Effect of Behavioural Biases on Individual & Professional Investors:
Behavioural finance is an area of finance that concentrates on psychology of financial markets and market participants' behaviours that underlie individual judgmental processes. According to Shefrin (2002), behavioural finance focuses on examining behaviour of practitioners who are prone to committing errors. It affects both individual and professional investors but to different extents. An individual investor purchases small amount of stocks compared to professional investor and is primarily concerned with managing his/her own stocks whereas professional investor either trades for his/herself or on behalf of financial organisations. Individual investors trade less frequently compared to professional investors and are deemed to be risk averse and poorly informed. Barber and Odean (2008) state that due to problem related to selecting a stock from thousands, individual investors are affected by biases more during buying stocks than selling but professional investors are affected during selling also because they deal in short selling. The major biases that affect above investors are discussed below.
Heuristic -driven Bias
Heuristic refers to a process where people use trial and error method to find things for themselves which ultimately leads to the formulation of rules of thumb accompanied by certain errors. These rules of thumb developed are known as heuristics and these errors are known as biases which are discussed below:
i) Availability Bias
This bias affects investors because the likelihood of an event is related directly to how easily it can be remembered or brought to mind. Events which are very familiar, recent or highlighted by media overestimate the likelihood of such events and investors become more optimistic about the related stocks. Knowing this, companies advertise more in order to have greater liquidity. Therefore, investors draw inferences using rules of thumb and from just the information that they have at their disposal and individual investors are affected more compared to professional investors by this bias.
ii) Representativeness Bias
The brain of investor reduces complexity of analysing information by using shortcuts one of which is representativeness. Investors believe that things that have similar qualities are quite alike and therefore their judgements are based on stereotypes. Gambler's fallacy, law of small numbers and ignoring regression towards mean are biases which are related to representativeness. An example of it is "good firm good stock" syndrome where investors are optimistic about the future of past winners and pessimistic about the future of past losers. But De Bondt and Thaler (1985) argue that past losers in preceding years outperform past winners over subsequent years. Due to this bias both individual and professional investors are affected during predicting markets, picking stocks and choosing mutual funds and leads to momentum investing.
iii) Anchoring and Adjustment Heuristic
When investors are asked to make quantitative assessment their views are affected by suggestions. Anchoring and adjustment bias comes into effect when investors remain anchored to old information and do not adjust satisfactorily to new information. As a result of this bias individual investors due to lack of information become conservative and under react to new information and create overly narrow confidence bands due to lack of expertise. This bias affects professional investors to lesser degree compared to individual investors.
Overconfidence
Overconfidence in investors is caused by illusion of knowledge and control. Overconfidence leads investors to overestimate their knowledge, underestimate the risks they can face and exaggerate their ability in controlling events. This overconfidence causes investors to feel that their stocks will perform better than that of peers. Professional investors believe their own skill to manage stocks. They also suffer from overconfidence but the effect is reduced due to their stock picking skill. Odean (1998) explains that overconfident investors own more risky stocks compared to rational investors. The implication of overconfidence to individual investors is that they take bad bets because of their inability to realize that they are at an informational disadvantage. According to Gervais and Odean (2001), investors overestimate the degree to which they consider themselves responsible for the success. Individual investors are not well caliberated due to overconfidence compared to professional investors.
Aversion to Ambiguity
Investors feel afraid of investing in situations involving ambiguity. The flip side of this is the preference for the known and the fear of the unknown. It occurs when people prefer familiar to unfamiliar. This bias towards familiarity affects people not only in trading but also in other spheres of life. Employees invest in stock of their own company and investors invest in their own country than investing internationally because they are more familiar with financial markets of their own country. Professional investors are more optimistic about their home markets compared to international markets. Professional investors are also affected by this bias even though they have they have highly available data.
B. Judgement Bias
Both individual and professional investors' decision processes are limited by personal judgment which often leads to errors and biases in decision making.
Loss Aversion
Loss aversion presents theory about loss tolerance. Kahneman and Tversky (1979) claimed that "losses loom larger than gains". They found that people take more account of losses than gain. Gross (1982) illustrates that individual investors don't want to give up the hope of making money. They continue to gamble to get even before getting out of the investment - "get-evenitis". Thaler and Johnson (1985) argue about "Break Even Effect" that decision makers usually face difficulties in closing mental accounts to realize losses. Another effect derived from loss aversion is endowment effect which leads to Status Quo bias. This also complies with some individual and professional investors who hold established investment position and not reallocate portfolio. Samuelson and Zeckhauser (1988) mention that individuals are prone to status quo bias when making actual decision. They find the existence of this bias even when there is no specific gain/loss framing effects.
