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1
Introduction This text presents proofs of the CAP model.
Note that footnotes, e.g., [2] can be viewed by clicking them. 2 The CAP-model This section presents a
derivation of the capital asset pricing model (CAPM). The CAP-model is a
ceteris paribus model. It is only valid within a special set of assumptions.
They are: ·
Investors are risk averse individuals who maximize the expected
utility of their end of period wealth. Implication: The model is a one
period model. ·
Investors have homogenous expectations (beliefs) about asset returns.
Implication: all investors perceive identical opportunity sets. This is,
everyone have the same information at the same time. ·
Asset returns are distributed by the normal distribution. ·
There exists a risk free asset and investors may borrow or lend
unlimited amounts of this asset at a constant rate: the risk free rate (kf).
·
There is a definite number of assets and their quantities are fixed
within the one period world. ·
All assets are perfectly divisible and priced in a perfectly
competitive marked. Implication: e.g. human capital is non-existing (it is
not divisible and it can’t be owned as an asset). ·
Asset markets are frictionless and information is costless and
simultaneously available to all investors. Implication: the borrowing rate
equals the lending rate. ·
There are no market imperfections such as taxes, regulations, or
restrictions on short selling. Step 1.
The derivation of the CAP-model starts by assuming that all assets are
stochastic and follow a normal distribution. This distribution is described
completely by its two parameters: mean value (m) and variance (s2). The mean value is a measure of location among many such as median
and mode. Likewise, the variance value is a measure of dispersion among many such as range, semiinterquartile range,
semivariance, mean absolute deviation (For definitions of the
mentioned measures of location and dispersion, see Copeland and Weston
[1988, pages 146-153]). In
the hypothetical world of the CAPM theory all that the investor bothers
about is the values of the normal distribution. In the real world asset
return are not normally distributed and investors do find other measures of location and dispersion relevant.
However, the assumption may be seen as a reasonable approximation and it is
needed in order to simplify matters. As a result the mean and the
variance of an asset X is defined as:
and the covariance and the
correlation coefficient between two assets X and Y are:
where pi is the probability of a
random event Xi, and N is the total number of events. |
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Some mean and varians properties can be
derived[2]: Property 1: E[X + c] = E[X] + c Property 2: E[cX] = cE[X] Property 3: VAR[X + c] = VAR[X] Property 4: VAR[cX] = c2VAR[X] where c is a constant. Consider
a portfolio of two risky assets, X and Y with a % in asset X and (1- a) % in asset Y. They are both normally
distributed. The return on this portfolio (using property 1 and 2) is: mp =
E[kp] = E[aX + (1- a)Y] = E[aX] + E[(1- a)Y] = aE[X] + (1- a)E[Y] (3) and the varians on this portfolio is: s2p = VAR[Rp] = E[(kp - E[kp])2]
= E[({aX + (1- a)Y} - E[aX + (1- a)Y])2] (using property 2)
= E[({aX + (1- a)Y} - {aE[X] + (1- a)E[Y]})2]
= E[({aX - aE[X]} + {(1- a)Y - (1- a)E[Y]})2]
= E[(a{X - E[X]} + (1- a){Y - E[Y]})2]
= E[a2(X - E[X])2 + (1- a)2(Y - E[Y])2 + 2a(1- a)(X - E[X])(Y - E[Y])] (using property 2)
= a2E[(X - E[X])2]+ (1- a)2 E[(Y - E[Y])2]+ 2a(1- a)E[(X - E[X])(Y - E[Y])] (using property 4)
= a2VAR[X]+ (1- a)2VAR[Y]+ 2a(1- a)COV[X,Y]
= a2VAR[X]+ (1- a)2VAR[Y]+ 2a(1- a) rxy sxsy (4) Very important the equations (1)
- (4) demonstrate the concept of portfolio diversification. In general it is
true that VAR[Rp] < aVAR[X] + (1- a)VAR[Y]
if -1 ≤ rxy < 1. In words, the variance of a
portfolio is less than the simple average of variances of the assets in the
portfolio if the assets are not perfectly correlated. This will not be
demonstrated rigorously but set rxy = 0, VAR[X] = VAR[Y], and a = 0,5 then {VAR[Rp] < aVAR[X] + (1- a)VAR[Y]} becomes {0,5VAR[X] < VAR[X]}.
