Behavioral
economics
and behavioral finance are closely related fields which
apply scientific research on human and social cognitive and emotional
biases to better understand economic decisions and how they affect
market prices, returns and the allocation of resources. The fields
are primarily concerned with the rationality, or lack thereof,
of economic agents. Behavioral models typically integrate insights
from psychology with neo-classical economic theory.
Academics
are divided between considering Behavioral Finance as supporting
some tools of technical analysis by explaining market trends,
and considering some aspects of technical analysis as behavioral
biases (representativeness heuristic, self fulfilling prophecy).[1]
Behavioral
analyses are mostly concerned with the effects of market decisions,
but also those of public choice, another source of economic decisions
with some similar biases.
History
During the
classical period, economics had a close link with psychology.
For example, Adam Smith wrote The Theory of Moral Sentiments,
an important text describing psychological principles of individual
behavior; and Jeremy Bentham wrote extensively on the psychological
underpinnings of utility. Economists began to distance themselves
from psychology during the development of neo-classical economics
as they sought to reshape the discipline as a natural science,
with explanations of economic behavior deduced from assumptions
about the nature of economic agents. The concept of homo economicus
was developed, and the psychology of this entity was fundamentally
rational. Nevertheless, psychological explanations continued to
inform the analysis of many important figures in the development
of neo-classical economics such as Francis Edgeworth, Vilfredo
Pareto, Irving Fisher and John Maynard Keynes.
Psychology
had largely disappeared from economic discussions by the mid 20th
century. A number of factors contributed to the resurgence of
its use and the development of behavioral economics. Expected
utility and discounted utility models began to gain wide acceptance,
generating testable hypotheses about decision making under uncertainty
and intertemporal consumption respectively. Soon a number of observed
and repeatable anomalies challenged those hypotheses. Furthermore,
during the 1960s cognitive psychology began to describe the brain
as an information processing device (in contrast to behaviorist
models). Psychologists in this field such as Ward Edwards, Amos
Tversky and Daniel Kahneman began to compare their cognitive models
of decision making under risk and uncertainty to economic models
of rational behavior. In Mathematical psychology, there is a longstanding
interest in the transitivity of preference and what kind of measurement
scale utility constitutes (Luce, 2000).
An important
paper in the development of the behavioral finance and economics
fields was written by Kahneman and Tversky in 1979. This paper,
'Prospect theory: Decision Making Under Risk', used cognitive
psychological techniques to explain a number of documented divergences
of economic decision making from neo-classical theory. Over time
many other psychological effects have been incorporated into behavioral
finance, such as overconfidence and the effects of limited attention.
Further milestones in the development of the field include a well
attended and diverse conference at the University of Chicago (see
Hogarth & Reder, 1987), a special 1997 edition of the Quarterly
Journal of Economics ('In Memory of Amos Tversky') devoted to
the topic of behavioral economics and the award of the Nobel prize
to Daniel Kahneman in 2002 "for having integrated insights from
psychological research into economic science, especially concerning
human judgment and decision-making under uncertainty."
Prospect theory
is an example of generalized expected utility theory. Although
not commonly included in discussions of the field of behavioral
economics, generalized expected utility theory is similarly motivated
by concerns about the descriptive inaccuracy of expected utility
theory.
Behavioral
economics has also been applied to problems of intertemporal choice.
The most prominent idea is that of hyperbolic discounting, in
which a high rate of discount is used between the present and
the near future, and a lower rate between the near future and
the far future. This pattern of discounting is dynamically inconsistent
(or time-inconsistent), and therefore inconsistent with some models
of rational choice, since the rate of discount between time t
and t+1 will be low at time t-1, when t is
the near future, but high at time t when t is the
present and time t+1 the near future. As part of the discussion
of hypberbolic discounting, has been animal and human work on
Melioration theory and Matching Law of Richard Herrnstein. They
suggest that behavior is not based on expected utility rather
it is based on previous reinforcement experience.
Methodology
At the outset
behavioral economics and finance theories were developed almost
exclusively from experimental observations and survey responses,
though in more recent times real world data has taken a more prominent
position. fMRI has also been used to determine which areas of
the brain are active during various steps of economic decision
making. Experiments simulating market situations such as stock
market trading and auctions are seen as particularly useful as
they can be used to isolate the effect of a particular bias upon
behavior; observed market behavior can typically be explained
in a number of ways, carefully designed experiments can help narrow
the range of plausible explanations. Experiments are designed
to be incentive compatible, with binding transactions involving
real money the norm.