Mental Accounting
According to Thaler (1984), decision makers divide types of gambles into particular accounts and use different decision rules. Gross (1982) propose "Hedonic Editing" which acclaimed that some investors transfer their assets from one mental account to another, rather than closing position and realizing losses. Thaler and Johnson (1990) also mention hedonic editing by observing how people respond to controlled set of problems and found that people are not uniform in tolerance for risk. Some of them have risk preference more than others. This particular bias can affect individual investor's decision more than professional's since there might be some controlled regulations.
Frame dependence
People's conceptions of acts or outcomes are related to a particular frame which is controlled by formulation of the problem or characteristics of decision maker. Biases and errors arise when the framing is opaque and there are difficulties seeing through problem solving process. Both individual and professional investors suffer from frame dependence, depending on each person's characteristics.
Regret and Pride
Regret is an emotion that one experiences when he makes wrong decision. It is the feeling affiliated with guilty for not making the right decision and being responsible for the losses; while pride is the counterparty of regret. Normally, a regret of commission is more hurtful than a regret of omission. According to Shefrin and Statman (1985), regret is caused by closing the stock account at loss; while pride is caused by closing at gain. Individual investors can be affected by regret and pride more comparing to professional investors.
v) Disposition Effect
This phenomenon arises when investors are obsessed with holding losers (stocks that perform poorly) too long and sell winners (stocks that outperform the market) too soon. Shefrin and Statman (1985) state that disposition is the circumstance where people realize losses in long-term and realize gains in short- term.
Why do individual investors keep investing even if they lose?
Odean (1999) explains that individual investors trade too much due to overconfidence and there is a possibility that overconfident investors may trade even if their returns are not enough to cover trading costs. They can even reduce their returns due to excessive trading even though trading costs are low. Individual investors display excessive optimism, are overconfident and discount diversification. Statman (2002) explains that hope and fear may be the strongest forces driving investing. Pope (1983) explains the reason individual investors continue investing even though they face losses by saying "people can dream from age nineteen to ninety-nine that they will become millionaires after next drawing." He further states that you can aspire to become millionaire either through regular contributions to 401(k) accounts or through only other options - lottery and stock trading. The greed and hope that they can do it in future what they have not been able to do in past are the driving forces in never ending trading of individual investors.
Conclusion
Studying the above behavioural biases we conclude that individual investors are affected more compared to professional investors as individual investors are greedier, overconfident and risk averse. Professional investors fair better because they are better informed and more experienced. So affect of behavioural biases on the investing decisions of investors is worth consideration.
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References
Brad, M. Barber, and Terrance, Odean 2008, All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors, The Review of Financial Studies, 21(2), 785-818.
De Bondt, Werner F.M. and Thaler, Richard 1985, Does stock market overreact? , Journal of Finance, 40(3), 793-805.
Gross, Leroy 1982, The art of selling intangibles: How to make your million ($) by investing other people's money, New York Institute of Finance.
Kahneman, Daniel. and Amos, Tversky., 1979, Prospect theory: An analysis of decision under risk, Econometrica Vol. 47, 263-291.
Meir, Statman 2002, Lottery players/stock traders, Financial Analysts Journal, 58(1), 14-21.
Montier James, 2002, Behavioural finance: Insights into irrational minds and markets, Wiley Finance.
Nofsinger, John, R., 2007, The psychology of investing, 3rd Edition, Prentice Hall.
Pope, R. 1983, The pre-outcome period & the utility of gambling, in foundation of utility & risk theory with applications, Edited by B.P. Stigum and F. Wenstop. Dordrencht, Netherlands, Reidel: 137-177.
Samuelson, William and Zeckhauser, Richard 1988, Status quo bias in decision making, Journal of Risk and Uncertainty, 1: 7-59.
Shefrin, Hersh., 2002, Beyond greed and fear: Understanding behavioural finance and psychology of investing, Oxford University Press.
Shefrin, Hersh and Statman, Meir 1985, The disposition to sell winners too early and ride losers too long: Theory and evidence, The Journal of Finance, Vol. XL, No. 3.
