Discuss about the Capital Asset for Corporate Financial Management.
Decision-making is an essential part of business operations that uses several tools examining alternatives and appropriate values based on the market and economic indications. Sensitivity analysis is one of the tools that help the management in taking business decision with respect to capital budgeting techniques. It refers to a technique that is used to measure different values in terms of independent variable that affect dependent variable with respect to certain assumptions. Management use Sensitivity analysis is used to make business decisions for the purpose of indicating simulation to measure uncertainties in the input data values (Tjader et al. 2014).
Moreover, capital budgeting is a technique that helps the organizational management in taking decision for consideration of certain project. The capital budgeting process is considered by estimating probable inflows and outflows in terms of present value of economy by using several techniques like Net Present Value, Pay Back Period or Internal Rate of Return. However, sensitivity analysis is a process that offers further understanding on reliable outcomes of the probable investment alternatives that helps in taking accurate decision (Kazlauskien? and Christauskas 2015).
Undertaking of certain project for an organization involves financial effect and investment period return that the organization expects to generate covering the probable expenses. Accordingly, the management uses relevant discounting rates and standard internal rate to project future income in terms of present year’s market value. Accordingly, Sensitivity analysis is used to estimate inflows and outflows of the budget by considering relevant factors of economy, inflation rate, interest rate or foreign exchange fluctuation rate. Method of sensitivity analysis is used to measure the probable risks that may involve in new pr future projects so that the management can check the possible variations to earn maximum return from the future project (Spronk, Steuer and Zopounidis 2016).
For instance, determination of enterprise value of Woolworths Limited considers the method of sensitivity analysis with respect to debt and equity for the purpose of its capital structure for future. If the sensitivity analysis used for reduction of debt capital ratio by 10% assuming the value of debt is constant while increasing value of equity then the average cost of capital would be 5.55%. On the contrary, 25% reduction of debt equity in terms of sensitivity analysis, other factors remaining same average cost of capital would be 5.46% (Woolworthsgroup.com.au. 2017). Hence, sensitivity analysis assists the organizational management in taking better decision to generate maximum return by applying minimum costs.
Apart from the necessary estimations, sensitivity analysis on capital budgeting, certain risks are also involved for appropriate estimation on future performance. The assumptions may not be as per the future economic conditions and may not determine accurate outcome or unreliable results that affect the investment funds. Business organizations involves several risk for considering project to generate maximum return and business profit which can be minimized by appropriate use of sensitivity analysis. It assists the organizational management to assess the risk factors to determine the appropriate value of expected net profit (Magni 2016).
Scenario analysis is the procedure used to estimate the anticipated value of a business portfolio after considering specific period based on certain assumptions. Portfolio value is measured by the organizational management for several reasons that involves capital budgeting for the purpose of appropriate business decisions. Accordingly, scenario analysis is a tool that managers utilize to determine the value of portfolio by considering risk factors on interest rate changes, inflate rates and foreign exchange fluctuations. This method is used to evaluate and analyze the unfavorable events that affect the net outcome of the proposed business projects for the benefit of the company (Fujimori et al. 2014).
In order to maintain sustainable growth of the business organization it is essential to consider investment opportunities along with the profit maximization which involves capital budgeting techniques. It is important to consider probable risk factors to measure the expected outcome of the proposed investments that is determined by using several techniques line net present value, internal rate of return, discounting method or payback period. Accordingly, scenario analysis tool is used by the management of the organization to evaluate the consequences of different modes of investment eliminating the risk factors (Chow 2014). For instance, if the present economy has high inflation then the net present value of investment might be low in comparison to the result of investment value during low inflation. Therefore, it is essential to consider the scenarios to determine the precise outcomes of the proposed project or investment. Use of scenario analysis for the purpose of capital budgeting should be based on realistic and probable factors to determine the possible and appropriate result. Hence, three types of scenarios are used evaluate the project outcomes i.e. base case, best case and worst case depending on the nature of projects (Lee et al. 2016).
