Discuss About The Capital Management Components On Corporate?
In the market economy, one of the important factors of economic growth is capital accumulation and investment of capital. One of the crucial conditions for any business entity to ascertain viability, profitability and development of its own is the effectiveness of the invested capital. Based on the long-term goals the firms have, they incorporate the decision of financing and investing (Daunfeldt and Hartwig 2014). The likely outcome of the investment made are always concern of the business and the knowledge of such procured by them based on capital budgeting techniques and various analyses which are conducted prior the investments are being made.
The paper gives an outlined discussion about the role and requirement of capital budgeting. It further discusses the concepts of sensitivity analysis, scenario analysis, break-even analysis and simulation technique and their applicability in helping the investing business body to procure knowledge about the expected outcome of their actions of investments.
The paper is prepared based on the motive to show how such theoretical analyses concept applies to business decision-making process and to what extent it influences such decisions
In order to take any decision regarding investment, a business always needs to undertake capital budgeting process that helps the business entity determine whether to take up the investment in certain projects. A business organization has to take decision regarding various issues like installation of new machines, new plants, replacement of old machines, launching new products, research and development for new projects all of which requires funding through the capitalization structure of the firms. The capitalization source of the company includes debt, equity or retained earnings received by the companies (Dutta and Babbel 2014.). Capital budgeting is a technique that rightly tries to allocate resources for capital utilization and investment expenditure so that the firm is able to derive higher return from the investments made and deliverance of higher payoffs to their shareholders. Important procedures or concepts applied in capital budgeting are:
Capital budgeting is important to help a firm take decision regarding its investment decision but it is not the only component to be carried, as there are other analysis needs to be followed too. Some of them are sensitivity analysis, scenario analysis and break even analysis followed by stimulation techniques (Nas 2016).
The investment decision is exposed to many challenges regarding the strength weakness of the project they are invested in. This further brings forth the associated risk factor that comes up in almost with every decision. To ensure effectiveness of the implementations, the set of risks associated with any projects should be assessed. There comes the importance of sensitivity analysis. It helps the investor attain additional insight about the decision made for incorporating any investment (Damodaran 2016).. This is a technique that helps the business determine the difference of the impact of independent variables on certain dependent variable under given assumptions. The independent variables are used as input variable that specifies the boundaries for the impacts assessed (Xu and Yuan 2015). For example, how the bond prices are affected by changes in interest rate and currency exchange rates can be assessed by running sensitivity analysis where bond price is treated as dependent variable and rate of interest and currency rate as independent variables.
SA examines the extent and viability of any project based on the quantifiable variables associated with the investment decisions (Mathuva 2015). The greater the fluctuation of the parameters the lesser is the risk inherent in the project. Sensitivity analysis helps to derive the net benefits derived from the project along with making a quantitative analysis of their influence. It includes testing of the effects of variation the cost and benefit variables that are selected based on the project’s internal rate of return or net present value.
In the algorithm of investment risk analysis, sensitivity analysis is one of the important tools that effectively quantify the risk analysis. The major purpose is to quantify the riskiness, the possible consequences by evaluating the risk (Maroyi and van de r Poll 2012). This analysis helps managers to assess the responsiveness and sensitivity of net present value of any project to the changes in the variables that are used to calculate it. NPV depends on various independent variables like volume of sales, selling price, initial outlay, investment cost and components, variables costs, interest rate on loans, discount rate and so on (Ba?bura, Giannone and Lenza 2015). With changing situations they receive impacts when calculated under alternative assumptions which rightly evaluate the amount of sensitivity they have with respect to the changes over time. The vulnerability of the project with respect to the changes in various dependent variables are assessed. Application of sensitivity analysis helps in locating the variables to which NPV is responsive and sensitive too. The extent f their changes are also detected before the business starts resulting in negative NPV. The possibility of whether or not a project would fail is captured by the analysis (Damodaran 2016).. Controlling of the variables affecting the performance of NPV are important to be taken care of since negative present value acts as one of the risk factor in the investment that a business would certainly want to avoid.
The next component in analysis comes the scenario analysis, which involves the process of estimation made about the expected value of any portfolio investment after a period. The estimations are based on the changes of the factors related to security of portfolios such as rate of interest. This kind of analysis helps the business assess the changes that might take place due to unfavorable event and their impact on the net value of the investment made (Sargent 2013). To examine the effect of theoretical worst-case scenario of the decision, the scenario analysis plays important role.
