Begrippen Behavioral Finance

Behavioral Finance: The field of finance that studies how psychological factors, cognitive biases and emotions influence economic and investment decisions and the functioning of markets.
Homo Economicus: The model of a fully rational agent who calculates all outcomes, maximises utility and has time-consistent preferences.
Expected Utility Theory: Von Neumann and Morgenstern (1947): a rational person chooses the option with the highest probability-weighted average of utility, provided preferences satisfy four axioms.
Completeness: Axiom that a person can always rank two options: either L ⪰ M, L ⪯ M, or both (indifference).
Transitivity: Axiom that preferences are consistent: if L ⪰ M and M ⪰ N, then L ⪰ N.
Continuity: Axiom that for L ⪯ M ⪯ N there is a probability p such that a mix of L and N is as good as M.
Independence axiom: Axiom that mixing two options with the same third lottery, at the same probability, does not change their ranking.
Risk aversion: Preferring a certain amount to a risky lottery with the same expected value; under EUT caused by a concave utility function.
Certainty equivalent: The certain amount that gives the same utility as a risky lottery; for the √W example about 104.7.
Endowment effect: The tendency to value an item more once you own it, so that Willingness To Accept exceeds Willingness To Pay.
Framing effect: Choices change when the same problem is presented differently, for example as lives saved versus lives lost.
System 1 and System 2: Kahneman's two modes of thinking: System 1 is fast, automatic and error-prone; System 2 is slow, effortful and more reliable.
Efficient Market Hypothesis: Fama (1970): asset prices fully and immediately reflect all available information, so no one can systematically beat the market.
Weak-form efficiency: Prices reflect all historical prices and volume, so technical analysis cannot earn excess returns.
Semi-strong-form efficiency: Prices reflect all public information, so fundamental analysis cannot systematically earn excess returns.
Strong-form efficiency: Prices reflect both public and private information, so even insiders cannot earn excess returns.
Arbitrage: Simultaneously buying an underpriced asset and selling an overpriced one to profit from the price gap, which pushes prices back to fair value.
Random walk: A price process where each change is an independent random shock, so future returns cannot be predicted from past prices.
Market anomaly: A predictable pattern in returns, such as the January effect, momentum or reversal, that is hard to explain under the EMH.
Momentum: The tendency of recent winners to keep outperforming and recent losers to keep underperforming over the following months.
Reversal: The tendency of long-term past losers to outperform long-term past winners over the next years.
Shefrin's three pillars: Heuristics, framing and market inefficiencies: the three building blocks of behavioral finance according to Shefrin (2002).
Familiarity bias: Preferring investments you know, such as home-country or employer stocks, which leads to under-diversification.
Bounded rationality: Simon's idea that human rationality is limited by incomplete knowledge, limited cognitive capacity and limited time, so people use shortcuts.
Prospect Theory: Kahneman and Tversky's (1979) descriptive theory of risky choice: outcomes are valued as gains or losses from a reference point and probabilities are weighted non-linearly.
Reference point: The benchmark, usually the status quo or purchase price, against which outcomes are coded as gains or losses.
Loss aversion: Losses are felt more strongly than equal gains; the coefficient λ ≈ 2.25 means a loss hurts about twice as much.
Value function: The S-shaped function v(x) in Prospect Theory: concave for gains, convex and steeper for losses.
Diminishing sensitivity: Each additional unit of gain or loss has a smaller effect, giving concavity for gains and convexity for losses.
Probability weighting function: The function π(p) that turns objective probabilities into decision weights: small probabilities are overweighted, large ones underweighted.
Certainty effect: Outcomes that are certain receive much more weight than outcomes that are merely very likely; it drives the Allais paradox.
Allais paradox: A pair of choice problems where most people's choices (1A and 2B) violate the independence axiom of Expected Utility Theory.
Ellsberg paradox: An urn experiment showing that people prefer bets with known probabilities to bets with unknown probabilities.
Ambiguity aversion: Dislike of situations where the probabilities themselves are unknown, beyond ordinary risk aversion.
Editing (processing) phase: First stage of Prospect Theory in which a choice is simplified through coding, combination, segregation, cancellation, simplification and dominance.
