Portfolio Theory and Behavioral Finance PDF

Portfolio Theory and Behavioral Finance w.MA.XX.IN.19HS.2024-HS Chapter 4a: Behavioral Biases Building Competence. Crossing Borders. Dr.-Ing. Martin Schnauss, CFA, FRM / Dr. Jan-Alexander Posth [email protected], [email protected], 202...

Portfolio Theory and Behavioral Finance w.MA.XX.IN.19HS.2024-HS Chapter 4a: Behavioral Biases Building Competence. Crossing Borders. Dr.-Ing. Martin Schnauss, CFA, FRM / Dr. Jan-Alexander Posth [email protected], [email protected], 2024 / Vers. 1.1.3 Topics Prospect Theory summary Prospect Theory and Framing Behavioral Biases – Cognitive Errors – Information Processing Biases – Emotional Biases -2- Behavioral Finance: Prospect Theory Prospect Theory… … in a nutshell -3- Where we come from… and where we need to be! Risk capital 4.5m: first hominids 300k: Homo sapiens 4.0k: first metallic money  ~here: “modern” concept of risk! 5.4k: first use of 3.5k: first alphabet number system 3.2k: sea-going trade 1.9k: use of abacus by Romans 180: plans for first analytical engine (Babbage, UK) Sources: http://www.southampton.ac.uk/~cpd/history.html 4 The PROBLEM General Idea: Important actors in the financial markets are humans. And humans act not always rationally. They are usually biased when they decide. Reasons: − Evolutionary selection pressure − Faster descisions − Value for survival and reproduction success Concept of Behavioral Bias: Fundamental conflict of poor (seemingly very efficient) cognitition and evaluation of investments. 5 The PROBLEM, cont’d 4.5m years of evolution have taught us to be very good at  dealing with complexity employing simplification and classification  efficiently running on auto-pilot in a known environment  reacting VERY fast (and hefty) to immediate danger  pattern recognition … unfortunately, we quite bad at  dealing with complexity on an abstract level, free from context  adapting to rapid change and/or new information  numbers and (especially) probabilities 6 Why do we need a paradigm shift? EMH deconstructed, part 1 Assumption #1: The market is not complete nor efficient &c.  Not all pricing-relevant information for a given security is always available to all market participants at the same time  Some information my only be known to insiders  Relevance of information (although publicly available) might not be recognised  News coverage might be low because of different public focus  This will be especially true for niche markets or small stocks with low analyst coverage  BUT: As the stock price increased (decreases) and/or news coverage increases a feedback cycle will be initiated, interlinking with the irrationality of the market participants -7- Why do we need a paradigm shift? EMH deconstructed, part 2 Assumption #2: The market participants are not acting rationally at all!  Market participant generally do not act rationally but are influenced by a profusion of behavioural biases, i.e. a paradigm shift from neoclassical finance to behavioural finance has occurred  Commonly known biases are: Recommended reading & source: Dhankar & Maheshwari (Behavioural Finance: A new Paradigm to explain Momentum Effect) -8- Why do we need a paradigm shift? EMH deconstructed, part 3 Excursus: Little rationality in markets… but lots of emotion!  “Men, it has been well said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, and one by one.” MacKay, 1841, Extraordinary Popular Delusions and Madness of Crowds Recommended reading & source: Gray & Vogel (Recommending the Trend: a Behavioral Basis for Momentum Strategies), www.cheatsheet.com -9- Remember: Utility as a Function of total Wealth Utility function is concave, resulting in risk aversion. 10 Now: Prospect Theory includes the consideration of losses Under loss aversion, the utility function considers changes from current wealth. It is convex to the left of the origin, indicating risk seeking behaviors when losses occur. “When in trouble, double!” 11 From Utility theory to Prospect theory – a necessary paradigm shift Kahneman and Tversky, Econometrica 1979 − Two elements, value function and weighting function − Elements replace utility function and probabilities in expected utility theory In Prospect Theory, the decision is based on considering different prospects. Thereby a function is used, which values prospects in relation to a reference point. − Step 1: framing the decision problem This will introduce the first biases… − Step 2: evaluating the prospects Read: “Thinking, Fast and Slow”, D. Kahneman, Penguin Books - 12 - Prospect Theory – why does it work? Conventional (normative) decision-analysis: Assumes outcomes of decisions (i.e. prospects) are described in terms of total wealth. BUT humans consider prospects in terms of gains, losses relative to some reference point or contextual reference frame (such current prices). Shape of the used value function is related to gains or losses: − concave for gains, and convex for losses − the valuation function has the largest steepness near the reference point. The value function is steeper in the losses domain than in the gains domain You learn a LOT form your failures! − reflecting that people are easier unhappy than happy − the positive effect of a gain is less than the negative effect of a loss in absolute terms. 