This analysis brings forth various possible outcomes that might be developed in future instead of fiving one specific estimation (Burns and Walker 2015). The scenario analysis is excluded of extrapolation that is it does not depend on the past trends followed by historical set of data. It also discards the past expectations to remain valid for future estimation analysis.
There are various methods to encounter scenario analysis common one being determination of standard deviation of the monthly or daily returns of security followed by computation of the expected value of the portfolios (Daunfeldt and Hartwig 2014). Based on the position of the standard deviation above or below the average rate of return, the analyst derives reasonable amount of certainty about the change in the valuation of any investment in a given time period after running simulations of the extreme results (Kaplan and Mikes 2012). Scenario analysis helps the business analyze the result of the extreme outcomes related to business in order to design and develop business strategy.
The process of scenario analysis not only helps in examining the potent of investment but also helps in assessing the values shifts of various financial institutions. In order to examine different outcomes emanating from financial decisions made by the consumers this analysis is helpful tool. The potential outcome of any financial decisions taken by business can be evaluated based on such analysis.
The scenario analysis helps to evaluate the potential variability that the net present value of capital budgeting project has. Based on the different scenarios the net present values might change and that are effectively captured by the scenario analysis. Based on the analysis made by the analyst, estimation of expected cash flows are derived which is known as base-case scenario. Net present value is computed for both the outcomes of vest case and worst-case scenario (Lam, Cheung, Tang and Ng 2012). The analysis of worst-case scenario is very helpful for the managers as it allows them to reap an idea about the extent to the fall in NPV. How NPV is affected due to simultaneous changes in various factors are rightly captured under scenario analysis.
The break-even analysis helps the business locate its operative level that faces equality between received revenue and incurred cost or expenditure. This analysis helps the business set its margin of safety with regards to the profit and loss incurred by the company. The margin of safety is ascertained when generated revenues exceed the cost of the business that is the exceeding of the break even point of the business (Burns and Walker 2015). Revenues can fall even staying above of the break even point. The analysis is concentrated to supply side of the business dealing with the costs of the sales. The analysis excludes the demand side impact of difference in the price levels (Hasan 2013).
The conduction of break-even analysis depends on the mostly concept of three types of costs. They are fixed cost, variable cost and semi-variable cost.
Fixed cost consists of the cost that has no impact on it due to the increase or decrease in the amount or production a business undertakes. It is the cost the company has to incur irrespective of the business activity and its condition. This is one of the major component of the total cost of any business (Daunfeldt and Hartwig 2014). A company paying an amount of $10,000 per month to pay for the cost of lease even if the production is halted falls under fixed cost category. Cost for the lease of land, advertisement, rents are included in the fixed cost that needs to be maintained anyhow even if the productions are not running.
Variable cost is dependent on the production of output. They are positive function of production amount since as the production rises they rise and fall with the decrease in the production (Brealey et al 2012). This includes costs of the direct inputs such as materials used in production and direct costs of labor and capital. The variable cost in the long run increases steeply as the production in expanded.
Semi variable cost is also semi fixed cost that includes combination of both these type. Up to certain level the cost of production remain fixed and beyond that, the cost starts to increase as the production increases (Bodie 2013). Semi variable cost leads to greater level of total cost for the expanded production and a fixed amount of cost for no production at the extreme case. Labor costs of factory workers are of this type of cost where for regular working hours they receive a fixed pay off and for hours beyond that they receive extra pay offs depending on the hours (Ba?bura, Giannone and Lenza 2015).
After evaluating, the cost of production next step in the break even analysis is to ascertain the price level which is partly responsible in generating greater revenues combined with amount of sales. Even the amount of sales depend on the pricing further (Hwang and Masud 2012). The prices can be competition driven in order to capture the higher market share based on profitability. Penetration pricing is another strategy applied by business in order to set strategy that focuses on attracting larger customer base toward their products (Bierman and Smidt 2012). Variable cost-plus pricing is the method of adding mark up to total variable cost when it comes to set the prices. It is expected that the mark up covers for the total or partial of the foxed costs and
helps in generating profit.
