The Complete Guide to
Cognitive Biases & Behavioral Finance
In this guide on behavioral cognitive biases, you will learn:
Looking for a particular topic? cognitive biases behavioral finance overconfidence bias endowment bias conservatism bias regret aversion bias loss aversion bias cognitive dissonance bias representativeness bias anchoring bias confirmation bias hindsight bias self-attribution bias optimism bias practical applications
Chapter 1:
Introduction to Behavioral Finance & Cognitive Biases
In classical finance, traders and investors should always make rational decisions to maximise their self-interests, but in practice, quite often they end up making decisions that are not always rational, due to the influence of emotions and cognitive biases.
There is a whole (relatively new field) of finance called behavioral finance, which seeks to understand why this happens.
Now, let’s get started with the basics!
Behavioral finance is the branch of finance that combines classical finance (rational decision-making) with the psychological/behavioral aspect of market participants.
In layman terms, classical finance tells us what people should do, whereas behavioral finance tells us what people actually do.
The main reason for this difference is that classical finance assumes that humans are rational decision-making robots, but in reality humans are subject to emotions, flawed thinking, cognitive biases, etc.
If you have tried trading in the markets, or even played a game of chance like poker, you will know how hard it is to make rational decisions once money is at stake, and greed and fear starts to cloud your judgement.
To help traders and investors overcome the problem of emotions in decision-making, the first step is to be aware of the situations in which we might exercise flawed thinking, in the form of cognitive biases.
Cognitive biases are systematic errors in thinking that affect the decisions and judgments that people make, so they might think they are making logical and rational decisions, but in reality they are not, because the thinking/deduction process is flawed.
In the following chapters, I have listed out various common cognitive biases, and simple steps which traders and investor should take to avoid falling into the trap of these biases.
Once you are aware of these biases in your decision-making, it would be easier to find ways to avoid or overcome them.
Chapter 2:
Overconfidence Bias
Overconfidence bias is a tendency for people to overestimate their skills, abilities, or talents.
This makes people think that they are actually better than they are, when they are in fact not.
This might cause traders to find too many “good” trades, thus leading to over-trading.
Overconfidence is the unwarranted faith in one’s intuitive reasoning, judgments, and cognitive abilities. Studies conducted have shown that people overestimate both their own predictive abilities and the precision of information that they have been given.
In addition, people are poorly calibrated in estimating probabilities – events which they think are certain to happen are often less than 100% certain to happen.
In short, people think that they are smarter and have better information than they actually do.
For example, they may get a tip from a broker or read something off the internet, and they’re ready to take action, such as placing a trade, based on the perceived knowledge advantage.
If there is no logical basis for the advantage, then this perceived edge does not exist at all, despite what the trader thinks he knows.
There are two kinds of overconfidence – prediction overconfidence and certainty overconfidence.
In prediction overconfidence, the confidence intervals that traders assign to their predictions are too narrow. An example of this is when gurus try to forecast precise price targets.
In certainty overconfidence, traders are too certain of their judgments. For example, after entering a “sure-win” trade, traders become blind to the prospect of a loss, and then feel disappointed or surprised that the trade performs poorly.
Always keep in mind that trading is a game of probabilities, and nothing is 100%.
The dangers of overconfidence are numerous.
For example, if traders overestimate their ability to pick a winning trade, they become blind to warning signs or information that indicate that their decision was wrong. This might make them enter bad trades or hold on to losing positions.
If traders believe they have special knowledge, they may also end up trading excessively. Overconfidence can also cause traders to underestimate downside risk, and in worse cases not using a stoploss.
“Too many people overvalue what they are not and undervalue what they are.”
– Malcolm S. Forbes
Chapter 3:
Endowment Bias
Endowment bias is the tendency for people to get attached to the things that they currently own, hence they are reluctant to let go of it, even if it means they can trade it for something better.
In trading, this can be dangerous if traders get attached to their positions, and refuse to get out even when they are wrong.
