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Process of Capital Budgeting and Its Stages

Question:

Discuss About The Simulation Techniques Financial Management?

The term capital budgeting can be said to be a process identification and selection of investments in various types of assets in either long term or short term. The process of capital budgeting is an ongoing process since a business organization is expected to make investments continuously. There are five stages involved in the process of capital budgeting. These stages include Screening and selection of investments (Stage 1), Proposal of capital budgeting (Stage 2), Authorization and approval of budgeting process (Stage 3), Tracking the project (Stage 4), and Post completion Audit (Stage 5) (Peterson & Fabozzi, 2002; Bierman & Smidt, 2007).

There are various techniques through which the capital budgeting decisions are taken such as Internal Rate of Return technique and Net Present Value technique, which can be used to make an evaluation of the project, i.e. whether to carry on with the project or not. The term Internal Rate of Return or simply IRR can be defined as a rate of discount on which the Net Present Value or the NPV of project cash flows becomes zero (Investopedia, 2017). In other words, IRR can be said to be a metric which is often used for the measurement of profitability of various alternatives of potential investments.

Net Present Value or NPV, on the other hand, can be defined as the present value of cash inflows minus the present value of cash outflows (Investopedia, 2017; Megginson et al., 2008). This is also used to evaluate the profitability from a given project.

Thus, in this assignment, various techniques such as sensitivity analysis, scenario analysis, simulation techniques and break even analysis in relation to the techniques of capital budgeting have been analyzed.

There are various ways in which risks can be handled effectively, which include both conventional and modern techniques. The modern techniques of handling risks in a capital budgeting decision project are statistical, quite complicated and sophisticated techniques of assessment of risks. These tools and techniques are specifically used for measuring risks in a capital budgeting decision. The detailed analysis of four of the major risk assessment techniques of capital budgeting are given below:

The most common method of evaluating risk in a capital budgeting decision is sensitivity analysis. With the help of this technique, the managers of a business organization can measure the sensitivity of a capital budgeting decision with respect to the changes whether big or small in the values of various factors. In other words, sensitivity analysis can be said to be a manner in which the changes in Net Present Value of a project can be analyzed if one or more variables associated with it are changed. This technique provides an indication of the level to which the Net Present Value and the Internal rate of Return are sensitive to changes in associated variables. If the sensitivity of the NPV of a project is on the higher side, it is indicative of the fact that the variable which is changed is critical for the project (Bedi, 2005). Various steps are involved in using sensitivity analysis for capital budgeting projects. These steps include the following:

Techniques of Capital Budgeting: Internal Rate of Return and Net Present Value

It is quite essential to identify all the variables which have the capability to influence the NPV or the IRR of a project.

The next step is to define the underlying relationship between the NPV or IRR and other variables.

After providing the definition, it is rather essential to analyze the impact of the change that has occurred in each of the variables on the NPV or IRR of the project.

While performing sensitivity analysis on a project, the decision maker has to take into consideration the NPV or the IRR of the project for each of the forecast. This analysis is based on three important assumptions, which are Optimistic, Expected and Pessimistic. These assumptions allow the manager of the project to ask 'What if' questions. For instance, what is the net present value of a project if the sales increase or decrease? Another question includes, what is the impact on the NPV of a project of increase or decrease in the selling price of the products.

Thus, it can be said that the sensitivity of change in one variable associated with a project can be measured with the help of using sensitivity analysis tool. This tool is also called as 'What if' analysis tool and it measures the sensitivity of the outcome of the project to changes in one or more variables. Such variables include change in volume, sales, price of the raw materials and purchases. The outcome of a project is more dependent upon particular types of inputs which are associated to the project rather than other inputs. If everything is kept constant and the change is made in one variable which is directly associated with the project the outcome from the project is bound to change. Thus, with the help of sensitivity analysis, we can analyze how sensitive our project is to change in volume or sales rather than WACC or any other variable. After this analysis, the managers will be able to focus upon putting in resources for ensuring accuracy in estimation for the inputs that are required so as to make the project a success (Madura, 2008; Samonas, 2015).

An example can be used to explain the process. A manufacturing company has to undertake a new project. The NPV calculated by the manager of the project is in positive, say $ 50000. The outlay required for the project is approximately $ 250000. The management of the company was interested in finding out the impact of change in selling price on the project's NPV. It is to be further assumed that the sensitivity analysis indicates a decline in selling price of the project by 5% and this change is likely to make the NPV negative. The signal given by this is that the project which is going to be undertaken is highly risky. On the other hand, if the NPV continues to be positive even with decline in sales by 25%, the project can be said to be having a low level of risk.

Risk Assessment Techniques for Capital Budgeting

It is clear from the above example that sensitivity analysis is essential for making the manager understand the level of risk involved in any new project which is planned to be undertaken by the organization.

It is widely known that the most common tool to assess project risk is sensitivity analysis. However, apart from sensitivity analysis there are some other tools as well which are often used by managers to determine risks while making capital budgeting decisions. The managers of an organization are always interested in evaluating the impact on a project given that all major variables change at the same point of time. This is a limitation of sensitivity analysis as the impact of change in only one variable can be determined. However, this limitation of sensitivity analysis can be resolved by scenario analysis. This method helps in the measurement of Net Present Value (NPV) of the project in different scenarios. It also includes making the change in several variables at one point of time since all the variables are interrelated with each other. In this technique, all the possible future events are analyzed by considering various alternative results (Baker & English, 2011). In a scenario analysis, there are several scenarios for showing possible future results and it is rather useful for generation of a combination of three different scenarios, namely, pessimistic, an optimistic and a most likely scenario. As per the experience of various experts, these three events or scenarios are essential for further discussion. However, any more scenarios than this will lead to an unclear analysis. This analysis basically has its focus upon estimating the value of a portfolio and whether it will increase or decrease if there is a best case scenario or a worst case scenario (Shodhganga, 2017).

