While traditional finance assumes that investors will rationally calculate probabilities of outcomes to maximize utility, behavioral finance suggests that we make decisions based on bounded rationality and instead of maximizing our benefit, we come to satisfactory conclusions without necessarily getting what is best.
Various biases that come with human behavior pose into question the efficient market hypothesis, one of the main issues of which is, in fact, that it assumes that all investors perceive all available information in the same manner. Yet, a simple example of difference in methods of value perception is frequently observed when two different investors might come to different conclusions about a stock’s fair value, if one of them evaluates a stock strictly based on its growth potential, while the other is looking for undervalued opportunities.
Below are some examples where investors do not fully act as rational agents to truly maximize utility, but are rather driven by some behavioral biases in their investment decisions and interpretation of outcomes and information.
Cognitive biases are often observed on how people process information using one research report to justify a stock purchase while they might have come across various other reports suggesting selling the stock. An example is the anchoring bias, when we tend to cling on to the first information that we received regardless of its reliability. If the first price of an asset that we heard of was quite larger than the one we observe presently we might get the impression that the asset is currently undervalued and presents a buying opportunity. Also, investors tend to make general market forecasts that are too close to current levels, forecasting DJIA index in a way narrower that would be suggested by historical standard deviation analysis (which would be rational behavior). Investors tend to stick too closely to their original estimates when new information is revealed about a company. Sometimes people anchor themselves to countries (Japan)or companies (GE,IBM) that have been powerhouses, even though they might have stagnated for years. Confirmation bias occurs when we tend to listen to information that confirms what we already knew and believed, or even interpret the information that we receive in a way that confirms what we already knew. Conservatism bias may cause investors to underreact to new information maintaining impressions derived from a previous estimate. An example is when an investor purchases a stock believing a ground-breaking product is about to be launched and holds on to the initial optimistic expectation even though the company announces financial difficulties in marketing the product.
Regret aversion bias is known as the cause of “herding”. Investors avoid taking their own decisive actions because they fear that whatever course they take will turn out suboptimal. People do not want to regret a decision they have made, thus they tend to conform with what others do. This behavioral pattern is known in finance as “herding”, where people buy in industries that others are buying and sell into others, regardless of their own judgement of whether it is a good time to sell or buy. Momentum is caused when people buy a stock because they think that others think it will rise. This can also occur from the bias of “group thinking” meaning that if 9 out of 10 people agree on something they can squeeze an individual’s good idea. Regret aversion can make investors unreasonably opt out of markets that have recently had losses and similarly hold on to winning stocks for too long. It can make people too conservative avoiding taking any risk and leading to below average performance.
An example is when traders believe that there is a rising asset price bubble and want to sell before the bubble bursts. There will still be though plenty of buyers, because they do not know when the bubble will burst and hope it still has room to expand before that happens. Psychology enters here because of the human tendency to extrapolate-to infer a trend from recent experience. This tendency is especially likely to occur in a situation of uncertainty since the immediate future cannot really be estimated. If the price trend is upward, there is often an irrational feeling that it will continue trending upward, at least for a time. Another explanation for that behavior could be the positive and negative connotation that some terms can have. For example, people do not like being called “Cassandras”, “prophets of doom”, “naysayers”, or even short sellers. Similarly, nobody likes the trader who pricks the stock bubble. “Pessimist” has a negative connotation, “optimist” a positive one especially in American culture where everything can be possible. Unreasonably, rosy forecasts tend to derive from biased feelings about specific current situations while largely ignoring the outcomes of previous related situations. One example of “recency bias” is when investors track fund managers who produce temporarily above average returns during a one, two- or three-year period. Recency bias can cause investors to ignore proper asset allocation when they become infatuated with a certain asset class.
Home bias is the tendency to overinvest in familiar securities. Investors sometimes believe that information on domestic assets is of better quality than that on foreign assets. People become unduly “patriotic” when looking for somewhere to invest especially in the US, even though 50percent of equity capitalization exists abroad. From one part, home bias is the tendency for investors to invest the majority of their portfolio in domestic equities, ignoring the benefits of diversifying into foreign equities, while it can also mean a preference for investing in what people are already familiar with rather than moving into the unknown. It is the “invest in what you know” ideology. Narrow range of experience and resonance might explain such behavior. People often opt for investments that match their personalities, such as someone who bargains leans towards value investing and an employee of a fast-growing high-tech company is prone to overestimate the proportion of corporate profitability that comes from the tech sector. Ambiguity aversion can cause investors to believe local indexes are less ambiguous than foreign and even that firms located close to them geographically are less ambiguous than those further away. Others might opt for their own employers’ stocks assuming familiarity.
