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, due to a mind dependence (in its extreme forms categorized as a pathology), which overcomes rational thinking and causes actions that bring damages to the person affected, and sometimes to others 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	03/6i + see emotions, sentiment, mood, attitude, heuristic, automaticity, trust
I love it! I hate it! Definition (affect): The affect is the conscious part of an emotion (see that word). Emotions, based on pain and pleasure, are factors in many decisions. Definition (affect heuristic): An affect heuristic is a quasi automatic emotional response / reflex (see automaticity bias) or decision, which is linked to: The decider's love / hate, or liking / dislike    of something or somebody, Or his / her mood (see that word), when    feeling happy or unhappy. The person might label its attitude as "instinct", whatever the real nature of the stimulus that influences it. This emotional behavior might to be illusory and go against rationality. This can be compounded by the fact that emotions (see that word) tend to have a primacy over reasoning. A doctor, lawyer or detective is hardly neutral when a case is about a member of its family. For investors, the affect heuristic can cause a home bias (see that word), a trust in what is familiar. Examples in investing Swindlers can take advantage of the (positive) affect heuristic, as a factor of trust A reason why Bernard Madoff was trusted by its victims is that it was considered as ...a nice guy. This trust factor can also encourage clanism / groupthink / mimicry / herding, as a     feeling of togetherness. According to a well studied example, people, and among them investors, tend to feel more    optimistic when the sun shines! They react or decide accordingly, for example they feel an impulse to consume or invest. A good feeling towards a stock (positive affect) might lead to a lower risk perception and a higher benefit perception, This goes against common market experience by which high return prospects entail usually a higher risk (see risk premium)

(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 / preference (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 surprises are always possible. Therefore it is not too easy to predict how each category of agent will react to a situation without falling into caricatures. Also, the relative weight of the various categories might evolve. Those models are also one of the tools of microeconomics. Whatever the difficulties involved, this rising branch of economics has the merit to 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. 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. Therefore, positive or negative" alphas", meaning excess or insufficient returns that would be independent of the risk would be impossible. Samely, predictable alphas would be illusive. The random walk hypothesis says 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.

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
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 totally 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 some pattern, if not because of "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, some organization or some category of people. That bias puts the blame, or the credit, 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 due to one's own skill. This can create a an overconfidence propicious to silly decisions the next times. 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

(*) To find those messages: reach that Behavioral-Finance group and, once there,
      1) click "messages", 2) enter your query in "search archives".

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