Evaluation phase: Second stage in which edited prospects are valued as V = Σ π(p<sub>i</sub>) v(x<sub>i</sub>) and the highest is chosen.
Disposition effect: Shefrin and Statman (1985): investors sell winning positions too early and hold losing positions too long.
House money effect: Thaler (1980): after gains, people are more willing to take risks because they treat profits as not really their own money.
Myopic loss aversion: The combination of loss aversion and frequent evaluation, which makes volatile assets feel riskier and lowers equity holdings.
Equity premium puzzle: The observation that stocks have historically earned much more than safe bonds, more than standard risk aversion can explain.
Sharpe ratio: Excess return over the risk-free rate divided by the standard deviation of returns: return per unit of risk.
Black Swan: A rare, extreme and hard-to-predict event that people tend to ignore because they focus on likely outcomes.
Descriptive versus normative theory: A descriptive theory explains how people actually choose; a normative theory prescribes how they should choose.
Heuristic: A mental shortcut for fast decisions under uncertainty that often works but can cause systematic biases (Tversky & Kahneman, 1974).
System 1: Fast, automatic, intuitive and emotional thinking that relies on heuristics and is prone to systematic errors.
System 2: Slow, conscious, effortful and analytical thinking that can monitor and correct System 1.
Cognitive Reflection Test: Short questions (such as bat and ball) with an intuitive wrong answer, used to see whether System 2 overrides System 1.
Availability heuristic: Judging the probability of an event by how easily examples come to mind, so vivid or recent events seem more likely.
Representativeness heuristic: Judging probability by similarity to a prototype, while neglecting base rates and sample size.
Base rate: The prior probability of an event in the population, such as the 15% share of blue taxis.
Bayes' theorem: Rule for updating a probability with new evidence: P(A|B) = P(B|A)P(A)/P(B).
Law of small numbers: The mistaken belief that small samples closely reflect the population (Kahneman & Tversky, 1971).
Sample size neglect: Ignoring that small samples produce more extreme and less reliable results.
Gambler's fallacy: The false belief that past outcomes of independent random events change the probability of the next outcome.
Hot-hand fallacy: The belief that a person or asset on a winning streak is more likely to continue it, even when outcomes are random.
Overconfidence: Overestimating one's knowledge, ability or the accuracy of one's predictions.
Overplacement: Believing one is better than the average person, such as 82% of drivers rating themselves in the top 30%.
Overprecision: Excessive confidence in the accuracy of one's estimates, shown by confidence intervals that are too narrow.
Illusion of control: The feeling that one can influence outcomes that are actually random.
Self-attribution bias: Crediting successes to one's own skill and blaming failures on bad luck.
Confirmation bias: Seeking and favouring information that confirms existing beliefs while ignoring contradicting evidence.
Recency bias: Giving excessive weight to the most recent events and expecting recent returns to continue.
Anchoring: Relying too heavily on an initial reference number, such as a purchase price, when making estimates.
Mental accounting: Thaler (1985): treating money in separate psychological accounts by source or purpose, although money is fungible.
Fungibility: The property that every unit of money is interchangeable with every other unit, whatever its source.
Portfolio segregation: Evaluating parts of a portfolio (for example safe bonds and risky stocks) separately instead of as one whole.
Price-to-book (P/B) ratio: Price paid divided by the book value of equity; NBG paid more than 4x book for Finansbank.
Efficient Market Hypothesis (EMH): The theory that security prices fully reflect all available information, so that no investor can systematically earn risk-adjusted excess returns using that information.
Weak-form efficiency: Prices reflect all information in past prices and trading volume, so technical analysis cannot earn excess returns.
Semi-strong-form efficiency: Prices reflect all publicly available information, such as financial statements and news, so fundamental analysis of public data cannot earn excess returns.
Strong-form efficiency: Prices reflect all information, public and private, so even insiders cannot earn excess returns.
Excess return (abnormal return): The return earned above what is expected for the risk taken, measured relative to a pricing model such as the CAPM.
Random walk: A process in which each change is unpredictable, P_t = P_(t−1) + ε_t, so the best forecast of the next price is the current price.
