Ok, apologies for the long post. But given the lack of practice questions in CFAI readings on behavioral finance, I made some outline notes of the main points based on LOS. Have pasted below in case anyone may find them useful
1. Heuristic-driven bias
1.1. Representativeness
Reliance on stereotypes
Tendency to base predictions on how representative something seems to be
1.2. Overconfidence
Setting confidence intervals too narrowly
Overconfident people tend to get surprised more frequently than anticipated
1.3. Anchoring and adjustment
Failure to fully incorporate new information into expectations
Earnings estimates not revised enough in response to new information
Results in analysts getting surprised repeatedly
1.4. Aversion to ambiguity
The unwillingness to go into the abyss
Rather take the sure bet than the uncertain bet with a potentially better outcome
2. Frame dependence
2.1. Loss aversion
People would rather take a gamble between a big loss and no loss rather than a certain small loss
Leads to investors holding onto loss-making investments in a gamble that they will regain value and they will not need to realize loss
2.2. Self-control
Source of the “don’t dip into capital rule”
Investors with this frame dependence prefer dividend-paying stocks because they believe it will control the urge to dip into capital. Such investors fear outliving their savings
2.3. Regret Minimization
Can lead investors to prefer dividend paying stocks. Allows them to finance consumption out of dividends rather than selling stock. If stock subsequently rises, they feel regret.
Selecting sub-optimal allocations for fear of future regret. Example: Markowitz
2.4. Money illusion
Tendency not to adjust for inflation
Someone who receives 5% pay rise with 4% inflation is regarded as better off than someone who receives 2% pay rise with 0% inflation
3. Inefficient markets
3.1. Effects stemming from representativeness
Investors become too optimistic about past winners and too pessimistic about past losers
Results in better future returns for past losers as these become undervalued
3.2. Effects stemming from conservatism (anchoring and adjustment)
Conservatism results in earnings estimates not being revised enough in response to new information
3.3. Effects stemming from frame dependence
Myopic loss aversion caused investors to shy away from stocks in the past, creating conditions for them to be able to outperform bonds by 7% in real terms
3.4. Effects stemming from overconfidence
Overconfident Investors take bad bets because they fail to recognize when they are at an informational disadvantage
Overconfident investors trade too frequently
4. Portfolios, pyramids, emotions and biases
4.1. Influence of hope and fear
Fear causes investors to look at things from the bottom up and ask how bad things can get
Hope causes people to look at things from the top down and emphasizes the need for potential on the upside
4.2. Pyramid systems to address security, potential and aspiration
Bottom layer of pyramid addresses security. Includes money market funds and CDS
Middle layer addresses potential and includes bonds. Includes use of zero-coupon bonds to fund things like college education
Top layer addresses aspirations and includes stocks needed for appreciation
Five-year rule: Don’t put money into stocks if you are less than five years from your goal
4.3. Effects of regret and self-attribution bias on financial advisor relationships
Financial advisor gives investor a psychological call option. Can blame advisor and avoid regret if things go well, but can claim the credit and attribute success to personal skills when things go right
4.4. Effect of overconfidence on portfolio construction
Overconfident investors fail to diversify because they are convinced that they can pick winners
Widespread naïve diversification using the 1/n rule
5. Investment decision making in defined contribution pension plans
5.1. Why DC plan participants create inefficient portfolios
5.1.1. Little or no investment knowledge
Only 20% of DC investors consider themselves knowledgeable
5.1.2. Bounds to rationality, self-control and self-interest
5.1.2.1. Bounded rationality
Limits on intelligence and time mean that individuals cannot solve problems optimally
Instead they use rules of thumbs (“heuristics”) to drive investment decisions
5.1.2.2. Bounded self-control
Even when the right thing to do is apparent, people may not do it (analogy with not exercising)
5.1.2.3. Bounded self-interest
People do not pursue their own self interest to the extent assumed
5.1.3. Impacts of status quo bias, loss aversion, 1/n diversification and the endorsement effect
5.1.3.1. Status quo bias
Empirical research suggests most plan participants never make any changes
5.1.3.2. Myopic loss aversion
Plan participants shown 1-year returns make much lower allocation to stocks than those shown 30-yr compound returns since the latter are much less likely to show loss
5.1.3.3. 1/n diversification
Strong tendency to allocate equally between funds on offer
5.1.3.4. Endorsement effect
Plan participants assume that the funds on offer are implicit guidance on what allocation to adopt. May lead to 1/n diversification
