• Rather than using conventional feedback loops, companies today are employing a new, stronger habit-forming mechanism to hook users—the Hooked Model.
• At the heart of the Hooked Model is a variable schedule of rewards: a powerful hack that focuses attention, provides pleasure, and infatuates the mind.
• Our search for variable rewards is about an endless desire for three types of rewards: those of the tribe, the hunt and the self.

Source: https://www.nirandfar.com/want-to-hook-your-users-drive-them-crazy/

It is a fascinating tool to augment commitment devices in a decision-making framework.

Illusion of control is where an individual feels that they can control an outcome in their environment[1], which leads to overconfidence (Phase 1 in the Dunning Krueger Effect[2]).  For investors, this leads to high degrees of portfolio concentration, increased trading frequency and more leverage.

The illusion of control is prevalent amongst traders, especially novice traders who believe that whatever simplistic process works ad infinitum.  If they survive and develop some tenor in the profession, they tend to use multiple heuristics or develop a more systematic approach, which can be fully autonomous.

As traders develop along the Dunning Krueger Curve, those who survive recognise that there is no control over the situation except their personal reaction function. 

Restrictions on bet size/individual weightings, stop loss exits or concentration limits or other such risk management strategies can limit the worst of it, as they hard code risk management into the process but the frequency of trading is only ameliorated through time and pain.  A greater appreciation of randomness comes with age.

Not being religious, it’s ironic that one of my favourite quotes comes from the Bible:

“I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, neither yet bread to the wise, nor yet riches to men of understanding, nor yet favour to men of skill; but time and chance happened to them all.”[3]

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[1] Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311-328.

[2] Please refer to Dunning Krueger Effect.

[3] Ecclesiastes 9.11, Holy Bible. King James Version.

This is a situation where an individual feels mental discomfort due to contradictory beliefs, attitudes or behaviours which results in a change of beliefs or attitudes to harmonise this friction[1].  Individuals are motivated to calm this dissonance by changing their behaviour, attitudes or actions.  This involves a strong form of confirmation bias[2], which allows the individual to filter any non-conforming information or evidence, when increased dissonance is experienced.

This is commonly seen in cults. Friction between cult beliefs and reality causes cognitive dissonance amongst members of the cult.  Members filter non-conforming information to the extent that they stop associating with anyone carrying a contradictory belief.  They cut off family and friends from the social circle and fill it with individuals who share the same beliefs.  This creates an echo chamber within an epistemic network, which reinforces their belief, calming their cognitive dissonance.  A milder variation of this can be seen through society with such conspiracy as Covid-19 or 5G[3].

Humans desire for consistency and habit are directly rooted in our demand for less cognitive load, a ‘laziness’ which pushes us to use heuristics, which can push us to change habits, behaviours and actions, to decrease the load that cognitive dissonance places on our amygdala.

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[1] Festinger, L. 1919-1989. (1962) A theory of cognitive dissonance / Leon Festinger. Stanford University Press. Available at: https://research.ebsco.com/linkprocessor/plink?id=9a1ee125-ca54-3298-a920-ea3cb9caf99e (Accessed: 7 May 2024).

[2] Confirmation bias refers to a tendency to search for, interpret, favour, and recall information that supports existing beliefs, while ignoring any contradictory evidence or information.

[3] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8576388/

Mental Accounting postulates that individuals focus on independent economic buckets instead of the overall economic outcome[1].   This is built upon the foundations of the framing effect in prospect theory, where an opinion is formed based on how the information is provided, a positive opinion correlates to positive information and vice versa.

This can be seen where individuals are more likely to spend their bonus as it is framed as a reward for hard work as opposed to their normal wage, which is framed as money for expenses.

Traders often take more risk when they are winning as opposed to when they are losing, the house money effect[2].  This is an inherent view that when they have more, they can bet more, however circumstances often change after a winning run and if bet sizes are larger than normal then losses would be larger than normal, a better strategy would be to bet consistently, providing that one has an edge.

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[1] Thaler, R.H. (1999) ‘Mental Accounting Matters’, Journal of Behavioral Decision Making, 12(3), pp. 183–206. doi:10.1002/(SICI)1099-0771(199909)12:3<183::AID-BDM318>3.0.CO;2-F.

[2] Where individuals take greater risks with money they perceive as “gains” or “house money” than they would with their original investment, savings, or baseline wealth.

