Do not judge your decisions by the outcome alone
Ananya Roy
We grow up hearing about actions and consequences, cause and effect, sowing and reaping, despite which we tend to forget the link between cause and effect, and over-emphasize the effect when evaluating our decisions. As Dr Phillip Gribble succinctly put it, “Today is yesterday’s effect and tomorrow’s cause”.
Don’t mix up cause and effect
Just because driving in an inebriated state didn’t get you killed once doesn’t mean that it was a good decision to drive drunk. Similarly, just because you were not selected in a job interview doesn’t mean it was a bad decision to appear for the interview. When we judge a decision by the outcome alone, without paying heed to the rationality of the decision at the time it was made, we succumb to what is referred to as outcome bias.
Oftentimes, the outcome not only influences our evaluation of worthiness of a decision, but also distorts our memory of the time when the decision was made. One soon develops a false sense of appreciation or deprecation for oneself - “I should have known I won’t get killed if I drive drunk; I am a great driver” or “I should have known I won’t get the job; I am not good enough”. But these musings are usually far from the truth–no matter how good a driver you are, drinking increases your reaction time, making an accident more likely. So, your decision to drink and drive was wrong regardless of you actually meeting an accident or not; and appearing for the interview was the right call if you believed at the time of interviewing that your skill-set matched the job description.
Outcome bias in investing
These behavioural fallacies extend to investing as well. Consider the case of an investor who bought shares of a company on a friend’s “strong feeling”, following which the stock went up because of a buyback announcement. Insofar as the friend is not involved in insider trading, the favourable outcome had nothing to do with the original decision. In the world of investing, it can safely be called a fluke. Now, if this investor seeks out his friend for another recommendation based on how his first one panned out, he would be giving in to outcome bias. He would be wrongly attributing the fluke to his friend’s investment acumen. Once you attribute enough such fortunate outcomes to someone’s investment capabilities, it inevitably leads to misplaced confidence or overconfidence.
What is scarier is that it’s not just retail investors who fall prey to such behavioural fallacies. Even if you hire a professional to manage your money, outcome bias, hindsight bias, and overconfidence can still take the portfolio down. Investors’ bouquets and brickbats to the portfolio manager are very often driven by recent performance, and it is all too easy to get carried away by it and attribute the performance or lack thereof to the manager’s decisions and skills. Say, we have two portfolio managers, one of whom works in the large-cap space and the other in mid-caps. Post the mid-cap carnage in 2018, the former would be in high spirits and might be tempted to attribute the good times to his investment skills, while the reality may just be that he was in the right place at the right time. If he is not cognizant of this and the fact that times change, he won’t be prepared to face the inescapable risk-on rally when it arrives. As a matter of fact, professional fund managers, given the reputation that they must maintain and the much higher scale of adulation and criticism that they receive, are more prone to attributing extraneous events to their investment acuity.
A strategy that avoids behavioural fallacies
Well, Conventional Fund Managers, to be more accurate. Conventional managers usually work with strategies which are “fluid”–they change based on the manager’s views at the time, and this makes them black boxes and susceptible to behavioural biases. In contrast, Quantitative Fund Managers research an investment philosophy through rigorous back-testing over long periods and across various market scenarios. It is only after becoming certain of the robustness of their strategy that they lock it down, after which it is a numbers-only club. Once the strategy is up and running, the latest dataset (for example, P/E in case it’s a value-oriented strategy) feeds into the system and drives the strategy, keeping out any human intervention. During the research phase, results of the simulated back-tests yield confidence in the strategy and once it is live, the numbers do the bidding. Obvious by now should be the fact that at no point during this process does overconfidence bias get a chance to take hold of the decisions being made.
This scientific approach to investing provides a one-stop solution for all behavioural biases in investing. It has a multi-trillion dollars investment globally and is already on its way to mainstream investing in India. We will take this a step further next Monday.
(The author is an associate portfolio manager with Reliance Capital. Views are personal. She tweets at @anayaroycfa)
This is the sixth of a series of articles that are published every Monday on how to avoid irrational behaviour while investing. Click for reading part1, part2, part3, part4, and part5
