160708 - Applied Behavioral Economics

APPLIED BEHAVIORAL ECONOMICS

Michal Stupavský, CFAPrague, 8 July 2016

2Applied Behavioral Economics8 July 2016

2) Valuation methods that do not involve forecasting

Foundations of behavioral economics

AGENDA

Behavioral biases

Behavioral corporate finance

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2) Valuation methods that do not involve forecastingFOUNDATIONS OF BEHAVIORAL ECONOMICS


2) Valuation methods that do not involve forecastingTraditional economics vs. Behavioral economics

Traditional economics Behavioral economics

• Normative approach describing how real world should function

• Not able to explain real world interactions• Homo oeconomicus, rationality• Continuous dynamic optimization, equilibrium• Efficient market hypothesis, Modern portfolio

theory, mean-variance analysis (expected returns, volatility of returns), CAPM

• Positive approach describing how real world is functioning

• Based on academic research in cognitive psychology

• (Rational) irrationality• Emotions, optimism, pessimism, greed and fear

dominates all decision-making (under risk)• Prospect theory (Kahneman, Tversky – 1979),

cornerstone of behavioral economics, behavioral biases leading to suboptimal decision-making



Why do economics agents behave in a way which we can daily see?

Why do investors achieve unsatisfactory returns?

Why do they hold undiversified portfolios?

Why do they trade too often?

Why do they seek only information confirming their previous views and decisions?

Why do investors tend to sell investments with paper profits too soon and hold losing positions too long?

Why do sunk costs matter a lot?

Why are corporate managers keen to continue losing (pet) projects?

Why do they overpay in acquisitions?

Why do economic agents do not learn from their past mistakes?

Behavioral economics answers questions such as…


2) Valuation methods that do not involve forecastingBehavioral finance – Micro & Macro

Micro-behavioral finance Macro-behavioral finance

• Analyzes behavioral biases which distinguish individual investors from totally rational economic beings – homo oeconomicus – from neoclassical economics

• Questions totally rational decision-making

• States that behavioral biases have a profound impact on decision-making and can drive suboptimal decision-making and errors that directly contradict with traditional finance

• Analyzes market anomalies that distinguish financial markets from efficient markets assumed by traditional finance

• At the same time questions this informational efficiency of markets

• States that financial markets are impacted by behavioral influences (market anomalies, bubbles, excess volatility, limited arbitrage)



• Fast and successful development of behavioral finance (economics) from 1970s

• Daniel Kahneman and Amos Tverky (academic psychologists) – The most famous paper Prospect Theory: An Analysis of Decision under Risk – Econometrica, 1979

• Prospect theory is cornerstone of behavioral finance, behavioral economics overall – Descriptive alternative to mainstream expected utility theory

• Framing – Form versus substance, risk-seeking versus risk-aversion depending on losses or gains

• In 2002, Kahneman received the Nobel Memorial Prize in Economics, despite being a research psychologist, for his work in prospect theory, decision making and judgment under risk, i.e. in real world conditions. (Amos Tversky died in 1996)

Prospect theory – Cornerstone of behavioral economics (Kahneman, Tversky –1979)

Daniel Kahneman (1934) Amos Tversky (1937-1996)


2) Valuation methods that do not involve forecastingValue function – Cornerstone of prospect theory (Kahneman, Tversky –1979)

•Reference point (price), relative values (changes) are important, not absolute values

•Concave in gains, convex in lossesÞ Risk-seeking in losses, risk-aversion in

gainsÞ 2 –2.5 times steeper in losses, people feel

losses much more than gains•Framing – format versus substance – frame

can change your decision making completely!•Mental accounting and disposition effect


2) Valuation methods that do not involve forecastingProspect theory versus mainstream expected utility theory

• Absolute values matter, not relative changes (in wealth)

• Utility = p1u(x1) + p2u(x2) + … + pnu(xn)

• General risk-aversion due to concavity• Gains and losses are felt in the same way

(magnitude)

• Relative values (changes) matter, not absolute values

• Value = w1v(x1) + w2v(x2) + … + wnv(xn)

• Concave in gains, convex in losses• => Risk-seeking in losses, risk-aversion in gains• Losses are felt 2 –2.5 times more than gains of the

same magnitude


2) Valuation methods that do not involve forecastingProspect theory – Weighting function

•Weighting function Real perception of probability is biased, in contract to mainstream expected utility ⇒theory

•Overweighting of low (and high) probabilities•Underweighting of medium probabilities

•Value = w1v(x1) + w2v(x2) + … + wnv(xn)

• ⇒ Consistent diversion from expected utility theory predictions within decision-making under risk (in real life)



Game No. 1: A friend will offer you the following game. Pick one of the two options that you regard as more attractive:

Option A – € 2,000 with a probability of 33%, € 1,920 with a probability of 66% and € 0 with a probability of 1%.