AR(1) process: An autoregressive model P_t = α + ρP_(t−1) + ε_t in which today's value depends on yesterday's; with ρ below 1 the series reverts to the mean α/(1 − ρ).
Mean reversion: The tendency of a price or return to move back toward a long-run average after a deviation.
Joint hypothesis problem: Every test of market efficiency is also a test of the assumed pricing model, so abnormal returns may reflect inefficiency or a wrong model.
Null hypothesis: The default assumption in a statistical test, here that markets are efficient and returns are unpredictable, which researchers try to reject with evidence.
CRSP: The Center for Research in Security Prices at the University of Chicago, whose US price databases from the 1960s enabled large-scale tests of the EMH.
Passive management: Investing by holding a market index (index funds, ETFs) at low cost instead of trying to beat the market, a strategy inspired by the EMH.
Excess volatility: Shiller's (1981) finding that stock prices fluctuate much more than changes in fundamentals such as dividends can justify.
Momentum: Short-term positive dependence in returns: assets that performed well recently tend to keep performing well for some months.
Long-term reversal: The tendency of assets with extreme past performance over several years to move in the opposite direction afterwards.
Overreaction: A price move that goes too far in response to news and later partly reverses.
Underreaction: A price that adjusts too slowly to news and keeps drifting in the direction of the news.
Technical analysis: Forecasting prices from patterns in past prices and volume, such as support, resistance and head-and-shoulders patterns.
Support and resistance: Price levels where buying (support) or selling (resistance) has repeatedly stopped a decline or a rise, according to technical analysts.
Head and shoulders: A chart pattern of three peaks, the middle one highest, which technical analysts read as a reversal from a bullish to a bearish trend.
Psychological barrier: A round-number price level, such as Dow 1,000, at which investors behave differently even though it has no economic meaning.
Bubble: A period in which prices rise far above fundamental value because investors buy as others buy and believe 'this time is different'.
Narrative economics: Shiller's idea that stories spread like epidemics, shape expectations and drive economic and market outcomes.
Anchoring: Basing judgments on an arbitrary reference point, such as a round number or a past price.
Herding: Investing as the majority does instead of relying on one's own information.
Framing effect: The tendency of people to make different choices depending on how economically identical options are presented, for example as gains or as losses.
Gain frame / loss frame: Describing outcomes relative to a low reference point as amounts saved or won (gain frame), or relative to a high reference point as amounts lost (loss frame).
Reference dependence: Evaluating outcomes as gains or losses relative to a reference point, such as the purchase price, rather than as final wealth.
Loss aversion: Losses hurt more than equal-sized gains please, roughly twice as much (λ ≈ 2.25 in prospect theory).
Narrow framing: Evaluating each investment or each short period in isolation instead of the total portfolio over the long horizon.
Myopic loss aversion: The combination of frequent portfolio evaluation and loss aversion, which makes investors avoid risky but profitable assets such as stocks (Benartzi & Thaler, 1995).
Equity premium puzzle: The finding that stocks have historically earned far more than safe bonds, more than standard models of risk aversion can justify.
Arbitrage: Buying an underpriced asset and selling an equivalent overpriced asset to profit when their prices converge.
Limits of arbitrage: The risks and costs (fundamental risk, noise trader risk, implementation costs) that stop arbitrageurs from fully correcting mispricing.
Fundamental risk: The risk that news hits the imperfect substitute used as a hedge, so an arbitrage position loses money.
Noise traders: Investors who trade on emotion, rumours, hype or frames rather than fundamentals.
Noise trader risk: The risk that noise traders push mispricing further before it corrects, forcing arbitrageurs to add capital or liquidate (Shleifer & Vishny, 1997).
Pairs trading: Going long one stock and short a similar stock when their usual price relationship (for example equal P/E) breaks, betting on convergence.
Law of One Price: Two economically identical assets should trade at the same price, P_A = P_B.
Closed-end fund: A fund with a fixed number of exchange-traded shares that cannot be redeemed at NAV, so its price can deviate from NAV.
Net asset value (NAV): The market value of a fund's assets minus liabilities, per share.
Smart beta: Rules-based strategies that weight stocks by factors such as value, momentum, size or low volatility instead of market capitalisation.
