Introduction:
A Feasibility or Feasibility Study establishes the conditions that make the investment project viable, that is, that allow it to be carried out successfully; It also determines the functions or priorities to be taken into account throughout its development. To carry out this feasibility study, the traditional methods for the Financial Evaluation of an investment project should be used, such as the Net Present Value, the Internal Rate of Return and the Payback Period.
The consideration of risk in the evaluation of an investment proposal can be defined as the process of developing the probability distribution of some of the economic criteria. Generally, the most common probability distributions obtained in an evaluation correspond to the Net Present Value and the Internal Rate of Return. However, to determine the probability distributions of these comparison bases, it is necessary to know the probability distributions of the uncertain elements of the project such as: life, cash flows, interest rates, changes in parity, inflation rates among others.
In the financial evaluation of investment projects, a risk is associated that is explained by the uncertainty involved in considering a NPV equal to zero, that is, that the project is affordable since I recover only what I invest, a NPV greater than 0, is that is, that the project is profitable and I recover the investment with profits and a NPV less than 0, that is, that the project is not profitable, without taking into account other variables such as the IRR which has to be greater than the opportunity cost of capital.
This justifies the need to study uncertainty, which means that more things can happen than will.
For this reason, other procedures have been developed for project analysis, such as sensitivity analysis, stalemate analysis, simulation, and decision trees.
Simulation is a sophisticated system with statistical bases to deal with uncertainty by gathering different components of cash flows in a mathematical model that by repeating the process many times, a probability distribution of project returns can be established.
The performance of the simulation provides an excellent basis for making decisions, as the decision maker can consider a continuum of risk-return alternatives rather than a single point estimate.
Definition of Simulation.
"Simulation is a numerical technique that is used to carry out experiments on a digital computer, based on a logical-mathematical model that is programmed in the computer and that describes the behavior of the components of the system and their interaction over time." (one)
“Simulation is a specific type of modeling in which we try to represent reality in a simplified way. As with mathematical-statistical models, simulation models have a series of inputs or starting data that the researcher includes in the model and a series of outputs or results that emerge from it. " (two)
«The simulation is the representation of a process or phenomenon by means of another simpler one, that allows to analyze its characteristics; But the simulation is not only that, it is also something very daily, nowadays, it can be from the simulation of an exam, which the teacher does to her student for a ministry exam, the
production of textiles, food, toys, construction of infrastructures by means of models, even virtual training of combat pilots. » (3)
"Simulation is nothing more than the use of a system model that has the desired characteristic of reality, in order to reproduce the essence of real operations (…)" (4)
"It is a representation of reality through the use of a model or other mechanism that will react in the same way as reality under a set of given conditions." (5)
Simulation is very useful to solve a business problem in which all the values of the variables are not known in advance, or are only partially known, and there is no way to find them easily.
It consists of the construction of a certain type of mathematical model that describes the functioning of the system in terms of individual events and components. In addition, the system is divided into elements and their interrelations with a predictable behavior, at least in terms of a probability distribution, for each of the possible states of the system and its inputs.
Misuse of Simulation.
The financial manager is like a detective, who must use all the clues. The simulation should be as one more way to obtain information about expected managerial flows and risk. But the final investment decision applies only one figure, the net present value.
The financial manager is not given the cash flow distributions, but the net present values or the internal rate of return. Isn't a complete distribution of net present values better than a single number? But we will see that this extra reasoning is better and leads the CFO into a trap.
The cash flows from each iteration of the simulation model are converted to a net present value by discounting them at the risk-free rate. Why are they not discounted at the opportunity cost of capital? Because if you know what this is, you don't need a simulation model, except perhaps to facilitate forecasting of cash flows. The risk-free rate is used to avoid prejudging the risk.
The expected net present value does not take risk into account. Risk is reflected in the dispersion of the net present value distribution. Thus, the term net present value takes on a very different meaning than usual. If an asset has a certain number of possible present values, it makes little sense to associate the present value with the price at which the asset could sell in a competitive capital market.
If two projects that are not related are combined, the risk of the net present value of the combined projects will be less than the average risk of the net present values of the two separate projects.
This not only goes against the principle of value activity, but also encourages promoters of marginal projects to disrupt the system by submitting joint proposals.
It is very difficult to interpret the distribution of net present values. Since risk-free time is not the capital opportunity cost, there is no economic basis for the discounting process. Since the mechanics as a whole are arbitrary, managers can only be told how to decide or what to do if inspiration never comes.
Some of these difficulties can be avoided by presenting a distribution of internal rates of return. This avoids the use of a discount rate
arbitrary at the expense of introducing the problems associated with the internal rate of return. In addition, the manager is again left contemplating the distribution without guidance regarding the appropriate balance between expected returns and profitability variances. However, the standard deviation of the internal rate of return could be used as an approximation of the relative risk of projects in the same line of business.
Steps to follow to simulate an investment project.
The steps to follow to simulate an investment project are very well exposed by Raúl Coss (6) and correspond to those defined by other authors in a general sense.
The logic to follow to simulate an investment project is as follows:
1. Input data.
- Tax rate Opportunity cost of capital Project parameters and their probability distributions
2. Random variable generator.
- Normal.Uniform.Exponential.Empirical.
3. Investment model.
Depreciation.
- It is calculated based on the type of asset and the industrial activity in which they are used.
Evaluation criteria.
- Internal Rate of Return, Net Present Value, Return on Investment, Payback Period.
4. Probability distribution of the selected evaluation criterion.
- Histogram Cumulative histogram.
5. Statistical analysis.
- Mean Standard deviation Range
6. Decision.
Conclusions.
- The advantages of using a financial simulation model to know the viability of an investment project is that these models are applicable to a multitude of products and sectors. They can be adapted to the specific characteristics of the project under study. A financial simulation model allows you to devote your attention to making the decision whether or not to invest in the project, or to focus on improving those aspects that can make it more profitable. Instead of wasting time designing complex financial models, you just use them. It improves the decision-making process because when your provisions have a high financial impact, a simulation model allows you to change the key points of your investment and evaluate multiple scenarios. You will immediately see the effects, and you can,reach optimal decisions quickly and easily.
Bibliographic references.
- Hillier, FS and Lieberman, GJ Introduction to Operations Research. McGraw - Hill Interamericana. P. 153. 1991.FIERING, M. B and M. M Hufshmidt: "Simulation Techniques for the Design of Water Resources Systems". Harvard University Press, Massachusetts, USA, 1966. p. 205. Ariza, FJ (1997a). Use of simulation to control errors in rasterization. In Mapping n1 p. 39. Ariza, FJ (1997c). Simulation and decision making with GIS. PhD course. Jaen University. p. 45.Thierauf, RJ and Grosse, RA "Decision making through operations research." Chapter 15, Mexico, 1999, p. 463 - 464.Coss, RB 1997. »Analysis and Evaluation of Investment Projects». Editorial Limusa. Mexico DF p 61- 78.
