Capital Aasset Pricing Model and Techniques

Before understanding the relationship of sensitivity analysis to capital budgeting it is very important to understand the concept of capital budgeting and sensitivity analysis. Capital budgeting is a procedure which helps the businesses to take decisions with regards investing into a project or not. Basically it helps to determine the investment that an entity has to make in a particular project and the expected revenue and income that the project will generate in future for the entity. Sensitivity analysis is nothing but a method which helps to analyse the same in detail so that a more sound decision can be taken with regards the same. Sensitivity analysis helps the organization to gauge into various scenarios and circumstances with regards the project in case the estimates and circumstances do not fall into place and become undependable. It is basically changing the assumptions and applying a hit and trial method to the calculations basis the changed assumptions so as to find out the expected result out of such a change. Thus in this manner the decision makers can give a second thought before investing in their money (Koening, 2015). They can come to know what losses they may have to suffer by investing in any project basis this assumptions and estimate. The said analysis highlights upon the modification in the input that would affect the net result from any project. Change is constant and hence variations will happen to the base suppositions and it is this alteration which the sensitivity analysis details about. It helps to find out the most favourable levels of inputs in a project. Therefore this is a statistical analysis of the data basis changes in the numbers such as quantity and prices. Thus sensitivity analysis details about finding the extent to which changes can be made to the input factors so that the ultimate result remains unchanged. Thus sensitivity analysis helps in capital budgeting because of the following reasons: Helps in taking a more sound decision and thus testing the results in a more detailed manner. Helps to detect errors and thus try to mitigate the same Helps to develop the model more accurately by detecting errors and trying to find solution to mitigate those errors. Develop a will knitted linkage between the input and the output variables. Therefore it is understood that the main purpose of this analysis is not assess risk but to make certain the receptiveness of the NPVs to the various variables which help to calculate it. The same is because NPV is calculated basis assumptions which is why the scenario in which capital budgeting decisions are taken is uncertain (Zhamoida, & Matsiuk, 2011). It is the most acceptable method of analysis of various changes one by one in the variables and the assumptions being made which would in turn have a bearing on the cash flow and the return from a project. As the name suggest, scenario analysis helps in taking capital budgeting decisions and techniques by taking into account unconventional possible results. The analysis is conducted in a fashion which would help to find out the net result due to an action or activity under various other set of factors such as how an NPV of a project would differ if the inflation shoots up or down. However it is equally important to know that scenario should be such which can exist in actual sense and not fictional in nature. Generally three kinds of scenarios are considered good, base and worst for computing the NPVs of a project (Boundless.com., 2012). It is an analytical tool unlike the sensitivity analysis which uses statistical tool. After the NPVs are computed then a probability of occurrence of such a scenario is allotted to ease situation and then the expected NPV and standard deviation of the NPV is calculated. This is known as coefficient variation and a CV of 1 is considered to be ideal. However on comparing the two CV basis the scenario then the one with a lower CV is considered to be more preferable than the one with a higher CV. Thus it can be said that scenario analysis although is also a behavioural approach similar to sensitivity analysis yet the former defines the capital budgeting techniques more broadly. It takes into consideration various variables together such as cash inflows, outflows and cost associated with capital invested. For example an entity should take into consideration both high and low inflationary factors and compute the implication of the same on the project’s Net present value. Each situation will affect all the above mentioned variables at the same time thus resulting into differing levels of NPV. Thus giving the decision makers a more detailed method of analysing the capital budgeting techniques used by organizations before investing into a project. Furthermore scenario analysis used in various capital budgeting techniques helps to give a summary about the risk associated with the various assets wherein the assets with higher risk will have more volatile values and vice versa. Scenario analysis entails how much economic sense does it make in investing into any project for an organization. Further by doing the analysis taking into consideration the worst scenario as well, one can take proactive measures to try to reduce the risks associated with the worst scenario   (Kengatharan, 2016). Thus on a summarizing note one can say that scenario analysis helps in detailing investments during situations which are even unfavourable in nature. It