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Module 5 Slides (1)

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Module 5: The Capital Asset Pricing
Model
Written by
Mike Shin
The University of Sydney Business School
The University of Sydney
Page 1
Purpose of the Slides
1. These are supplementary slides to the modules.
2. Keep these as a reference and do not rely solely on them.
The University of Sydney
Page 2
Beta
– Before we continue where we left off in Module 4 on Portfolio Theory, it is
useful to introduce the concept of beta.
– Beta - Beta is a measure of a stock's market risk. It measures how sensitive
the stock is to market movements.
– We measure systematic risk or market risk with beta.
– The risk of a well-diversified portfolio depends on the market risk of the
stocks in the portfolio.
The University of Sydney
Page 3
Beta
– The formula for beta is:
πΆπ‘œπ‘£ π‘…π‘š , 𝑅𝑖
β𝑖 =
σ2π‘š
–
–
–
–
β𝑖 = Beta for stock i
π‘…π‘š = Returns for the market
𝑅𝑖 = Returns for stock i
σ2π‘š = Variance for the market
The University of Sydney
Page 4
Beta
– We interpret beta like this:
– Stocks with beta > 1 tend to amplify the overall movements of the
market
– Stocks with beta < 1 tend to dampen the overall movements of the
market
– Stocks with beta = 1 tend to move 1-1 with the market
The University of Sydney
Page 5
Beta
– We spent a lot of time on portfolios so can we use the same concept for
portfolios?
– Portfolio Beta - Portfolio beta measures the systematic risk of a portfolio,
just as beta for an individual stock measures the systematic risk of the stock.
The University of Sydney
Page 6
Beta
– Portfolio Beta (2 stocks)
β𝑝 = ω1 β1 + ω2 β2
–
–
–
–
–
β𝑝 = Portfolio beta
ω1 = Weight on stock 1
ω2 = Weight on stock 2
β1 = Beta of stock 1
β2 = Beta of stock 2
The University of Sydney
Page 7
Beta
– Portfolio Beta (2 stocks)
β𝑝 = ω1 β1 + ω2 β2 + β‹― + ω𝑛 β𝑛
– β𝑝 = Portfolio beta
– ω𝑖 = Weight on stock i
– β𝑖 = Beta of stock i
– That is, the portfolio beta is just the weighted average of all the
individual betas.
The University of Sydney
Page 8
CAPM
– The capital market line (CML) turns out to lead to the CAPM.
– The CAPM equation is:
𝐸𝑅𝑖 = π‘Ÿπ‘“ + β𝑖 πΈπ‘…π‘š − π‘Ÿπ‘“
–
–
–
–
πΆπ‘œπ‘£ π‘…π‘š , 𝑅𝑖
β𝑖 =
σ2π‘š
𝐸𝑅𝑖 = Expected return of stock i
π‘Ÿπ‘“ = Risk-free rate
β𝑖 = Beta for stock i
πΈπ‘…π‘š = Expected return of market
The University of Sydney
Page 9
CAPM
– The CAPM is a complete formula for finding the required rate of return.
– Why? Because we know π‘Ÿπ‘“ , β𝑖 , πΈπ‘…π‘š .
– Because it prices any asset, we call it the capital asset pricing model
(CAPM).
– Another interpretation of CAPM is:
π‘Ÿπ‘–π‘ π‘˜ π‘π‘œπ‘Ÿπ‘Ÿπ‘’π‘π‘‘π‘–π‘œπ‘› π‘“π‘œπ‘Ÿ π‘ π‘‘π‘œπ‘π‘˜ = β𝑖 ∗ π‘šπ‘Žπ‘Ÿπ‘˜π‘’π‘‘ π‘Ÿπ‘–π‘ π‘˜ π‘π‘Ÿπ‘’π‘šπ‘–π‘’π‘š
π‘…π‘’π‘žπ‘’π‘–π‘Ÿπ‘’π‘‘ π‘Ÿπ‘Žπ‘‘π‘’ π‘œπ‘“ π‘Ÿπ‘’π‘‘π‘’π‘Ÿπ‘› = π‘Ÿπ‘“ + π‘Ÿπ‘–π‘ π‘˜ π‘π‘œπ‘Ÿπ‘Ÿπ‘’π‘π‘‘π‘–π‘œπ‘› π‘“π‘œπ‘Ÿ π‘ π‘‘π‘œπ‘π‘˜
The University of Sydney
Page 10
CAPM
– What does this mean for the expected returns for a stock?