  • The first is related to determining the factors on the basis of which various scenarios will be built.
  • The second one is related to identification of number of scenarios for analyzing each of the given factors.
  • The third one is related to the estimation cash flows from the asset under each of the given scenarios.
  • The fourth step is related to estimating the probabilities and on the basis of such probabilities computation of expected NPV will be undertaken (Dayananda, 2002).

The most crucial variable on which the capital budgeting decisions are usually made is the volume of sales that will be generated if a project is undertaken. If any organization is planning to enter into a new market, it is rather difficult to analyze and evaluate the sales from the project. This is the major reason of considering sales the most essential variables as compared to the others. One of the most popular techniques to evaluate capital budgeting decisions is break even analysis. It is usually used for evaluating the relationship between profitability of the organization as well as sales volume (Cafferky, 2010). There are several types of breakeven measures such as pay-back period which can be interpreted on the basis of the time period till the project attains break-even point. However, the time value of money is completely ignored in this break even analysis (Shim & Siegel, 2007). All the measures of the break-even point have a same types of goal. With the help of break-even analysis, the managers of a project will be able to determine the volume of sales that would be generated if a project is accepted. With the help of this information, the managers will be able to take a capital budgeting decision whether the project must be accepted or not and whether the project will be profitable in the long run (Brigham & Houston, 2015).

Sensitivity Analysis

One another technique to identify the level of risk while undertaking a new project is the simulation technique. Simulation technique is a statistical tool which is often employed by the managers to identify the level of risk involved in a project while making capital budgeting decisions. Simulation model is somewhat related to sensitivity analysis. However, there are more advantages of the simulation model than the sensitivity model. This method is more comprehensive than the model of sensitivity analysis. In this method, the impact of a single variable on NPV of a project is not tested rather the model of simulation technique helps in enabling the probable value distribution of NPV with respect to changes in all the variables. This change can be tested in one run only. This method provides better information and understanding of the various kinds of risks associated with decisions related to investments. In order to perform effectively, the simulation process requires a computing package which is sophisticated and latest as it helps in generating the results of the process with ease (Chan & Wong, 2015).

There are various steps that are involved in the process of simulation which helps in making good investment decisions. The first step involved in the process is related to developing a model specific to the investment project which is going to be used by the software in computer. After the development of the model, a random value is calculated by the computer which is in terms of NPV (Shodhganga, 2017). This will be done for each and every identified variable with respect to the model. For each random values set generation of a new series of NPV as well as cash flows. The most significant variables in a particular project of capital budgeting are the size of the market, share in the market, sales price, fixed costs, salvage value of the assets, variable cost and also the rate of growth. Generation of random values is repeated over a number of times. This activity of generation of random numbers helps in developing probability distribution. This probability distribution so generated helps in the computation of expected value of the standard deviation and also the NPV of the project. This value of standard deviation so derived is then used to determine the risk related to the project (Jain & Khan, 2007).

Conclusion

From the above explanation it can be deduced that the development of probability distribution is not only more dependable but it allows the managers to take decisions continuously with possible outcomes rather than taking decisions at a single point estimation.

References

Baker, H.K. & English, P., 2011. Capital Budgeting Valuation: Financial Analysis for Today's Investment Projects. John Wiley & Sons.

Bedi, A., 2005. Capital Budgeting. Deep and Deep Publications.

Bierman, H. & Smidt, S., 2007. The Capital Budgeting Decision: Economic Analysis of Investment Projects. Routledge.

Brigham, E.F. & Houston, J.F., 2015. Fundamentals of Financial Management. Cengage Learning.

Cafferky, M., 2010. Breakeven Analysis: The Definitive Guide to Cost-Volume-Profit Analysis. Business Expert Press.

Chan, N.H. & Wong, H.Y., 2015. Simulation Techniques in Financial Risk Management. John Wiley & Sons.

Dayananda, D., 2002. Capital Budgeting: Financial Appraisal of Investment Projects. Cambridge University Press.

Investopedia, 2017. Internal Rate Of Return - IRR. [Online] Available at: https://www.investopedia.com/terms/i/irr.asp [Accessed 17 September 2017].

Investopedia, 2017. Net Present Value - NPV. [Online] Available at: https://www.investopedia.com/terms/n/npv.asp [Accessed 17 September 2017].

Jain & Khan, 2007. Financial Management. Tata McGraw-Hill Education.

Madura, J., 2008. International Financial Management. Cengage Learning.

Megginson, W.L., Lucey, B.M. & Smart, S.B., 2008. Introduction to Corporate Finance. Cengage Learning EMEA.

Peterson, P.P. & Fabozzi, F.J., 2002. Capital Budgeting: Theory and Practice. John Wiley & Sons.

Samonas, M., 2015. Financial Forecasting, Analysis and Modelling: A Framework for Long-Term Forecasting. John Wiley & Sons.

Shim, J.K. & Siegel, J.G., 2007. Handbook of Financial Analysis, Forecasting, and Modeling. CCH.

Shodhganga, 2017. Capital Budgeting Practices - A Theoretical Framework. [Online] Available at: https://shodhganga.inflibnet.ac.in/bitstream/10603/43628/8/08_chapter%202.pdf [Accessed 17 September 2017].

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