Simon, Gervais, and Terrance, Odean 2001, Learning to be overconfident, The Review of Financial Studies, 14(1), 1-27.
Terrance, Odean 1998, Volume, volatility, price, and profit when all traders are above average, Journal of Finance, LIII, 1887-1934.
Terrance, Odean 1999, Do investors trade too much? , The American Economic Review, 89(5), 1279-1298.
Thaler, Richard and Johnson, Eric 1985, The break even effect, Forthcoming working paper.
Thaler, Richard and Johnson, Eric 1990, Gambling with the house money and trying to break even: the effects of prior outcomes on risky choice, Management Science, Vol. 36, No. 6, June 1990
Thaler, Richard 1984, Using mental accounting in a theory of consumer behavior, Working Paper, Cornell University.
Post Earnings Announcement Drift Anomaly:
Since Ball and Brown (1968) published the first paper about post-earnings announcement drift (hereafter PEAD), the predictability of abnormal return after the earnings announcement has been one of the most robust anomalies in the asset pricing literature over the past four decades (Ke and Ramalingegowda, 2005). One of the most influential papers in the literature is Bernard and Thomas (1990) (hereafter BT), which address that the predictable return comes from the implement of models as well as investors' delayed response to the available earnings information. Although, Ball and Bartov (1996) question about the BT's hypothesis of investors' naïve prediction action, BT's work still provides the classic explanation about PEAD.
Over recent years, a large amount of academic papers have pushed the research of PEAD into great details. For example, Asthana (2003) shows the way IT influences PEAD; Chordia and Shivakumar (2005) prove the portion of PEAD can be explained by Inflation Illusion; Francis et al (2007) verify the relationship between Information Uncertainty and PEAD.
However, previous PEAD studies are mainly based on the US market, while the international evidence is quite sparse. This essay will first focus on and critically analyze some interesting empirical findings from the US market, and then discuss evidence of PEAD on the international level.
PEAD in US
Transaction Costs
One of the most interesting questions is that whether PEAD, regarded as a market anomaly, leads to positive profits net of transaction costs in the real world. The previous famous research (BT'89; BT'90; Ball, 1992) rule out transactions costs as an explanation for drift. Bhushan (1994) address that transaction costs (direct or indirect) can result in drift and are positively related to it. But he does not clarify whether transaction costs can overweight the profits made from this market anomaly.
Recent empirical findings show some rather conflicting results regarding this particular issue. Investigating the role of institutional investors, Ke and Ramalingegowda (2005) find that transient institutions can exploit the PEAD. Those transient institutions in the research earned quarterly average abnormal returns of 5.1% (or 22% annually) after transaction costs, but direct and indirect trading costs significantly reduce their aggressiveness in exploiting PEAD. Battalio and Mendenhall (2007) take into account of bid-ask spreads' impact on the profitability of a PEAD strategy and find that the long-short strategy continued to make money.
However, Avramov, et al (2006) finds that the short-run reversal strategies at the weekly and monthly frequencies are unprofitable after accounting for transaction costs. Tarun et al (2009) show that transaction costs (including the market impact costs and short-sale costs) account for 70-100 percent of the paper profits from a long-short strategy designed to exploit the PEAD. Therefore, although this strategy provides positive monthly value-weighted return, transaction costs have 'eaten up' almost all the paper profits.
These conflicting empirical findings may due to the choice of sample, use of high-frequency transaction data, inclusion of different transaction costs and so on. But they inspire us that any market anomalies (including PEAD) should be studied in the context of transaction costs, which have great impact on the profitability of price momentum strategies.
Individual vs. Institutional
Another puzzle about PEAD is whether individual investors or institutional investors are the source of PEAD. Bernard and Thomas (1990) provide evidence that PEAD is due to naive investors' under-reaction to the implications of current earnings for future earnings, but they do not define naive investors. It is worthwhile dividing investors into two categories - Individual investors and Institutional investor.
Usually individual investors are considered as 'naïve' investors, because they normally are not as sophisticated as institutional ones. Bartov et al. (2000) find that it is individual investors who contributed to PEAD, for example, PEAD was stronger in firms with high proportion of individual shareholdings and low proportion of institutional shareholdings. However, Hirshleifer et al. (2008) point out the result from Bartov et al. (2000) is a mixed outcome therefore does not provide a strong evidence to support his conclusion. Moreover, they examine the role played by individual investors again but find no evidence to prove trading by individual investors would induce dramatic earnings surprises which consequently lead to PEAD.
