- A bias towards optimism often leads investors to have an unrealistically positive view of themselves and their futures.
- Optimism bias and cognitive dissonance also lead many individual investors to overestimate their investment results.
- While investor beliefs in their ability to predict probable outcomes (overconfidence) increases with information, studies show there is no corresponding increase in prediction accuracy.
In Behavioral Finance: Loss and Regret Aversion, we further examined the investor bias theories that emerged from Daniel Kahneman and Amos Tversky’s (K&T) psychological research of behavioral economics and finance. In their work, K&T introduced Prospect Theory1, which posits that loss aversion (being risk averse in order to avoid the pain of financial loss) and regret aversion (investor indecision and inaction to avoid responsibility for a poor result) influence investor decisions.
K&T’s research also revealed that human decision-making processes are distorted by inherent biases toward optimism and overconfidence. These subjective perceptions, when present to a significant degree in the financial decision-making process, can result in miscalculating the value of an opportunity.
If humans were not inherently optimistic, we might not have evolved to this point. It takes optimism to take risks, plan for a future and defer gratification. That bias toward optimism often leads us to have an unrealistically positive view of ourselves and our futures. Studies show that most people view themselves as above average in many categories and that their futures are brighter than those of others.
Mergers and acquisitions (M&A) deals provide an example of optimism expressed through the evaluation of opportunities—specifically the character of synergies expected to increase the combined firm’s value as well as the time it will take to realise that added value. Often, the optimism proves unwarranted as the “acquiring company’s stock declines roughly two-thirds of the time.”
Optimism bias may also lead individual investors to overestimate their own investment results. They subconsciously choose results from their portfolios that match their optimistic self-perception as investors, and fail to measure the results of their entire portfolio. To counter this bias, investors need to adopt an outsider’s view when evaluating investment ideas because the insider’s view is usually overly optimistic. As Michael Mauboussin puts it in Think Twice: Harnessing the Power of Counterintuition, insider optimism is susceptible to “anecdotal evidence and fallacious perceptions.”2
An outsider, however, “asks if there are similar situations that can provide a statistical basis for making a decision. Rather than seeing a problem as unique, the outside view wants to know if others have faced comparable problems and, if so, what happened. The outside view is an unnatural way to think, precisely because it forces people to set aside all the cherished information they have gathered.”2
Overconfidence is an “unwarranted faith in one’s intuitive reasoning, judgments, and…abilities,” cognitive and otherwise 3. Most people can probably recount times when they may have exhibited overconfidence. Do you believe you are an above-average driver? If so, it might be helpful to know that 80% of drivers share the same belief.
Investors are not immune to this phenomenon and some believe it is the most detrimental bias for investment results; overconfident investors tend to chase returns and underestimate risk.
In fact, studies have demonstrated that confidence in our ability to predict probabilistic outcomes increases with information, despite the absence of a corresponding increase in prediction accuracy. For example, MBA students, many of whom worked in jobs where they performed financial forecasting, were asked to predict future corporate earnings in an advanced financial-statement analysis class. Actual company data was disguised as a part of the study and presented in three sets: baseline information (including the prior three quarters of earnings-per-share, net sales and stock prices); baseline information plus redundant news information (e.g. information that was already included in the baseline data); and baseline information plus non-redundant news information (e.g. the company increased the quarterly dividend).
The study revealed that the redundant information made subjects significantly more confident in their forecasts compared to the baseline case. In addition, non-redundant information made subjects considerably more confident than both the baseline case and the redundant case. Forecast accuracy, however, was substantially diminished under both the redundant and non-redundant conditions compared to baseline.”4
Put simply, prediction accuracy decreased as the amount of available information, redundant and non-redundant, increased.
Does Information Positively Correlate with Probability?
For any investment opportunity, there are usually only a few pieces of information that explain a significant amount of the opportunity’s value. Investors often search for an edge by meeting with management or researching arcane information. This can result in an overemphasis on their additional knowledge while more-important information becomes underemphasised, leading to overconfidence.
In addition, baseline probabilities—long-term results delivered by a company—can explain a lot, yet a significant amount of investor value estimates are often based on what could happen in subsequent years. What could happen is simply not known today.
The next paper in our series, entitled: “Behavioural Finance: Cognitive Dissonance, Confirmation and Recency,” examines subsequent behavioural investment bias discoveries.
More in the Behavioral Finance Series
- Behavioral Finance: Loss and Regret Aversion
- Behavioral Finance: The Three A's - Availability, Anchoring, and Adjustments
1 Kahneman, D. and Tversky, A. “Prospect Theory: An Analysis of Decision under Risk”Econometrica. 1979.
2 Mauboussin, Michael J., Think Twice: Harnessing the Power of Counterintuition Harvard Business School Press, 2009. pp. 4-6.
3 Pompian, Michael M. Behavioral finance and wealth management: how to build optimal portfolios that account for investor biases, John Wiley and Sons, 2006. p. 51.
4 Fred D. Davis, Gerald L. Lohse, Jeffrey E. Kottemann “Harmful effects of seemingly helpful information on forecasts of stock earnings.” Journal of Economic Psychology, Volume 15, Issue 2. June 1994. pp. 253-267.
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