The foundation of the familiarity heuristic is an offshoot of the availability heuristic[1], whereby individuals employ a judgemental heuristic where individuals estimate probability distributions using the most readily available information, leading to systematic biases.  This grows into the familiarity bias, where familiarity is favoured as it is perceived to carry less risk, over the unusual.  It takes less cognitive energy to filter non-conforming information, which can trigger cognitive dissonance[2] than to process it. 

A feature of this heuristic in finance is the home market bias, where investors prefer the comfort of investing in their own local market as opposed to foreign ones, so the ASX[3] for Australians.  Having a home market bias does introduce some issues into investor portfolios, especially in Australia, where there is a high percentage sector weight to Finance and Materials in our index and minimal weight to Technology and Health, which lessens the power of diversification within the portfolio[4].

Over the years, the barriers to investing offshore have decreased as online services[5]have proliferated and its now cheap and easy for investors to add offshore diversification to their portfolios.  One way of encouraging clients to step out of their f familiarity zone is to add holdings slowly and with minimal weights to start if they are attempting direct investments.  From an asset allocation perspective, the same can apply, begin with a smaller weight to get clients comfortable with the new experience, before increasing the weights as they get more comfortable with the experience.

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[1] Tversky, Amos; Kahneman, Daniel (1973). “Availability: A heuristic for judging frequency and probability”. Cognitive Psychology. 5 (2): 207–232. doi:10.1016/0010-0285(73)90033-9. ISSN 0010-0285.

[2] Refer to Cognitve Dissonance.

[3] Australian Stock Exchange.

[4] https://www.vanguard.com.au/personal/learn/smart-investing/investing-strategy/home-equities-bias

[5] eToro, IG, Superhero, CMC Markets, Stake etc

Recency bias is the tendency for individuals to recall and emphasise the most recent events as opposed to those in the past.  Furthermore, if the event has not been experienced, individuals will tend to ignore the event.  This was promulgated on the serial position effect[1], which is the tendency to recall the first and last event in a series and forget the middle.  It’s a natural heuristic process as it requires less energy and time to remember two nodes and infer the path. 

Investors naturally extrapolate current events into the future, in a linear regression fashion, conveniently forgetting that market events move in a sinusoidal manner.  This results in investors being overweight growth at the end of bull markets and panic selling at the end of bear markets.

To counter this bias, we need to educate the investor that history moves in waves, and the most damage done to an investor portfolio is self-inflicted.  Tackling recency bias is important, in the advice sequence as once investors are overweight growth during a downturn, loss aversion[1] and panic set in, and managing client expectations in that scenario becomes extremely difficult.

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[1] Refer Prospect Theory.

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[1] Ebbinghaus, Hermann (1913). On memory: A contribution to experimental psychology. New York: Teachers College.

This is the effect that individuals overestimate their ability and skills in many domains[1].  They suffer from a lack of competence, cognitive skills and a lack of self-assessment capability.  This is seen in students’ estimation of their ability and test scores as seen in the figure below[2].  Those in the bottom quartile of skill and ability perceive their ability to be much higher than their actual test scores as opposed to the top quartile where the actual test score is higher than their perceived ability or knowledge. 

The graph below[3] shows a good depiction of the cognitive bias that most individuals suffer on their road to knowledge and mastery.

On the journey toward being a professional trader, the older ones realise how little they know and how much more work lies ahead. Most novice traders are too confident of their abilities, bet too big and generally don’t survive their initial year.

“The more you know, the more you realize you don’t know.”[4]

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[1] Kruger, Justin; Dunning, David (1999). “Unskilled and Unaware of It: How Difficulties in Recognizing One’s Own Incompetence Lead to Inflated Self-Assessments”. Journal of Personality and Social Psychology. 77 (6): 1121–1134. CiteSeerX 10.1.1.64.2655. doi:10.1037/0022-3514.77.6.1121. PMID 10626367. S2CID 2109278.

[2] Ibid pp 1124

[3] https://ardalis.com/the-more-you-know-the-more-you-realize-you-dont-know/

[4] Aristotle

The disposition effect is when investors sell winners too early and hang onto loser for too long[2]. This is a manifestation of the Allais paradox[1], which showed an inconsistency between the theory of expected utility and the sub-optimal and often irrational choices that individuals make. Its foundations are built upon several theories.  One such is prospect theory, where investors fear losses more than they cherish gains, hence individuals would delay the realisation of losses.  Another is seeking pride and avoiding regret, where a realisation of the loss would be proof that their judgement was flawed and not taking the loss would avoid regret. 

This can be seen in the behaviour of investors, where they are twice as likely to sell a winning stock than a losing stock[3].  The average investor would have a greater ratio of average unrealised losses than the average ratio of realised gains. 

