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Explain and graphically depict how Security Market Line (SML) is different from Capital Market Line (CML). Identify and discuss the importance of minimum variance portfolios?

Why CAPM equation might be more relevant than other equations when calculating required rate of return.

The Security Market Line

The security market line graphically represents the Capital asset Pricing Model (CAPM). The SML is a hypothetical construct that is based on a world of perfect data. However, with the absence of this data, an individual can make assumptions that the historical data will most likely provide them with accurate expectation on the kind of returns as well as the risks expected on a particular investment. However, the capital market line is the line that intersects the returns from an investment that is considered to be a no-risk investments as well as the whole market’s returns. The aim of this report is to discuss the differences between security market line and the capital market line. Additionally, it discusses the importance of minimum variance portfolios, including the reasons why the CAPM model is a more relevant approach in calculating the required rate of return.

The SML is used to draft the systematic, the non-diversifiable risk which is expressed as a beta versus the return from the whole market within a specified time (Behr, Guettler. and Miebs, 2013, pp.1238). Additionally, it also indicates all the risky marketable securities.

The security market line’s Y-intercept is an expression of a risk-free interest rates which represents the return’s theoretical rate on an investment that has got no risk. When used in the portfolio management, the SML is used to represent the opportunity costs of an investment (Moten and Thron, 2013, pp.87). All the securities which are considered to be correctly priced are plotted on the security market line. The assets that are undervalued are those that lie above the line due to the yielded high risks on a higher investment. Additionally, the assets that are located below the line are overvalued as a result of the given risk that they yield on lower return.

The market security line is equivalent to the market risk premium and is used to reflect on the trade-off of the risk-return at a given period. The market security line results from the idea that investors are risk-averse, and thus, there is an expectation that the volatility of a risky investment will be offset by a premium. In any perfect world that has got perfect data, all the capital investments are found on the SML (Barberis, et al, 2015, pp.15). This model is thus important in understanding the CAPM approach.

However, the capital market line is applied during the evaluation of portfolio performance. The main difference between the efficient frontier and the CML is that the capital market line incorpor1ates the no-risk investments. Every portfolio that is found along the market line is an efficient portfolio (Ghosh, Julliard and Taylor, 2016, pp.500). Any the other point that is found in any other point below the line is considered to give lower returns but at the same risk, thus making it unideal.

The Capital Market Line

The CML can be described as a measure that is used when evaluating portfolio performance and it is the graph that is used in asset driving models to determine a market portfolio’s rates of return. The CML is thus made of use when describing the efficient portfolios’ rates of return, which are dependent on the risk level of a particular portfolio, inclusive of the free rate of return. The CML is influenced by the idea that a market portfolio will be possessed by every investor (Zhang, 2017, pp.551). There is a positive correlation between quantum risks with the expected return. The CML’s equation is shown:

To deduce the capital market line, a tangent line is drawn beginning from an intercept point that is found on an efficient frontier, and this tangent line extends to the point where there is a match in the expected return and a returns risk-free rate.

The minimum variance portfolio is a risk-based approach to the construction of the portfolio (Maio, 2013, pp.127). It is a portfolio of securities that are combined with the intention of minimizing the overall portfolio’s price volatility. Volatility is mostly used instead of a variance when it comes to investment and it is a statistical measure of the movement in prices of a particular security’s price, either upward or downward. An investment’s volatility is as also interchangeable in meaning with its market risk. Thus, the greater an investment’s volatility, the higher is the market risk. This shows that if an investor seeks to minimize the risk, they also intend to minimize the upwards and downwards movements of a security’s price.

 Thus, instead of using the risk and the return information during portfolio selection, the minimum variance portfolio is constructed by the use of only measures of risk. One of the reasons that may influence the investors to opt for an approach that is risk-based is because it is very difficult and hard to measure future or the expected returns (Pla-Santamaria and Bravo, 2013, pp.191). However, measuring risk is much easier. Hence, this results in a more robust portfolio that is less subject to estimation risk. The minimum variance is closely related to the modern portfolio theory as well as the efficient frontier.

