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Hypothesis and the extent to which they can be explained by behavioural finance theories Finance that is based on rational and logical theories, such as the capital asset pricing model (CAPM) and the efficient market hypothesis (EMH). These theories assume that people, for the most part, behave rationally and predictably. The Efficient market hypothesis assumes that financial markets incorporate all public information and assets that share prices reflect all relevant to the firm information (Fama, 1970). Relevant information includes past information, publicly available information and private information.
Efficient market is divided into three categories. Weak form efficiency is when stock prices reflect only the past information, semi-strong form is when past information and all publicly available information is reflected and strong form is when all the past, publicly available and information only available to company insiders is reflected on the stock prices. However, there are some anomalies and behaviors that couldn’t be explained by EMH. Market participants often behaved very unpredictably.
However there is a new study called behavioral finance that is trying to explain all these anomalies.
Behavioral finance studies the irrational behavior of the investors. Weber (1999) makes the following observation: ‘Behavioral Finance closely combines individual behavior and market phenomena and uses the knowledge taken from both the psychological field and financial theory’. Behavioral finance attempts to identify the behavioral biases commonly exhibited by investors and also provides strategies to overcome them. Some of the main problems with EMH may be cause by heuristic responses to new information, psychological anchors, overconfidence, social fads, framing and regret avoidance and herd behavior.
Overconfidence: According to Nevins (2004), overconfidence suggests that investors overestimate their ability to predict market events, and because of their overconfidence they often take risks without receiving commensurate returns. Odean (1998) finds that investors tend to overestimate their ability, unrealistically optimistic about future events, too positive on self-evaluations, over-weight attention getting information that is consistent with their existing beliefs, and over-estimate the precision of their own private information.
Overconfidence about private signals causes overreaction and hence phenomena like the book/market effect and long-run reversals whereas self-attribution maintains overconfidence and allows prices to continue to overreact, creating momentum. In the longer-run there is reversal as prices revert to fundamentals. Psychological Anchors, Overreaction: Good news should raise a business’ share price accordingly, and that gain in share price should not decline if no new information has been released since. Reality, however, tends to contradict this theory.
Oftentimes, participants in the stock market predictably overreact to new information, creating a larger-than-appropriate effect on a security’s price. Furthermore, it also appears that this price surge is not a permanent trend – although the price change is usually sudden and sizable, the surge erodes over time. Heuristic responses to new information: Availability heuristic is used to evaluate the frequency or likelihood of an event on the basis of how quickly instances or associations come to mind. When examples or associations are easily brought to mind, this fact leads to an overestimation of the frequency or likelihood of this event.
Example: People are overestimating the divorce rate if they can quickly find examples of divorced friends. People tend to be biased by information that is easier to recall. They are swayed by information that is vivid, well-publicized, or recent. People also tend to be biased by examples that they can easily retrieve. ( Tversky and Kahneman, 1974) Confirmation bias is a cognitive bias whereby one tends to notice and look for information that confirms one’s existing beliefs, whilst ignoring anything that contradicts those beliefs. It is a type of selective thinking.
The reason for overconfidence may also have to do with hindsight bias, a tendency to think that one would have known actual events were coming before they happened, had one been present then or had reason to pay attention. Hindsight bias encourages a view of the world as more predictable than it really is (Shiller, 2000). This is the characteristic of investors, when looking back, seeing events that took place in the past as having been more predictable than they seemed before they happened. Likewise, things that didn’t happen seem, with hindsight, much less likely to have happened than they did beforehand.
Self-attribution bias occurs when people attribute successful outcomes to their own skill but blame unsuccessful outcomes on bad luck (Shefrin, 1999). Availability bias is the availability deviation is a general rule or a mental shortcut which lets people guess the probability of a result and to what percent it may appear in their daily life. Those who commit such a deviation consider the easily recalled events more probable than those they can hardly imagine or perceive. Availability bias declares the person’s tendency toward deciding and judging based on available and easily accessible data (Tversky and Kahneman, 1982).
Herd behavior which is the tendency for individuals to mimic the actions (rational or irrational) of a larger group. Blackmore (1991) states ‘Within an hour of birth , humans engage in imitation’. There are a couple of reasons why herd behavior happens. It’s unlikely that a large group could be wrong. After all, even if you are convinced that a particular idea or course or action is irrational or incorrect, you might still follow the herd, believing they know something that you don’t. Recency bias is the tendency for people to place greater importance on more recent data or experience.
This is the problem of putting too much weight on current events or data and not enough weight on past, historic trends. Many investors expect the market to continue rising in a current bull market; likewise, these same investors often expect a current bear market to get worse. Recency is shown in momentum investing when investors buy “hot” stocks simply on the basis of their recent strong performance. Kahneman and Tversky (1973) find that people usually forecast future uncertain events by focusing on recent history and pay less attention to the possibility that such short history could be generated by chance.