Using traders as an example, the first cohort of traders who don’t survive are those who cannot realise their losses quickly and/or hang onto their gains.  They lack discipline and are plagued with the disposition effect.

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[1] Allais, Maurice (1979). Allais, Maurice; Hagen, Ole (eds.). Expected Utility Hypotheses and the Allais Paradox. D. Reidel Publishing Company. doi:10.1007/978-94-015-7629-1. ISBN 978-90-481-8354-8.

[2] Shefrin, H. and Statman, M. (1985) ‘The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence’, Journal of Finance (Wiley-Blackwell), 40(3), pp. 777–790. doi:10.1111/j.1540-6261.1985.tb05002.x.

[3] Barber, B.M. et al. (2007) ‘Is the Aggregate Investor Reluctant to Realise Losses? Evidence from Taiwan’, European Financial Management, 13(3), pp. 423–447. doi:10.1111/j.1468-036X.2007.00367.x

Prospect theory[1], developed by Kahneman and Tversky, observed the asymmetric value felt by individuals in losses over gains as seen in figure below. This contradicts the premise that individuals are utility-maximising agents, which if true, the value function would be a linear 45° line.

This is best seen in the distribution function of stock market returns as seen below in the figure below, which has kurtosis and a fatter left tail.  If humans were profit-maximizing agents, the distribution would be more normal, however as individuals feel loss twice as powerfully as they feel gains, the losses are magnified by panic selling when the markets are falling.

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[1] Kahneman, D. and Tversky, A. (1979) ‘Prospect Theory: An Analysis of Decision under Risk’, Econom etrica, 47(2), pp. 263–291. doi:10.2307/1914185.

Traditional finance or classic economics, portrays a person as a rational, self-interested individual who can maximise their utility, with full agency and information, able to discern the best course of action amongst their choices.  In essence, a perfectly rational human being.

This has evolved to the current bastion neoclassical thought exemplified by the Chicago School[1], which is heavily influenced by rational expectations theory[2]. A classic example is Fama’s Efficient market Hypothesis[3], which postulates in securities markets prices are perfectly efficient and reflect all available information. This is predicated upon the assumption that individuals are always maximising their expected utility when making decisions.

Traditional finance took a one-dimensional approach, considering man as an island, when constructing their theories for the sake of convenience.

“Behavioral Economics is the combination of psychology and economics that investigates what happens in markets in which some of the agents display human limitations and complications.”[4]

As the economic profession developed, new theories were developed to supplement the one-dimensional assumption that individuals are pure utility maximizing agents.  Many studies have shown that individuals are more likely to consider sub-optimal economic outcomes stemming from behavioural biases or risk mitigation purposes.  Thus, the field of behavioural finance was developed to understand the human decision-making process in practice as opposed to a simplified theoretical version expounded by classical economics.

Behavioural finance is a multi-dimensional approach to analysing the true reaction function of agents on a macro and micro economic level in a better approximation of reality.

The best example between traditional finance and behavioural finance is the Ultimatum game. This is where one player is given a sum of money and proposes a split with the second player, the second player can accept the split or reject the split, if the second player rejects the split, then none of the players get anything, if the second players accept, both part ways with the split determined by the first player.  Offers less than 30% to the second player are rejected 50% of the time[5]. 

A utility maximising individual should have chosen any outcome as their base case was nothing and any split is something.  Results show that other issues come to fore, such as personal equity, when humans make decisions.  While traditional finance does provide a simple guide to understanding human behaviour, it is too simplistic a model.  Behavioural finance is a burgeoning field which seeks to better understand our decision matrix.

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[1] University of Chicago

[2] John F. Muth (1961) “Rational Expectations and the Theory of Price Movements” reprinted in the new classical macroeconomics. Volume 1. (1992): 3–23 (International Library of Critical Writings in Economics, vol. 19. Aldershot, UK: Elgar.)

[3] Fama, Eugene F. “Efficient Capital Markets: A Review of Theory and Empirical Work.” The Journal of Finance 25, no. 2 (1970): 383–417. https://doi.org/10.2307/2325486.

[4] Mullainathan, Sendhil and Thaler, Richard H., Behavioral Economics (September 2000). Available at SSRN: https://ssrn.com/abstract=245828 or http://dx.doi.org/10.2139/ssrn.245828

[5] Güth, Werner; Schmittberger, Rolf; Schwarze, Bernd (1982). “An experimental analysis of ultimatum bargaining” (PDF). Journal of Economic Behavior & Organization. 3 (4): 367–388. doi:10.1016/0167-2681(82)90011-7