Week Seven Lecture Notes PDF

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Chapter Twelve: Behavioral Analysis and Technical Analysis    

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Schiller (1987) o Showed that there was a 6% growth in the S&P 500 from 1926 to present There is price volatility though ^ compared to the actual value Behavioral Finance: Is the psychology of markets TEST Behavioral Finance versus Conventional Finance: o Conventional Finance: Prices are correct and equal to intrinsic value, resources are allocated efficiently, consistent with EMH (efficient market hypothesis) o Behavioral Finance: What if investors don’t behave rationally? The Behavioral Critique o Two categories of irrationalities:  1. Investors do not always process information correctly  2. Even when given a probability distribution of returns, investors may make inconsistent or suboptimal decisions Errors in Information Processing: Misestimating True Probabilities o 1. Forecasting Errors: Too much weight is placed on recent experiences o 2. Overconfidence: Investors overestimate their abilities and the precision of their forecasts o 3. Conservatism: Investors are slow to update their beliefs and under react to new information o 4. Sample Size Neglect and Representativeness: Investors are too quick to infer a pattern or trend from a small sample Behavioral Biases: Examples o 1. Framing: How the risk is described, “risky losses” vs “risky gains” can affect investor decisions o 2. Mental Accounting: Investors may segregate accounts or monies and take risks with their gains that they would not take with their principal o 3. Regret Avoidance: Investors blame themselves more when an unconventional or risky bet turns out badly o 4. Prospect Theory  Conventional View: Utility depends on level of wealth  Behavioral View: Utility depends on changes in current wealth Limits to Arbitrage o Behavioral biases would not matter if rational arbitrageurs could fully exploit the mistakes of behavioral investors o Fundamental Risk  “Markets can remain irrational longer than you can be remain solvent”  Intrinsic value and market value may take too long to converge o Implementation Costs  Transaction costs and restrictions on short-selling can limit arbitrage activity

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o Model Risk  What if you have a bad model and the market value is correct? Limits to Arbitrage and the Law of One Price o Siamese Twin Companies o Equity Carve-outs  3Com and Palm  Arbitrage limited by availability of shares for shorting o Closed-end funds  May sell at premium or discount to NAV Bubbles and Behavioral Economics o Bubbles are easier to spot after they end  Dot-com bubble  Housing bubble  Kindleberger (MIT)-Manias, Panics, and Crashes  Hits an apex, and people start to lose money, the apex is the mania, the beginning of the drop is the panic, and the end is the crash  The key thing is timing, “buy low, sell high” the issue is people are not doing that  When you get that excess liquidity, each subsequent bubble takes more liquidity.  Markets go to bubbles when there is excess liquidity in the system Technical Analysis and Behavioral Finance o Technical analysis attempts to exploit recurring and predictable patterns in stock prices o Disposition effect: The tendency of investors to hold on to losing investmentsFinal  Demand for shares depends on price history  Can lead to momentum in stock prices, if something is going up it continues to go up  Once a stock breaks below the noise level, is get out, take the loss and reevaluate, do not hold on Technical Analysis: Trends and Corrections o Momentum and moving averages  The moving average is the average level of prices over a given interval of time, where the interval is updated as time passes  Bullish signal: Market price breaks through the moving average line from below, it is time to buy  Bearish signal: When prices fall below the moving average, it is time to sell  By taking the blue line from the moving average, you are able to separate the noise Technical Analysis: Relative Strength

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o Relative Strength  Measures the extent to which a security has out- or underperformed either the market or its industry  Relative Strength= Security Price/Industry Price Index  Pricing ratio implies outperformance o Breadth: Often measured as the spread between the number of stocks that advance and decline in price Technical Analysis: Sentiment Indicators o Trin statistic  Trin=Volume declining/number declining/Volume advancing/number advancing  Numbers over 1.0 are bearish o Confidence Index  The ratio of the average yield on 10 top-rated corporate bonds divided by the average yield on 10 intermediate-grade corporate bonds  Higher values are bullish o Put/Call Ratio  A rising ratio might indicate pessimism  A lower ratio points to optimism

Chapter Thirteen: Empirical Evidence on Security Returns 

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Capital Asset Pricing Models consist of two parts: o 1. Optimal P derivation based on risk tolerance and input list o 2. Derive predictions about expected returns in equilibrium Measurement Error in Beta o Problem: If Beta is measured with error, then the slope coefficient of the regression equation will be biased downward and the intercept biased upward o Solution: Construct P with large dispersion of beta. Then, by ranking them, they yield insightful Summary of CAPM Tests o 1. Expected rates of return are linear and increase with beta, the measure of systematic risk o 2. Expected rates of return are not affected by nonsystematic risk Early versions of the Multifactor Model o Chen, Roll and Ross 1986 o Growth rate in industrial population o Changes in expected inflation o Unexpected inflation o Unexpected changes in risk premiums on bonds o Unexpected changes in term premium on bonds Fama-French-Type Factor Models o Size and book-to-market ratios explain returns on securities

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o High book to market firms experience higher returns (value style). o Smaller firms experience higher returns o FF quantifies the size risk premium  Size and value are priced risk factors, consistent with APT Risk-based Interpretations o Liew and Vassalou  Style seems to predict GDP growth and relate to the business cycle o Petkova and Zhang  When the economy is expanding, growth beta > value beta  When the economy is in recession, value beta > growth beta Behavioral Explanations for Value Premium o “Glamour firms” are characterized by recent good performance, high prices, and lower book-to-market ratios o High prices reflect excessive optimism plus overreaction and extrapolation of good news Momentum: A fourth factor o The original Fama-French model augmented with a momentum factor has become a common four-factor model used to evaluate abnormal performance of a stock portfolio o Winners minus losers (WML)-winners/losers based on past returns o Markets go through cycles, where each style or philosophies are going to go in and out of favor, it is not going to work for all seasons, therefore, styles will have to switch o Try to isolate momentum and define it, and understand how to use it o True: Momentum worksFINAL TEST QUESTION Liquidity and Asset Pricing o Liquidity involves  Trading costs  Ease of sale  Necessary price concessions to affect a quick transaction  Market depth  One of the links that connects the black swan event, these are absences of liquidity vehicles Equity Premium Puzzle o The returns of taking risk are too high or the risk pricing is too lowTest question Survivorship Bias o Estimating risk premiums from the most successful country and ignoring evidence from stock markets that did not survive for the full sample period with impart an upward bias in estimates of expected returns...