The overall assessment aims in comparing SML and CML line, which helps investors for improving their current investment scope. In addition, the discussion on the significance of minimum variance portfolio is mainly conducted, which helps in depicting the level of income that could be generated from the portfolio. Furthermore, the minimum portfolio variance actually allows the investors for improving their current return generation capability and generates high cash inflow by adding low risk to investment. Lastly, the significance of CAPM model is also depicted in the assessment, as it adequately depicts the relevant rate of return from investment.
The above figure depicts the Security Market Line, which depicts the relationship between the systematic risk and expected return of the stock. The calculation conducted in the SML line mainly allows the investor to detect the level of relationship between the expected return and beta of the organisation.
The above figure depicts CML line, which allows the investors for identifying the level of returns, which can be generated from an investment. In addition, the CML line directly helps in detecting the efficient frontier for the selected portfolio, which can allow the investor to generate higher return, while having low risk.
There are certain differences between the Security Market Line and Capital Market Line, which are depicted as follows.
The main target scope of both CML and SML are different, while it also has alternative usage for the investor. From the relevant evaluation it can be detected that SML line mainly targets one stock at a time, while it determines its overall risk and return from investment. On the other hand, investors using the CML line mainly focuses on analysing a portfolio, which hold more than one stocks. Hence, it could be deducted that SML calculation mainly evaluates only one stock, while CML uses more than one (Frazzini and Pedersen 2014).
Both the method uses different types of risk attributes for understanding the level of risk, which is associated with the investment. In addition, from the evaluation it can be detected that beta is used for determining the overall values of SML for each stock. This beta values are mainly derived from the response rate towards the market index, which leads to the price change of the stock. On the other hand, the calculation of CML line mainly uses standard deviation, which is calculated from the return of the stock. The calculation directly helps in understanding the level of risk associated with investment in particular stock. Hence, the standard deviation value of each stock is used for determining the total risk of the portfolio for the investor.
The focus of the CML line is to define the efficient portfolio, which can be used by the investor to support their risk and return attributes. On the other hand, the SML line directly defines both efficient and non-efficient stock, which are depicted in the graph. Hence, investors using the CML measure would eventually help in portraying the accurate return and risk, which has generated from investment. therefore, the CML method depicts the level of weight in each stock, which should be invested by the investor for obtaining the high returns from investment, while reducing its total risk attribute (Ahmed and Zlate 2014).
From the evaluation it can be detected that Capital Market Line is mainly considered superior in nature, as it evaluates the overall risk factors, which is not identified by SML. The calculations of CML directly allows the investor to bank of the systematic risk from investment, which helps in making adequate investment decisions. The superiority in measuring risk factors of CML method is mainly depicted by its efficient frontier, which directly evaluates level of investment that needs to be conducted by the organisation for generating higher return. On the contrary, the risk depicted by SML line is relative to the market price fluctuations, which only depicts the risk projected from fluctuating market index value.
Figure 3: Depicting the Minimum variance portfolio graph
(Source: Maillet, Tokpavi and Vaucher 2015)
The above figure mainly depicts the level of minimum variance portfolio, which can be used by investors to maximising the level of return by occurring the lowest risk. In addition, the portfolio directly depicts the curve, which contains the minimum variance portfolio, where the overall risk is lower. The minimum portfolio variance is mainly obtained by changing the weights of portfolio stocks to generate higher rate of return from investment, while having the least risk. In this context, Bodnar, Mazur and Okhrin (2017) stated that with the implementation of minimum variance portfolio investors are able to utilise both riskless and high-risk security for maximising the returns from investment. The significance of the minimum variance portfolio is depicted as follows.
With the implementation of minimum variance portfolio investors are mainly able to detect the accurate weights of stock, which need to be invested by the investor. In addition, from the evaluation it can also be detected that companies using the minimum variance method is able to detect the risk and return attributes that can be generated from portfolio. Furthermore, from the evaluation it can also be detected that investor are able to detect the accurate weights, which needs to be maintained in the portfolio for the composition of the stock for obtaining the level of return with the least risk associated with investment. Xing, Hu and Yang (2014) argued that during the financial crises the minimum variance portfolio does not perform according to anticipation, as its crisis effects the risk and return attributes of the whole capital market.
The second major significance of the minimum variance portfolio is its capability for reducing the overall risk from investment. The method directly allows the investors to combine the stocks and derive the combination which portrays the least risk from investment. Furthermore, the adequate curve is developed, where the point at the which the combination of the efficient frontier portrays the least risk is taken into consideration by the minimum variance portfolio. This directly increases the chance of portfolio outperformance, which can be conducted for improving the level of returns from investment. In similar context, Bjork, Murgoci and Zhou (2014) indicated that investor using the minimum variance portfolio only tends to ensure constant returns and does not bank on abnormal returns from investment.
The third significance of the minimum variance portfolio is the protection, which it provides the investors during their investment phase. This increment in protection level ensures the investor to boost their current return generation capability for ensuring higher returns from confined risk. The protection system allows the investor for reducing the level of risk by utilising the weights, standard deviation and return of the stocks. therefore, investors could use the technique for improving their current return generation capability.
