How Mean-Variance Optimization Differs from CAPM
Summary
Mean-variance optimization is a general portfolio framework that evaluates portfolios by expected return and variance or standard deviation of returns. Under suitable distributional assumptions, it identifies efficient portfolios: those offering the best expected return for a given level of risk. The framework does not by itself require the market portfolio to be optimal or prescribe a single relationship between risk and expected return.
The Capital Asset Pricing Model adds equilibrium assumptions. If investors choose efficient portfolios and markets clear, the aggregate market portfolio can also be efficient, yielding the CAPM relationship between expected return and market beta. The document explains that CAPM is therefore a more specific result built on mean-variance reasoning, rather than an equivalent framework. These conclusions depend on assumptions about investor behavior, equilibrium, and the relevant return distribution; the discussion is conceptual and provides no empirical test of whether those assumptions hold in practice.
Key ideas
- Mean-variance optimization selects portfolios by balancing expected return against variance or standard deviation.
- The framework can be used without assuming that the market portfolio is efficient.
- CAPM adds investor and market-equilibrium assumptions to derive expected returns related to market beta.
- The CAPM relationship depends on its assumptions and is not an empirical finding established by this discussion.
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# Difference between CAPM and mean variance optimization
# Difference between CAPM and mean variance optimization
Is the mean variance optimization the same thing as the capital asset pricing model? Or is the mean variance only a part of CAPM?
## Answer by Drew (score 5, accepted)
https://quant.stackexchange.com/a/15780
Mean-Variance Optimization is a generic framework that creates optimal portfolios relative to two measures of risk - mean and standard deviation (covariation). It holds in general for elliptical distributions where the scale and location of the distribution are the only sources of risk and return. For a Normal Distribution this is $(\mu, \Sigma)$.
CAPM is a strict set of equilibrium assumptions made on the mean-variance framework to obtain certain results for the behaviour of the representative agent in the market. Namely, that is all agents were rational, with concave quadratic utility functions dependent on the first two moments, then the market portfolio would be the optimal portfolio and all other returns could be determined by their "$\beta$" to the market. The key idea behind this is that all risk and return originates from a single factor, the market. So risk can be decomposed into two components, the systematic and the idiosyncratic. But, diversification (ala Mean Variance) can remove the idiosyncratic risk, so no rational agent should price it. As a result, all expected returns are given by the beta (covariation, regression coefficient) to the market.
## Answer by Fab (score 1)
https://quant.stackexchange.com/a/70861
The CAPM is basically mean variance optimisation plus equilibrium.
Mean variance optimisation answers a simple question: what portfolios have the greatest expected return for a given variance? Those are the efficient portfolios. The set of efficient portfolios is convex: any portfolio of efficient portfolios is efficient again.
Now, the CAPM proceeds like this:
- all investors are mean variance optimisers, so they each want an efficient portfolio.
- equilibrium obtains, so each investor has an efficient portfolio. Then, by convexity,
- the market portfolio (which is just the portfolio of all individual portfolios) is efficient.
Then the famous CAPM formula holds:
$E[r_p] = r_f + \beta_{p,m}(E[r_m] - r_f)$
where $p$ is any portfolio (or simple asset), $E[r_m]$ is the expected return of the market, $r_f$ is the risk free return (or the expected return of the zero covariance portfolio of the market if there's no risk free asset), and $\beta_{p,m}$ is the beta of $p$ with respect to the market.
Note that this famous formula holds (by pure math) whenever $m$ is an efficient portfolio. So all that is necessary for the CAPM to hold is above 3 (which in turn follows from 1 and 2).
## Answer by markowitz (score 0)
https://quant.stackexchange.com/a/26170
Mean variance and CAPM are not the same thing.
Neither the mean-variance model are the part of the CAPM. Rather the CAPM, in certain sense, is an part of the mean variance model.
To put it better, if we have $N$ risky assets plus a riskless one then we can achieve the a la CAPM representation. Moreover if the tangency ptf overlap the market ptf, as the CAPM assumption impose (equilibrium), we have the standard CAPM.
In other way, if the mean variance model do not hold neither the CAPM hold. Instead if the CAPM not hold the mean variance can hold still. The mean variance is more general.Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.