– Beta = 1 means 𝐸𝑅𝑖 = πΈπ‘…π‘š
– Beta = 0 means 𝐸𝑅𝑖 = π‘Ÿπ‘“
– Beta > 1 means 𝐸𝑅𝑖 > πΈπ‘…π‘š
– Beta < 1 means 𝐸𝑅𝑖 < πΈπ‘…π‘š
The University of Sydney
Page 11
CAPM
– We graph this relationship:
– The line is called the security market line (SML).
The University of Sydney
Page 12
CAPM
– Investors are rewarded for taking beta risk.
– If a stock has a higher beta that means the stock should return more on
average than a lower beta stock.
– The difference between the expected return implied by the CAPM and the
actual return of the stock is called alpha.
The University of Sydney
Page 13
Alpha
– How do we know how good a fund manager is?
– Alpha - Alpha is a measure of the skill or performance of an investment. It
is the difference between the expected return predicted by the CAPM and
the actual return of the investment.
– Alpha is also called abnormal return.
– When related to CAPM, it is also sometimes called Jensen's alpha.
The University of Sydney
Page 14
Alpha
– The formula for alpha is:
α = 𝐸𝑅 − π‘Ÿπ‘“ + β 𝐸(π‘…π‘š ) − π‘Ÿπ‘“
–
–
–
–
–
α = Alpha
𝐸𝑅 = Expected return of stock (or portfolio)
π‘Ÿπ‘“ = Risk-free rate
β = Beta of the stock (or portfolio)
πΈπ‘…π‘š = Expected return of market
The University of Sydney
Page 15
Alpha
– It is important to note that ER here is not the same as the CAPM expected
return but our best estimate using the actual returns of the investment.
– Thus, alpha is always calculated after returns have been realised.
The University of Sydney
Page 16
Alpha
– Alpha can also be positive, negative, or zero.
– Then a positive alpha implies that the investment is doing better than the
CAPM predicts. That is, the investment is generating more expected returns
while taking less risk.
– Similarly, a negative alpha implies that the investment is doing worse than
the CAPM predicts.
The University of Sydney
Page 17
Performance Evaluation
– A simple manner to evaluate the performance of an investment is to consider
its arithmetic and geometric average rate of return.
– The average return can be compared to a benchmark, such as an
appropriate market index or the median return of funds in a comparison
group.
– Risk-adjusted performance evaluation methods were proposed soon after
the Capital Asset Pricing Model (CAPM) theory was developed.
The University of Sydney
Page 18
Performance Evaluation
𝐸(𝑅𝑝 ) − π‘Ÿπ‘“
π‘†β„Žπ‘Žπ‘Ÿπ‘π‘’ π‘…π‘Žπ‘‘π‘–π‘œ =
σ𝑝
– 𝐸(𝑅𝑝 ) = Expected return of portfolio
– π‘Ÿπ‘“ = Risk-free rate
– σ𝑝 = Standard deviation of portfolio
π‘‡π‘Ÿπ‘’π‘¦π‘›π‘œπ‘Ÿ π‘…π‘Žπ‘‘π‘–π‘œ =
𝐸(𝑅𝑝 ) − π‘Ÿπ‘“
𝛽𝑝
– 𝛽𝑝 = Beta of portfolio
The University of Sydney
Page 19
Performance Evaluation
𝐽𝑒𝑛𝑠𝑒𝑛′ 𝑠 π‘Žπ‘™π‘β„Žπ‘Ž = 𝐸𝑅 − π‘Ÿπ‘“ + β 𝐸(π‘…π‘š ) − π‘Ÿπ‘“
–
–
–
–
𝐸𝑅 = Average return of portfolio
π‘Ÿπ‘“ = Risk−free rate
β = Beta of the portfolio
𝐸(π‘…π‘š ) = Expected return of market
The University of Sydney
Page 20
Performance Evaluation
Which measure is appropriate?
The University of Sydney
Page 21
CAPM in Practice
– Does the CAPM work? We can check using statistical techniques.
– Here, we will not require you to know how to run a regression, but just to
know the empirical facts about CAPM.
– Regression - Regression is a statistical tool to determine the best linear fit
between the data.