Moreover, to generate accurate outcomes for the proposed projects, management can use multiple scenarios using the component of estimated cash flows for each of the scenarios. Considering the factors of macro- economy in terms of rate of interest, rate of foreign exchange or rate of inflation, the probability result can be analyzed having the knowledge on industrial benchmark (Cairns, Goodwin and Wright 2016). For instance, management of Wesfarmers Limited uses different scenarios for the purpose of opening new stores at different location in order to measure the expected income after considering the probable expenses and projected risk factors. Scenarios and factors on store location, consumers’ demand, average size of stores and other differences along with the economic and realistic risks would be considering before investing in opening a new store (Wesfarmers.com.au. 2017). Decision tree is another method used in scenario analysis to measure the value of assets as per the probability of future income along with the application of test series to indentify the factors of failure. Hence, it can be said that the scenario analysis is considered to measure and evaluate the certainty of investment outcome as a result of future and probable economic risks.
Capital Asset pricing Model (CAPM): It is a model used to measure and describe the association between the systematic risk of the investment and anticipated return for the investment in stocks or securities. The model considers systematic risk as well as unsystematic risk to determine the realistic expected return from the proposed investment using the capital budgeting technique. In finance, the model of CAPM is used to measure the “required rate of return” for proposed investment of risky assets (Mackay and Haque 2016).
Capital Market Line (CML): “Capital Market Line is a tangent line” used to present the market portfolio for proposed risky assets. It is drawn from the risk- free point to the point of feasible region for the investments or assets that contains risk, which determines the value of risk factor for the proposed investment. A tangent line resulting from the combined point of market portfolio and assets that are risk free represents the Capital Market Line that depicts the “rate of return”. The Capital Market Line represents the risk factor through the model of Capital Asset Pricing Model that is used to measure the fair value of investment in comparison with the market price (Bertin 2016).
In view of the explanation of Capital Asset pricing Model and Capital Market Line, it can be said that there are certain similarities and differences between the two models that is used to determine the expected return of the proposed investments. CAPM is a model that measures the anticipated return of the investment in equity of the organization that is based on the anticipated market return, risk free rate of return along with the risk variance represented by beta (Demir, Fung and Lu 2016). Accordingly, the expected return of the investment portfolio is represented by the following formula Re = Rf + B [E (Rm) – Rf] which represents:
Re: Return on equity
Rf: Risk free rate of the securities
E (Rm): Expected rate of return on the portfolio of market
B: Beta coefficient and
B [E (Rm) – Rf]: represents the difference between the anticipated return of market security and rate of risk- free rate that is referred as market premium.
Similarly, Capital Market Line represents the tangent line based on the CAPM model that is used to plot the anticipated stock return on one axis against the corresponding beta on other axis. The slope of the capital market line presents and depicts the market premium to evaluate the overvaluation or undervaluation of the proposed investment (Kim and Kim 2016).
In order to measure the expected return of the proposed investment securities, it is essential to consider the total risk of security that involves two types of risk i.e. systematic risk and unsystematic risk. This element of risk is measured and variances and represented by beta coefficient which defines the sensitivity of the securities as per the change in the market return and market risk (Vasicek, McQuown and Vasicek 2016). Accordingly, Capital Asset Pricing Model is used to determine the expected return of the proposed investment, which is graphically represented by Capital Market Line. As total risk of an investment, security contains systematic risk that is related to the market and cannot be diversified as well as unsystematic risk, which is related to the particular stock and can be removed by considering the diversification process in investment. Hence, as per the CAPM Model, coefficient of beta represents the systematic risk of the securities, which is determined by using the co-variance of market securities as well as market variance (Parigi, Pelizzon and Thadden 2014).
The relationship between CAPM and CML determines the overall anticipated rate of return of the investment securities that associates the probable risk factor. Accordingly, the Capital Market Line provides the information on overvaluation or undervaluation of securities of the company. For instance, if expected rate of return of a security against its risk component beta is drawn over the capital market line, then the security is said to be undervalued. On the contrary, if expected return of a stock against its risk factor is drawn below the Capital Market Line, then the stock is said to be overvalued since the graph indicates that the investor would consider small amount of risk for the associated systematic risk (Bertin 2016).
Other than the similarities and relationship between the Capital Asset Pricing Model and Capital Market Line, the two models are different in certain terms. Capital Market Line represents the securities value considering the entire market in terms of probable risk and return to determine the efficiency of the investment portfolio.
On the contrary, Capital Asset Pricing Model is used to compute the expected return of the security by considering systematic risk, risk free rate of securities and bonds along with the market premium rate.
