonds
Odean’s study of overconfidence in the
marketplace
What happens in financial markets when people are
overconfident?
• Trading volume increases: overconfidence generates trading.
Those who trade more frequently fare worse than those who
trade less
• Overconfident traders hold under-diversified portfolios; riskier
portfolios though they have the same degree of risk aversion
• Overconfident insiders improve price quality; overconfident
noise traders worsen it
• Men are more overconfident than women; men trade more
frequently (45% more) than women, men earn less returns
than women (one percent less).
• Single men and single women the results are larger (67%
more trading, 1.4% less)
Trading Behavior and Returns
Individual investors who hold common stock directly pay a
tremendous performance penalty for active trading
• Odean study “trading can be hazardous to your wealth”
– Studied 66,465 households from 1991 to 1996
– Most frequent traders earn 11.4% (turn over 75% of
portfolio)
– Average household earned 16.4%
– Market benchmark was 17.9%
• Odean study on On line traders
– Studied 1607 traders on line, compared with 1607
telephone traders
– On line traders experienced strong performance prior to
going on line
– After on line, less profitable, lagging the market by three
points
– Explained by overconfidence, self attribution bias, illusion
Overconfidence and the Disposition Effect
Investors
weight
recent
observations
too
heavily
(representativeness heuristic)
Investors under weight prior information
Investors commit the gambler’s fallacy: expecting recent events
(downturns in stock prices) to reverse
Disposition effect: Investors hold on to losers in their portfolio
(because they can’t be wrong), and sell winners.
Investors judge their decision on the basis of the returns realized
not paper money returns, then holding losers will avoid
confronting their true abilities.
Investors won’t learn from mistakes, continue as overconfident.
Odean’s research confirms Disposition Effect
Odean looks at trading decisions of investors at discount
brokerage
Stocks traders buy under perform those that they sell
Level of Over-confidence changes
dynamically
Depending upon the success or failure, level
of overconfidence changes
• A trader is not overconfident when he
begins to trade
• Overconfidence increase over his first
several trading periods early in his career
– These overconfident traders survive the
threat of arbitrage, that is, they are not
the poorest traders
– Initial success increases overconfidence
• Overconfidence declines thereafter
two types of investors
• Irrational amateurs: that tend to
carry stock at prices different from
the efficient prices because of their
wrong notions of stocks to be under
or overvalued.
• Rational professionals: that
predicts the nature of the stocks
efficiently, clearly and come to some
conclusions
Factors….
•
•
•
•
•
•
•
•
•
•
•
Age
Education
Experience
Wealth
Mood
Gender
Profession
Liability
Society
Availability
Economy
Behavioral Finance Models
•
•
•
•
•
•
•
•
•
•
Rational behavior
Over and Under-reaction
Mental Compartments
Over Confidence
Disjunction Effect (Cognitive Psychology or
anomalies)
Prospect theory
Expected Utility Theories
Momentum
Technical analysis
Contrarian strategies
Cognitive Psychology
• Overconfidence:
– Too little Diversification… Ritter (2002)
– According to Ross (1987), “overconfidence can
be clearly related to some deep-set
psychological phenomena” or even to some
broader complexity like “incapability of making
adequate allowance for the uncertainty in
one’s own view”, “a more global difficulty tied
up with multiple mental processes”
– “representativeness heuristic”…Tversky and
Kahneman (1974)
Overreaction:
• The reason behind the low returns on Glamour stocks
{Stocks with high returns in the past (3-5 years) and
are more preferred by the investors} as compared to
the Value stocks {Stocks with low returns in the past
(3-5 years) and are not generally preferred by the
investors} in the future is because of the overreaction
of the investors…. DeBondt and Thaler (1985)
• Firms list their stocks to take advantage of the
market’s overreaction arises because of their recent
superior performance” (Dharan and Ikenberry (1995);
Fama (1993)
• “price-ratio”
hypothesis
.According
to
which
companies with high P/E are considered to be
“Overvalued”
• Volatility of stock: overreaction of the investors is
one of the possible reason behind the frequent
movement of security prices following stock splits
(Ohlson and Penman (1983), Jain (2011)) and
initial public offerings (Ibbotson and Ritter (1988)
and Ritter (1991)
• People/investors “Overreact to unexpected and
Dramatic news” which is in violation of Bayes’
rule (DeBondt and Thaler (1985)
Under reaction:
•
“Momentum effect”- This is because investors
think the earnings to be mean-reverting resulting in
under reaction whenever any change in earnings
occurred but when at a later stage, they prove to be
wrong then stock prices exhibit a slow response to
the earnings announced in the past (Barberis,
Shleifer and Vishny (1998)
• “Principle of Conservatism” (coined by Edwards
(1968)) . According to which if any change occurs,
individual tend to take time in order to adjust to that
change and hence underreacts (Ritter (2002)
Disjunction Effect:
• It can be defined as the propensity for the
people/investors to wait until they know everything
about the market or the subject whether or not the
information is of prime importance to oneself and if that
information will make any difference in the decision
making or not (Shiller (2001)).
• According to Savage (1954), “disjunction effect is a
contradiction to the sure-thing principle of rational
behavior”.
• Disjunction effect explains the volatility of
speculative stock prices after or before
announcement occurs (Shafir and Tversky (1992)
the
any
Mental Compartments
• Planning and Budgeting
• “people think naturally on the “safe” part of the
investment i.e. protected against the downside
risk and “risky “part of the investment is planned
to earn higher abnormal return to become rich”-Shefrin and Statman (1994)
• January effect: January is the month in which
maximum stock prices appreciation can be seen
as individual treats January to be the starting of
their new investments researched in as many as
15 countries (Gultekin and Gultekin (1983)
Expected Utility and Prospect
Theory
• “it offers economical representation of
truly rational behavior under uncertainty”
(Shiller (2001)
• it has “systematically mispredicted human
behavior” (Shiller (2001); Allais (1953)
• according to the prediction of the
Expected Utility Theory, this should not
happen and individuals were supposed to
stick to their preferences as the certainty
increases not the price.