The University of Sydney
Page 22
CAPM in Practice
– The way we test CAPM is the following regression equation:
π‘Ÿπ‘– = α𝑖 + β𝑖 π‘Ÿπ‘š + ϡ𝑖
–
–
–
–
–
π‘Ÿπ‘– = Excess return of stock (or portfolio) i
α𝑖 = Alpha for stock (or portfolio) i
β𝑖 = Beta for stock (or portfolio) i
π‘Ÿπ‘š = Excess market return
ϡ𝑖 = Idiosyncratic risk for stock (or portfolio) i
The University of Sydney
Page 23
CAPM in Practice
– Investors are rewarded for taking beta risk.
– If a stock has a higher beta that means the stock should return more on
average than a lower beta stock.
– The difference between the expected return implied by the CAPM and the
actual return of the stock is called alpha.
The University of Sydney
Page 24
CAPM in Practice
– Because CAPM says that a stock's beta determines the expected return, a
test of the CAPM is to say that alpha is zero.
– Another graphical way to test the CAPM is to use portfolios. That is, we put
stocks with similar betas into a portfolio and see how well the portfolios do
in terms of average annual returns.
The University of Sydney
Page 25
CAPM in Practice
Beta-Sorted Portfolios from 1960-2017
The University of Sydney
Page 26
CAPM in Practice
– Here we see that while the CAPM is not perfect, portfolios do seem to line
up around the SML and that higher beta stocks tend to have higher
expected returns, which is exactly the prediction of the CAPM.
– To summarise the main facts on testing the CAPM:
– 1. CAPM seems to do fairly well
– 2. Other factors besides market beta seem to matter (like size and book
value)
– 3. There are measurement problems with testing the CAPM
The University of Sydney
Page 27
CAPM in Practice
–
–
–
–
Practical Issues with CAPM:
1. Estimating beta is very difficult
2. Finding the market portfolio is difficult
3. Determining expected returns is difficult
–
–
–
–
CAPM Assumptions:
1. Risk-free rate is actually risk-free
2. Investors can borrow and lend at the same rate
3. Markets and in equilibrium and are efficient
The University of Sydney
Page 28
APT
– Arbitrage Pricing Theory (APT) - APT is a model that relates a stock's
return to many different influences or "factors".
– APT makes different assumptions than the CAPM.
The University of Sydney
Page 29
APT
–
–
–
–
CAPM is derived through:
Investor preferences
Portfolio theory
Equilibrium condition
– APT:
– Assumes factors matter
– No-arbitrage condition
The University of Sydney
Page 30
APT
– Equilibrium - Equilibrium means that supply equals demand. This is a
theoretical concept that cannot be verified in real life.
– While we did not explicitly assume equilibrium, the theory behind CAPM
depends on equilibrium. We will not go too deep into the theory here, but
equilibrium can sometimes be a strong assumption.
– No Arbitrage Condition - The no-arbitrage condition just means that you
cannot make arbitrage profits.
The University of Sydney
Page 31
APT
– Factors are anything that may influence an asset's expected returns.
– Some examples of factors are (1) market factor, (2) size factor, (3) GDP
factor, and (4) book value factor.
The University of Sydney
Page 32
APT
– For 2 factors, the APT model is:
𝐸𝑅 = π‘Ÿπ‘“ + β1 π‘Ÿ1 + β2 π‘Ÿ2
𝐸𝑅 = Expected return of the stock
π‘Ÿπ‘“ = Risk-free rate
β1 = Beta for factor 1
β2 = Beta for factor 2
π‘Ÿ1 = Risk premium for factor 1
π‘Ÿ2 = Risk premium for factor 2
The University of Sydney
Page 33
APT
– For n-factors, the APT model is:
𝐸𝑅 = π‘Ÿπ‘“ + β1 π‘Ÿ1 + β2 π‘Ÿ2 + β‹― + β𝑛 π‘Ÿπ‘›
𝐸𝑅 = Expected return of the stock
π‘Ÿπ‘“ = Risk-free rate
β𝑖 = Beta for factor i
π‘Ÿπ‘– = Risk premium for factor i
The University of Sydney
Page 34
APT
– APT is not necessarily better or worse than CAPM. Like any model, it has its
advantages and disadvantages.
– Advantages:
– 1. Does not require equilibrium
– 2. Allows multiple sources of systematic risk
– Disadvantages:
– 1. No theoretical justification for factors
– 2. Having a linear relationship is restrictive
The University of Sydney
Page 35
The End
The University of Sydney
Page 36
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