13 Prospect Theory Value function (Kahnemann, Tversky Original) Concave Convex - 14 - Prospect Theory: Framing Prospect Theory Framing - 15 - Prospect Theory… leads naturally to Framing! Positive or negative Prospects are framed as gains or as losses! “frame-of-mind” Even different ways of descriptions of a prospect which highlight a loss in comparison to a gain lead to different decisions. − i.e. framing a prospect in certain way by changing the reference point leads to different decisions. − This reflects the properties of the value function (loss aversion, steepness in loss area). 16 Ready to be Framed? – An example… Imagine a Country is preparing for the outbreak of a killing disease, expected to kill 600 people. For which program would you vote?: What about the expected values? C: If program A − A: C isis adopted, 400 people adopted, 200 people will willbe die. saved. (Negative) (Positive) B: If program B − D: D is is adopted, adopted, there is one there is one third third probability probability that that 600 people nobody willwill die be saved and and two two thirds thirds probability probability that nowill that 600 people people will be saved. (Positive) die. (Negative) For which program would you vote?: If a loss seems certain, you’re − C: If program C is adopted, 400 people will die. (Negative) more willing to gamble! − D: If program D is adopted, there is one third probability that nobody will die and two thirds probability that 600 people will die. (Negative) 17 … and another one! Consider the following two Prospects: A: Having a 10% chance of winning $95 and a 90% chance of losing $5. B: Having to make a payment of $5 to participate in a lottery with a 10% chance of winning $100 and a 90% chance of winning nothing. What about the expected values? Which prospect would you choose? - 18 - Prospect Theory in a nutshell Under prospect theory, humans separate their prospects into positive and negative, relative to a status quo. Humans rarely considering absolute values and weight them according to their probability. Humans do not act in “symmetric fashion”: This leads several biases, for instance loss aversion, endowment effects or status quo bias. Humans use frames to make decisions. 19 Behavioral Finance: Behavioral Biases The landscape of Behavioral Biases source: CFA Learning material - 20 - Behavioral Biases: An overview Behavioural Biases Information Cognitive Errors Emotional Biases Other Biases Processing Conservatism Anchoring Loss aversion Gambler’s Fallacy Aversion to Mental accounting Overconfidence Herd behaviour ambiguity Confirmation Framing Self control Representativeness Overreaction Status Quo Illusion of control Endowment Hindsight Regret aversion Naïve Diversification Source: CFA Institute 21 Behavioral Biases Cognitive Errors: Conservatism Conservatism Bias: People tend to overweight the base rates and underweight the new information, resulting in revised beliefs about probabilities and outcomes that demonstrate an under-reaction to the new information. – Many people become anchored to their ideas and will not update their expectations when new information arrives (anchoring bias) – Only tentative and insufficient reaction to news – This under reaction to news leads to momentum in stock returns (initial under-reaction). - 22 - Behavioral Biases Cognitive Errors: Aversion to Ambiguity Aversion to Ambiguity Bias People prefer the familiar to the unfamiliar. An investment manager with deeper knowledge and experiences in bonds prefers the certainty of bond cash flows to the uncertainty of risk asset cash flows, even though investors might receive appropriately higher returns for assuming that risk. - 23 - Behavioral Biases Cognitive Errors: Confirmation Confirmation Bias People give more weight to evidence that (1) supports their beliefs and (2) ignore or modify evidence that conflicts with their beliefs. Also: Self-attribution bias “Human Ratio” behind it: – faulty reasoning - easily corrected – feelings - harder to correct - 24 - Behavioral Biases Cognitive Errors: Disjunction Effect Disjunction Effect Bias: Inability to make a decision that is contingent on future information Shafir & Tversky: People who took one of Samuelson’s lunch colleague bet were asked if they would take another. Most took the second bet whether or not they won the first. But most would not take second bet before outcome of first was known. Reaction of stock market to news - 25 - Behavioral Biases Cognitive Errors: Representativeness Representativeness Bias: People classify new information based on past experiences and classifications. Judgements based on