People who exhibit endowment bias value an asset more when they own it, as compared to when they don’t.
This is inconsistent with standard economic theory, which asserts that a person’s willingness to pay for a good should always equal the person’s willingness to accept disposition of the good.
In essence, this bias is a mental process in which a differential weight is placed on the value of an object.
That value depends on whether one possesses the object and is faced with its loss or whether one does not possess the object and has the potential to gain it.
If one loses an object that is part of one’s endowment (ownership), then the magnitude of this loss is perceived to be greater than the magnitude of the corresponding gain if the object is newly added to one’s endowment.
For example, this bias influences traders to hold onto losing positions because they feel that they “own” the position, and are reluctant to close it and enter a better position instead, although the potential gains are higher.
This is often the result of decision paralysis, which places an irrational premium on the compensation price demanded in exchange for the disposal of the endowed asset.
One way to break free from flawed thinking is to ask yourself, “if you did not have any positions at the moment, would you still choose to take the same position which you are currently holding?”
If you answered no, then you might want to reflect on why you are still holding onto it.
“A wise man should have money in his head, but not his heart.”
– Jonathan Swift
Chapter 4:
Conservatism Bias
Conservatism bias is the tendency for people to stick to their existing thoughts and opinions, making it hard for them to change their minds and adapt to new information.
For traders, this is dangerous if they are too slow to see changes in trends or market direction, causing them to be stuck with wrong positions, or miss out on new opportunities.
Conservatism bias is a mental process in which people cling to their prior views or forecasts at the expense of acknowledging new information.
For example, suppose a trader receives some bad news regarding a company’s earnings and that this news negatively contradicts another earnings estimate issued the previous month.
Conservatism bias may cause the trader to under-react to the new information, maintaining impressions derived from the previous estimate rather than acting on the updated information.
It is important to note that the conservatism bias may appear to conflict with representativeness bias, but the latter refers to over-reacting to new information, while conservatism bias refers to under-reacting to new information.
The problem arises when traders cling to a particular view, behaving inflexibly when presented with new information which could signal a change in trend or underlying price action.
Even when conservatism-biased traders do react, they do so more slowly, and will have increased difficulty in dealing with this new information.
The key here once again is adaptability and objectivity, and when the wisest course of action becomes clear, it should be implemented resolutely and without hesitation.
A good trader is continually assessing and re-assessing the situation, and not getting tied down to a particular viewpoint.
Chapter 5:
Regret Aversion Bias
Regret aversion bias is the tendency for traders to choose their action (or inaction) based on whichever gives them the least regret afterwards.
This might cause them to avoid having to make a decision, such as holding losses in hope of a rebound instead of cutting loss, because if a rebound happens after they cut their losses, they would feel great regret.
People exhibiting regret aversion avoid taking decisive actions because they fear that, in hindsight, whatever course they select will prove less than optimal. Basically, this bias seeks to forestall the pain of regret associated with poor decision-making.
It is a cognitive phenomenon that often arises in traders, causing them to hold onto losing positions for too long in order to avoid admitting errors and realizing losses.
Regret aversion also makes people unduly apprehensive about taking positions after a string of losses, as they feel instinctively driven to conserve, to retreat, and to lick their wounds.
This might cause them to hesitate most at moments that actually merit aggressive behaviour.
This can also affect a person’s response to winning positions.
For example, traders might be unwillingly to sell an in-the-money position despite negative signals, choosing to cling on to it because they fear that the stock might continue to soar even higher once they sell it.
People who are regret-averse try to avoid distress arising from two types of mistakes, (i) errors of commission and (ii) errors of omission.
The former occurs when we take misguided actions, while the latter arises from misguided inaction, that is, opportunities overlooked or foregone.
The other danger comes from “herding behaviour” where traders simply try to follow the crowd, since following the mass consensus diffuses responsibility and hence the potential for future regret.