Nonetheless, Ke and Ramalingegowda (2005) also modify the way of researching based on the work of Bartov et al. (2000). They directly examine the trading behavior of institutional investors after earnings news rather than testing investors' efficiency of information processing. Their findings are consistent with Bhushan (1994)'s expectation that naïve investors such as individual investors is a source of PEAD while sophisticated investors such as institutional investors contribute to the persistence of PEAD.
Stock-related Findings
Empirical findings have also shown relations between PEAD and some stock-related characteristics. For instance, drift is inversely related to firm size (e.g., Foster, Olsen, and Shevlin, 1984; BT'89; BT'90); Brav and Heaton (2006) also find that drift is prevalent in stocks with smaller size.
However, Bhushan (1994) reports that there is a lack of interest for institutional investors to invest in smaller firms, and that those investments with largest firms can finally meet the investment objectives. Therefore, even though PEAD is tested to be negatively correlated to firm size, there is little empirical evidence showing that investment in smaller firms that try to exploit PEAD is profitable.
International PEAD
While PEAD is an established anomaly in the US, it is worthwhile studying non-US stock markets to see whether PEAD exists in the international context to challenge the view of efficient capital markets.
UK
For UK market, Hew et al. (1996) address evidence of PEAD in the London Stock Exchange, but their research is based on a limited sample and limited sample period. While Liu et al (2003), with a comprehensive, study on the UK market and the significant evidence of PEAD in the UK. They show the existence of the drift using three different earnings surprise measures based on the time-series of earnings, market prices and analyst forecasts. This takes into account the concerns of Livnat and Mendenhall (2006) that different measures of earnings surprise may raise different results about the drift.
Moreover, they support BT (1990)'s work that investors fail to realize the full implications of current earnings for future earnings. Thus Liu et al (2003) conclude semi-strong form of market inefficiency in the UK market. One important insight given by their research is that it questions whether there is a systematic failure for investors to process information, which constitutes a clear objection of the efficient markets hypothesis.
China
Chinese Market is different from U.S. market in legal environment, corporate governance and investor composition. Limited empirical finding shows mixed views regarding PEAD.
Liu et al (2002) examine the subsequent excess returns after loss warning announcement in Chinese stock market and find significant positive cumulative abnormal return (from day 2 to 60) of 7.81% on average. This return reversal pattern around loss warning announcement do not support the BT (1989)'s study that investors may under-react to earnings information. However, given the fact that Liu et al (2002) use limited sample size and period of only 315 events from 1999 to 2001, it causes doubts about the presence of PEAD in China market.
Yang and Zhou (2004) claim that they find no drift in China. But Tan (2008), who employed 345 events over the period from 2000 to 2005, find the existence of such drift in China, and also show that PEAD can be partially interpreted as compensation for liquidity.
Belgium
For a smaller capital market like Belgium, Van Huffel, Joos, and Ooghe (1996) analyse the existence of PEAD on Brussels Stock Exchange and applied market model and the size-adjusted returns model to estimate expected returns. But they fail to find a systematic PEAD in either model, although they discover that for the size-adjusted returns model a CAR pattern for large firms consistent with the results reported in the literature. Their research shows no evidence of PEAD in Belgium.
The international evidence is quite sparse and mixed. Del Brio et al (2002) and Booth et al (1997) find post-earnings announcement drift in the Spain and Finland, respectively. William et al (2006) also show that in Greek market PEAD existed in 20% of stocks with comparatively high liquidity and low transaction costs. A recent paper by Griffin et al (2007) test the degree of information efficiency of stock prices in 56 markets around the world and conclude that PEAD is present in 30 of 41 markets but, on a relative scale, abnormal returns associated with drift are not larger in emerging markets.
Conclusion
In sum, after nearly four decades, post-earnings announcement drift is still one of the most robust anomalies that attract a lot of financial research, which continuously provide new evidence for the phenomena. Although PEAD is not found in every country, debates like the reasons of PEAD and whether it is profitable will continue in the near future. Beyond this essay, we suggest further research can focus on the methodology of measuring PEAD and more empirical influence of it.
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