A Critical Analysis of: Investor Irrationality and Self-Defeating Behavior
FIN645

Introduction For many years, finance traditionalists have held on to the theory that markets are efficient and that prices correctly reflect the information available to the market as a whole. This has come to be known as the efficient market hypothesis which was originally postulated by Eugene Fama in 1965. After a thorough statistical study of the movements of investment prices Fama concluded that “such movements were essentially random and unpredictable” (Shefrin p.75). Fama pointed out that “in an efficient market, prices correspond to intrinsic (or fundamental) value” (Shefrin p.75). In short, what the theory concludes is that it is impossible to beat the market; that no investor can ever purchase undervalued stocks or sell stocks at inflated prices. The market will always correct itself by incorporating all relevant information into the price of a security thus eliminating an individual investor’s ability to outperform. EMH has grown to become a cornerstone of financial theory and is still applied by many traditionalists when attempting to explain the behavior of financial markets.
While there is much evidence in support of this theory there is an equal amount dissention. There are many who argue that there is ample evidence available that counters the central ideas of EMH and demonstrate its shortcomings such as: individuals who have shown that they can consistently beat the market as in the case of Warren Buffet; or the recent bursting of the dot com and real estate bubbles, two events which clearly show that market prices can seriously deviate from their fair values. Given the mounting evidence in direct contrast to EMH “new attempts are being made to explain the behavior of financial markets, one of the foremost of which is in the area of behavioral finance” (Singh p.116).
In his article Investor Irrationality and Self Defeating Behavior: Insights from Behavioral Finance, author Sudhir Singh discusses the central tenets of behavioral finance in an attempt to reveal its impact on “investment decision-making at the individual level” (Singh p.117). He presents the concepts central to behavioral finance and a number of psychological biases that result in poor investment decision. He then discusses their implications for financial markets and also presents strategies, which he believes, investors can follow that will aid them in avoiding the pitfalls that many of these biases lead to. Singh believes that the study of behavioral finance will have the greatest impact on the individual investor as the awareness it brings forth will keep them from exhibiting these suboptimal behaviors.
Article Summary In his article Singh states that “interest in behavioral finance has been fueled by the inability of the traditional finance framework to explain many empirical patterns, including stock market bubbles… these models are incomplete, since they do not fully consider individual behavior” (Singh p.116). A central component of EMH is that investors behave rationally, yet, the belief that human flaws are consistent and measurable is gaining traction in the financial industry and there are many who believe that this irrationality can be predicted and exploited for big gains. This is in direct contrast to the theory presented by Fama many years ago. Behavioral finance is now replacing the rational behavior of investors with “cognitive psychology (how people think) and limits to arbitrage (when markets will be inefficient)” (Singh p.117). More specifically it is challenging the long held notion that markets are efficient because they take into account all past and present information that is available to the market as a whole. Behavioral finance states that investors are not rational and that they will be swayed by psychological biases which in turn will impact the efficiency of markets. The biases highlighted by Singh are heuristics, anchoring, the gamblers fallacy, overconfidence, mental accounting, framing, representativeness, conservatism, the disposition effect, loss aversion, and regret aversion.
Heuristics: Heuristics are mental shortcuts that have been developed to ease decision making in an increasingly complex world. In financial decision-making it can lead to poor decisions as the mental shortcuts are usually accompanied by biases as evidenced by the way “many people spread their savings evenly across several investment products without consideration to the riskiness of the alternatives, or the suitability in the 401(k) portfolio” (Singh p.117). This lack of proper analysis when making a decision is rooted in investor’s tendency to take shortcuts and do what appears to be correct.
Anchoring: Anchoring refers to the bias of individual investors to evaluate share price by referencing old trading ranges. The example provided by Singh is that of a stock trading at $10 a share. It is announced that earnings have increased by 300% yet the stock only rises to $12. He points out that the stock did not increase higher because investors “believe that the earnings increase is temporary when, in fact, the company will probably maintain its new earnings level” (Singh p.118). The investors that are anchored to the previous ranges and chose to ignore this earnings increase hold back the increase in price. This in turn results in a stock that is undervalued that can potentially be exploited for big gains.