Option B – Sure € 1,920.

Mini-case study ⇒ Prospect theory vs. Expected utility theory, certainty effect (1)

€ 1,927.20

€ 660

€ 652.80


Option C – € 2,000 with a probability of 33% and € 0 with a probability of 67%.

Option D – € 1,920 with a probability of 34% and € 0 with a probability of 66%.




Option A – € 3,200 with a probability of 80%.



€ 2,560

€ 640

€ 600


Option C – € 3,200 with a probability of 20%.

Option D – € 2,400 with a probability of 25%.




Option A – 50% change to win a 3-week vacation in Great Britain, France and Italy.

Option B – A sure 1-week vacation in Great Britain, France and Italy.



Option C – 5% change to win a 3-week vacation in Great Britain, France and Italy.

Option D – 10% change to win a 1-week vacation in Great Britain, France and Italy.



Game No. 7: Think about the following two-stage game. In the first stage there is a 75% probability that the game will end without any reward, and 25% probability, that will get into the second stage. If you get into the second stage, you have to pick one of the two options that you regard as more attractive:



Mini-case study ⇒ Prospect theory vs. Expected utility theory, isolation effect

€ 640

€ 600




Option A – € 800 with a probability of 50%.

Option B – Sure € 400.

Mini-case study ⇒ Prospect theory vs. Expected utility theory, risk-seeking vs. risk-aversion

€ 400


Option C – Loss of € 800 with a probability of 50%.

Option D – Sure loss of € 400.

A loss of € 400





Option B – € 3,200 with a probability of 25% and € 1,600 with a probability of 25%.

Mini-case study ⇒ Prospect theory vs. Expected utility theory, shape of value function (1)


Option C – A loss of € 4,800 with a probability of 25%.

Option D – A loss of € 3,200 with a probability of 25% and a loss of € 1,600 with a probability of 25%.

€ 1,200

€ 1,200

A loss of € 1,200

A loss of € 1,200



Game No. 12: A friend will offer you a bet on a fair coin. If you lose, you have to pay € 50. What is the minimum sum that you need to win to make this bet attractive enough for you?

€ 0-25 € 25-50 € 50-75 € 75-100 € 100-125 € 125-150 More than € 150

Mini-case study ⇒ Prospect theory vs. Expected utility theory, shape of value function (2)




Option A – € 4,000 with a probability of 0.1%.

Option B – Sure € 4.

Mini-case study ⇒ Prospect theory vs. Expected utility theory, weighting function


Option C – A loss of € 4,000 with a probability of 0.1%.

Option D – A sure loss of € 4.

€ 4

A loss of € 4


2) Valuation methods that do not involve forecastingMental accounting and disposition effect

•Direct application of prospect theory (Kahneman, Tversky)•Shefrin, Statman (1985) – The Disposition to Sell Winners Too Early and Ride

Losers Too Long: Theory and Evidence•Disposition effect = Predisposition of investors to hold investment positions with

paper losses too long and sell investment positions with paper gains too early• ⇒ In start contrast with mainstream finance; Sub-optimal decisions; Strong

implications for corporate finance – Sunk costs matter a lot, pet projects•Loss aversion, risk-seeking in losses, regret aversion bias, confirmation bias•Some investor will never sell anything with loss „Honey, come on, it will improve, it

is only paper loss“•„Transfer your assets“•Use stop-losses!

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Game No. 15: Think of the following investment situation. You bought 100 shares of company XYZ for € 40 per share. Therefore the value of your current investment position is € 4,000. In the following trading period the share price declined by 15% to € 34. Therefore the value of your current investment position after the first trading period is € 3,400. As the investor you have to now decide for one of the following two options:

Option A – You will immediately sell your investment position with a loss of 15%.