The minimum variance portfolio is a unique portfolio that is found on the efficient frontier. As shown in the figure above, the minimum variance portfolio depicts a portfolio which has got the lowest standard deviation and which can be constructed using a set of securities that investors can invest in (Caballero, Teruel and Solano, 2014, pp.334). The advantage with this portfolio is that when calculating the minimum variance portfolio weights, it only uses the covariance matrix but there is no need of having expected returns to determine the weights.

Minimum Variance Portfolios

Generally, the minimum variance portfolio combines the investments that have a low correlation. Correlation is used to measure how two investments move with one another. For instance, 50% bonds and 50% stocks is a simple minimum variance portfolio since there are two investments that have a correlation that is low to one another (DeMiguel, et al, 2013, pp.1897). This is because stocks are considered to be highly volatile while the bonds tend to be more consistent. Most of the minimum variance portfolios do vary from a traditional portfolio mix that involves a mix of bonds and stocks. Instead of investing in a mix that consist of bonds that are low risk and the stocks that are high risk, the minimum variance portfolio is a mix of the highly volatile individual securities that have got a low correlation (Džaja and Aljinovi?, 20130, pp.169). In building a minimum variance portfolio, the investor would have to combine either low volatile investments or volatile investments that have a low correlation to each other. However, the latter portfolios common in the construction of a minimum variance portfolio. Portfolios with low correlation are those investments that perform differently or are at least not too similar within the same economic and the market environment. For example, this is regarded as diversification’s prime example because when investors diversify their portfolio, they mainly aim at reducing volatility, which is the minimum variance portfolio’s basis.


The minimum variance portfolio is very important to the investor because once they mix a set of securities that are volatile and which do not tend to move with one another, the investors are in a position to hedge against loss, while at the same time maximizing on their earnings. To have a minimum variance portfolio, it does not necessarily involve mixing highly volatile investments. Rather, it involves having a low correlation between an investor’s investments.

Relevancy of the CAPM Model

The required rate of return is an integral part of most metrics that are applied in corporate finance as well as the equity valuation. The RRR is defined as the amount of profit that is required to carry on with an investment (Boyd, et al, 2014, pp.44). This measure helps the investors decide if they should go on and purchase an investment. Nonetheless, the RRR goes beyond defining an investment’s return but also takes into consideration the factors in risks in determining the potential return. Also, the RRR sets the minimum amount of return that is acceptable by an investor, considering the company’s capital structure and all the available options. When calculating the required rate of return, the factors considered are the whole market’s return, returns that could be obtained from a risk-free investment, including the stock’s volatility.

The Required Rate of Return

Since the investors are risk averse, they mainly choose to hold a securities’ portfolio aimed at taking advantage of benefits resulting from diversification. Hence, when they decide whether they are going to invest in a given stock, what they seek to understand is the contribution of the stock to their portfolios in reference to the expected return and risk (Choi, et al, 2017, pp.193). However, an individual stock’s standard deviation does not show the contribution of specific stock to the diversified portfolio’s return and risk. This call for another measure risk that is capable of measuring the systematic risk of a security. The CAPM provides the measure of a security’s systematic risk thus making it more relevant compared to the other equations during the calculation of the RRR on an investment.

 Pricing risk and efficiently allocating capital appears to be important for factor-based strategies that mostly target the mispricing and the market abnormalities aimed at improving the returns. The CAPM model thus offers a theoretical look in the manner in which stocks are priced in the financial markets, while allowing the investors to gauge the future returns (Wilson, et al, 2014, pp.6). Being one of the modern portfolio theory’s central focus, the model has got several uses in the investment world, which includes estimating the cost of capital.