Key
observations
There are
three main themes in behavioral finance and economics (Shefrin,
2002):
- Heuristics:
People often make decisions based on approximate rules of thumb,
not strictly rational analyses. See also cognitive biases and
bounded rationality.
- Framing:
The way a problem or decision is presented to the decision maker
will affect his action.
- Market
inefficiencies: There are explanations for observed market outcomes
that are contrary to rational expectations and market efficiency.
These include mispricings, non-rational decision making, and
return anomalies. Richard Thaler, in particular, has described
specific market anomalies from a behavioral perspective.
Recently,
Barberis, Shleifer, and Vishny (1998), as well as Daniel, Hirshleifer,
and Subrahmanyam (1998) have built models based on extrapolation
(seeing patterns in random sequences) and overconfidence to explain
security market over- and underreactions, though such models have
not been used in the money management industry. These models assume
that errors or biases are correlated across agents so that they
do not cancel out in aggregate. This would be the case if a large
fraction of agents look at the same signal (such as the advice
of an analyst) or have a common bias.
More generally,
cognitive biases may also have strong anomalous effects in aggregate
if there is a social contamination with a strong emotional content
(collective greed or fear), leading to more widespread phenomena
such as herding and groupthink. Behavioral finance and economics
rests as much on social psychology within large groups as on individual
psychology. However, some behavioral models explicitly demonstrate
that a small but significant anomalous group can also have market-wide
effects (eg. Fehr and Schmidt, 1999).
Behavioral
finance topics
Some central
issues in behavioral finance are why investors and managers (and
also lenders and borrowers) make systematic errors. It shows how
those errors affect prices and returns (creating market inefficiencies).
It shows also what managers of firms or other institutions, as
well as other financial players might do to take advantage of
market inefficiencies.
Among the
inefficiencies described by behavioral finance, underreactions
or overreactions to information are often cited, as causes of
market trends and in extreme cases of bubbles and crashes). Such
misreactions have been attributed to limited investor attention,
overconfidence / overoptimism, and mimicry (herding instinct)
and noise trading.
Other key
observations made in behavioral finance literature include the
lack of symmetry between decisions to acquire or keep resources,
called colloquially the "bird in the bush" paradox, and the strong
loss aversion or regret attached to any decision where some emotionally
valued resources (e.g. a home) might be totally lost. Loss aversion
appears to manifest itself in investor behavior as an unwillingness
to sell shares or other equity, if doing so would force the trader
to realise a nominal loss (Genesove & Mayer, 2001). It may
also help explain why housing market prices do not adjust downwards
to market clearing levels during periods of low demand.
Applying a
version of prospect theory, Benartzi and Thaler (1995) claim to
have solved the equity premium puzzle, something conventional
finance models have been unable to do.
Presently,
some researchers in experimental finance use experimental method,
e.g. creating an artificial market by some kind of simulation
software to study people's decision-making process and behavior
in financial markets.
Behavioral
finance models
Some financial
models used in money management and asset valuation use behavioral
finance parameters, for example
- Thaler's
model of price reactions to information, with three phases,
underreaction-adjustment-overreaction, creating a price trend
One characteristic
of overreaction is that the average return of asset prices following
a series of announcements of good news is lower than the average
return following a series of bad announcements. In other words,
overreaction occurs if the market reacts too strongly or for too
long (persistent trend) to news that it subsequently needs to
be compensated in the opposite direction. As a result, assets
that were winners in the past should not be seen as an indication
to invest in as their risk adjusted returns in the future are
relatively low compared to stocks that were defined as losers
in the past.
Criticisms
of behavioral finance
Critics of
behavioral finance, such as Eugene Fama, typically support the
efficient market theory (though Fama may have reversed his position
in recent years). They contend that behavioral finance is more
a collection of anomalies than a true branch of finance and that
these anomalies will eventually be priced out of the market or
explained by appealing to market microstructure arguments. However,
a distinction should be noted between individual biases and social
biases; the former can be averaged out by the market, while the
other can create feedback loops that drive the market further
and further from the equilibrium of the "fair price".
A specific
example of this criticism is found in some attempted explanations
of the equity premium puzzle. It is argued that the puzzle simply
arises due to entry barriers (both practical and psychological)
which have traditionally impeded entry by individuals into the
stock market, and that returns between stocks and bonds should
stabilize as electronic resources open up the stock market to
a greater number of traders (See Freeman, 2004 for a review).
In reply, others contend that most personal investment funds are
managed through superannuation funds, so the effect of these putative
barriers to entry would be minimal. In addition, professional
investors and fund managers seem to hold more bonds than one would
expect given return differentials.