The way out of this is to have confidence in your methods and your skill, so that despite a string of losses, you will still be able to trade consistently, because you know that in the long run, you will be able to recoup those losses and turn up a profit when you manage to catch the big moves. The key here is discipline and consistency.
“I visualized my grief if the stock market went way up and I wasn’t in it – or if it went way down and I was completely in it. My intention was to minimize my future regret, so I split my retirement plan contributions 50/50 between bonds and equities.” – Harry Markowitz, father of Modern Portfolio Theory
Chapter 6:
Loss Aversion Bias
Loss aversion bias is the tendency for people to avoid losses, even if such avoidance can subsequently lead to even more losses in the future.
This leads to traders not wanting to cut losses (in the hope that prices might rebound), or taking profits too early (afraid that they might lose their open profits if the market moves against them).
Loss aversion bias was developed by Daniel Kahneman and Amos Tversky in 1979 as part of the original prospect theory.
Basically, it suggests that psychologically, the possibility of a loss is on average twice as powerful a motivator as the possibility of making a gain of equal magnitude.
In short, it suggests that people woud prefer to avoid a loss to realizing a gain.
Loss aversion can prevent people from cutting losing trades, even when they see no prospect of a turnaround.
Some industry veterans have coined a diagnosis of “get-even-itis” to describe this widespread affliction, whereby a person waits too long for a trade to rebound instead of cutting their losses.
This is dangerous because the best response to a loss is to cut it fast and move on to a better trade.
Similarly, loss aversion bias can make traders dwell excessively on risk avoidance when evaluating possible gains, since dodging a loss is a more urgent concern than seeking a profit.
When their trades start to show a profit, loss-averse traders hasten to lock in profits, fearing that, the market might reverse itself and rescind their profits.
The problem here is that exiting too early to protect gains severely limits upside potential. This prevents traders from catching the big moves.
This is where the importance of the stoploss comes in.
If a trader is disciplined, and has a preset stoploss point, the trader will exit a losing trade once the stoploss point is breached.
This removes any blind hope of a rebound, and by squaring off positions, it puts the trader in a neutral frame of mind to enter the next trade, and at the same time frees up the capital for it.
“Win as though you were used it to, lose as if you enjoyed it for a change.” – Ralph Waldo Emerson
Chapter 7:
Cognitive Dissonance Bias
Cognitive dissonance bias occurs to people when what they think is correct or real turns out to be wrong in reality, and they have difficulty adjusting and updating their way of thinking.
For example, a trader might have a very bullish view of the market, but if the market goes down instead, the trader will need to accept that his view was wrong, and adapt to the new reality.
When newly acquired information conflicts with preexisting understandings, people often experience mental discomfort – a psychological phenomenon known as cognitive dissonance.
Cognitions, in psychology, represents attitudes, emotions, beliefs, or values; and cognitive dissonance is a state of imbalance that occurs when contradictory cognitions intersect.
This term encompasses the response that arises as people struggle to harmonize cognitions and thereby relieve their mental discomfort.
For example, a trader might take a long position in a stock thinking that the trend is up, however when a new cognition that favours a downtrend is introduced, representing an imbalance, cognitive dissonance then occurs in an attempt to relieve the discomfort with the notion that perhaps the trader did not make the right decision.
People will go to great lengths to convince themselves that the decision they made was the right one, to avoid the mental discomfort associated with their wrong decision.
Psychologists hence conclude that people often perform far-reaching rationalizations in order to synchronise their cognitions and maintain psychological stability.
There are actually two kinds of cognitive dissonance bias – (i) selective perception, where people only register information that appears to affirm a chosen course, and (ii) selective decision making, where people rationalise actions in order to stick to an original course.
The dangers are obvious.
Traders who are not bias-free cannot read the markets objectively, and will not be able to adapt fast enough to changing market conditions.
Selective decision making could also lead to a resistance to cutting losses, and coming up with various excuses to avoid admitting their initial entry was indeed erroneous.
The key to overcoming this is to immediately admit that a faulty cognition has occurred, address feelings of unease and take appropriate rational action.