Option B – You will keep your investment position one more trading period where there are two possibilities with the same probability: Share price will come back to € 40 per share or share price will lose another 15% to € 28 per share.

Mini-case study ⇒ Prospect theory vs. Expected utility theory, disposition effect

Game No. 16: Think of the following investment situation. You bought 100 shares of company ABC for € 40 per share. Therefore the value of your current investment position is € 4,000. In the following trading period the share price increased by 15% to € 46. Therefore the value of your current investment position after the first trading period is € 4,600. As the investor you have to now decide for one of the following two options:

Option A – You will immediately sell your investment position with a gain of 15%.

Option B – You will keep your investment position one more trading period where there are two possibilities with the same probability: Share price will decline back to € 40 per share or share price will rise by another 15% to € 52 per share.


2) Valuation methods that do not involve forecastingBEHAVIORAL BIASES


2) Valuation methods that do not involve forecastingBehavioral biases

• Inborn human characteristics / errors documented by academic research in cognitive psychology

• Leading to systematically sub-optimal and irrational decisions – in contrast to standard economics of homo oeconomicus

Former heavy-weight

superchampion

Wladimir Klitschko


2) Valuation methods that do not involve forecastingCategorization of behavioral biases

1) Cognitive errors, heuristics, mental shortcuts

a) Biases pertaining to rigidity of opinions (cognitive dissonance)

i. Conservatismii. Status quoiii. Confirmationiv. Representativenessv. Illusion of controlvi. Hindsight

b) Biases pertaining to information processing

i. Anchoring and adjustmentii. Mental accountingiii. Framingiv. Under-reaction and over-reaction v. Availability

2) Emotional biases

i. Loss aversionii. Overoptimismiii. Overconfidenceiv. Illusion of knowledgev. Self-attributionvi. Self-controlvii. Status quoviii. Endowmentix. Regret aversionx. Home bias


2) Valuation methods that do not involve forecastingFraming bias

What does it mean?• People’s decisions are not based on the substance/content of the information, but on the form in which it is presented• ⇒ Inconsistent decisions/choices – It has been proved that when we ask people almost the same question, only if we

formulate it differently, people will consistently answer in a different way (Kahneman, Tversky) suboptimal decisions⇒Real life example• Lives saved versus lives lost – 1) A –200 saved, B – 33% we save all 600 and 66% that all die A (C equivalent) (risk ⇒

aversion); 2) C – 400 certain death, D – 33% probability no one dies, and 66% probability that all die D (B equivalent) ⇒(risk seeking)

Investing• Investment with a loss, broker might say to a client : a) „Transfer your assets“ versus b) „Sell this losing position (mental

account closed / loss aversion / regret aversion) and buy this new investment

How to make better decisions?• Deep and complex analysis, try to formulate problems and questions differently

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Question No. 17: Imagine that the Czech Republic is preparing for an outbreak of an unusual disease which is going to kill 600 people. Doctors are proposing the following two programs how to tackle the disease:

If program A is accepted, 200 people will be saved.

If program B is accepted, there is a third (33.3%) probability that all people will be saved and a two thirds (66.7%) probability that no one will be saved.

Which program are you going to select?

Mini-case study ⇒ Framing bias

Question No. 18: Imagine that the disease from the question No. 17 is back. It is going to kill 600 people again. Doctors are proposing the following two programs how to tackle the disease:

If program C is accepted, 400 people will die.

If program D is accepted, there is a third (33.3%) probability that no one will die and a two thirds (66.7%) probability that 600 people will die.

Which program are you going to select?


2) Valuation methods that do not involve forecastingRepresentativeness bias

What does it mean?

• People have a natural tendency to evaluate all matters based on how they look like, first and quick look, rather than based on true statistical probabilities. Human thinking is driven rather by stories making about matters’ description rather than by analytical logic.

• ⇒ Consistent and predictable errors in decision-making in stark contrast with expected utility theory. Base-rate neglect (law of large numbers) and sample size neglect (“law of small numbers”).

Real life example

• Conjunction fallacy, e.g. heart attack study.

Investing

• Gamblers fallacy, i.e. betting on a change of an illusory trend, and Hot hand fallacy, i.e. betting on a continuation of an illusory trend.

How to make better decisions?