helps to find solutions during worst cases also thus trying to consider investment in various projects minutely. Definition of the Capital Asset Pricing Model: The said model is built on the Markowitz’s mean-variance-efficiency model where the patrons who are reluctant towards taking risk on investments are concerned only about the returns and the profits they expect from their investment and the difference of returns and risk. Thus the said model defines the linkage between the return and risk associated with an asset. It enables determination of the appropriate required rate of return of an asset but only in theory. It helps to take calls about addition of assets or more investment securities to an already diversified portfolio (Fama & French, 2004). The graphical representation of the formulae of CAPM is known as the security market line. Definition of Capital Market line: The Capital Market Line is plotted on the capital asset pricing model which helps to illustrate the rate of return that could be expected to receive from a well built portfolio but depending upon the level of risk associated with the portfolio of the entire market and the risk free rate of return. It is a digression from the point of interception found on the efficient frontier stretched towards the return expected from an investment which is equivalent to the risk free rate of return. There lie a number of differences between the two mentioned terms. Similarities also exist but the same is very few in comparison to the differences. The similarities between a CAPM and CML would be discussed in the form of a relationship that exists between the Capital market line and the Security market line which is a graphical representation of the CAPM. The SML is considered to be an integral part of the CML in a Capital Asset Pricing Model specifically when the risk attached to a security or an investment is computed. Their relationship depicts the similarity as one shows the risk associated with individual securities whereas the other considers these individual securities and forms the entire portfolio.   Thus performance of a single security will impact the performance of the portfolio as well. Therefore we can say that both these help to depict the association of risk with various investment securities as well as portfolio as a whole. Thus the similarity is such that both the CML and SML hypothesize a straight line association between risk and return. The CML and SML also talks about systematic risks and portfolios whic h are risk free although the SML also includes the inefficient portfolios as well. Just as their exists a relationship between CAPM and CML due to similarities between the two, similarly the two concepts differ amongst each other for various reasons illustrated below. The CML is a line that depicts the rate of return which is dependent upon the rate of return which is free from adequate risk and the level of risk for various investment groups. However CAPM or the SML line used to represent the CAPM formulae is a graphical presentation of the risk and return in a market at a particular point of time. The measurement of risk factors is another difference between the two concepts. The CML uses standard deviation to gauge risk whereas for CAPM the risk factors are firmed via the beta coefficients. Therefore the former is a measurement basis which risk is calculated in totality whereas the later tells about the contribution of the security or the investment towards the risk on the entire portfolio. CML portrays only portfolios which are competent and proficient whereas the Security Market Line used to depict the CAPM, portrays both competent and non-competent portfolios. While calculating the return, the Y Axis depicts the return anticipated from a portfolio in case of a CML and the return that the individual investments gives are shown by the Y axis in case of the SML. The X axis of CML depicts the standard deviation whereas the X axis of the SML depicts the Beta of the shares and individual investments. The two axis is well depicted in the graphs below of both CML and SML wherein the horizontal axis of the SML depicts the methodical risk and that of CML is overall risk. The CML establishes the portfolio of the entire market and such assets which are free from any risks, SML establishes all the factors associated with investments made (Campbell, 2013). Boundless.com., (2012), Scenario Analysis, Available at https://www.boundless.com/finance/textbooks/boundless-finance-textbook/the-role-of-risk-in-capital-budgeting-12/scenario-and-simulation-assessments-99/scenario-analysis-427-7232/ (Accessed 19 th January 2017) Campbell, B., (2013), CAL vs. CML vs. SML., Available at https://luckyhy.weebly.com/uploads/3/9/3/2/39328787/cal_vs._cml_vs.pdf (Accessed 19th January 2017) Fama, E.F., & French, K.R., (2004), The Capital Asset Pricing Model: Theory and Evidence, Journal of Economic Perspectives, vol.18, no. 3, pp. 49-51 Kengatharan, L., (2016), Capital Budgeting Theory and Practice: A Review and Agenda for Future Research, Applied Economics and Finance, Vol. 3, no.2, pp.15-38 Koening, E., (2015), Sensitivity Analysis for Capital Budgeting, Available at https://smallbusiness.chron.com/sensitivity-analysis-capital-budgeting-10153.html (Accessed 19th January 2017) Zhamoida, O.A., & Matsiuk, M.S., (2011), Sensitivity Analysis in Capital Budgeting, Economic Herald of the Donbas, vol.4, no.26, pp.132-136

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