5.1.4. Why do DC plan participants invest heavily in own company stock?
Employees tend not to view their companies as risky as they prefer to “invest in the familiar”
Similar to “home country bias” in many portfolios
6. Folly of forecasting
6.1. Illusions of knowledge and control
Illusion of knowledge: economist and analysts think they know more than everyone else
Empirical evidence suggests investment professionals are more confident in their forecasting than the general public
Analysts cite “detailed knowledge”, “experience” and “hard work” as factors behind their forecasts. Points to an illusion of control
The worst forecasters tend to be the most overconfident ones
6.2. Ego defense mechanisms
Forecasters exhibit strong evidence of conservatism bias – tendency to hang onto views for too long
Five common defenses:
The “if” only defense: They would have been correct if original advice had been followed
The “ceteris parebus” defense: Something else out of the ordinary occurred
The “I was almost right” defense
The “It just hasn’t happened yet” defense
“Single prediction defense”: Framework was right even though forecast was wrong. The “forecasting is pointless defense”
6.3. Why are forecasts still used
Investors feel that in order to outperform, they need insight that others don’t have
Anchoring: tendency to latch unto irrelevant information
7. Survey of behavioral finance
7.1. Critique of classic observation that rational agents will undo mispricing
Strategies to exploit mispricing can be risky and costly, allowing the mispricing to remain unchallenged
7.2. “There is no free lunch” and “prices are right”
“There is no free lunch” can be true in efficient and inefficient markets
“Prices are right” is only true in an efficient market
“Prices are right” implies “No free lunch” but not vice versa
7.3. Risks and costs associated with arbitrage
7.3.1. Fundamental risk
Risk that bad news about fundamental value causes further adverse price movements.
Can try to hedge with offsetting position in similar security, but substitute securities are never perfect
If the R-squared on a regression of stock returns on substitute securities is greater than 25%, then the hedge is almost perfect
7.3.2. Noise trade risk
Risk that noise traders (e.g. pessimistic investors in a perceived undervalued stock) continue to push the stock down and make the mispricing worse
If mispricing that the arbitrageur is trying to exploit worsens, short-term oriented investors may conclude he is incompetent or lenders could require higher margin and lead to forced selling. Makes arbitrageur more cautious from the start
7.3.3. Implementation costs
Transaction costs can make it unattractive to exploit mispricing
Cost of finding a mispricing can be substantial
7.3.4. Sufficient conditions for arbitrage to be limited
7.3.4.1. If no perfect substitute:
Arbitrageurs are risk averse. Ensures no single arbitrageur can wipe out mispricing
Fundamental risk is systematic in that it can’t be eliminated by taking many substitute positions. Ensures that large number of smaller investors cannot wipe out mispricing.
7.3.4.2. If a perfect substitute exists:
Arbitrageurs are risk averse and have a short-term horizon. Ensures that mispricing cannot be wiped out by a single arbitrageur
Noise trader risk is systematic. Ensures that even a large number of small investors cannot eliminate the mispricing.
7.3.5. Evidence
7.3.5.1. Royal Dutch and Shell
Ratio of Royal Dutch and Shell should have been 1.5 throughout, but this has not always the case historically.
8. Alpha hunters and Beta grazers
8.1. Chronic versus acute inefficiencies
Acute inefficiencies can be arbitraged away
Chronic inefficiencies are less discernable and more resistant to resolution
8.1.1. Convoy behavior
Herding or clustering behavior of institutional funds
Critical mass of investors can form a pricing consensus that becomes a de facto reality even if it is erroneous
8.1.2. Bayesian rigidity
Extreme case of anchoring and conservatism
8.1.3. Price target revisionism
Tendency to revise price targets higher when they have been achieved rather than close out the position
8.1.4. Ebullience cycle
Tendency to leave envelope unopened when things are going bad
Tendency to open envelopes in up market, creating ebullient atmosphere and even more aggressive investment
8.2. Rebalancing behavior
8.2.1. Holders: Effectively reduce equity allocation in falling markets. Little market impact
8.2.2. Rebalancers: Have a smoothing effect
8.2.3. Valuators: Includes both contrarians and momentum strategists. Contrarians have moderating impact on market trends while momentum strategists magnify them