• Deep and complex analysis, try to formulate problems and questions differently. Always try to discern true probabilities and use them in your analysis. Do not base your decision-making on stories-making.



Question: Michel is single, open and very smart. She has a Master degree from philosophy. As a student she was interested a lot in topics such as discrimination and equality. What is more probable?

A – Michel works in a bank.

B – Michel works in a bank and is active in feminist movement.

Mini-case study ⇒ Representativeness bias

Conjunction fallacy

Bank employeesActivists in

feminist movement

Bank employees and at the same time activists in feminist movement



Question: Assume that a fair coin has been tossed three time and every time heads was tossed. If you had to stake € 1,000 on another toss, what would be your choice? Heads, tails or no preference?

Mini-case study ⇒ Representativeness bias Gamblers fallacy & Hot hand fallacy⇒


2) Valuation methods that do not involve forecastingGamblers fallacy & Hot hand bias “Local” representativeness⇒

• Base-rate neglect (law of large numbers) ⇒ Gamblers fallacy Betting on a ⇒ change of an illusory trend • Sample size neglect (“law of small numbers”) ⇒ Hot hand fallacy Betting on a ⇒ continuation of an illusory trend

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2) Valuation methods that do not involve forecastingOveroptimism bias

What does it mean?

• Everybody wears „pink glasses“

Real life example

• 80% of drivers rate themselves as above-average

Investing

• „My investment performance will be ca 25% every year“


• Think in terms of „probability distributions“

• DCF, Capital projects analysis – be conservative

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Question No. 1: What would you characterize yourself as regards your personality?

A – I am an optimist.

B – I am a pessimist.

C – I am something in between.

Mini-case study ⇒ Overoptimism bias

Question No. 2: What would you characterize yourself as regards your studying efforts?

A – I am an above average student.

B – I am an average student.

C – I am a below average student.

Question No. 3: What would you characterize yourself as regards your driving skills?

A – I am an above average driver.

B – I am an average driver.

C – I am a below average driver.

Question No. 4: What would you characterize yourself as regards your investing skills?

A – I am an above average investor.

B – I am an average investor.

C – I am a below average investor.


2) Valuation methods that do not involve forecastingOverconfidence bias

What does it mean?• Poor calibration, too narrow confidence intervals People are surprised more often compared to their ⇒

expectations, predominantly on the downside; Connected to fat-tail problem (VaR, stress testing, sensitivity analysis) and black-swan concept

Real life example• State 90% confidence interval of number of Africa population Only 50% answers correct Poor calibration, ⇒ ⇒

frequent surprisesInvesting• Portfolio return range in one year -5% - 25% Unexpected underperformance of majority of investors⇒• Too frequent trading (Trading is hazardous to your wealth – Barber, Odean), Men vs. WomenHow to make better decisions?• Investors should focus on long-term horizon of at least 5 years and do not gamble / speculate, avoid short-term

gambling / casino• DCF, Capital projects analysis – Sensitivity analysis / scenarios analysis / stress testing / crash tests – Worst case

scenarios should be on average even much worse



Question No. 1: State your 90% confidence band / interval of the market capitalization of the US equity index S&P 500.

Mini-case study ⇒ Overconfidence bias

Question No. 2: State your 90% confidence band / interval of the number of the European Union’s inhabitants.

Question No. 3: State your 90% confidence band / interval of the nominal value of the German government debt.


2) Valuation methods that do not involve forecastingIllusion of control bias (1)

What does it mean?

• People think they can control random and / or uncontrollable events

Real life example

• Taleb (Fooled by Randomness, 2001) – The real world is much more unpredictable than we think. People interpret reality in such a way that they form stories that puts well to each other.

