The financial projections used in decision-making are associated with a degree of uncertainty regarding the correct choice of the hypotheses used or the certainty of the value of the variables, which is why it is necessary to place ourselves in several scenarios, in which the hypotheses and the value of the variables over which we have less control and which in turn have the greatest impact on the results must be varied. expected results. The above process is known as Sensitivity Analysis.

Purpose of sensitivity analysis: it consists of improving the quality of the information used so that the decision maker has additional tools that allow them to achieve better results and generate greater competitive advantages.

Sensitivity Analysis, also called Post-Optimization Analysis, also consists of determining how sensitive the optimal solution is to the change of some of the data or parameters, keeping the rest fixed (John & Faulín, 2023).

Intangible and intangible financial modeling, sensitivity analysis consists of analyzing how the different economic values of a set of independent variables affect a specific dependent variable, as well as knowing how it will respond, among the different economic scenarios.

In finance, sensitivity analysis is used to model the performance outcome of changes in interest rates, and asset prices, as well as changes in demand, in the formation of investment portfolios and the mix of their assets. Also, changes in systemic or market risk, unsystematic risk, as well as the change in the variables associated with different investment strategies.

Sensitivity analysis is the procedure by which it is possible to determine how much the objective function (IRR or NPV) is affected or how sensitive it is to changes in certain variables of the investment, considering that the others do not change. (Baca, 2022; Morales & Morales, 2009).

Forms of study of sensitivity: according to research conducted by John and Faulín (2023).

The first is to solve the entire problem again every time some of the original data has been modified. This method can take a long time to determine all the variants when we are faced with a large set of possible changes.

The second way is that once a problem has been solved, we proceed to analyze how the optimal result obtained would be affected by the variation within a "tolerable" range, of the value of one of the variables, keeping the value of the remaining variables fixed.

If the effects of varying more than one parameter (or a parameter beyond the “tolerance range”) are studied, the problem must be reprogrammed.

Methods to study sensitivity: to obtain a measure of the variability in the results according to the research of Tejeda and others (2015) and Pérez and others (2012), the following methods can be mentioned:

Informal method: the analyst assesses the stability of the variables.

Decision tree: Future decision points and possible uncertain events are displayed; in which case each alternative is presented as a branch of the tree.

Monte Carlo model: links sensitivities and probability distributions of input variables. An uncertainty analysis allows you to quantitatively assess the variability of the model components for a specific situation and deduce an uncertainty distribution for each state or output variable of the model (Monod et al., 2006). Generally, this analysis is carried out using Monte Carlo simulation (Saltelli et al., 2008).

Dupont Method: measures the company's profitability about sales, and total asset turnover, which indicates how efficiently assets have been used to generate sales.

Software and sensitivity: there are different software’s on the market, among them we can mention the following: @RISK, Managerial Analyzer Delfos Pro, Oracle Crystal Ball, EasyPlanEx, RealiaSoft RENO, MultiPlanEx, these softwares perform financial analysis, investment projection, as well as the financial sensitivity analysis.

Economic and financial indicators are useful tools that benefit organizations by facilitating timely and appropriate decision-making in relation to their corporate and financial strategies.

Next, the evolution of some economic and financial indicators of the Mexican environment is described and shown to facilitate decision-making related to personal and business strategies in an integral manner.

1. NATIONAL CONSUMER PRICE INDEX (INPC)

Born in 1995 and reflecting changes in consumer prices, it measures the general increase in prices in the country. It is calculated fortnightly by the Bank of Mexico and INEGI (2021). INPC is published in the Official Gazette of the Federation on the 10th and 25th of each month. The reference period is the second half of December 2010.

2. THE PRICE AND QUOTATION INDEX OF THE MEXICAN STOCK EXCHANGE (IPC)

Represents the change in the values traded on the Mexican Stock Exchange concerning the previous day to determine the percentage of rising or falling of the most representative shares of the companies listed therein.

3. EXCHANGE RATE

It is the value of the Mexican peso concerning the dollar calculated with the daily average of the five most important banks in the country, which reflects the spot price (cash), negotiated between banks. It is highly related to Inflation, the interest rate, and the Mexican Stock Exchange.

4. EQUILIBRIUM INTERBANK INTEREST RATE (TIIE)

On March 23, 1995, the Bank of Mexico, to establish an interbank interest rate that better reflects market conditions, released the Interbank Equilibrium Interest Rate through the Official Gazette of the Federation.

5. CETES RATE OF RETURN

6. INVESTMENT UNITS (UDIS)

The UDI is a unit of account of constant real value to denominate credit titles. It does not apply to checks, commercial contracts, or other acts of commerce.

In these uncertain times, it is very important to apply the best mathematical models to carry out the appropriate analyzes that offer us the necessary information to make business decisions related, among others, to investment, opportunity costs, market share, sales forecasts, plans business, business valuation or risk assessment.

REFERENCES

Baca, G. (2022). Project evaluation. México: McGraw Hill.

BANXICO. (2024). Sistema de Información Económica. México, Banco de México. Link: http://www.inegi.org.mx/sistemas/bie/

INEGI. (2024). Banco de Información Económica. Mexico: Instituto Nacional de Geografía y Estadística. Link: http://www.inegi.org.mx/sistemas/bie/

John, A. A, & Faulín, J. (2023). Sensitivity Analysis with Excel and Lindo. UOC, e-Math Project: Funded by the Secretary of State for Education and Universities (MECD).

Monod, H.; Naud, C. & Makowski, D. (2006). Uncertainty and sensitivity analysis for crop models, pp 55-96. In Working with dynamic crop models. Evaluation, analysis, parameterization, and applications. Wallach, D.; Makowski, D.; Jones, J.W. (eds). Elsevier. Amsterdam.

Morales, A., & Morales, J. (2009). Investment projects. Evaluation and formulation. McGraw Hill: Mexico.

Pérez, S., Cruz, D. & Quiroz, L. (2012). Sensitivity analysis of financial indicators in the evaluation of investments. In MSMEs. VI Meeting of Research in Economic and Administrative Sciences.

Tejeda, R., Trueba, A., López, N., & Rodríguez, R. (2015). Development of an information system for the analysis of financial sensitivity for Mexican Micro, Small and Medium Enterprises. In Micro, small and medium-sized enterprises in the economic, cultural and technological development of Mexico.

Saltelli, A.; Ratto, M.; Andrew, T.; Campolongo, F.; Cariboni, J.; Gatelli, D.; Saisana, M. & Tarantola, S. (2008). Global sensitivity analysis. The first. John Wiley and Sons. New Jersey, USA. 292 p. doi: 10.1002/9780470725184.oth1

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