It is believed the net effect of the gains and losses involved with each choice are combined to present an overall evaluation of whether a choice is desirable. However, research has found that we don’t actually process information in such a rational way. In 1979, Kahneman and Tversky presented an idea called prospect theory, which contends that people value gains and losses differently, and, as such, will base decisions on perceived gains rather than perceived losses.
Thus, if a person were given two equal choices, one expressed in terms of possible gains and the other in possible losses, people would choose the former – even when they achieve the same economic end result. Regret avoidance is the tendency to avoid actions that could create discomfort over prior decisions, even though those actions may be in the individual’s best interest. Researchers have argued that one of the reasons that investors are reluctant to sell losing positions is because to do so is to admit a bad decision. This reluctance can be linked to both regret avoidance and belief perseverance.
To avoid the stress associated with admitting a mistake, the investor holds onto the losing position and hopes for a recovery. According to prospect theory, losses have more emotional impact than an equivalent amount of gains. Prospect theory also explains the occurrence of the disposition effect, which is the tendency for investors to hold on to losing stocks for too long and sell winning stocks too soon. The most logical course of action would be to hold on to winning stocks in order to further gains and to sell losing stocks in order to prevent escalating losses.
The flip side of the coin is investors that hold on to losing stocks for too long. Investors are willing to assume a higher level of risk in order to avoid the negative utility of a prospective loss. Unfortunately, many of the losing stocks never recover, and the losses incurred continued to mount, with often disastrous results. The January-Effect is where the average monthly return for small firms is consistently higher in January than any other month of the year; in the UK this is observed in April. This contradicts with EMH, as EMH predicts that stocks should move at a random walk.
January returns are greatest due to yearend tax loss selling of shares disproportionally (Branch 1977). Another anomaly of this type is the Weekend-Effect, where Fama (1980) found that returns on Mondays tend to be negative if compared to any other week day, but this has disappeared in the UK by the 1990s. Some theories that explain the effect attribute the tendency for companies to release bad news on Friday after the markets close to depressed stock prices on Monday. Others state that the weekend effect might be linked to short selling, which would affect stocks with high short interest positions.
Alternatively, the effect could simply be a result of traders’ fading optimism between Friday and Monday. Index effect is a phenomenon where the addition to, or deletion from, a stock index causes a change in the price, trading volume, volatility or operating performance of the stock concerned. A stock entering an index will automatically receive increased demand from institutional investors – principally index tracker funds and exchange trade funds (ETFs) – while a deleted stock will experience reduced demand.
The fact that a stock jumps in value upon inclusion is once again clear evidence of mispricing: the price of the share changes even though its fundamental value does not. Another anomaly is P/E effect from CAPM model; portfolios with low P/E ratios outperform those with high. The low price-earnings ratio effect occurs because stocks with low price-earnings ratios are often undervalued and their prices eventually rise because investors become pessimistic about their returns after a bad series of earning or bad news.
A company with high price to earning tends to overvalued (De Bondt and Thaler, 1985). Winner-Loser anomaly De Bondt and Thaler (1985) found that shares which initially earn extreme positive return (winners) or extreme negative returns (losers) experience extended reversals in their performance over long horizons. De Bondt and Thaler (1985) suggested the overreaction hypothesis as an explanation of their result. This hypothesis claims that the market overreacts to information. That is, the market overweights the most recent information and underweights earlier information.
However, this phenomenon is reversed when it is recognized that the market’s expectations were indeed an overreaction to the information released. This hypothesis also offers an explanation of the P/E effect. Fama and French (1992) showed that a powerful predictor of returns across securities is the ratio of the book value of the firm’s equity to the market value of equity. After controlling for the size and book-to-market effects, beta seemed to have no power to explain average security returns. One explanation is that investors overreact to growth aspects for growth stocks, and value stocks are therefore undervalued.
According to some academics, the ratio of market value to book value itself is a risk measure, and therefore the larger returns generated by low MV/BV stocks are simply a compensation for risk. Low MV/BV stocks are often those in some financial distress. All of these anomalies may be explained by behavioral finance. Behavioural finance is the study of the influence of psychology on the behavior of financial practitioners and the subsequent effect on markets. Behavioural finance is of interest because it helps explain why and how markets might be inefficient.
There are series of behavioural biases – strange twists in human nature that cause us to act irrationally and against our own interests. On the other hand all of these anomalies may instead be an artifact of data mining. After all, if one reruns the computer database of past returns over and over and examines stock returns along enough dimensions, simple chance will cause some criteria to appear to predict returns. May be this is why some anomalies appear to be lost at some point of time e. g. the weekend effect during the 90s.
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