Investing

• Internet and online trading (marketing campaigns tell us that it will improve our performance) – Various tools should improve our analytical skills and performance (Barber, Odean) Speculative investments, well too much ⇒trading (overconfidence, overoptimism)

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2) Valuation methods that do not involve forecastingIllusion of control bias (2)


• Realize that „Investing is a probability activity“; World is much more complex and uncertain than you think

• Business strategy / capital project / DCF Pay much more attention to risk analysis / sensitivity and scenarios ⇒analysis, stress testing + add business decision making / business strategy complex thinking, do not bases your investment decision only on DCF / NPV

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2) Valuation methods that do not involve forecastingConfirmation bias

What does it mean?• People generally look only for supportive evidence and disregard any contradictory evidence

Real life example• „My car is the best because this test showed that…, but this test’s bad result is not relevant/it was wrong“

Investing• Demo-account / online trading – 300% performance in 3 months real investing will be also that good⇒• Mental accounting, disposition effect, loss aversion, regret aversion we look for confirmation that our decision ⇒

(and currently big paper loss) was right and avoiding any contradictory evidence

How to make better decisions?• 1) Why not invest in this asset – contra-confirmation, and then 2) why invest; take into account all facts and info,

only this way of thinking and decision making will allow you to learn from past mistakes• CAPEX management – Sunk cost problem, pet projects, regret aversion bias

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2) Valuation methods that do not involve forecastingAnchoring and adjustment bias

What does it mean?

• Any data, proposals, informatio act on us as achors, despite being totally irrelevant sometimes

• When new relevant information appears, adjustment of judgments is very slow and rigid.

Real life example

• 21st Century Investor – Book signing on 25 September 2013 – Wladimir Klitschko example

• Kahneman and Tversky – Wheel of fortune

Investing

• Sell-side analysts investment recommendations, stock target prices and their adjustments


• Forget about price you bought the share for

• Before any business negotiation / discussion be well prepared and have your own strong view not to be anchored by the other party’s viewpoints

• Valuation – Reverse-engineered DCF models What is the current market ⇒price implying/pricing, fundamentally justified price multiples

http://blog.pdus2go.com/wp-content/uploads/2012/08/Anchor.jpeg



Write down last three figures of your mobile number.

Mini-case study ⇒ Anchoring and adjustment bias

Is the number of general practitioners in Prague higher or lower than this number?

Write down your best estimate of general practitioners in Prague.


2) Valuation methods that do not involve forecastingSelf-attribution bias

What does it mean?• „Our successes are caused by our skills, knowledge and hard work, but our failure are caused by someone

else or bad luck“Þ People do not learn from their past failures and mistakes!

Real life example• Failing to pass an important exam

Investing• Successful and unsuccessful stock picks

How to make better decisions?• Investing – Write down detailed records of your investment decisions and actions• Try to be as frank as possible to yourself, try to avoid any regrets• Analyze current decisions and results of past decisions in consistent and open way

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2) Valuation methods that do not involve forecastingMini-case study

⇒ Self-attribution bias


2) Valuation methods that do not involve forecastingUnder-reaction and over-reaction bias

What does it mean?

• People systematically underestimate and under-react to abstract, statistical and highly relevant information, and on the other hand, overweight and overreact to striking, noisy but much less relevant information and data

Real life example

• Underreaction to growing weight as a result of overeating, overreaction to ads on diet cocktails

Investing

• Stock market – Outperformance of losers and underperformance of winners (Werner de Bondt) – 1985 – Does stock market overreact? Contrarian investing rocks!⇒

• Overreaction to earnings season compared with under-reaction to long-term fundamental trends in the company (industry)

• Noise-traders risk (irrational investors) – Big risk to fundamental (relatively rational) investors – Market inefficiencies can even increase…yes, mean-reversion, but only in the very long-term horizon of several, rather many years


• Try as much as possible to focus on core underlying data, information and probabilities, and avoid a too big focus on unimportant yet spectacular and attention-grabbing data, information and news



⇒ Under-reaction and over-reaction bias

• Werner de Bondt (1985) – Does stock market overreact? Outperformance of losers and underperformance of ⇒winners Contrarian investing rocks!⇒


2) Valuation methods that do not involve forecastingConservatism bias

What does it mean?• We do not want to change a lot our opinions, our past decisions, and especially accept others’ opinions which

differ / contradict to ours• It causes slow decision-making, connected to under-reaction

Real life example• Voting preferences, political parties; newspapers …right vs. left

Investing• Changing your stock broker or asset manager might be rather difficult and very slow process, despite you might

figure out that the others might be much better than your current ones• Very rigid and slow positioning to new investment / business opportunities that might appear in front of you in the

future

How to make better decisions?• Do not procrastinate, be proactive in all decision-making problems, do not be among the average!

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2) Valuation methods that do not involve forecastingAmbiguity aversion bias

What does it mean?

