Behavioural Finance — the investor is not a calculator

What behavioural finance studies

Behavioural finance is the study of how psychology influences the behaviour of market participants, individually and in groups, and the effect this has on markets. It is part of behavioural economics, and it tries to explain the gaps and market anomalies that standard finance cannot.

The assumptions of standard finance

Standard finance models assume that investors:

• are rational.
• are risk averse.
• are self-interested utility maximisers.
• update beliefs as new information comes in.
• have access to all available information.

Real investors look very different. The workbook's everyday examples:

• They hold concentrated portfolios instead of diversifying.
• They swing between greed and fear instead of making rational risk-return choices.
• They credit their own skill for wins that were really randomness.
• They confuse a good company with a good stock.
• They prefer domestic companies — home bias — because familiarity makes the risk feel lower.

Standard finance vs behavioural finance

Nobel laureates Daniel Kahneman (2002) and Richard Thaler (2017) are credited with bringing behavioural finance to the forefront and trying to integrate it with standard finance.

How people actually decide

Bounded rationality — Herbert Simon (1978)

Most investors have limited time, limited information, or limited ability to process complex information. Faced with many options, they get confused and settle on one that seems good enough, found through quick thumb rules. Instead of optimising, they "satisfice" — a blend of satisfactory and sufficient.

Three steps:

1. Process only the information that is manageable.
2. Apply rules of thumb or quick approaches.
3. Choose a satisficing solution.

Crucially, bounded rationality is not irrational decision-making. It is rational decision-making under boundary conditions. It sits between rationality (processing everything for the optimal answer) and intuition (experience).

Nobel laureate Herbert Simon (1978) is credited with the concept.

Prospect theory — Kahneman and Tversky (1979)

Prospect theory describes how people choose between risky alternatives and how they evaluate potential gains and losses. It considers how prospects are perceived depending on their framing, how gains and losses are evaluated, and how uncertain outcomes are weighted.

Choices happen in two phases:

1. Framing (editing) phase — heuristics are used for a preliminary analysis of the prospects.
2. Evaluation phase — the edited prospects are evaluated and the one with the highest perceived value is chosen.

The three premises:

• Choices are evaluated relative to a reference point (the person's well-being).
• People are risk-averse about gains (they realise them early) but risk-seeking about losses (they hold on longer).
• Monetary losses hurt more than monetary gains.

Biases: two families

Biases are how people process information through their experiences and preferences. It is impossible to be unbiased, but discipline and checklists help mitigate them. Investing biases fall into two categories:

Emotional biases

Loss aversion

People take chances to avoid losses but won't take chances with certain gains. Losses are significantly more powerful than gains.

Shefrin and Statman (1985) named the disposition effect: holding losers too long and selling winners too early. In their words, "people dislike incurring losses much more than they enjoy making gains, and people are willing to gamble in the domain of losses", so "investors will hold onto stocks that have lost value and will be eager to sell stocks that have risen in value."

Stereotyping

Under uncertainty, investors look for representative characteristics and decide based on the general perception of them. Example: believing a high-profile manager means a better-managed company and therefore a good investment.

Overconfidence

Unwarranted faith in one's own intuition, judgement and abilities. Most people rate themselves better than average. It intensifies with self-attribution bias — people "confuse brains with a bull market". Overconfidence leads to underestimating losses, blurs skill and luck, and feeds on itself through a feedback loop.

Visible as: portfolio concentration, sector or country bias, excessive trading, and sticking with loss-making stocks in sectors the investor thinks they know well.

Endowment bias

People value an asset more when they own it than when they don't. The investor believes her stocks are more valuable and the market will eventually recognise it. Two attributes: valuing ownership and loss aversion. Classic sign: inherited stocks are rarely sold, even when they do not fit the strategy.

Status quo bias and regret aversion

Wanting to avoid regret, a person takes no decision at all and keeps the status quo. It is closely linked to regret aversion — avoiding action for fear it will turn out badly.

Regret has two dimensions:

• Error of commission — regret over actions taken.
• Error of omission — regret over actions not taken.

Regret from commission is more intense than from omission, so people prefer the status quo. Complexity can also cause it. Richard Thaler showed that a simple nudge got employees to enrol in pension plans that had poor enrolment purely because of status quo bias.