Fundamental indexation: Weighting index constituents by fundamentals such as sales, cash flow or book value instead of market value (Arnott, Hsu & Moore, 2005).
Value factor: The tendency of cheap stocks (low P/E, P/B) to outperform expensive growth stocks, linked to overreaction and representativeness.
Momentum factor: The tendency of past 12-1 month winners to keep outperforming past losers, linked to underreaction and herding.
Low-volatility anomaly: The finding that low-risk stocks earn higher risk-adjusted (and often raw) returns than high-risk stocks, contrary to the CAPM.
Factor zoo: The more than 400 proposed return factors, many of which result from data mining and fail out of sample.
Animal spirits: Psychological forces such as confidence, emotion, narratives, fear and enthusiasm that drive economic behavior (Akerlof & Shiller, 2009).
Money illusion: Thinking in nominal rather than real (inflation-adjusted) terms.
DSGE model: Dynamic Stochastic General Equilibrium model: the standard macro model with a rational representative agent and perfect information.
Momentum: The tendency of assets with high returns over the past 3 to 12 months to keep outperforming, and of poor performers to keep underperforming.
WML (Winner minus Loser): The return of a portfolio long the top past-return decile (D10) and short the bottom decile (D1); the standard measure of the momentum premium.
Lookback period (J) and holding period (K): J is the number of months of past returns used to rank assets; K is how many months the resulting portfolios are held.
Cross-sectional momentum: Buying the assets that performed best relative to others and shorting the relative worst, regardless of whether their own returns were positive.
Time-series momentum: Going long an asset whose own recent cumulative return is positive and short one whose return is negative, judged asset by asset.
UMD (Up Minus Down): The momentum factor: a long-short winners-minus-losers portfolio, typically on a 12-2 lookback with monthly rebalancing, used next to market, size and value factors.
Alpha (α): The part of a portfolio's return that the factors in a regression cannot explain; a positive significant alpha signals an anomaly or skill.
Post-Earnings Announcement Drift (PEAD): The continued drift of a stock's price in the direction of an earnings surprise for weeks after the announcement, an example of underreaction.
Conservatism bias: The tendency to update beliefs too slowly when new information arrives, leading to underreaction.
Representativeness bias: Judging by similarity to a pattern, so that a short series of similar outcomes is extrapolated too far, leading to overreaction.
Herding: Imitating the trades of others in the belief that the crowd knows something, which amplifies existing trends.
Narrative momentum: Price trends fuelled by popular stories (AI, crypto, green tech) that reverse when the story changes.
Momentum crash: A sudden, severe loss of momentum strategies during sharp market reversals, such as the roughly 80% drawdown in 2009.
Volatility targeting: Scaling the size of a position so that its expected volatility stays near a target level, reducing exposure when markets are turbulent.
Golden cross / death cross: A short-term moving average crossing above (golden) or below (death) a long-term moving average, read as a bullish or bearish signal.
Overbought / oversold: RSI readings above 70 (overbought) or below 30 (oversold) that technical analysts interpret as signs of a possible reversal.
Support and resistance: Price levels where falling prices tend to stop (support) or rising prices tend to stall (resistance), often prior troughs and peaks.
Adaptive Markets Hypothesis: Lo's (2004) view that markets are adaptively efficient: strategies work until investors learn to neutralise them, and anomalies persist while human frictions exist.
Limits to arbitrage: Costs and risks (transaction and shorting costs, timing risk, limited capital) that stop rational traders from fully removing mispricing.
Mean reversion: The tendency of prices or returns to move back toward their long-run average after deviating from it.
Short-term reversal: Negative autocorrelation of returns over weeks or a month (Jegadeesh, 1990), mainly attributed to liquidity shocks and bid-ask bounce.
Long-term reversal: The tendency of 3-to-5 year losers to outperform 3-to-5 year winners over the following years (De Bondt & Thaler, 1985).
Bid-ask bounce: The mechanical negative autocorrelation in measured returns caused by trades alternating between bid and ask prices.
Contrarian strategy: Buying past losers and selling past winners, typically for 3 to 5 years, to profit from the correction of crowd overreaction.
Value effect: The outperformance of high book-to-market (value) stocks over low book-to-market (growth) stocks, interpreted in this lecture as long-term reversal.