stereotypes. – People tend to overestimate the representativeness of single observations and small samples – May result in overreaction and correction anomalies, e.g. reversal in prices - 26 - Behavioral Biases Cognitive Errors: Representativeness Heuristic (Representativeness …) People judge by similarity to familiar types, without regard to base rate probabilities. Tendency to see patterns in what is really random walk – Technical Analysis, e.g. random patterns are used for forecasting - 27 - Behavioral Biases Cognitive Errors: Illusion of Control Illusion of Control Bias: People tend to believe that they can control or influence outcomes when, in fact, they cannot. Believe in technical analysis and trading signals or patterns. - 28 - Behavioral Biases Cognitive Errors: Hindsight Hindsight Bias: People may see past events as having been predictable and reasonable to expect. - Very similar to illusion of control bias. Hindsight is always twenty-twenty. - 29 - Behavioral Biases Information Processing – Errors in information processing leads to: misestimate of probabilities of − Probable events. − The probability of events. − Future risks and returns. - 30 - Behavioral Biases Information Processing: Anchoring Anchoring Bias: When required to estimate a value with unknown magnitude, people generally begin by envisioning some initial default number—an “anchor”—which they then adjust up or down to reflect subsequent information and analysis. People place undue weight on the anchor. Note: The “anchor” still works even if it’s not related to the actual problem at all! "Would you sell a recent equity investment following a management announcement of a significant decline in the expected growth rate of revenue?" - 31 - Behavioral Biases Information Processing: Mental Accounting Mental accounting bias People treat one sum of money differently from another equal-sized sum based on which mental account the money is assigned to. Context again… Examples: – Treatment of real estates – Handling of wins on the stock market: “lets take more bets – is funny money anyway …” – Spending money you won in a lottery or you had to earn. - 32 - Behavioral Biases Information Processing: Mental Accounting Imagine the following situations: A. you have to offer to purchase a camera for $125 and a calculator for $15. The salesman mentions that the calculator is on sale for $10 at another branch of the store 20 minutes away by car. B. you have to offer to purchase a camera for $15 and a calculator for $125. The salesman mentions that the calculator is on sale for $120 at another branch of the store 20 minutes away by car. Who is willing to drive to the other store in A? What about the expected values? Who is willing to drive to the other store in B? - 33 - Behavioral Biases Information Processing: Framing Framing Bias People answer questions differently based on the way in which it is asked – or framed. Think about the question of rescued people from a deadly disease. Frame dependence: Investor behavior that depends on the way decisions are framed/presented. Peoples investment decisions are often framed to avoid losses rather than continuously reevaluate holdings. - 34 - Behavioral Biases Information Processing: Framing Three potential framing options: – Minimal – Topical – Comprehensive - 35 - Behavioral Biases Information Processing: Framing Framing for Minimal People consider only differences between local options. Example: Gaining $5, disregarding common features. Comprehensive Framing People consider something in relation to one other. Example: A customer might include both camera and calculator in relation to something else, for instance total monthly expenses - 36 - Behavioral Biases Information Processing: Framing Topical Framing People considers the context in which the decision arises. Example: The process of reducing the price of the calculator from $15 to $10. Context again… People usually frame decisions in terms of topical accounts. Example: The savings on the calculators are considered relative to their prices in each option - 37 - Behavioral Biases Information Processing: Overreaction Overreaction and availability Bias WYSIATI ! People base decisions on available information and resonation information, which they weight. Those information can have several sources: It can be caused by retrievability, categorization, a narrow range of experiences, and resonance. People take a heuristic (mental shortcut) approach to estimating the probability of an outcome. Sometimes they measure it based on how easily the outcome comes to their mind. - 38 - Behavioral Biases Information Processing: Forecasting Errors Forecasting Errors People tend to weight too much recent experience compared to prior beliefs – so called memory bias (also: exponential weighting in time series analysis). Analysts tend to excessively extrapolate historical trends when forecasting future earnings/cash flows - extrapolation bias. - 39 - Behavioral Biases Information Processing: Magical Thinking Magical Thinking Bias Skinner Example: B. F. Skinner 1948, fed hungry pigeons mechanically at 15-second intervals. Pigeons developed superstitions “Cargo cult” Peoples reactions to stock market events follow also patterns. These responses have similar origins. - 40 - Behavioral Biases Information Processing: Quasi-Magical Thinking Quasi-Magical Thinking Bias People bet more on coin not yet tossed. People pay more for lottery ticket in which they choose the number … a bit like Illusion of Control Bias - 41 - Behavioral Biases Information Processing: Sunk-Cost Sunk Costs Bias: Example 1: Playing with a tennis elbow in a tennis club, in spite of pain. This maintains the evaluation of the membership fee as a cost rather than a sunk loss. Example 2: Continuing a project that has already cost a lot without any results, rather than starting a new one, although the previous costs are sunk costs. - 42 - Behavioral Biases Information Processing: Sunk-Cost Sunk Costs Bias: Example 3: People tend to eat bad-tasting food just because they have already paid for. Framing negative outcomes as costs rather than as a loss improves subjective feelings - 43 - Behavioral Biases Emotional Bias: Loss Aversion Loss Aversion Bias People prefer avoiding losses as opposed to achieving gains. Example: Too late execution of stop loss order. Feeling of pain, when loosing – “if you are in trouble double” - 44 - Behavioral Biases Emotional Bias: Overconfidence Overconfidence Bias: People demonstrate unwarranted faith in their own intuitive reasoning, judgments, and/or cognitive abilities. This high level of confidence - overconfidence may result in overestimating knowledge levels, abilities, and access to information or e.g. underestimating forecast errors. – Some people exhibit overconfidence in their ability to pick stocks or – have an exaggerated belief that they will not be hurt by risk. As a result, they are willing to pay a too high price for a certain stock, in which they belief. - 45 - Behavioral Biases Emotional Bias: Overconfidence Example: on possible outcome: “Did you think at any point on February, 2009 that you had a pretty good idea when the market would rebound?” Institutional: 29% yes, Individual 28% yes Among buyers: 47%, 48% “If yes, what made you think you knew when a rebound would occur? Answers: “intuition,” “gut feeling,” “common sense” - 46 - Behavioral Biases Emotional Bias: Self Control Self-Control/Discipline Bias: People fail to act in pursuit of their long-term, overarching goals because of a lack of self-discipline. People tend to have an inherent conflict between short-term satisfaction and achievement of some long-term goals: – Choice between Short-term goals often “win” Going to a party or because they promise instant gratification! hard studying. – In economics, time preference (or time discounting, delay discounting, temporal discounting) is the current relative valuation placed on receiving a good at an earlier date compared with receiving it at a later date. => explains interest rates! - 47 - Behavioral Biases Emotional Bias: Status Quo Status Quo Bias: People do nothing instead of making a change - Do-nothing strategy. Example: Given no apparent problem requiring a decision, the status quo is maintained. This could result from a lack of knowledge or simply laziness. - 48 - Behavioral Biases Emotional Bias: Status Quo Status Quo Bias: People tend to make an initial asset allocation and then do nothing. Even when the portfolio risk and return characteristics are changing people tend to stick to their previous decisions. Thereby they might miss potentially return-enhancing opportunities. How frequently are investment portfolios reviewed? Perceiving the cognitive cost too high, participants might not evaluate their changing personal circumstances or the even different funds in the plan. - 49 - Behavioral Biases Emotional Bias: Endowment Endowment Bias – People value an asset more when they already have in their portfolio. – Thereby people tend to loose their objectivity. My choice, my baby! – It is more painful to give up an asset than it is pleasurable to buy it. - 50 - Behavioral Biases Emotional Bias: Fairness Fairness Bias: (Kahneman, Knetch and Thaler, 1986) Evaluate the two situations for fairness: – A shortage had developed for a car model and the dealer now prices it $200 above list price (not very acceptable for people) – A shortage had developed for a car model and the dealer, who had been giving $200 discounts, now sells the model for list price (much higher level of acceptance) - 51 - Behavioral Biases Emotional Bias: Fairness Perception of fairness depends on whether the question is framed as a reduction in gain or as an actual loss. Imposing additional costs is considered less fair than eliminating a discount. This is a reason why cash prices are presented as a discount, rather than credit prices as surcharge - 52 - Behavioral Biases Emotional Bias: Regret Aversion Regret Aversion Bias: People sometimes avoid making decisions because they fear that the decision will turn out poorly. Remember “Status Quo Bias” Simply put, people try to avoid the pain of regret associated with (probably) bad decisions. Investment decisions that resulted in a loss might stop the involved investors from making similar decisions, even if the new investment appears to be the best alternative. - 53 - Behavioral Biases Emotional Bias: Naive Diversification 1/n Naive Diversification Bias: – relates to framing and regret aversion. – People tend to divide their assets equally among all available alternatives. – Knowing generally that they should diversify their portfolios but unsure of exactly how to go about doing that, people tend to invest equal amounts in different investment opportunities disregarding the relevant return-risk profiles. Most important: risk! - 54 - Behavioral Biases Emotional Bias: Culture and Social Contagion Culture and Social Contagion Bias Social cognition, collective memory Durkheim, 1897, suicide rates differ across countries for no more reason than different cultural themes Durkheim concluded that: – Suicide rates are higher in men than women (although married women who remained childless for a number of years ended up with a high suicide rate). – Suicide rates are higher for those who are single than those who are in a sexual relationship. – Suicide rates are higher for people without children than people with children. – Suicide rates are higher among Protestants than Catholics and Jews. – Suicide rates are higher among soldiers than civilians. – Suicide rates are higher in times of peace than in times of war (For example, the suicide rate in France fell after the coup d'etat of Louis- Napoléon Bonaparte. War also reduced the suicide rate: after war broke out in 1866 between Austria and Italy, the suicide rate fell by 14% in both countries.). – Suicide rates are higher in Scandinavian countries. – The higher the education level, the more likely it was that an individual would choose suicide. However, Durkheim established that there is more correlation between an individual's religion and suicide rate than an individual's education level. Jewish people were generally highly educated but had a low suicide rate. - 55 - Behavioral Biases Emotional Bias: Certainty Effects, Probabilistic Insurance Example: Imagine the following insurance options: 1. Pay a premium for full coverage 2. Pay half the premium for full coverage during half the time, to be decided at random (e.g., only on odd dates of the month) How would you decide? - 56 - Behavioral Biases Emotional Bias: Certainty Effects - Probabilistic Insurance Probabilistic Insurance Bias: People tend to reject option (2), contrary to normative theory (because of the lower costs and the concave utility function people should prefer the option.) BUT: – The reason is that reducing the risk probability from p to p/2 has a smaller decision weight than reducing the risk from p/2 to 0 (the certainty effect) – Framing an insurance as giving full protection against specific risks makes it more attractive (e.g. only fire vs. flood and fire) - 57 - Behavioral Biases Other Biases: Gamblers Fallacy Gambler's Fallacy Bias: An individual erroneously believes that the onset of a certain random event is less likely to happen (again) following an event or a series of events. Think of roulette, where 5 times Red occurred an people start betting on Black. That could be incorrect because past events do not necessarily change the probability that certain events will occur in the future. Hasty generalization, “Law of small numbers” - 58 - Behavioral Biases Other Biases: Herd Behavior Herd Behaviour Bias Herd behaviour describes how people act together in a herd / group like animals. Especially in times of crises and extreme fear this strategy has proven to be a viable strategy for surviving. People have to be aware of this tendency of their behaviour. Remember: “Men, it has been well said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, and one by one.” - 59 - Summary Let’s sum it all up on one slide…  Risk has always been part of human life – consequently, behavioural patterns to deal with it have become encoded in our very genes over millions of years  Financial risk has been an integral part of human life for only a few millennia, making it hard to deal with  There is a fundamental disconnect between our “natural” risk management approach and the risk management concept necessary for finance  This results in Behavioural Biases that, in turn, corrupt our financial decision making every day  Most of the time, we do not act rationally at all but just being aware of the behavioural biases already helps  We may overcome these biases rationally but this costs a lot of effort and usually is slow compared to our instinctive reaction – which we naturally prefer 60