If you think you have made a bad trading decision, analyse the decision; if the fears prove correct, confront the problem head-on and rectify the problem.
This above all: to thine own self be true,
And it must follow, as the day the night.
– Polonius to Laertes, in Shakespeare’s Hamlet
Chapter 8:
Representativeness Bias
Representativeness bias is he tendency for people to inaccurately extrapolate a small pool of data and draw incorrect conclusions from it.
For example, a trader who has 5 winning trades in a row might think that his trading system is excellent, but in reality, if the same system is run over 1000 trades over a period of time, the success rate might only be 40%.
In order to derive meaning from life experiences, people have developed an innate propensity for classifying objects and thoughts.
When they confront a new phenomenon that is inconsistent with any of their preconstructed classifications, they subject it to those classifications anyway, relying on a rough best-fit approximation.
There are two main types of representativeness bias, namely (i) base-rate neglect and (ii) sample-size neglect. We will focus on the latter, since it occurs more frequently in trading.
In sample-size neglect, traders, when judging the likelihood of a particular trade outcome, often fail to accurately consider the sample size of the data from which they base their judgments. They incorrectly assume that small sample sizes are representative of populations.
This is also known as “the law of small numbers”.
This problem is observed when traders try to backtest systems by using small sample sizes of data, and extrapolate their favourable results.
However, these results are most likely not representative of the effectiveness of the system. This is a common tactic applied in marketing gimmicks.
Another common phenomenon has to do with hot tips.
For example, you might hear someone say “my broker gave me three great stock picks over the past month, and each stock is up by over 10%”.
While this is enough to sway most people, thinking that the broker is a genius, this assessment is based on a very small sample size.
If you want to evaluate the effectiveness of system or the stock-picking skills of a person, make sure you do it over a large sample size, and count both the hits and misses.
This will give you a more complete representation of reality.
Chapter 9:
Anchoring Bias
Anchoring bias is the tendency for people to get overly attached to their initial opinions, making it difficult for them to change their minds, and affecting how they view new information that comes in.
For example, traders often get attached to their entry price, and tend to measure the upside or downside of the market (as well as their profits and losses) using that price as a mental anchor.
Anchoring and adjustment is a psychological heuristic that influences the way people intuit probabilities.
Traders exhibiting this bias are often influenced by their initial opinions, the initial trend, or arbitrary price levels such as their entry or target prices – and tend to cling to these numbers when making their buy/sell decisions.
This is especially true when the introduction of new information regarding the security further complicates the situation.
Rational traders treat these new pieces of information objectively and do not reflect on purchase prices or target prices in deciding how to act.
Anchoring and adjustment bias, however, implies that investors perceive new information though an essentially warped lens.
They place undue emphasis on statistically arbitrary, psychologically determined anchor points. Decision making therefore deviates from neoclassically prescribed “rational” norms.
For example, traders who are anchored to the initial trend are slow to catch on when the trend has reversed, especially if they are caught on the wrong side of it.
This will lead to a reluctance to change their view and reverse their positions.
Traders who are anchored to price levels, such as their entry price, will refuse to cut their losses until prices go back to the entry price which they have anchored to.
Traders may also refuse to take profit at a less desirable price because they missed the chance to take profit at a more favourable price, and they have now anchored to that price and refuse to settle for less.
The key to overcoming this bias is to be flexible and objective, being able to evaluate prices and make decisions objectively, whether you are in, out, up or down.
Chapter 10:
Confirmation Bias
Confirmation bias is the tendency for people to collect evidence which supports their preconceived views, while ignoring or discarding evidence which contradicts that view.
Due to the large amount of information on the internet, it is easy for traders to find “experts” who agree with any view they have decided on, causing them to get “locked in” on a particular view, while thinking that everyone shares that same view.
Confirmation bias refers to a type of selective perception that emphasizes ideas that confirm our beliefs, while devaluing whatever contradicts our beliefs.