Furthermore, if rxy = -1 then {VAR[kp] < aVAR[X] + (1- a)VAR[Y]} becomes {0 = VAR[X] < VAR[X] } a perfect
hedge (the resulting portfolio is riskless)! The diversification property
implies that the minimum variance opportunity set will be convex, and this
is a necessary condition for the existence of unique and efficient portfolio
equilibrium. As will be seen this property is used for the derivation of the
CAP-model. The minimum variance opportunity set is the locus of mean and
variance combinations offered by portfolios of risky assets that yield the
minimum variance for a given return. The locus is illustrated as the fat
curve in figure I below. The convexity property holds for two risky assets
or more. The area on and behind the locus (the oval) is sometimes refereed
to as the portfolio production possibility area. Each point in this region
represent the return and risk from some single asset available in the
market, or some portfolio made on those assets. |
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Step 2. The next assumption is that
investors are risk averse and maximize expected utility. They perceive
variance as a bad and mean as a good. This is also illustrated in figure I
where tree risk-averse indifference curves are drawn. Now, the first
conclusion is. Proposition 1: An individual investor will
maximize expected utility of his end of period wealth where his subjective
marginal rate of substitution between risk and return represented by his
indifference curves is equal to the objective marginal rate of
transformation offered by the minimum variance opportunity set: MRSspmp = MRTspmp. Step 3. Assume now that there in
addition to the many risky assets exist a risk free asset and that investors
may borrow or lend unlimited amounts of this asset at a constant rate: the
risk free rate (kf). Furthermore, capital markets are assumed to
be frictionless. The effect on the shape of the portfolio production
possibility area is profound as illustrated in figure II below. |
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The reason for this dramatic change is
simple. With the existence of the risk free asset the mean and the variance
for a portfolio consisting of the risk free asset and the portfolio M (see
figure) will be: mp = aE[km] + (1 - a)kf (5) sp2 = a2VAR[km]+ (1- a)2VAR[kf]+ 2a(1- a)COV[km,kf] using
property 3 = a2VAR[km]+ (1- a)20+ 2a(1- a)0 = a2VAR[km] <=> sp = asm (6) This shows that the new minimum
varians opportunity set will be linear in the (m,sp) space and consists of portfolios with some
fraction a of portfolio M and (1 - a) of the risk free asset. In the following
an equation for the linear minimum variance opportunity set is developed.
Taking the derivative of (5) and (6) yields: ¶mp/¶a = E[km] - kf ¶sp/¶a = sm Therefore the slope of the line is: ¶mp/¶a /¶sp/¶a = (E[km] - kf)/sm (7) and since the intercept with the
mean axle is (s,m) = (0,kf) the equation for the
minimum variance portfolio is mp = kf + [(E[km] - kf)/sm]s = Rf + (E[km] - kf)s/ sm (8) This equation has come to be known as the
capital market line (CML). It is the fat line in figure II. This formula is
referred to as the capital portfolio pricing model (CPPM), because it prices
efficient portfolios. The following explains why. Step 4. Assume that all investors have
homogeneous beliefs about the expected distribution of returns offered by
all assets. Also, capital markets are frictionless and information is
costless and simultaneously available to all investors. Furthermore, there
are no market imperfections. Taken together this implies that all investors
calculate the same equation for the market capital line and that the
borrowing rate equals the lending rate. Within broad degrees of risk aversion each
investor will maximize their utility by holding some combination of the risk
free asset and the portfolio M. This property is known as the two-fund separation principle. It is
illustrated in figure II by the tangency of the indifference curves on the
CML for different degrees of risk. Step 5. Assume further that all assets
are perfectly divisible and priced in a perfectly competitive marked.
Furthermore, there is a definite number of assets and their quantities are
fixed within the one period world. Then the portfolio M turns out to be the
market portfolio of all risky assets. The reason is that equilibrium
requires all prices to be adjusted so that the excess demand for any asset
is zero. That is, each asset is equally attractive to investors. Theoretically
the reduction of variance from diversification increases as the number of
risky assets included in the portfolio M rise. Therefore, all assets will be
hold in the portfolio M in accordance to their market value weight: wi =
Vi/SVi, where Vi
is the market value of asset i and
SVi is the market value
of all assets. Proposition 2 may now be stated: Proposition 2: With all the above assumptions
in mind (step 1-5) the capital market line (8) shows the relation between
mean and variance of portfolios
(consisting of the risk free asset and the market portfolio) that are
efficiently priced and perfectly diversified. The capital market line equation could
rightly be called the capital portfolio pricing model (CPPM) since it prices
efficient portfolios. What is more interesting is to develop an equation for
pricing of individual assets. This is exactly what the capital asset pricing
model (CAPM) does. The CAP-model does not requires any new assumptions only
new algebraic manipulations within the framework of the CPP-model. |
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Step 6. From CPPM to CAPM. What
is wanted is a model for efficient pricing of capital for individual assets
(E[k], the CAPM), not one for efficient cost of capital for portfolios (mp, the CPPM). Now, imagine a portfolio
consisting of a% in a risky asset I and (1 - a)% in the market portfolio M from the
CPP-model. The mean and the variance of this portfolio is by definition E[kP] = aE[k] + (1 - a)E[km] (9) VAR[kP] = a2VAR[k]+ (1- a)2VAR[km]+ 2a(1- a)COV[k,km] <=> sRp = {a2VAR[k]+ (1- a)2VAR[km]+ 2a(1- a)COV[k,km]}-0,5 |