Cognitive errors

Mental accounting — Richard Thaler (1999, per the workbook)

People treat equal sums of money differently depending on which mental account they sit in — the money's origin and intended use — instead of seeing the bottom line. Money is fungible (interchangeable, with no labels), but mental accounts make it feel non-fungible.

Effects:

• More risk taken with windfalls or lottery winnings.
• Non-regular income (bonus, tax refund) spent extravagantly compared with salary.
• Separate buckets — retirement, children's education, marriage — lead to asset choices per bucket that a whole-portfolio view would have avoided.

Thaler's advice: treat all money the same, regardless of origin or use.

Framing

A person answers the same question differently depending on how it is asked. Two types in the workbook:

• Risky choice framing — "risk of losing 10 out of 100 lives" vs "opportunity to save 90 out of 100 lives".
• Attribute framing — a product that is "0% fat" vs "100% fat free".

The outcomes are identical, yet most people chose the second option in both. Investors must watch for framing when filling risk tolerance questionnaires (it can distort asset allocation) and when evaluating portfolio performance.

Anchoring

Relying heavily on pre-existing information — the anchor — so that everything after is seen in its light. Examples: the first price mentioned in a negotiation becomes the anchor; judging where a stock's price could go based on its past performance.

Fusion investing

Fusion investing combines fundamental analysis with behavioural finance. Fundamentals say price is the discounted value of future cash flows; yet short-term prices are volatile, driven by collective behaviour.

Benjamin Graham, father of value investing: "in the short run the market is a voting machine, and in the long run it is a weighing machine." Fusion investing integrates both machines — value-growth from fundamentals and momentum from behavioural finance.

Three steps:

1. Value screen — stocks showing promise on P/E, P/BV, P/S.
2. Fundamental strength filter — profitability, leverage and efficiency (e.g. Piotroski score), historical and forecast.
3. Momentum filter — stocks in a price uptrend.

What survives step 3 goes into the portfolio. Caveats: market data is insufficient to prove it conclusively; momentum is short-term, so it needs more frequent rebalancing than value-growth factors, which makes transaction costs and taxation critical.

The Piotroski score runs 0 to 9 across nine criteria of financial strength; 9 is best, 0 worst. It was devised by Joseph Piotroski, an accounting professor at Chicago.

Biases, anomalies, bubbles and crashes

Anomalies

A market anomaly is a departure of price from its expected value given fundamentals — a price change not explained by current or newly released information. Actual returns deviating from CAPM or other models are anomalies. They appear, disappear and reappear quite randomly; some vanish as people exploit them, others persist.

Biases create them. Overconfidence makes investors underestimate risk. Self-attribution makes them credit themselves for success and blame others for failure, seek confirming information and trade too often. The disposition effect explains momentum in prices.

Bubbles

Charles Kindleberger, in "Manias, Panics and Crashes" (1978), describes a bubble as a sharp, continuous rise in price where the early rise creates expectations of further rises, attracting speculators who want trading profits rather than long-term investment. In his view psychology is as important as finance and economics.

Why don't arbitrageurs stop bubbles? They suffer a synchronisation problem (coordinating their selling) and have different incentives to time the market — so bubbles persist longer.

Examples: Dutch Tulip mania of the 1630s, the South Sea Bubble and the Tech bubble of 2000. Kindleberger notes that Isaac Newton rode the South Sea Bubble in 1720: he got out at £7,000 after a profit of £3,500, re-entered, and ended up losing £20,000. His verdict: "I can calculate the motions of heavenly bodies, but not the madness of people."

Note: the workbook dates the South Sea Bubble as 1729–30 in one sentence and places Newton's South Sea trading in 1720 in the next (Chapter 14, p. 248). Both appear in the text; the workbook does not reconcile them.

Bubbles often emerge during structural changes in productivity — railways, electricity, technology. They start with a justifiable price rise; early investors make high returns; new investors pile in; cheap borrowing fuels it; prices reach unrealistic levels and analysts produce "new age" theories to justify them.

Four potential causes:

Keith Redhead (2008) — speculative bubbles are more likely where:

• the proportion of inexperienced traders is high.
• uncertainty about true value is high.
• there is a small chance of a very large profit.
• purchases can be financed by borrowing.
• short selling is difficult.

Crashes

The same process in reverse — everyone sells at the same time. Negative news, a change of opinion, a liquidity crunch or a return to fundamental pricing makes every investor try to exit before anyone else, and that jostling produces the crash.