• People are too cautious, extremely slow when facing new realities

Real life example

• “I have never been to Asia and Latin America, I am bit worried about potentially travelling there”

Investing

• Home-bias – Investing only in geographically close and well know region(s)


• Continuous studying on your own! Be expert in your area, be excellent!



⇒ Ambiguity aversion bias

• Picking marbles from a basket


2) Valuation methods that do not involve forecastingAvailability bias

What does it mean?• People have a natural tendency to grasp any irrelevant and often subconscious information when they have to

make decisions in real life, i.e. under uncertainty• When people have to make any judgments, any irrelevant data and information that they receive by chance have

a strong and consistent tendency to impact their reasoning, of course without them realizing this at all

Real life example• Deaths in the US – Sharks or fall airplane parts? Falling airplane parts 30 times higher probability!

Investing• Barber, Odean (2007) – All that glitters – Investors are buying stocks that are somehow grabbing their attention

How to make better decisions?• When making important decisions please do try to study all key historical data and statistics


2) Valuation methods that do not involve forecastingEndowment bias

What does it mean?• When owning something people have a systematic tendency to value it much more than other people who do not

own it• Causes in general much lower market traded volumes than implied by classical economics / expected utility theory

Real life example• Professor of economics – French wine• MBA students – Tea cups

Investing• Causes “irrational premium“ to assets we have in our portfolio

How to make better decisions?• Ask yourself: If I did not own it, would I buy it for the price I am attaching to it now (including the “irrational

premium“)• Experience lowers endowment effect


2) Valuation methods that do not involve forecastingHindsight bias

What does it mean?• Hindsight bias is a very strong natural tendency to ex-post explain all historical developments which are quite

often totally random driven by pure chance, or a tendency to state that we knew it all well in advance• Hindsight bias supports the opinion that the world is much more predictable than it really is• Connected to illusion of control bias• A went up, because B went up, because C went down Stories making (Robert Shiller)⇒Real life example• World War II

Investing• James Montier – Tech bubble – „They invested into it, but regard it now as a bubble“; GFC (great financial crisis)

How to make better decisions?• Do not make stochastic forecasts only for the future, but try to make it retroactively for the past developments as

well.• ⇒ Do not think in terms of stories, think rather in probability distributions; BUT when making interviews, speaking

on CNBC, speak rather in stories

https://www.google.cz/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRxqFQoTCKmEzrmw2McCFYX-LAodSZ0MPA&url=https://sites.google.com/a/gx.camden.k12.ga.us/mrs-thomas-5th-grade-class-1/home/social-studies/unit-7-world-war-ii-its-aftermath&psig=AFQjCNH_sORD_WTAQMaI434mOxSdSZ9rEw&ust=1441284257799882

http://www.google.cz/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRxqFQoTCK_57uGw2McCFYVcLAodXBMINQ&url=http://thehoopla.com.au/poor-moody-advice-bet/&v6u=https://s-v6exp1-v4.metric.gstatic.com/gen_204?ip=91.231.171.20&ts=1441197929496875&auth=b4s5sfgam5oo6lmrcg2xnvw5n2sm5x26&rndm=0.15030317797267956&v6s=2&v6t=27159&psig=AFQjCNEiM0ntrJpCeTof7z6AqFTzhw5Fmw&ust=1441284329416787


2) Valuation methods that do not involve forecastingDecoy effect

What does it mean?

• Decoy effect results in such a decision-making that when your counterparty (client, etc.) is in a process of picking one out of two options provided by you, she might make a strikingly different decision if she takes into account an additional third option - strictly disadvantageous (asymmetrically dominated) - option. This third option must be disadvantageous in all parameters vis-à-vis one of the original options (your preferred one) and at the same time disadvantageous vis-à-vis the second (counterparty's preferred) option only in several parameters. Third option ⇒is in fact just a decoy that should entice your counterparty to pick one of the original two options (your preferred one). This fact has been proved (on average) by academics and practiced many years in business fields such ⇒as marketing.

• Used a lot in retail when retailers want to get rid of some stuff.

Real life example

• Bottles of wine, etc.

Investing

• Bond funds vs. Equity funds. Equities too risky? Lets present commodities funds as well How to make better decisions?