Quantitative
behavioral finance
Quantitative
behavioral finance is a new discipline that uses mathematical
and statistical methodology to understand behavioral biases in
conjunction with valuation. Some of this endeavor has been lead
by Gunduz Caginalp (Professor of Mathematics and Editor of Journal
of Behavioral Finance during 2001-2004) and collaborators including
Vernon Smith (2002 Nobel Laureate in Economics), David Porter,
Don Balenovich, Vladimira Ilieva, Ahmet Duran, Huseyin Merdan).
Studies by Jeff Madura, Ray Sturm and others have demonstrated
significant behavioral effects in stocks and exchange traded funds.
The research
can be grouped into the following areas:
1. Empirical studies that demonstrate significant deviations from
classical theories.
2. Modeling using the concepts of behavioral effects together
with the non-classical assumption of the finiteness of assets.
3. Forecasting based on these methods.
4. Studies of experimental asset markets and use of models to
forecast experiments.
Critical
conclusions of behavioral economics
Critics of
behavioral economics typically stress the rationality of economic
agents (see Myagkov and Plott (1997) amongst others). They contend
that experimentally observed behavior is inapplicable to market
situations, as learning opportunities and competition will ensure
at least a close approximation of rational behavior.
Others note
that cognitive theories, such as prospect theory, are models of
decision making, not generalized economic behavior, and are only
applicable to the sort of once-off decision problems presented
to experiment participants or survey respondents.
Traditional
economists are also skeptical of the experimental and survey based
techniques which are used extensively in behavioral economics.
Economists typically stress revealed preferences over stated preferences
(from surveys) in the determination of economic value. Experiments
and surveys must be designed carefully to avoid systemic biases,
strategic behavior and lack of incentive compatibility, and many
economists are distrustful of results obtained in this manner
due to the difficulty of eliminating these problems.
Rabin (1998)
dismisses these criticisms, claiming that results are typically
reproduced in various situations and countries and can lead to
good theoretical insight. Behavioral economists have also incorporated
these criticisms by focusing on field studies rather than lab
experiments. Some economists look at this split as a fundamental
schism between experimental economics and behavioral economics,
but prominent behavioral and experimental economists tend to overlap
techniques and approaches in answering common questions. For example,
many prominent behavioral economists are actively investigating
neuroeconomics, which is entirely experimental and cannot be verified
in the field.
Other proponents
of behavioral economics note that neoclassical models often fail
to predict outcomes in real world contexts. Behavioral insights
can be used to update neoclassical equations, and behavioral economists
note that these revised models not only reach the same correct
predictions as the traditional models, but also correctly predict
some outcomes where the traditional models failed
References
- Kirkpatrick,
Charles D.; Dahlquist, Julie R. (2007). Technical Analysis,
The Complete Resource for Market Technicians, p. 49.
- Camerer,
C. F.; Loewenstein, G. & Rabin, R. (eds.) (2003) Advances
in Behavioral Economics
- Barberis,
N.; A. Shleifer; R. Vishny (1998) ``A Model of Investor Sentiment
Journal of Financial Economics 49, 307-343.
- Daniel,
K.; D. Hirshleifer; A. Subrahmanyam, (1998) ``Investor Psychology
and Security Market Over- and Underreactions Journal of Finance
53, 1839-1885.
- Lawrence A. Cunningham,
Behavioral Finance and Investor Governance, 59 Washington &
Lee Law Review (2002)
- Kahneman,
D. & Tversky, A. 'Prospect Theory: An Analysis of Decision
under Risk,' Econometrica, XVLII (1979), 263–291
- Kirkpatrick,
Charles D.; Dahlquist, Julie R. (2007) Technical Analysis,
The Complete Resource for Financial Market Technicians
- Luce, R
Duncan (2000). Utility of Gains and Losses: Measurement-theoretical
and Experimental Approaches. Lawrence Erlbaum Publishers,
Mahwah, New Jersey.
- Rabin,
Matthew; 'Psychology and Economics,' Journal of Economic
Literature, American Economic Association, vol. 36(1), pages
11-46, March 1998.
- Shefrin,
Hersh (2002) Beyond Greed and Fear: Understanding behavioral
finance and the psychology of investing. Oxford Universtity
Press
- Shleifer,
Andrei (1999) Inefficient Markets: An Introduction to Behavioral
Finance, Oxford University Press
- Shlomo
Benartzi; Richard H. Thaler 'Myopic Loss Aversion and the Equity
Premium Puzzle' (1995) The Quarterly Journal of Economics,
Vol. 110, No. 1.
External
links
|