Expected return = RF + β (RM – RF)

The risk-free rate of return equation is mostly represented by the government bonds because the interest payments are easily predicted and they are regular and because they have less risk of default (Bolek, 2014, pp.7). The equation’s second part [β (RM-RF)] is used to quantify the risk premium of an investment and is useful in determining the compensation demanded by investors if they buy asset’s inherent risk

Generally, the reason why the CAPM equation is more relevant compared to the other equations in determining the required rate of return are: first, the CAPM equation only takes into consideration the systematic risk, thus it reflects a reality in the incidence where many investors have portfolios that are diversified from which the unsystematic risk has been initially eliminated (Martin, 2017, pp.378). Second, it is regarded as a relationship that is theoretically-derived between the systematic risk that has been subject to frequent testing and empirical research and the required return. Third, the capital asset pricing model is considered to be a better approach of calculating the cost of equity compared to the dividend growth model since it explicitly considers the systematic risk level of a firm relative to the stock market as a whole (Wang, Yan and Yu, 2017, pp.401). Last, the CAPM model is clearly superior to the WACC model because it provides discount rates that may be used in investment appraisal.

The CAPM Approach


Significant differences exist between the SML and the CML. For instance, when measuring risk, the capital market line uses the standard deviation or the total risk factor while the security market line uses beta to measure risks and its helps in assessing the contribution of a risk for that portfolio. Also, the capital market line is used to define the efficient portfolio while that of the security market line defines both the efficient and non-efficient portfolios. The minimum variance portfolio is very important because it combines a set of securities that are volatile and which do not tend to move with one another thus hedging against risks. The CAPM model is a more relevant approach in measuring the required rate of return because it takes into consideration the systematic risks of a company relative to the whole stock market.


Baños-Caballero, S., García-Teruel, P.J. and Martínez-Solano, P., 2014. Working capital management, corporate performance, and financial constraints. Journal of Business Research, 67(3), pp.332-338.

Barberis, N., Greenwood, R., Jin, L. and Shleifer, A., 2015. X-CAPM: An extrapolative capital asset pricing model. Journal of financial economics, 115(1), pp.1-24.

Behr, P., Guettler, A. and Miebs, F., 2013. On portfolio optimization: Imposing the right constraints. Journal of Banking & Finance, 37(4), pp.1232-1242.

Bolek, M., 2014. Return on current assets, working capital and required rate of return on equity. e-Finanse: Financial Internet Quarterly, 10(2), pp.1-10.

Boyd, S., Mueller, M.T., O’Donoghue, B. and Wang, Y., 2014. Performance bounds and suboptimal policies for multi–period investment. Foundations and Trends® in Optimization, 1(1), pp.1-72.

Choi, N., Fedenia, M., Skiba, H. and Sokolyk, T., 2017. Portfolio concentration and performance of institutional investors worldwide. Journal of Financial Economics, 123(1), pp.189-208.

DeMiguel, V., Plyakha, Y., Uppal, R. and Vilkov, G., 2013. Improving portfolio selection using option-implied volatility and skewness. Journal of Financial and Quantitative Analysis, 48(6), pp.1813-1845.

Džaja, J. and Aljinovi?, Z., 2013. Testing CAPM model on the emerging markets of the Central and Southeastern Europe. Croatian Operational Research Review, 4(1), pp.164-175.

Ghosh, A., Julliard, C. and Taylor, A.P., 2016. What is the consumption-CAPM missing? An information-theoretic framework for the analysis of asset pricing models. The Review of Financial Studies, 30(2), pp.442-504.

Maio, P., 2013. Intertemporal CAPM with conditioning variables. Management Science, 59(1), pp.122-141.

Martin, I., 2017. What is the Expected Return on the Market?. The Quarterly Journal of Economics, 132(1), pp.367-433.

Moten Jr, J.M. and Thron, C., 2013. Improvements on secant method for estimating internal rate of return (IRR). Int. J. Appl. Math. Stat, 42(12), pp.84-93.

Pla-Santamaria, D. and Bravo, M., 2013. Portfolio optimization based on downside risk: a mean-semivariance efficient frontier from Dow Jones blue chips. Annals of Operations Research, 205(1), pp.189-201.

Wang, H., Yan, J. and Yu, J., 2017. Reference-dependent preferences and the risk–return trade-off. Journal of Financial Economics, 123(2), pp.395-414.

Wilson, M., Hallam, P.J., Pecheone, R. and Moss, P.A., 2014. Evaluating the validity of portfolio assessments for licensure decisions. education policy analysis archives, 22(6), p.n6.

Zhang, L., 2017. The investment CAPM. European Financial Management, 23(4), pp.545-603.

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