This can be thought of as a form of selection bias in collecting evidence to support certain chosen beliefs.
For example, you may believe that more red cars drive by your house during the summer than during any other time of the year; however, this belief may be due to confirmation bias, which causes you to simply notice more red cars during summer, while overlooking them during other months.
This tendency, over time, unjustifiably strengthens your belief regarding the summertime concentration of red cars.
To describe this phenomenon another way, we might say that confirmation bias refers to our all-too-natural ability to convince ourselves of whatever it is that we want to believe.
We attach undue emphasis to events that corroborate the outcomes we desire and downplay whatever contrary evidence arises.
For traders, this is dangerous because traders who are entrenched in their opinion will only actively seek out information that confirms their opinion, while ignoring those that do not.
This is especially true for traders who rely heavily on indicators, since many indicators will give conflicting signals, and it is not hard for a trader to find those indicators which support a chosen viewpoint.
Another hazard comes in the form of marketing gimmicks and market gurus, who like to make a lot of (absurd) forecasts based on their “sure-win” trading method or system.
To newbie traders, they may appear to have a very high success rate, mostly because people want to believe the guru, hence they will celebrate his successful predictions while ignoring his less-accurate (or completely off) forecasts.
Once again, objectivity is necessary to see both sides of the coin, and the best way if you want to test if a method works is to record every signal (whether it is a gain or loss), and not just record those instances where it worked, while ignoring those times when it did not.
“It is the peculiar and perpetual error of the human understanding to be more moved and excited by affirmatives then by negatives.”
– Francis Bacon
Chapter 11:
Hindsight Bias
Hindsight bias is the tendency for people to look back at the past and think that it was easy to predict the future, given that they now already know the outcome.
This might make traders think that they are better and smarter than they actually are, because they will tend to remember their winning trades (successful predictions), while downplaying or forgetting their losing trades (wrong predictions).
Described in simple terms, hindsight bias is the impulse that insists: “I knew it all along!”
Once an event has elapsed, people afflicted with hindsight bias tend to perceive that the event was predictable – even if it wasn’t.
This behaviour is precipitated by the fact that actual outcomes are more readily grasped by people’s minds than the infinite array of outcomes that could have but didn’t materialize.
Therefore, people tend to overestimate the accuracy of their own predictions.
This is not to say, obviously, that people cannot make accurate predictions, merely that people may believe that they made an accurate prediction in hindsight.
This affects future forecasting, because a person subject to hindsight bias assumes that the outcome he or she ultimately observes is, in fact, the only outcome that was ever possible.
Thus, he or she underestimates the uncertainty preceding the event in question and underrates the outcomes that could have materialized but did not.
One detriment of hindsight bias is that it can prevent learning from mistakes.
People with hindsight bias connected to another psychological bias, anchoring, find it difficult to reconstruct an unbiased state of mind, simply because it leads people to exaggerate the quality of their foresight.
When hindsight-biased traders have a winning trade, they tend to rewrite their own memories to portray the positive developments as if they were predictable.
Over time, this rationale can inspire excessive risk-taking, because they believe they have superior predictive abilities.
Hindsight-biased traders also “rewrite history” when they fare poorly and block out recollections of prior, incorrect trades in order to alleviate embarrassment.
This form of self-deception, in some ways similar to cognitive dissonance, prevents traders from learning from their mistakes.
In order to overcome hindsight bias, it is necessary, as with most biases, for the trader to understand and admit their susceptibility.
One way to face the facts is to keep a trading journal, and use it to record your analysis and reasons for every trade, as well as the thought-process and emotional swings that went with the whole trade.
This will be useful when you look back to the past after the event, and will prevent any disillusioned thinking.
“You didn’t know it all long; you just think you did.”
– James Montier
Chapter 12:
Self-attribution Bias
Self-attribution bias is the tendency for people to take credit for any success, while blaming others or external factors for any failure.