Prospect Theory
• Prospect Theory can be defined as a
mathematically formulated theory that
substitutes
“weights”
instead
of
“probabilities” and “value function” instead
of “utility function” in expected utility theory.
• In Prospect Theory, individuals are working
to maximize the weighted sum of value
rather than utility whereby weights are not
equal to probabilities (Kahneman and
Tversky (1979); Shiller (2001)
• according to this theory, (in the previous example
given by Allais (1953)) people will assign very high
weight to event which is very certain and little
weight to event which is not very certain
irrespective of the price/constant to be the same
• “Human behavior towards risk” can also be studied
by replacing probabilities with weights in the
expected utility theory. For example “public
enthusiasm for high price lottery with low winning
probability and hence low expected payout”
(Kahneman and Tversky (1979)) or “overpaying for
airline flight insurance”
Limits to Arbitrage
• “A market with millions of small arbitrager taking large
number of tiny positions can make the market efficient
by making the price to drive towards the fundamental
value in different markets” (Fama (1965); Sharpe (1964)
and Ross (1976)
• According to “limits to Arbitrage” as there are some
investors that buys the overpriced and sell the
underpriced securities in turn disturbing the parity
condition in the short run and hence giving losses to the
arbitrager which restricts them to take small position
because of the risk perception (Ross et al. 2008)
• Arbitraging activities are also limited because of the
capital requirements, lack of perfect knowledge and the
risk involved to make the markets efficient and hence is
one of the anomalies of ‘Efficient Markets
Trading Strategies
• Momentum Trading Strategy: buying past
winners and selling past losers”),
• Technical Trading Strategy: buy when ‘buy
signal’ emits and sell to hold cash when ‘sell
signal’ emits
• Contrarian Trading Strategy: also known
as “Value strategies” which is opposite to
momentum strategy i.e. “buying past losers
and selling past winners” to avoid herding with
the other participants in the stock market
Why so desperate
CAD
Depreciating
INR
Falling GDP
Fiscal
deficit
Unemploy
ment
Inflation
Why so
desperate
THERE IS NO REASON TO BE DISAPPOINTED . INDIA WILL PROGRESS
VERY FAST AND THE SKILLS OF OUR YOUTH WILL TAKE INDIA AHEAD.
Cognitive bias..
• A cognitive bias refers to a systematic pattern of
deviation from norm or rationality in judgment,
whereby inferences about other people and situations
may be drawn in an illogical fashion.
• Individuals create their own "subjective social
reality" from their perception of the input and not
the objective input, may dictate their behavior in
the social world.
• Thus, cognitive biases may sometimes lead to
perceptual distortion, inaccurate judgment, illogical
interpretation, or what is broadly called irrationality.
From Wikipedia, the free encyclopedia
Neuro Finance: Inside the investor's brain
•
In Neuro finance:
– It examines experimentally the nature of the cognitive
processes engaged in acquiring and processing informa
tion in financial decision making.
– It further studies how people select action plans based
on the acquired representations of the values of poten
tial investment prospects.
•
Goals:
– to identify what kind of information the human brain can
process efficiently (and what kind it cannot), as well as
the environmental conditions facilitating or hampering
this information processing.
– to better understand how investment decisions are
tuned depending on the appreciation of distinct kinds of
uncertainty, such as risk, jump risk, and estimation
uncertainty
(ambiguity
and
model
uncertainty).
Neuro Finance
• The epistemology underlying neurofinance is dif
ferent and reflects recent advances in decision
neuroscience.
• We’re
initially
agnostic
(doubtful
or
noncommittal ) about the degree of rationality of
people, i.e, we do not take people to be limited in
their computational capabilities. Rather, we infer
their degree of sophistication experimentally,
from the observation of behavior and neural activ
ity during cognitive tasks performed in the lab.
• These cognitive tasks replicate challenges that
are routinely encountered in real world financial
decision-making.
Challenges…
• Learning asset distributions that jump over time (objec
tively very hard but in effect easier for people than
one would thought)
• Learning to avoid seemingly-glamorous but suboptimal
investments (not easy because we lack self-control)
• Properly perceiving financial market returns (not easy
either, owing to some ingrained biases that plague
human perception!)
• Making everyday predictions about key financial phe
nomena such as price changes, etc.
• One important aspect of this new paradigm is
to examine in the lab which environmental
conditions hamper the emergence of rational
ity, and which conditions help make people
smart.
• Thus, Neuro finance affords a unique opportu
nity to:
– develop acute prediction of investors’ behavior
– identify environmental markers of behavioral
sophistication/irrationality in financial markets
– create nudges to aid decision making
Methodology…
• Methodology-wise, neurofinance lies at the inter
section of experimental economics and computa
tional neuroscience.
• It replicate in the lab core challenges faced by
finance practitioners, and examine how lab sub
jects (regular people as well as finance profession
als) solve these challenges.
• It does two things:
– Look at behavior
– Scan the brain of the subjects during the experi
ment
What for? Implications for the
industry
• Portfolio managers and traders have to process informa
tion on the spot in rapidly changing environments.
• Little is known about how to tailor organizational and
individual decision-making processes to help people
process information efficiently in such contexts.
• By identifying environmental factors improving efficient
information processing, it is hoped that research in neu
rofinance will produce practical results on how to
improve investment and trading decisions, at both indi
vidual
and
organizational
levels.
world's happiest man‘…Matthieu Ricard, a 69-year-old Tibetan Buddhist monk
Thank you
3/3/16
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