BKM Chapter 12 Flashcards
Primary difference between traditional financial theory and behavioral finance theory
(BKM - 12)
traditional financial theory assumes investors are rational, behavioral finance theory does not
Complaint from behavioral financial theorists about traditional financial theory
(BKM - 12)
traditional financial theory ignores how people actually make decisions and that people make a difference (b/c investors do not always behave rationally)
Types of irrationalities under behavioral financial theory (2)
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- information processing errors
2. behavioral biases
Information processing errors
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mis-estimations of probabilities of events or the associated ROR
Behavioral biases
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investors often make inconsistent, sub-optimal, or otherwise irrational decisions
Types of information processing errors (4)
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- forecasting errors
- overconfidence
- conservatism
- sample size neglect & representativeness bias
Forecasting errors (aka memory bias) information processing error & related phenomenon explained
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tendency to give too much weight to recent experience compared to prior beliefs when making forecasts
> > may explain why high P/E ratio firms perform worse than low P/E ratio firms
Overconfidence information processing error & related phenomenon explained
(BKM - 12)
investors overestimate their ability to accurately predict stock returns
> > may explain popularity of active portfolio management despite underperformance
Conservatism information processing error & related phenomenon explained
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investors may be too slow to update beliefs in response to new information
> > may explain the momentum effect if investors are slow to recognize news
Sample size neglect & representativeness bias information processing error & related phenomenon explained
(BKM - 12)
investors may not account for sample size & treat small samples as though they are equally representative compared to large samples (e.g. infer patterns too quickly and extrapolate them too far into the future)
> > consistent with overreaction & correction anomalies
Types of behavioral biases (5)
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- framing
- mental accounting
- regret avoidance
- affect
- prospect theory
Framing behavioral bias
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decisions are impacted by how choices are framed
> > risky gains are more likely to be rejected compared to risky losses
Mental accounting behavioral bias
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investors differentiate decision making based on different goals that may elicit different levels of risk aversion
ex: standard brokerage account vs. child’s education fund
Anomalies that may be explained by the mental accounting behavioral bias (2)
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- disposition effect
- momentum in stock prices - more willing to invest more when they are ahead because the funds are viewed as coming from capital gains vs. out of pocket
Regret avoidance behavioral bias and anomalies explained (2)
(BKM - 12)
investors feel more regret when less convential investments go bad (b/c it reflects bad decision making vs. bad luck)
> > may explain:
- small firm effect
- high book-to-market ratio effect
Affect behavioral bias
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feeling of “good” or “bad” that investors may attach to a stock
Examples of affect behavioral bias (3) and trend in prices and ROR
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- public perception of socially responsible policies
- attractive working conditions
- popular products
generally see increased prices and lower ROR
Prospect theory behavioral bias and findings (2)
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alternative view of relationship b/w wealth and risk aversion that plots utility against changes in wealth and finds:
- risk aversion does not decrease as wealth increases
- investors are risk-seeking regarding losses
Traditional relationship between utility, wealth, and risk aversion
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utility increases at a decreasing rate as wealth increases»_space; leads to higher risk aversion
Reason that mis-pricing from behavioral biases does not lead to arbitrage opportunities under behavioral finance theory
(BKM - 12)
b/c of the limits to arbitrage
Limits to arbitrage under behavioral finance theory (3)
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- fundamental risk
- implementation costs
- model risk
Fundamental risk limit to arbitrage
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risk of under-pricing becoming worse in the short-term when buying an under-priced stock
(e.g. price does not converge to it’s intrinsic value within the investment horizon)
Implementation cost limit to arbitrage & examples (3)
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possible to profit from short-selling when securities are over-priced, but high costs of short-selling can be a barrier
Ex:
- high cost to borrow shares
- short-selling may not be possible due to trading restrictions
- shares may not even be available to short
Model risk limit to arbitrage
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risk that the model used to identify mis-priced securities is flawed
> > makes exploiting arbitrage opportunities risky
Examples of limits to arbitrage and the Law of One Price (3)
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- Siamese twin companies - merged operations that should have similar prices
- equity carve-outs - spinoffs/separations that should have similar prices
- closed-end funds - pooled assets that often sell at premiums/discounts from net asset value
Criticisms of behavioral finance theory (2)
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- anomalies are inconsistent between types of irrationality - suggest overfitting of behavioral biases to anomalies
- difficult to assess the statistical significance of results
Relationship between technical analysis and behavioral finance (2)
(BKM - 12)
technical analysis relies on identifying momentum in stock prices and momentum can be explained by behavioral biases
- disposition effect - creates momentum because investors are not acting rationally
- overconfident investors trade more - increased trading volume is seen as an indicator of positive returns
Disposition effect
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tendency to hold on to losing investments because investors do not want to realize losses
Market indicators used in technical analysis to identify profit opportunities (3)
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- moving averages (MA)
- relative strength
- breadth
Moving average (MA) market indicator in technical analysis and relationship between MA and current stock price
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measures the overall trend/momentum of a security
= avg prior n days of stock prices
MA > current price when prices are consistently falling
MA < current price when prices are consistently rising
Bullish signal in moving averages
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shift from a falling trend to a rising trend (= buy signal)
graphically: current stock price pierces MA from below
Bearish signal in moving averages
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shift from a rising trend to a falling trend (= sell signal)
graphically: current stock prices pierces MA from above
Relative strength market indicator in technical analysis, formula, & buy signal
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measures how well an individual stock performs relative to the market
relative strength = individual stock price / market index for the same industry
buy signal = consistently increasing ratio (indicates market strength)
Breadth market indicator in technical analysis, formula, & buy signal
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extent movement in a market index is reflected in the price movement of all socks
breadth = # market advancers (stock price increases) - # market decliners (stock price decreases)
buy signal = positive trends
Market sentiment
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general level of optimism among investors
Market sentiment indicators (3)
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- Trin statistic
- confidence index
- Put/Call ratio
Trin statistic definition, formula, & buy signal
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measure of the extent trading volume is associated with market movement
Trin = (volume declining / # declining) / (volume advancing / # advancing)
buy signal: trin < 1 (indicates higher volume of advancing vs. declining stocks)
sell signal: trin > 1
Confidence index definition, formula, & buy signal
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measures how well lower-rated corporate bonds perform relative to higher-rated corporate bonds
confidence index = avg. yield on top 10 rated corporate bonds / avg. yield on 10 intermediate-grade corporate bonds
buy signal: ratio trending towards 1 (suggests a lower risk premium is required for lower-rated bonds)
Put/Call ratio definition, formula, & buy signal
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measures extent investors are betting on stock price decreases relative to stock price increases
put/call ratio = # outstanding puts / # outstanding calls
intuitively, buy signal = decreasing put/call ratio (more bets on price increases), but consensus is mixed