Investor sentiment: Non-fundamental optimism or pessimism, shared by many investors, that moves asset prices away from fundamental value.
Excess volatility: Shiller's finding that stock prices fluctuate far more than subsequent changes in dividends can justify.
Baker and Wurgler index: A sentiment index formed as the first principal component of six market proxies such as IPO activity, turnover and the closed-end fund discount.
Principal component analysis (PCA): A statistical method that finds the weighted combination of several variables explaining most of their common variation.
Closed-end fund discount: The percentage by which a closed-end fund's market price is below its net asset value; a small discount signals optimism.
Turnover ratio: Trading volume divided by market capitalisation; high turnover signals overconfidence and noise trading.
Dividend premium: The valuation gap between dividend-paying and non-paying firms; a small premium means investors favour risky growth.
Equity share in new issues: Equity issues as a share of total new issues (equity plus debt); a high share suggests managers see shares as overpriced.
Story stocks: Firms valued mainly for a narrative about the future rather than current earnings, typically very sensitive to sentiment.
Search Volume Index (SVI): Google's scaled measure (0 to 100) of search intensity for a term, used as a real-time proxy for attention or fear.
Nowcasting: Estimating current economic conditions with real-time data before official statistics are published (Choi and Varian, 2012).
Loughran and McDonald dictionary: A finance-specific list of positive and negative words for measuring the tone of financial texts.
Narrative contagion: Shiller's idea that economic stories spread from person to person like a virus and change behavior.
Affect heuristic: Judging risk and return through feelings, so emotions dominate probability assessments.
Liquidity spiral: A loop in which falling prices force leveraged traders to sell, which lowers prices and funding liquidity further (Brunnermeier and Pedersen, 2009).
Animal spirits: Akerlof and Shiller's (2009) term for the confidence, fear and stories that drive economic cycles.
Forward guidance: Central bank communication about the likely future path of policy, used to manage expectations.
VIX: The CBOE index of 30-day implied volatility of the S&P 500 from option prices, known as the fear index.
Complacency effect: The tendency for very low fear readings (low VIX) to precede sharp market falls.
AAII net sentiment: The percentage of bullish minus the percentage of bearish respondents in the weekly AAII survey.
Contrarian indicator: A measure whose extreme readings are used to bet against the crowd, for example buying when fear is extreme.
MOVE index: ICE BofA index of implied volatility in U.S. Treasury markets, built from 1-month options on 2, 5, 10 and 30-year bonds.
Fear & Greed Index: CNN index from 0 (extreme fear) to 100 (extreme greed) combining seven market indicators.
Attention-driven buying: Retail buying of stocks that catch attention through news, searches or social media, often followed by an attention crash.
Michigan Consumer Sentiment Index (MCSI): Monthly survey-based index of about 500 U.S. households measuring consumer optimism; a leading indicator since 1946.
Herding: Imitating the actions of others while ignoring one's own information, producing correlated trades without a common fundamental cause.
Informational herding: Following others because their actions are believed to reveal information that one does not have.
Reputational (career-based) herding: Following other managers or analysts to protect one's reputation or job, since being wrong together is less costly than being wrong alone.
Emotional (social) herding: Following the crowd because of feelings such as FOMO, social proof or the comfort of the group rather than information.
Information cascade: A situation in which each investor rationally ignores her private signal and imitates earlier investors, so later actions add no new information (Bikhchandani, Hirshleifer and Welch, 1992).
Sequential herding: Banerjee's (1992) model in which investors decide one after another and follow predecessors once a few have made the same choice.
LSV measure: Lakonishok, Shleifer and Vishny's (1992) institutional herding statistic: the absolute deviation of the buyer proportion in a stock from its expected value, minus an adjustment factor.
Adjustment factor (AF): The expected value of |p − E(p)| when institutions trade independently, subtracted in the LSV measure to remove chance imbalances.
CSAD: Cross-sectional absolute deviation: the average absolute difference between individual stock returns and the market return on a day.
CSSD: Cross-sectional standard deviation of stock returns around the market return, used by Christie and Huang (1995).
γ2 (gamma 2) in the CSAD regression: The coefficient on the squared market return; a significantly negative value means dispersion rises less than linearly with market moves, which indicates herding.