8.2.4. Shifters: Shift in allocations due to fundamental change in circumstances.
1. Heuristic-driven bias
1.1. Representativeness
Reliance on stereotypes
Tendency to base predictions on how representative something seems to be
1.2. Overconfidence
Setting confidence intervals too narrowly
Overconfident people tend to get surprised more frequently than anticipated
1.3. Anchoring and adjustment
Failure to fully incorporate new information into expectations
Earnings estimates not revised enough in response to new information
Results in analysts getting surprised repeatedly
1.4. Aversion to ambiguity
The unwillingness to go into the abyss
Rather take the sure bet than the uncertain bet with a potentially better outcome
2. Frame dependence
2.1. Loss aversion
People would rather take a gamble between a big loss and no loss rather than a certain small loss
Leads to investors holding onto loss-making investments in a gamble that they will regain value and they will not need to realize loss
2.2. Self-control
Source of the “don’t dip into capital rule”
Investors with this frame dependence prefer dividend-paying stocks because they believe it will control the urge to dip into capital. Such investors fear outliving their savings
2.3. Regret Minimization
Can lead investors to prefer dividend paying stocks. Allows them to finance consumption out of dividends rather than selling stock. If stock subsequently rises, they feel regret.
Selecting sub-optimal allocations for fear of future regret. Example: Markowitz
2.4. Money illusion
Tendency not to adjust for inflation
Someone who receives 5% pay rise with 4% inflation is regarded as better off than someone who receives 2% pay rise with 0% inflation
3. Inefficient markets
3.1. Effects stemming from representativeness
Investors become too optimistic about past winners and too pessimistic about past losers
Results in better future returns for past losers as these become undervalued
3.2. Effects stemming from conservatism (anchoring and adjustment)
Conservatism results in earnings estimates not being revised enough in response to new information
3.3. Effects stemming from frame dependence
Myopic loss aversion caused investors to shy away from stocks in the past, creating conditions for them to be able to outperform bonds by 7% in real terms
3.4. Effects stemming from overconfidence
Overconfident Investors take bad bets because they fail to recognize when they are at an informational disadvantage
Overconfident investors trade too frequently
4. Portfolios, pyramids, emotions and biases
4.1. Influence of hope and fear
Fear causes investors to look at things from the bottom up and ask how bad things can get
Hope causes people to look at things from the top down and emphasizes the need for potential on the upside
4.2. Pyramid systems to address security, potential and aspiration
Bottom layer of pyramid addresses security. Includes money market funds and CDS
Middle layer addresses potential and includes bonds. Includes use of zero-coupon bonds to fund things like college education
Top layer addresses aspirations and includes stocks needed for appreciation
Five-year rule: Don’t put money into stocks if you are less than five years from your goal
4.3. Effects of regret and self-attribution bias on financial advisor relationships
Financial advisor gives investor a psychological call option. Can blame advisor and avoid regret if things go well, but can claim the credit and attribute success to personal skills when things go right
4.4. Effect of overconfidence on portfolio construction
Overconfident investors fail to diversify because they are convinced that they can pick winners
Widespread naïve diversification using the 1/n rule
5. Investment decision making in defined contribution pension plans
5.1. Why DC plan participants create inefficient portfolios
5.1.1. Little or no investment knowledge
Only 20% of DC investors consider themselves knowledgeable
5.1.2. Bounds to rationality, self-control and self-interest
5.1.2.1. Bounded rationality
Limits on intelligence and time mean that individuals cannot solve problems optimally
Instead they use rules of thumbs (“heuristics”) to drive investment decisions
5.1.2.2. Bounded self-control
Even when the right thing to do is apparent, people may not do it (analogy with not exercising)
5.1.2.3. Bounded self-interest
People do not pursue their own self interest to the extent assumed
5.1.3. Impacts of status quo bias, loss aversion, 1/n diversification and the endorsement effect
5.1.3.1. Status quo bias
Empirical research suggests most plan participants never make any changes
5.1.3.2. Myopic loss aversion
Plan participants shown 1-year returns make much lower allocation to stocks than those shown 30-yr compound returns since the latter are much less likely to show loss
5.1.3.3. 1/n diversification
Strong tendency to allocate equally between funds on offer
5.1.3.4. Endorsement effect
Plan participants assume that the funds on offer are implicit guidance on what allocation to adopt. May lead to 1/n diversification
