Behavioral finance FAQ / Glossary (A)

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Ac - Ad


Dates of related message(s)
in the
Behavioral-Finance group (*):

Year/month, d: developed / discussed,
i: incidental

Accumulation / Distribution


00/8i,12i + see distribution /
accumulation,
congestion / (price)
cluster, percolation + bfdef3

Active / passive investing



Because of its length, this article
       is in a 
separate page

of this "A"  glossary section

Adaptation / Adaptable / Adaptive (system, economics, market)


02/10i - 04/9i - 05/2i - 06/4i
+ see dynamical systems,

evolutionary economics,
chaos theory, percolation

Addiction


00/10i,12d + see overtrading,
commitment, willpower,
habit,
automaticity

How to resist it?

Definition

Addiction is a recurrent compulsion,

It shows a mind dependence (*) that overcomes rational thinking.

=> It generates actions that bring damages to the affected person, and
      sometimes to others.

(*) in its extreme form categorized as a pathology,

Addiction and stock trading

Stock trading can become addictive, thus be a psychological disorder
           like any other.

This could result in "noise trading" / "overtrading" (see those words) which
entails:

For the trader, high risks and costs.

In the market, return and price anomalies.

At least if the contagion spreads (see herding) to many investors and is
exacerbated by greed or fear.

(under- / slow) Adjustment



Because of its length, this article
     
is in a separate page
      of this "A" glossary section

Administration / administrative behavior

04/9i + see corporate behavioral finance,

public choice, principal-agent

Af - Ag


Dates of related message(s)
in the Behavioral-Finance group (*):

Year/month, d: developed / discussed,
i: incidental

Affect, affect heuristic

Because of its length, this article
       is in a 
separate page

         of this "A"  glossary section

(principal-) Agent / Agency theory

08/i,8i,11i - 03/1i + see ethical,
moral hazard,
perverse incentive

Agent-based model

01/5i - 03/2i,8i,9i,12i - 04/2i
- 08/11i + see style

Let us pack all those people inside the computer
and see what comes out!

In economics / finance, an agent-based model (or agent model) is a software
that simulates
the actions (buying / selling) of several types of agents
(professionals / general public, etc),

Application to financial markets

Money-chasing clans in the hard drive

When the agents are investors, the simulation takes into account that each
category has its style / profile / preferences

(short term, long term, fundamentalist, "technicalist", follower, contrarian,
etc...).

The aim of the simulation is to see how the interactions
between
those clans impact market prices, trends, returns, volatilities...

It would help to understand those phenomena, and if possible to predict
them.

Those agent-based models might be better predictors of dramatic
"non linear" disruptions and unbalances
than those working on
standard mathematics equations.

They include more "artificial intelligence", but of course they are worth only
what their assumptions about behaviors are worth.

The snag is that human uncertainty is at play, thus that surprises
are always possible.

Therefore it is not too easy to predict how each category of agents will
    react to a situation without falling into caricatures.

Also, the relative weight of the various categories might evolve.

Those models are also microeconomics tools.

Whatever the difficulties involved, this rising branch of economics has the
meritto try to start from field work and ground level realities
more than from large equilibriums between aggregate national or international
data.

Al-Am


Dates of related message(s)
in the Behavioral-Finance group (*):

Year/month, d: developed / discussed,
i: incidental

Algorithmic trading

See system trading

Alpha coefficient (excess / insufficient return)

00/6d - 01/9i - 02/7i,8i
+ see (sector) rotation

Does the lottery wheel choose its winners and losers?

Definition:

The alpha coefficient measures anomalous asset returns.

Those can be defined as returns that are - rather durably (not just
accidentally) -
above or below what the standard theories (*) predict,

(*) Namely the CAPM and the RWH (see those acronyms) predict.


So what about those theories ?

Let us remind that those theories consider that:

Only differences in risk / volatility, or different "betas",

explain differences of returns between assets.

The alpha coefficient appears in the CAPM equation,

but is theoretically equal or close to zero in that model.

Thus, positive or negative" alphas", meaning excess or insufficient

returns that would be independent of the risk would not be
possible.

Samely, predictable alphas would be illusive.

The random walk hypothesis states you cannot beat the market
by predicting the next price moves and returns.

But in practice,

History shows sizeable positive or negative alphas,

in certain time frames, or in some sectors or stocks.

The past performances of fund managers in a given period are
   measured in alphas.

Here, alphas are extra or insufficient returns for their portfolios,

compared to the general market performance.

Usually a past performance in a past situation
does not
guarantee
a similar performance in a
future situation,

but some - rare - people might recurrently have more
skill (see luck vs. skill) than the average player to adapt
their practices.

Alternation (of trends)

00/6i,7d,8i + 01/11i
+ see cycle, trend + bfdef3

Altruism

08/6d, 09/6d + see ethics,
needs, fairness, genetic utility

Moral incentives vs. money incentives.

Altruism, as an interest for other people more than for the self, should not be
neglected as a motivation, including in economics.

Altruism, and what they see as fairness or common
good, can make people do positive things they would
not do for money

This does not mean that all moral motivations and "good intents"
bring
always positive results Some can be overly emotional and self
defeating, and sometimes manipulated.