Another behavioral mistake investors can make, is when they buy and sell based on feeling and anecdote and do not make decisions based on actual statistics, but rather on stories that they hear from others and trending news, thus not properly calculating the probability of an adverse event. An extraordinary event is more intriguing, becomes over projected and more discussed in the news, making people underestimate daily dangers that can contribute to an adverse outcome. An example is when people by word of mouth keep listening in the news about a new trending company (Zoom) and assign to it the wrong probability of appreciating in value because it has been over projected as a fad. Another example is when there has been a recent crisis and people fear that the same crisis could be soon repeated due to their recent experience assigning a larger probability of a seriously adverse event than mathematically reasonable. Availability bias is a rule of thumb that allows people to estimate the probability of an event based on how common it appears in their lives. Examples involve retrievability, where investors when asked to identify the best mutual fund company they often choose one that engages heavily in advertising (Fidelity).
Another common error involves the “Gambler’s Fallacy”, making people believe that gambling luck is abundant besides mathematical evidence. “The law of small numbers” is the non-scientifically based assumption that small numbers faithfully represent populations or real data. Gambler’s fallacy arises out of a belief in the law of small numbers, or the erroneous belief that small samples must be representative of the larger population; all “stains” or different observations must eventually even out in order to be representative. Getting heads five times in a row when tossing coin, does not mean that someone has more than a 50/50 chance of making the right prediction of the next toss. An example of the gambler’s fallacy is also the feeling that a number that has not shown up on the lottery or on a roulette wheel for a while has to be ‘due’. In finance this can be observed if the stock market has gone up for a period, some investors fear that at any minute everything is going to go into reverse. They announce they are not investing anymore as the market is about to crash soon. The opposite, known as the “hot-hand effect”, is observed when we compare the rising stock market example to how we tend to think about house prices, and rather irrationally get a totally different reaction. As property prices rise, people claim it is a safe bet to invest in the house market because they do not perceive a reason why prices should not continue rising. Because house price crashes are relatively rare, there’s less available information about available which makes them less dreaded. This also touches the availability bias mentioned above.
Representativeness bias can also occur due to people’s tendency to categorize companies, as “value stocks”, for instance, and conclude on their risk-return potential based on that categorization, without performing careful research on the specific company. In those cases, investors ignore the statistically dominant result in order to satisfy their need for patterns. Similar mistakes can be made when evaluating the record of stock analysts, investors often focus on the success of an analyst’s past few recommendations and might simply rely and follow the analyst based on a limited data sample. Similarly, they can opt for a fund that has performed well over recent quarters without a careful evaluation of the longer-term overall skill of management.
Another mistake that investors can make is known as short term gratification. Instant gratification is a term that refers to the temptation, and resulting tendency, to forego a future benefit in order to obtain a less rewarding but more immediate benefit. An example is when people are spending easily money that they believe were easily acquired, even though it is actually just as valuable as a similar amount acquired by a longer and harder process. This is an irrational treatment of money, known as mental accounting, treating various sums of money differently based on where they are categorized (work, inheritance, gambling, bonus).
Loss aversion is a major subject of investors’ behavioral biases. It involves feeling worse about losing an amount of money than feeling rewarded from gaining a similar amount. This can cause, when markets go down, investors to fear more about losing more money and sell their holdings causing the market to drop further. Loss aversion refers to having a much greater desire to avoid any risk that could bring about a loss, rather than to acquire a similar gain. Loss aversion can cause selling winners too early (too much trading leading to suboptimal results) and to unknowingly take more risk in the portfolio if they just sold the underperforming asset. Investors are waiting for the stock to reach a certain price, the entry point or a round number, in order to buy or sell. How things are presented can also have a different effect, meaning that an identical outcome can cause more distress, if it is framed as a loss rather than as a missed opportunity for a gain. Loss aversion can cause investors to hold unbalanced portfolios when rebalancing is needed to suit the client’s strategic goals. People answer questions differently concerning their risk tolerance based on how they are framed, if they are worded more in the “gain” than the “loss” or “risk” frame. Negative framing and loss aversion together lead to excessive aversion.