This is stochastic linear programming helps the firm to derive the expected return of investments assessing the inbuilt risk factors in portfolios. It helps to assess the NPV associated with different projects (Bhattacharya 2014.). Different probabilities are associated with different outcomes and often it is not possible to produce exact probabilities of any event. Range of probabilities is existent. Having knowledge of different probabilities help in calculating the interrelations among the variables through the process of simulation. For example, a distribution of NPV can be derived based on the probable availability of cost-saving percentage and low usage of energy. This gives the probability assigned with each possible NPV (Bardach and Patashnik 2015). This further helps in deriving the discount rate to evaluate the uncertainty and riskiness associated with the NPV. Simulation helps in deriving the risk prone of the projects. Higher riskiness creates more hurdles for the business compared to lower risk detected. The adjustments of risk are hence important factor to be taken care of. There are two ways to adjust the returns of a project face higher risk by increasing the discount rate or making reduction the payment (Ba?bura, Giannone and Lenza 2015). Increasing the discount rate is composed of base risk free rate and a value added beyond a point depending upon the level of risk. Higher risk calls for higher premium and greater uncertainty leads to fall in NPV as the discounted rate for future are high. This further implies the necessity of the project to have higher internal rate of return to exceed the rate of hurdles (Hill 2013).
From the above discussion the role of capital budgeting teamed up with sensitivity analysis scenario analysis and breakeven analysis are well understood. In the modern world of market economy investment and capital expansion plays important role in ascertaining growth of business by tapping market potentials. How effective investment decisions are for the business organization are well analyzed based on these methods and techniques of analysis and simulations. How certain internal as well as external factors of business affect the business operation and the outcome of its decision are greatly based on the results of such analyses that helps the firm to identify and set strategies according to such issues. Thus in decision making of business entity the aforementioned analyses play bigger role consolidating the process of capital budgeting.
Ba?bura, M., Giannone, D. and Lenza, M., 2015. Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections.International Journal of Forecasting, 31(3), pp.739-756.
Bardach, E. and Patashnik, E.M., 2015. A practical guide for policy analysis: The eightfold path to more effective problem solving. CQ press.
Bhattacharya, H., 2014. Working capital management: Strategies and techniques. PHI Learning Pvt. Ltd..
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Bodie, Z., 2013. Investments. McGraw-Hill.
Brealey, R.A., Myers, S.C., Allen, F. and Mohanty, P., 2012. Principles of corporate finance. Tata McGraw-Hill Education.
Burns, R. and Walker, J., 2015. Capital budgeting surveys: the future is now.
Damodaran, A., 2016. Damodaran on valuation: security analysis for investment and corporate finance (Vol. 324). John Wiley & Sons.
Daunfeldt, S.O. and Hartwig, F., 2014. What determines the use of capital budgeting methods? Evidence from Swedish listed companies. Journal of Finance and Economics, 2(4), pp.101-112.
Dutta, K.K. and Babbel, D.F., 2014. Scenario analysis in the measurement of operational risk capital: a change of measure approach. Journal of Risk and Insurance, 81(2), pp.303-334002E
Hasan, M., 2013. Capital budgeting techniques used by small manufacturing companies. Journal of Service Science and Management, 6(01), p.38.
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Hwang, C.L. and Masud, A.S.M., 2012. Multiple objective decision making—methods and applications: a state-of-the-art survey (Vol. 164). Springer Science & Business Media.
Kaplan, R.S. and Mikes, A., 2012. Managing risks: a new framework.
Lam, K.C., Cheung, S.O., Tang, C.M. and Ng, S.T., 2012. Capital budgeting evaluation practices of building contractors in Hong Kong. Construction Economics and Building, 2(1), pp.81-93.
Maroyi, V. and van de r Poll, H.M., 2012. A survey of capital budgeting techniques used by listed mining companies in South Africa. African Journal of Business Management, 6(32), p.9279.
Mathuva, D., 2015. The Influence of working capital management components on corporate profitability.
Nas, T.F., 2016. Cost-benefit analysis: Theory and application. Lexington Books.
Sargent, R.G., 2013. Verification and validation of simulation models.Journal of simulation, 7(1), pp.12-24.
Xu, C. and Yuan, S., 2015. An analogue of break-even concentration in a simple stochastic chemostat model. Applied Mathematics Letters, 48, pp.62-68.
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