This leads traders to think that they are better than they are, causing them to become overconfident, and because they do not admit their mistakes, they will not learn from them, which means they will likely repeat those mistakes
Self-attribution bias (or self-serving attributional bias) refers to the tendency of individuals to ascribe their successes to innate aspects, such as talent or foresight, while more often blaming failures on outside influences, such as bad luck.
There are actually two kinds of self-attribution bias, namely self-enhancing bias and self-protecting bias.
Self-enhancing bias represents people’s propensity to claim an irrational degree of credit for their successes, for example, if people intend to succeed, then outcomes in accordance with this intention will be perceived as the results of them acting to achieve the intention, regardless of whether the actions indeed played a crucial role.
Self-protecting bias represents the corollary effect – the irrational denial of responsibility of failure, for example people trying to maintain their self-esteem by protecting themselves psychologically as they attempt to comprehend their failures.
Irrationally attributing successes and failures can impair traders in two ways.
First, people who aren’t able to perceive the mistakes they’ve made are, consequently, unable to learn from those mistakes.
Second, traders who disproportionately credit themselves when desirable outcomes do arise can become detrimentally overconfident in their own market savvy, leading to overconfidence bias.
When trades turn out well, people like to think that their method or analysis was fantastic, and that they are good traders.
When trades do not turn out well, people will blame their broker, their platform, the news – basically anything but themselves.
As you can see, over time, this leads traders to think that they are much better than they actually are.
One way to overcome this bias is to treat both winning and losing trades as objectively as possible, tabulating and recording them to obtain a running record.
It also helps to do an objective post-trade analysis, reviewing your records to learn from past mistakes.
With sufficient data, one can then objectively analyse the consistency of the methods and returns, and as they say – the numbers do not lie.
“Don’t confuse brains with a bull market.”
Chapter 13:
Optimism Bias
Optimism bias is the tendency for people to be over-optimistic about themselves or outcomes that involve themselves, in effect thinking that they are luckier or better than others.
When evaluating trading opportunities, this misleads traders to focus only on the upside returns, causing them to neglect the risk or loss from a downside scenarios, which in turn causes them to have no risk management plans in place.
Most people have heard of “rose-tinted glasses” and know that those who wear them tend to view the world with undue optimism.
Studies have shown that with respect to most positive traits, for example driving ability, good looks, sense of humour, physique, etc, most people tend to rate themselves as above average.
Logically speaking, this is not possible.
Traders, too, tend to be overly optimistic about the markets, the economy, the economy, and the potential for positive performance of the investments they make.
Many overly optimistic traders believe that bad investments will not happen to them – those only afflict “others”.
Such oversights can damage portfolios because people fail to mindfully acknowledge the potential for adverse consequences in the investment decisions they make.
Optimism can cause traders to think that they are getting above-market returns, when in fact they need to take into account things like inflation, commissions, and whether they would be better off simply buying an index fund.
Another danger is when traders read too much into rosy forecasts about the economy or a particular earnings forecast, which could cause them to take larger or more risky positions than they should due to “hope”.
Optimism bias can cause traders to think that they are above-average traders, simply because they are optimistic people in general, or to believe that they are above average in other areas of their life, such as driving ability or social skills, which could further lead to overconfidence bias.
“Comedy is acting out optimism.”
– Robin Williams
Chapter 14:
Practical Applications to Trading
Knowing all the different cognitive biases and dangers of emotional decision-making can make us more aware of whether we are thinking logically and making the right decisions.
But it can hard to be on 100% alert all the time, especially on stressful days.
So, what are some of the simple habits we can cultivate to eliminate or reduce the risks of cognitive biases?
Conclusion
I hope you have enjoyed this guide on how to tackle behavioral cognitive biases.
Now I’ll like to hear from you: what is your key take-away from this trading guide?
What of these biases are you struggling with the most?
Which do you think will have the greatest impact on your trading results if you manage to overcome it?
Are there any other behavioral biases that we have missed out?
Let me know by leaving a quick comment below right now.
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