The desire to avoid losses by selling existing familiar assets can result in an “endowment effect”, where people start valuing an item more highly once they own it and feel they have property rights on it. It is inconsistent with economic theory that a person’s willingness to pay for an asset should equal the persons willingness accept dispossession measured in terms of compensation. Endowment bias causes investors to hold securities they have either inherited or purchased because of familiarity and of avoidance of the transaction costs and perceived tax consequences. Owning Apple stocks can give people, after they have been acquired, the bias that they are a valuable holding that they must hold on to and shouldn’t let go making them unwilling to trade them with some other technology stock of similar magnitude.
Choice support bias can occur when we support the advantages of an asset and overlook at its downsides just because it was our choice and we do not want to admit we made a bad decision, a behavioral pattern that stems from cognitive dissonance that can cause investors to get caught up in herds of behavior. Similarly, Ostrich bias occurs when we focus on positive and reject negative information as an outlier and even stop searching for contradicting evidence. In finance, the ostrich effect occurs when investors are in dangerous or risky financial situations but choose to pretend that these situations do not exist. A study showed that investors when deciding whether to sell or retain an investment are affected by the difference between the security’s purchase price and current price and might even be tempted to “double down” continuing a risky investment hoping to “break even” to avoid the humiliation of admitting a bad investment. Selective perception is a similar behavior when we tend to overlook evidence that contradicts our beliefs and expectations. Or, cognitive dissonance, when two or more contradictory beliefs are held and can cause investors to believe “it is different this time”, as when in the late 1990s many disregarded the fact that there were no excess returns from purchasing the most expensive stocks around. Cognitive dissonance when new information conflicts pre-existing views can lead to holding losers and averaging down.
Outcome bias is observed when we judge the efficacy of a decision by observing the outcome that occurs after the decision was made and we ignore the prevailing condition at the time the decision was made. This is also known as consequentialism, that can cause investors to only trust their instinct and overlook suggestions by others because the outcome of their decision eventually turned out to be right at some case even if it was luck. Hindsight bias is the impulse “I knew it all along”, after an event has occurred people feel it was predictable even if it was not. An example is in 1999 nobody viewed the rising indexes as a short-lived bubble even if a basic consideration previous business cycles would have shown the bull market would pull-back, however many experienced investors believed “it is different this time”.
Another biased behavior known as Overconfidence can also stem from this pattern. Some correct decisions can increase our confidence to the point that we believe that whatever stock we pick is the best option. Self-enhancing bias is people’s tendency to claim an irrational degree of credit for their success, while self-protecting bias is the irrational denial of responsibility for failure (bad luck). Overconfidence is also observed in people, like traders, who think they have too much expertise in a certain field.
Overconfident investors can trade excessively as a result of believing that they possess special knowledge, an attitude shown to lead to excessive trading and suboptimal results. Active investors, those who have earned their own wealth in their lifetime, believe in themselves and have high risk tolerance as long as they believe they have high control of their investments. They rather irrationally hold the belief that by their involvement, gathering tremendous information or believing they can control the fate of a company, they can reduce risk to an acceptable level. Illusion of control can cause investors to use limit orders in order to experience a false sense of control over their investments. Overconfident investors hold undiversified portfolios (portfolio concentration) taking more risk than they tolerate, underestimating their down side risks.
Survivorship bias is when an analyst evaluates the performance of funds or individual stocks based on the ones currently survive, using only the end of period survivors, disregarding the ones that have failed and excluding the ones that no longer exist. We easily overlook funds or small growth firms that did not succeed typically because of their lack of visibility. Another example is when we simply follow the example of a millionaire investor and neglect the fact that there are other people who have followed those patterns but have not really succeed into becoming millionaires.
Finally, there is the blind spot bias, meaning that when people are asked how biased they are, most of them believe that they are less biased than the average person. So when it comes to evaluating our investing behavior, there is also our bias to overlook that we follow cognitive biases when we make our decisions.