• How to make better (investment) decisions? Deep and complex analysis, try to formulate decision-making ⇒problems and questions in various and different ways from all the angles possible. And in this particular case you should in general appropriately design your own criteria / KPIs so that you will be able as much “rationally” as possible to sort the options available according to your “rational” optimum, i.e. your expected future utility stream, taking into account time value of money / (hyperbolic) discounting. And of course, please do not forget that your counterparty might use the same tactics against you as well.



⇒ Decoy effect

• Bottles of wine, need to get rid of, i.e. to sell any particular bottles?



Question: There is a very dangerous algae growing in the lake. Every day the space covered with algae doubles. If the algae takes 48 days to cover the whole lake, how long does it take to cover a half of the lake?

Mini-case study ⇒ Cognitive reflection / System X and system C



Question: And now we will play the following very simple game. Pick a number between 0 and 100. A winner of this game will be the one of you who picks a number closest to two thirds of the average picked number. So what is your pick?

Mini-case study ⇒ Intensity of (ir)rationaly & Strategic thinking


2) Valuation methods that do not involve forecastingBEHAVIORAL CORPORATE FINANCE, INCL. DEAL MAKING


2) Valuation methods that do not involve forecastingBehavioral corporate finance – Key issues

• Behavioral biases influencing managers can dominate financial interest of shareholders (owners)

• Behavioral finance holds important implications for the practice of corporate decision-making as well

• Key behavioral biases in place:• Overoptimisim and overconfidence biases• Confirmation bias• Loss aversion bias• Framing bias• Self-attribution bias• Anchoring and adjustment bias

• Despite the advice offered by Brealey and Myers (Principles of Corporate Finance), corporate decision-makers often treat sunk costs as relevant

• Visibility, pet projects, loss aversion bias

• Group (committee) decision-making often amplify individual errors

• Agency costs – Separation of ownership and managerial control

• Behavioral influences are akin to agency costs


2) Valuation methods that do not involve forecastingUnder-reaction and over-reaction of investors

=> Be contrarian investor!

• Stock repurchases (stock buy-backs) are a signal that corporate managers feel the stock of their firm is seriously undervalued.

• Stock market appears to under-react to the information inherent in corporate announcements.

• James Montier (2002, page 174):

„On thing is very clear, investors should in general be very sceptical of any firm seeking to raise funds in the market place. IPOs, SEOs (SPOs), convertible bonds, stock-finance mergers and acquisitions all bode badly for investors. Extreme caution should be exercised before investing in stocks that offer up a good story in return for further financing.“



• Kahneman, D. (2011) Thinking, fast and slow. New York, Farrar, Straus and Giroux.

• Montier, J. (2002) Behavioral Finance: Insights into Irrational Minds and Markets, WILEY, Chichester, West Sussex, England.

• Montier, J. (2007) Behavioral Investing: A practitioner’s guide to applying behavioral finance, WILEY, Chichester, West Sussex, England.

• Pompian, M. (2006) Behavioral Finance and Wealth Management: How to Build Optimal Portfolios That Account for Investor Biases, WILEY, New Jersey, USA.

• Shefrin, H. (2002) Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing, Oxford University Press, New York, USA.

• Shefrin, H. (2007) Behavioral Corporate Finance: Decisions that Create Value, McGrawHill/Irwin, New York, USA.

• Shiller, R. (2005) Irrational Exuberance, Second Edition, Princeton University Press, USA.

• Taleb, N. (2004) Fooled by Randomness –The Hidden Role of Chance in Life and in the Markets, Penguin Books, London, England.

• Taleb, N. (2007) The Black Swan –The Impact of the Highly Improbable, Penguin Books, London, England.

Behavioral finance – References



• To be an expert in standard mainstream economics is not enough to be top-tier finance professional in 21st century.

• Good working knowledge of behavioral economics is an essential complement which pushes you up in the „league-table“ of finance experts.

• Work on your „behavioral resistance“ and do not fall into behavioral traps.

• Knowledge of behavioral economics, and behavioral biases in particular, is applicable in all areas of business, e.g. consulting, business negotiation, deal making, corporate communication, marketing, HR, etc., and significantly improves your performance.

Summary



Michal Stupavský, CFA

[email protected]

Thank you for your attention!

Documents

160708 - Applied Behavioral Economics