Ambiguity aversion, ambiguity premium

01/2i + see uncertainty

An


Dates of related message(s)
in the Behavioral-Finance group (*):

Year/month, d: developed / discussed,
i: incidental

(mental) Anchor / Anchoring



  Because of its length, this article
        
is in a separate page
         of this "A" glossary section



(market) Anomaly



  Because of its length, this article  
         is in a  separate page
         of this "A" glossary section

Anticipation



  Because of its length, this article
        
is in a   separate page
         of this "A" glossary section

Ap - As


Dates of related message(s)
in the Behavioral-Finance group (*):

Year/month, d: developed / discussed,
i: incidental

APT

See Arbitrage Pricing Theory

ARCH / GARCH models

00/6i,10d + see
heteroskedasticity + bfdef3

(limited) Arbitrage

(absence of / limits of) Arbitrage opportunity

Arbitrage pricing theory (APT)

  Because of their lengths,
        those articles are in a

        separate page
        of this "A" glossary section

Archetype (stock, trader)

00/12i + see profiling,
type, prototype, style

An archetype is a common traditional mental reference to represent
ideally
a given category
of things or phenomena (of stocks, of investors,
for example...).

While "prototype" is used to describe a new design or phenomenon,
archetype refers to old examples, real or invented.

Both are found in finance: old categorizations as well as new paradigms.

A stereotype is a common, very superficial and aproximative (even
sometimes false) representation,

Aristotle bias 



See binary logic, narrow
thinking, fuzzy logic,
yin yang,
reductionism,
stereotype

The Aristotle bias, or binary logic, is a reductive way to
categorize complex and gradual situations or concepts as

either 100% true or 100% false, 100% right or 100% wrong

Artificial Intelligence (AI)


00/7i + see soft computing,
genetic algorithm, fuzzy,
non
linearity, agent-based model

Better than natural intelligence ?

In a nutshell, research in artificial intelligence would make computer draw
lessons from their own experience
and also avoid the human cognitive
biases, thus could make better decisions.
But many snags have to be overcome, if only because human beings use
not just logic and information to find creative solutions and bet on them,
notably in totally new situations in which there is no precedents

Asymmetry / skew



Because of its length, this article
       is in a
separate page

of this "A" glossary section

Att


Dates of related message(s)
in the Behavioral-Finance group (*):

Year/month, d: developed / discussed,
i: incidental

Attachment bias

See endowment effect

Attention anomaly, bias, disorder



Because of its length, this article
is in a separate page
of this "A" glossary section

(common) Attitude



Because of its length, this article
is in a separate page

of this "A" glossary section

Attractor

00/5d,11i,12d - 01/8i,11i

What if chaos were not fully chaotic?

Attractors are a chaos theory concept that can be applied - metaphorically
or directly -
to some phenomena detected by Behavioral Finance.

In financial markets we may call attractor, in the broad sense,

any recurrent pattern of market or stock

behaviors - either biased or unbiased - that can be quantified.

Those patterns might be real or imaginary depending on circumstances.

Some real market phenomena seem to escape pure randomness and fit
   a
pattern, if not because of the "laws of chaos", at least as a result of
   some behavioral biases

On the other hand, some precautions are needed so as not to "see" illusive

patterns (see representativeness heuristic) in all market evolutions.

Examples of "attractors" in finance

Trends, momentums, alternation/cycles,

Specific distribution curves of prices / volatility / returns,

Stock types,

Price levels,

Paradigms of valuation...

Att


Dates of related message(s)
in the Behavioral-Finance group (*):

Year/month, d: developed / discussed,
i: incidental

Attribution bias / error



00/9i,12i - 01/3i,5i - 02/2i,8i + see
rationalization,
self attribution,
deification / demonization, story
+ bfdef2

I am OK, you are not OK, or maybe more OK than OK.

Definition

The attribution bias is the tendency to explain immediately a - pleasant or
unpleasant - event
, without further analysis, by attributing its
responsibility
(or at least its origin) to somebody, an organization or a
category of people.

That bias puts the blame, or the credit,
with a high risk of false attribution, on:

An identified person(s), for example the central bank president,

Or oneself (self-attribution, self-serving bias, group-
   serving bias
).

For example, a random streak of luck in financial operations,
mostly when the market is favorable,
might be considered as a result
of one's own skill.
This can build an overconfidence propicious to silly decisions the next
times.

 Extreme cases

Thus, in its extreme form:

A biased attribution can take the shape of

deification / demonization (see those words),

A self-serving attribution might show
overconfidence or even narcissism (see those words).
An highly dangerous arrogance and hubris that would
affect the next decisions.

The attribution bias can also be at play when people attribute a pattern
to some series or collections of events (see representativeness heuristic).

Au - Az


Dates of related message(s)
in the Behavioral-Finance group (*):

Year/month, d: developed / discussed,
i: incidental

Automaticity, autopilot bias



  Because of its length, this article
        
is in a separate page
         of this "A" glossary section

Availability bias, availability heuristics

See heuristic, primacy

Jumping on the first interpretation.

The availability heuristics is a cognitive bias using an oversimplified decision
process based on how easily:

Information is found or recalled

(this gives a primacy to the most immediate, visible or easy to memorize
one)

Or the causes or consequences of a situation are imagined.

See the "heuristic" detailed article.

Careful, you might be judged according to the first impression you
give!

(disappointment, loss, risk, regret, uncertainty... ) Averse, Aversion

Aversion, disposition and prospects

Because of their lengths, those
articles
are in a separate page

 of this "A" glossary section

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