Gamblers Fallacy: This bias occurs when investors believe that past performance has an effect on current outcomes. “This illusion may encourage the purchase or sale of a share on the grounds that the recent bad/good luck of the firm must be about to change” (Singh p.118).
Overconfidence: Overconfidence tends to result in an over estimation of one’s predictive abilities. This leads investors to trade excessively through the belief that they can consistently select the best investment. This increase of trading decreases the overall success of investors leading to more mispriced securities on the market.
Mental Accounting: This bias points to investor’s tendency to separate their world into differing mental accounts. It is typically used as a method of self-control. “Many investors still divide their money into a mental account for downside protection (containing cash and bonds) and a mental account for upside potential (containing stocks, options, and lottery tickets). Holding low risk investments inside a pension plan for retirement and high risk assets out-side of it demonstrates a similar mindset” (Singh p.119). This can lead investors to make inefficient decisions that subsequently lead to missing out on another more profitable opportunity. If the decision behind a loss or gain is not in line with their mental accounting, they may not make a move.
Framing: This bias pertains to the choice of words that are used to present a particular situation. Depending on how a question, suggestion, or issue is framed, an individual will differ in their response to it. “Framing is important to understand as it reflects the tendency of people to make different choices based on how the decision is framed… framing shows that the manner in which a concept is presented to individuals matters” (Singh p.119). Depending on the way an investor frames their decision on a security, either as a high probability for a gain or loss, can greatly impact what decision is ultimately made.
Representativeness: This bias refers to “the tendency of decision-makers to make decisions based on stereotypes, to see patterns where perhaps none exist” (Singh p.119). An example provided by Singh is when investors chase hot stocks and concurrently avoid the ones that have recently shown poor performance. This indicates that long term averages are not properly considered.
Conservatism: The conservatism bias is shown when investors are slow to adjust to change clinging to ways that things have normally been. Market conditions change frequently; the investors who show conservatism may miss the signs that are pointing towards this change resulting in missed opportunity.
Disposition Effect: This bias refers to investors patterns of avoiding the realization of a loss to instead seek out a realized gain. “The disposition effect is reflected in aggregate stock trading volume. During a bull market, trading tends to grow. If the market then turns south, trading volume tends to fall” (Singh p.119).
Loss Aversion: The loss aversion bias points to the fact that for most investors, “the mental penalty associated with a given loss is greater than the mental reward from a gain of the same size” (Singh p.120). This type of investor will be hesitant to realize a loss and “may even take increasing risks to escape from a losing position” (Singh p.120). Evidence of this is shown when investors attempt to increase the likely hood of recovering a loss on a stock when they purchase more of it as its price continues to drop. This averaging down method is increasing their risk as they are increasing their holdings in a falling stock.
