Quiz 2 Flashcards
What is the purpose of an efficient frontier?
- To maximize diversification and utility
- Non-systematic risk can be diversified out with greater than 20 securities
- E(r) of the diversified portfolio is the same as an individual asset
Process for efficient Frontier
- Find the scenarios: Probabilities that each will occur
- Find the average E(r) for each of the assets using each scenario
- Find the standard deviation of the expected returns
- Find the Cov(rS,rB)
- Find the correlation Coefficient
- -1<= row <= 1 : 1 -> Perfectly correlated -1 -> perfectly negatively correlated 0 -> not correlated
- 3 Rules :
Expected Returns
Excess Returns
Variance - Efficient frontier is finding the combination of different portfolios that push the curve toward Nirvana
CAPM Assumptions
- All assets can be traded
- All info is publicly available
- No taxes on returns
- No transactions costs that limit trading
- Unlimited borrowing/ borrowing at risk free rate
- All investors are the same
- —– Have a one period
- —– All are rational / mean variance optimizers
- —– All have homogeneous expectations about risks and returns
Issues with Estimating Beta
- Hypothesis that premium for Beta is the same as the market risk premium is typically rejected
- —- Problem 1) true market portfolio is not fully tradable and therefore can’t be measured
- —- Problem 2) Beta are very difficult to precisely estimate and/or they may change over time
- —- Problem 3) Risks other than the sensitivity to the market portfolio may matter to investors
- There is evidence that other variables impact Beta : B/M, P/E, Prior Returns, liquidity
- —- These variables may capture risks that are important to investors
- —- These variables capture market under reactions, over reactions, or non efficient information
Fama-French 3 factor model
E(r) are determined by exposure to the market portfolio as well as additional risk factors
- B/M and Market Cap predict returns
- Stocks with similar B/M ratios or market cap have returns that move together
Pros and Cons of multi-factor models
- Multi-factor requires predictions of future values so there is less certainty
- when considering past returns, multi-factor is better because if accounts for all relevant risks
Efficient Market Hypothesis
- Information about past events should not be useful for predicting changes in price; Price changes should reflect new information
Weak form efficiency
Post Market Data
Semi strong form efficiency
All public information
Strong form
All public information and private information
Against EMH
- Anomalies disappear once they are discovered
- Results that persist are likely due to risk; could reflect investor behavior
Overconfidence
- Excessive trading tends to decrease returns
- S&P500 index beats most returns long term
- Men are less risk averse than women
- —-Investors do not always process information correctly
- —-Investors make inconsistent or sub-optimal decisions
How might investors process information correctly
- Conservatism - Investors are too slow in updating beliefs
- Might also apply to institutional investors - they may be more skeptical about new information
- sample size neglect and representatives
- —- People tend to believe that small sample of outcomes is representative of the population
- —- Momentum and reversal: maybe investors are initially slow to update beliefs, but then over react
how might they make sub-optimal decisions even if they correctly process information
- Anchoring/priming
- Nudges
- Framing
- Mental Accounting
- Loss Aversion
Prospect Theory
Investor utility depends on gains/ losses from starting position
— (10% gain yields less satisfaction than -10% losses yield less satisfaction)
Sunshine is strongly correlated to stock returns
- Gains don’t outweigh trading costs