Raw fraction of institutions buying: Sias's (2004) measure: the share of institutions trading a stock in a quarter that increased their holding.
Spurious herding: Similar decisions caused by reacting to the same common information; consistent with market efficiency (Bikhchandani and Sharma, 2000).
Intentional herding: Deliberately copying other investors regardless of one's own information; can push prices from value and create systemic risk.
Anti-bubble: A downward price spiral driven by the same imitative behavior as a bubble, as Johansen and Sornette (1999) found in the Nikkei.
Social proof: The belief that what the majority does must be correct.
Conformity bias: Adjusting one's views and actions to match the majority for acceptance and safety.
FOMO: Fear of missing out: anxiety about being left out of a rising market, which drives late buying.
Short squeeze: A rapid price rise that forces short sellers to buy back shares to limit losses, which pushes the price up further.
Herding cycle: Initial trend, imitation, trend reinforcement and collapse or panic, after which the cycle restarts.
Crowded trade: A position held by many funds at the same time, which becomes dangerous when they all try to exit together.
Fire sale: Forced selling of assets at prices far below fundamental value, typical when a herd reverses.
Circuit breaker: A temporary trading halt triggered by large price movements, meant to stop panic selling.
Cramer effect: Short-term price reactions caused by retail investors following TV stock picker Jim Cramer, an example of herding plus a celebrity effect.
Bubble: A situation in which an asset's price rises significantly above its intrinsic value because of excessive demand, optimism and herding, usually followed by a sharp crash.
Intrinsic value: The value of an asset justified by its fundamentals, mainly the present value of its expected future cash flows.
Narrative contagion: Shiller's idea that a success story spreads from person to person like a virus, creating expectations and buying that push prices up.
FOMO: Fear of missing out: the fear of being left out while others profit, which pushes investors to buy late in a rally.
Herding: Investors imitating each other's trades instead of acting on their own information or analysis.
CAPE (Shiller P/E): The price of an index divided by the 10-year average of inflation-adjusted earnings; used to judge long-run over- or undervaluation.
Forward P/E: Price divided by analysts' expected earnings for the next year; sensitive to analyst optimism and bias.
Tobin's Q: Market value of a firm divided by the replacement cost of its assets; above 1 suggests overvaluation, below 1 undervaluation.
Price-to-Book (P/B): Market capitalization divided by the book value of equity; most useful for banks and industrial firms.
Financial Instability Hypothesis: Minsky's theory that long stable periods lead to rising leverage (hedge, speculative, Ponzi finance), which makes the financial system fragile.
Ponzi finance: A financing position in which income does not cover interest, so the borrower depends on rising asset prices to service the debt.
Displacement: The first stage of a bubble: a new technology or political change that creates new profit expectations.
Margin call: A lender's demand for extra collateral when the value of a leveraged position falls, often forcing sales.
Moral hazard: Taking or allowing excessive risk because someone else bears the cost, as with brokers issuing loans they did not have to keep.
Calendar anomaly: A systematic, predictable return pattern linked to the calendar, such as a month, day of the week or holiday.
January effect: Higher stock returns in January, especially for small caps, linked to tax-loss selling, window dressing and the disposition effect.
Tax-loss selling: Selling losing stocks before year-end to realise a capital loss that reduces taxes, which depresses their prices temporarily.
Window dressing: Fund managers selling losers and buying winners before a reporting date so that the portfolio looks better to clients.
Disposition effect: The tendency to sell winners too early and hold losers too long, avoiding the realisation of losses.
Turn-of-the-month effect: Higher returns on the last 3 to 4 trading days of a month and the first 3 days of the next month.
Halloween effect (Sell in May): The November to April period delivers far higher returns than the May to October period.
Day-of-the-week (weekend) effect: Systematically lower, on average negative, returns on Mondays and higher returns on Fridays.
Holiday effect: Unusually high returns on the trading day before a holiday.
Mood hypothesis: The idea that investor mood (for example lower on Mondays or in dark months) changes risk appetite and therefore prices.
Post-earnings announcement drift (PEAD): The tendency of prices to keep moving in the direction of an earnings surprise for 60 to 90 days, showing underreaction.