To determine the efficient frontier of a mean-variance framework, one needs estimates of the expected return $r_i$, the variance $\sigma_i^2$ and the co-variance $\sigma_{ij}^2$ for each stocks $i$, $j$. For $n$ stocks, you have to estimate a total of $\frac{n(n-1)}{2}$ correlation coefficients. Index models are used, to reduce this huge amount of needed estimates.
Single Index Models
It is assumed, that the return of a stock can be written as
$$r_i = a_i + \beta_i r_m + e_i$$
,where $r_m$ denotes the market-return, $e_i$ a mean-zero error term and $\beta_i$ a stocks beta. The key assumptions are:
$$\operatorname{E}[e_i(r_m-\bar{r}_m]=0$$
$$\operatorname{E}[e_ie_j]=0$$
This implies, that the only reason stocks vary together, systematically, is because of a common comovement with the market. One can show, that the covariance can be expressed as
$$\sigma_{ij}^2 = \beta_i \beta_j \sigma_m^2$$
, where $\sigma_m^2$ denotes the variance of the market-return. In summary, if you assume the single-index model, you just have to estimate a total of $3n+1$ parameters for $n$ stocks.
CAPM
The CAPM is an economic theory in equilibrium with further assumptions for an investor's utility-preference function, costless diversification,...
Combing the economic theory from Markowitz portfolio-diversification, Von Neumann and Morgenstern expected utilities etc. leads to the CAPM (where $r^f_t$ denotes the risk-less rate of interest):
$$r_{i,t}-r^f_t = \alpha_i + \beta_i(r^m_t-r^f_t)+ \epsilon_{i,t}$$
, with the following (strong) assumption:
$$\alpha_i = 0$$
You may look at this excellent answer with more details.
Differences from Single Index Models and the CAPM
In fact, the single index model is just a statistical technique, because you can replace $r_m$ with any other variable you think fits best to explain a stocks return. The CAPM however is an economic model in equilibrium, where the market-portfolio return $r_m$ is a clearly determined portfolio (of all risky assets, investments, also human-capital...). See also this answer:
The $\beta_i$ for a stock in the single-index model is not the same $\beta_i$ as in the CAPM.
Reference:
Elton/Gruber/Brown/Götzmann (2014), Modern Portfolio Theory and Investment Analysis, ed. 9, John Wiley & Sons.
I have one doubt though. In the last line you said that the β for SIM and CAPM is not the same (which makes sense to me now).
The question then is how is it possible for us to interpret β as the measure of non-diversifiable risk under the CAPM. The math which justifies such an interpretation is the variance decomposition into specific risk and market risk, which we perform under the SIM (and not under CAPM).
– Dhruv Gupta Jan 29 '19 at 14:32