Why do most investors not let go of their losing investments for long and exit from their winning ones far too quickly? Why do people find it difficult to give up something they own even for an objectively greater value? Why do humans act so irrationally so often?
Research conducted by a community of exemplary behavioural economists over the last 50 years has an answer. They reveal that a set of hardwired systematic errors, commonly known as biases, might be at play. Nobel laureate Daniel Kahneman and Amos Tversky codified one set of explanations in their seminal work, Thinking Fast and Slow, by building the Prospect Theory.
Why the obvious irrationality?
The application of Kahneman and Tversky’s work, like that of other stalwarts of behavioural finance – including Richard Thaler, another Nobel laureate – goes much beyond the realm of investing. The prospect theory of Kahneman says the view of traditional utility theory doesn’t stand in the real world.
Utility theory’s proposition that rational individuals make choices to maximise their satisfaction doesn’t hold in the face of uncertainty. Humans process uncertainty in a way that makes them “risk-seeking for losses” and “risk-averse for gains”, which is an epiphany for many. Humans show the nature of “loss aversion” and not “risk aversion”. This might also explain why individuals anticipate a break-even on a loss-making investment before making an exit. However, individuals are quick to book profits on investments before they lose out on that as well.
Similarly, Richard Thaler’s work on discovering critical behavioural errors – bounded rationality, lack of self-control, and mental accounting, among others – has found great application in the real world. For instance, the Save More Tomorrow (SMarT) retirement savings programme in the US is meant to nudge people to save more by utilising their “lack of self-control” to build a savings habit. This was achieved by keeping the option to “save a portion of salary increment in the future” checked by default.
Two areas where India successfully leveraged nudging to bring about massive social changes are Swachh Bharat Mission (SBM) and Beti Bachao, Beti Padhao (BBBP). In SBM, the government leveraged the power of social conformity by recruiting more than 5 lakh “swachhgrahis” who were tasked with reinforcing the message of SBM using the power of their social ties. People were more receptive to someone they knew advocating change than some unknown person. Similarly, in BBBP, leveraging the power of social norm was the key. Campaigns like “Selfie with Daughter” encouraged people to change their view of the girl child being a burden, by showing how thousands of their countrymen were also taking such photos. This quickly became a social norm, and conformity ensued.
The world of psychology is fascinating for its revelation of our minds’ often-irrational workings. Investors and the public are possibly becoming more cognizant of these vagaries of the mind, as shown by the ever-increasing acceptance of behavioural economics and behavioural finance fields.Are you aware of your mind tricks?
A slew of mental errors – biases – exist that disproportionately impact investors’ choices. A few prominent biases are representative bias, confirmation bias, cognitive dissonance, endowment effect, anchoring and framing bias and regret aversion bias. If one recognises and takes charge of these irrational behaviours, it can significantly improve the investing experience of the individual.
For instance, confirmation bias is at play every time any positive news surfaces of a company in which an investor holds a long position. Notwithstanding any negative news, the investor is likely to disproportionately weigh the positive news and stay invested. Similarly, cognitive dissonance is at play whenever some negative news of the invested company surfaces, and the investor is likely to either rationalise the news to view it as insignificant or rather blame circumstances for making irrational investments.
How to use awareness?
So, what impact can all this awareness of biases have on stakeholders in the financial ecosystem? We’ll consider two important stakeholders – the financial advisor and the customer.
For advisors, whether humans or algorithms, the knowledge will help them better understand a situation and serve their clients accordingly. For instance, the most prominent psychographic models in behavioural finance are the Barnewall Two-Way Model (1987) and the BBK Five-Way Model (1986). Both models categorise investors based on specific defining characteristics. The use case of this categorisation is that the advisor can fine-tune advice to the client’s needs on the basis of their personality type and biases, as each personality type comes with a set of most susceptible biases. This can result in a more mutually beneficial relationship.
For instance, Barnewall’s model categorises investors as being either passive or active. A passive investor might be either highly or moderately passive – termed conservative passive and moderate passive, respectively, by Barnewall. Now, a conservative passive investor is likely to harbour emotional biases like regret aversion – being indecisive for fear of making a poor decision – and loss aversion and cognitive biases like mental accounting – valuing the same amount of money differently, often based on certain subjective categories of mental accounts, and anchoring and adjustment bias.
Biases in robo-advisory
With the ever-increasing pace of technological developments and an increasingly enabling environment for startups in India, many fintech players are catering to clients’ wealth management advisory needs via their robo-advisor-based services. Fundamentally, robo-advisors are algorithm-based solutions that input information on a user’s financial position, goals, risk appetite and market expectations, among others, to customise an investment plan at minimal cost.
One concern might be that because the business model of startups rests on certain trained algorithms, the very nature of the advice relayed by them to the user on the basis of the background and certain inputs may be biased. The data the algorithms were trained on might be biased for multiple reasons, like data source and data type.
This renders the concern of the nature of the advice being objective and optimum. However, it is to be seen how such companies further fine-tune the models to provide objective advice to clients.
Solution to biases
If you’re an individual concerned about the biases you inherently harbour, the advice for you is to become more self-aware of your mental patterns by maintaining a journal for self-introspection and by practicing mindfulness.
If you have to gain success in the markets, becoming a rational contrarian working against the ubiquitous desire for social coherence (loosely, herd mentality) is a necessity. This will only happen if you keep a check on your mind tricks and continuously strive to understand your own biases and irrationalities.
Eliminating the biases might not be realistically possible, but as Warren Buffet says, “Be a learning machine”. Never halt the endeavour of conquering self and thereby conquering the world.
(Neelam Rani is Associate Professor at IIM Shillong. Abhishek Singhal, Student in Post Graduate Program at IIM Shillong also contributed to the article.)