Regret Aversion: This bias can affect investors in multiple ways. When deciding whether an investment will continue to be held, an investor may hold on to a poorly performing security in an attempt to avoid the regret that naturally follows the making of a decision that led to a loss. Moreover, when analyzing a new investment opportunity, an investor may “avoid sectors/firms which have performed poorly in recent times, in anticipation of the regret they would feel if they made the investment and subsequently lost money” (Singh p.120). According to Singh these biases can have major implications for financial markets because they can directly contradict EMH and cause investments to deviate from their fundamental values. “It is argued that because these biases are an inherent part of all our decision-making processes, they can systematically distort market behavior” (Singh p.120). Singh states that the presence of these biases can lead to: inaccurate responses to news or price fluctuations, past trends incorrectly being applied to future outcomes, lack of attention to sound fundamentals underlying a stock, or unjustified attention being paid to a stock based on popularity. The potential for these patterns to exist shows that investors, contrary to what is stated by EMH, can potentially outperform the market through exploitation of these “pricing anomalies to capture superior, risk-adjusted returns” (Singh p.120). However, the traditionalists who support EMH argue that “smart money will exploit such anomalies and drive prices to their fundamental values” (Singh p.120). Arbitrageurs can come in and correct the misevaluations before they become too large but if barriers exist then even arbitrage will fail to correct them. “Other research, however, shows that rational investor trading is unable to completely offset the actions of irrational investors” (Singh p.120)”. To avoid being influence by the biases listed by Singh suggests that investors utilize the strategies of:
Understanding biases: awareness of the biases will aid in their avoidance
Being aware of the reasons for investing: specificity when making investment goals will enable investors to make better decisions for the long term
Quantifying investment criteria: this will prevent one from “acting on rumors, emotion, and other detrimental biases” (Singh p.121)
Diversifying: The spreading of investments across different industries will limit ones exposure to risk or over-investing in a stock or industry that they are familiar with
Controlling one’s investment environment: this involves controlling trading volume and keeping review of investment portfolios to consistent time periods (such as once a month) to keep decisions in check and avoiding knee jerk reactions
Understanding that earning the market rate of return, or even slight underperformance, should not be anathema: by aiming for abnormal profits one increases their exposure to biases that contribute to lower returns. “Portfolio strategies based on indexing inhibit the deleterious effects of biases and wring out the emotion out of investing are, therefore, deemed the most successful” (Singh p.121). This is in agreement with the low returns anomaly.
In conclusion Singh states behavioral finance is still growing, and that while it is clear that biases do have an effect on prices in financial markets, they do not “quash all the predictions of efficient market theory” (Singh p.122). Because of this Singh advocates a “diverse approach in the choice of theoretical explanations of the behavior of financial markets” (Singh p.122). He argues that in the end, the individual investor will benefit the most from this research but also that “not many will disagree that the stock market bubble burst of 2000 or in 2008 is better explained by hubris and irrational exuberance grounded in behavioral finance than by the efficient markets theory” (Singh p.122).
Analysis
The author makes a compelling case for behavioral finance and why it deserves serious consideration when the behavior of financial markets is being researched. As has been discussed throughout the semester, whether the decision involves a CFO, an investor, or one who is the subject of prospect theory research the psychological aspect of their decisions plays an important role in the outcome and this cannot be ignored. As Shefrin points out “because psychologically induced mistakes can be, and often are, very expensive, studying behavioral corporate finance is vital” (p. 3). Valuations, capital budgeting, risk and return, capital structure or any one of the host of other topics that pertain to financial markets all have one thing in common; they each involve decisions being made by human beings.
One thing that can be said for sure is that human beings can be very irrational and the range of emotions, thoughts, or biases that are involved when decisions need to be made can include countless variations. If one were to look at the history of psychology, they would find there hundreds upon hundreds of books and theories that have been (and are still being) written with the purpose of attempting to explain the human experience. It is only natural then that these same considerations be applied in ‘all’ areas where human decision making is involved. It would be the height of vanity if one were to believe that they could explain anything involving an individual’s decision making without some consideration of the psychological aspects of the situation. While it is true that financial markets themselves are not human those that most influence its behavior are. To assume that through knowledge or experience alone, one can remove themselves from the effect of these biases is to state that one can remove themselves from the very thing that makes them human. Behavioral finance may never provide a final explanation of how financial markets behave and as Singh states, a combination of all theories would probably be the best course of action; however, the light that it sheds on the human element is one that was sorely needed and one that should not be ignored by anyone who serious about understanding how and why financial markets behave as they do.

References
Ackert, L.F., Deaves, R. (2010). Behavioral Finance. South-Western Cengage Learning
Singh, S. (2012). Investor irrationality and self-defeating behavior: Insights from behavioral finance. Journal of Global Business Management, 8(1), 116-122. Retrieved from http://ezproxy.umuc.edu/login?url=http://search.proquest.com/docview/993153659?accountid=14580
Shefrin, Hersh M., (2007). Behavioral Corporate Finance McGraw-Hill Irwin