Further, Capital Market Line is considered to measure the performance of the investment portfolio using the capital budgeting technique to evaluate over or under valuation of proposed securities. However, CAPM model is determines expected return of proposed securities for individual investors that assist in analyzing the risk tolerance in accordance with the current market risk factor.
Capital Market Line is a graphical representation, which is dependent on the risk level and return level of the entire market portfolio stating the positive co- relation between the value of risk and anticipated return from the stock (Demir, Fung and Lu 2016).
It has been observed that the Capital Market Line presents better measure of effective and efficient investment portfolio since it consider the factor of overall market risk and economic inflation rate. Besides, Capital Asset Pricing Model provides value of expected return of a particular stock based on the current risk of the stock and market premium rate. Hence, CAPM model does not provide the result on overall market for the investment purpose since it considers a particular stock from the individual or organizational perspective. Moreover, Capital Market Line as well as Capital Asset Pricing Model is correlated which determines the efficiency of the investment return in the market and the efficiency of the investors to consider the risk element associated with the proposed investment (Mackay and Haque 2016).
Reference List
Bertin, C.H.A.B.I., 2016. Empirical Test of the Capital Asset Pricing Model (Capm) on The Equity Market of Nairobi. Indian Journal of Applied Research, 6(1).
Cairns, G., Goodwin, P. and Wright, G., 2016. A decision-analysis-based framework for analysing stakeholder behaviour in scenario planning. European Journal of Operational Research, 249(3), pp.1050-1062.
Chow, J.Y., 2014. Activity?Based Travel Scenario Analysis with Routing Problem Reoptimization. Computer?Aided Civil and Infrastructure Engineering, 29(2), pp.91-106.
Demir, E., Fung, K.W.T. and Lu, Z., 2016. Capital Asset Pricing Model and Stochastic Volatility: A Case Study of India. Emerging Markets Finance and Trade, 52(1), pp.52-65.
Fujimori, S., Kainuma, M., Masui, T., Hasegawa, T. and Dai, H., 2014. The effectiveness of energy service demand reduction: A scenario analysis of global climate change mitigation. Energy policy, 75, pp.379-391.
Kazlauskien?, V. and Christauskas, ?., 2015. Business valuation model based on the analysis of business value drivers. Engineering Economics, 57(2).
Kim, K.H. and Kim, T., 2016. Capital asset pricing model: A time-varying volatility approach. Journal of Empirical Finance, 37, pp.268-281.
Lee, S., Cho, C., Hong, E.K. and Yoon, B., 2016. Forecasting mobile broadband traffic: Application of scenario analysis and Delphi method. Expert Systems with Applications, 44, pp.126-137.
Mackay, W. and Haque, T., 2016. A study of industry cost of equity in Australia using the Fama and French 5 Factor model and the Capital Asset Pricing Model (CAPM): A pitch. Journal of Accounting and Management Information Systems, 15(3), pp.618-623.
Magni, C.A., 2016. An average-based accounting approach to capital asset investments: The case of project finance. European Accounting Review, 25(2), pp.275-286.
Parigi, B.M., Pelizzon, L. and Thadden, V., 2014. Stock market returns, corporate governance and capital market equilibrium. Corporate Governance and Capital Market Equilibrium (October 2014). ECGI-Finance Working Paper, (362).
Spronk, J., Steuer, R.E. and Zopounidis, C., 2016. Multicriteria decision aid/analysis in finance. In Multiple Criteria Decision Analysis (pp. 1011-1065). Springer New York.
Tjader, Y., May, J.H., Shang, J., Vargas, L.G. and Gao, N., 2014. Firm-level outsourcing decision making: A balanced scorecard-based analytic network process model. International Journal of Production Economics, 147, pp.614-623.
Vasicek, O.A., McQuown, J.A. and Vasicek, O.A., 2016. The Efficient Market Model. Finance, Economics and Mathematics, pp.169-194.
Wesfarmers.com.au. (2017). Home. [online] Available at: https://www.wesfarmers.com.au [Accessed 5 Jan. 2017].
Woolworthsgroup.com.au. (2017). Woolworths Group: Quality Brands and Trusted Retailing. [online] Available at: https://www.woolworthsgroup.com.au/ [Accessed 6 Jan. 2017].
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