5.1.4. Why do DC plan participants invest heavily in own company stock?
Employees tend not to view their companies as risky as they prefer to “invest in the familiar”
Similar to “home country bias” in many portfolios
6. Folly of forecasting
6.1. Illusions of knowledge and control
Illusion of knowledge: economist and analysts think they know more than everyone else
Empirical evidence suggests investment professionals are more confident in their forecasting than the general public
Analysts cite “detailed knowledge”, “experience” and “hard work” as factors behind their forecasts. Points to an illusion of control
The worst forecasters tend to be the most overconfident ones
6.2. Ego defense mechanisms
Forecasters exhibit strong evidence of conservatism bias – tendency to hang onto views for too long
Five common defenses:
The “if” only defense: They would have been correct if original advice had been followed
The “ceteris parebus” defense: Something else out of the ordinary occurred
The “I was almost right” defense
The “It just hasn’t happened yet” defense
“Single prediction defense”: Framework was right even though forecast was wrong. The “forecasting is pointless defense”
6.3. Why are forecasts still used
Investors feel that in order to outperform, they need insight that others don’t have
Anchoring: tendency to latch unto irrelevant information
7. Survey of behavioral finance
7.1. Critique of classic observation that rational agents will undo mispricing
Strategies to exploit mispricing can be risky and costly, allowing the mispricing to remain unchallenged
7.2. “There is no free lunch” and “prices are right”
“There is no free lunch” can be true in efficient and inefficient markets
“Prices are right” is only true in an efficient market
“Prices are right” implies “No free lunch” but not vice versa
7.3. Risks and costs associated with arbitrage
7.3.1. Fundamental risk
Risk that bad news about fundamental value causes further adverse price movements.
Can try to hedge with offsetting position in similar security, but substitute securities are never perfect
If the R-squared on a regression of stock returns on substitute securities is greater than 25%, then the hedge is almost perfect
7.3.2. Noise trade risk
Risk that noise traders (e.g. pessimistic investors in a perceived undervalued stock) continue to push the stock down and make the mispricing worse
If mispricing that the arbitrageur is trying to exploit worsens, short-term oriented investors may conclude he is incompetent or lenders could require higher margin and lead to forced selling. Makes arbitrageur more cautious from the start
7.3.3. Implementation costs
Transaction costs can make it unattractive to exploit mispricing
Cost of finding a mispricing can be substantial
7.3.4. Sufficient conditions for arbitrage to be limited
7.3.4.1. If no perfect substitute:
Arbitrageurs are risk averse. Ensures no single arbitrageur can wipe out mispricing
Fundamental risk is systematic in that it can’t be eliminated by taking many substitute positions. Ensures that large number of smaller investors cannot wipe out mispricing.
7.3.4.2. If a perfect substitute exists:
Arbitrageurs are risk averse and have a short-term horizon. Ensures that mispricing cannot be wiped out by a single arbitrageur
Noise trader risk is systematic. Ensures that even a large number of small investors cannot eliminate the mispricing.
7.3.5. Evidence
7.3.5.1. Royal Dutch and Shell
Ratio of Royal Dutch and Shell should have been 1.5 throughout, but this has not always the case historically.
8. Alpha hunters and Beta grazers
8.1. Chronic versus acute inefficiencies
Acute inefficiencies can be arbitraged away
Chronic inefficiencies are less discernable and more resistant to resolution
8.1.1. Convoy behavior
Herding or clustering behavior of institutional funds
Critical mass of investors can form a pricing consensus that becomes a de facto reality even if it is erroneous
8.1.2. Bayesian rigidity
Extreme case of anchoring and conservatism
8.1.3. Price target revisionism
Tendency to revise price targets higher when they have been achieved rather than close out the position
8.1.4. Ebullience cycle
Tendency to leave envelope unopened when things are going bad
Tendency to open envelopes in up market, creating ebullient atmosphere and even more aggressive investment
8.2. Rebalancing behavior
8.2.1. Holders: Effectively reduce equity allocation in falling markets. Little market impact
8.2.2. Rebalancers: Have a smoothing effect
8.2.3. Valuators: Includes both contrarians and momentum strategists. Contrarians have moderating impact on market trends while momentum strategists magnify them
8.2.4. Shifters: Shift in allocations due to fundamental change in circumstances.