The fourth significance of the minimum variance portfolio is its attribute for adding both riskless and riskiest stocks in one portfolio for determining the adequate composition of stocks. These combinations of stocks are mainly allowing the portfolio to increase its overall reach on both aspects of investment. This attribute of the minimum variance portfolio is actually allowing the investors to maximise the level of income from their investment by accommodating the riskless and riskiest stocks available from the options. Therefore, from the evaluation it can be detected that investor with the use of minimum variance portfolio is able to detect the level of income and the risk associated with investment (Yang, Couillet. and McKay 2015).
The above figure 4 directly depicts the formula for Capital Asset Pricing Model, which can help in detecting the return that needs to be provided from investment. The formula depicted in the above figure indicates the use of beta, return on market and risk-free asset for identifying the return, which can be generated from investment. There are different types of equations, which are used by investors for identifying the overall return that might be generated from investment. Hence, from the evaluation it can be detected that big fund manager and investors use the Capital Asset Pricing Model for detecting the level of returns, which can be generated from a particular stock. In this context, Sattar (2017) stated that CAPM model uses beta for detecting the level of returns, which can be generated from investment. However, Bao, Diks and Li (2018) argued that CAPM method mainly uses single period transaction method, which increases the level of risk from investment.
There are different level of advantages and disadvantages situated with the Capital Asset Pricing Model, as it allows the investor to detect the maximum return, which needs to be provided by stock for particular risk. The calculation of CAPM directly indicates the level of returns, which can be provided by each of the stocks. Leaving the Capital Asset pricing model other methods also use by the investors for improving their current investment scope and detect stocks which has the highest return from investment. Leaving the Capital Asset pricing model other methods also use by the investors for improving their current investment scope and detect stocks which has the highest return from investment. Model such as Fama-French 3 Factor Model and Modified Fama-French Model are adequately used by investors for detecting the level of returns that will be generated from a particular stock. However, the Capital Asset pricing model is relatively considered to be one of the adequate methods, which allows investors to understand the level of risk and return that needs to be provided from a particular stock (Nasiri et al. 2017). Furthermore, the Capital Asset Pricing Model used in other models increases the reliability of the method in improving the level of return from investment.
There are different level of advantages and disadvantages associated with the use of CAPM method, which are depicted as follows.
Conclusion:
The assessment aims in identifying the significance of Capital Asset Pricing Model, which allows investors to identify investment scope. The difference between the security market line and capital market line is also depicted in the assessment, which allows the investors to select the adequate method for creating their portfolio. The significance of the minimum variance portfolio is also depicted, which relatively allows the investors to minimize the risk from investment and maximize the level of income that could be generated from the creative portfolio. Minimum variance portfolio that it allows the best tools to create an adequate portfolio comprising of stocks with high risk and risk free assets.
References and Bibliography:
Ahmed, S. and Zlate, A., 2014. Capital flows to emerging market economies: a brave new world?. Journal of International Money and Finance, 48, pp.221-248.
Bao, T., Diks, C. and Li, H., 2018. A generalized CAPM model with asymmetric power distributed errors with an application to portfolio construction. Economic Modelling, 68, pp.611-621.
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.
Björk, T., Murgoci, A. and Zhou, X.Y., 2014. Mean–variance portfolio optimization with state?dependent risk aversion. Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics, 24(1), pp.1-24.
Bodnar, T., Mazur, S. and Okhrin, Y., 2017. Bayesian estimation of the global minimum variance portfolio. European Journal of Operational Research, 256(1), pp.292-307.
Christensen, H.B., Hail, L. and Leuz, C., 2016. Capital-market effects of securities regulation: Prior conditions, implementation, and enforcement. The Review of Financial Studies, 29(11), pp.2885-2924.
Frazzini, A. and Pedersen, L.H., 2014. Betting against beta. Journal of Financial Economics, 111(1), pp.1-25.
Hur, S.K. and Chung, C.Y., 2017. Revisiting CAPM betas in an incomplete market: Evidence from the Korean stock market. Finance Research Letters, 21, pp.241-248.
Jylhä, P., 2018. Margin requirements and the security market line. The Journal of Finance, 73(3), pp.1281-1321.
Lal, I., Mubeen, M., Hussain, A. and Zubair, M., 2016. An empirical analysis of higher moment capital asset pricing model for Karachi stock exchange (KSE). Open Journal of Social Sciences, 4(06), p.53.
Maillet, B., Tokpavi, S. and Vaucher, B., 2015. Global minimum variance portfolio optimisation under some model risk: A robust regression-based approach. European Journal of Operational Research, 244(1), pp.289-299.
Nasiri, M., Alishah, A.Y., Sayyahmelli, S.A.S. and Karimi, A., 2017. Estimating Expected Return based on Capital Asset Pricing Model compared with Stock Interest Rate at Tehran Stock Exchange. HELIX, 7(2), pp.1406-1415.
Sattar, M., 2017. CAPM Vs Fama-French three-factor model: an evaluation of effectiveness in explaining excess return in Dhaka stock exchange. International Journal of Business and Management, 12(5), p.119.
Xing, X., Hu, J. and Yang, Y., 2014. Robust minimum variance portfolio with L-infinity constraints. Journal of Banking & Finance, 46, pp.107-117.
Yang, L., Couillet, R. and McKay, M.R., 2015, December. Minimum variance portfolio optimization in the spiked covariance model. In IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)(2015).
Yang, L., Couillet, R. and McKay, M.R., 2015. A robust statistics approach to minimum variance portfolio optimization. IEEE Transactions on Signal Processing, 63(24), pp.6684-6697.
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