The investment risk assessment for a new product launch.

Petre, Mihai ; Ispas, Constantin ; Mohora, Cristina 等

1. INTRODUCTION

1.1 Investments Role in Social-Economic Environment

Investments play an important role for companies because it affect, at the same time, the demand and the offer.

The implementation of a project in products manufacturing and/or services area results in offer growth and diversification and, if the offer is validated on the market, additional income for the companies (Caouette, 1998).

The projects and investment programs developement result in capital growth. So, investments are the main things for real economic restructuration, creating newer and more viable structures regarding the societies strategic targets. Investment projects are the main methods for obtaining newer technical and technological solutions provided by scientific research.

The investment concept is identical with: to transfer, to provide, to offer and it can be extended to efforts made in order to gain future benefits (by efforts, it does not mean only financial ones).

The share of "intellectual" investments becomes more important but, for present projects, it is very difficult to evaluate its value in money.

From the dedicated literature, the most pertinent definition, considered by a large group of specialists, is the one made by Pierre Masse ("Les choix des investissements". Dunod, Paris) which defines investment as a "change of an immediate and certain satisfaction, which is abandoned, for a future expectation that can be obtained using as prime element the invested goods", in short version, "an uncertain spending for an uncertain future".

The common point consists in the nature of engaged resources: material resources, human resources, technical resources, monetary resources, etc.

The concept of investment emphasis on the domain of application and through its content.

Starting from project manager "main paper", the investment risk is calculated. The first step in risk assessment, named TOP RANK, calculates the sensitivity analysis, choosing the significant inputs for which the selected output is more sensitive (Ispas, 2005).

The second step consists on the output variation risk and the final value in euros of the input significant variations.

2. INVESTMENT RISK ASSESSMENT FOR THE NEW PRODUCT LAUNCH

Sensitivity analysis shows the profitability indices distribution area, used for different evolution scenarios. The key factors are to test the project benefits and to order the indices regarding their impact on the outputs.

The purpose for a sensitivity analysis is to identify the model variables or to model critical parameters, of which variations, positive or negative, in comparison with the optimal case study values, leads to the most significant variations on profitability main indices, respectively RIR and VNP.

The identification criteria for these variables are changing in accord with the project characteristic and must be done with high accuracy.

The sensitivity analysis was made calculating in Excel the "main paper", with Palisade Decision Tools software, important software for sensitivity analysis and risk assessment case study.

The "What If" simulation has generated the results which proved that the most important share in risk assessment is "the exchange rate", the remaining parameters having insignificant influence on the output.

2.1. Risk analysis

2.1.1 Implementing the mathematical model in Palisade @Risk; Inputs

Starting from the sensitivity analysis, the mathematical model is made with Excel and it is correlated with the results obtained with TOP RANK. The economical and financial market information, the "exchange rate" input, in thousands of lei/thousands Euro at an exchange rate lei/Euro, was defined as the most significant variable that generates risk (Ispas, 2005).

Variable element modelling

From GENERAL DEVICE, the exchange rate in thousand of lei/ thousands of euros from 17.03.2008 was used. Considering the estimated forecast information from National Bank, triangular probability distributions were defined, concentrated around the medium value of 3,7538, with a maximum value of 3,9 and a minimum value of 3,5.

The program ran a Monte Carlo simulation with one hundred iterations. Each iteration acquired new values for "GENERAL DEVICE" (without VAT).

2.1.2. Monte Carlo simulation statistical results using 10 000 iterations

The results analysis

Analyzing the table and variable statistical summary of the model it results that the "GENERAL DEVICE" value (without VAT) can vary between a minimum value of 1 250 thousands of [euro] and a maximum value of 1 346 thousands of [euro], with a 90% probability of occurrence. The statistical average value is around 1 291 thousands of [euro], extremely close to the estimated value of 1 293 thousands of [euro] obtained through direct calculation; this result places the project targeted value, in risk conditions, way below the +/- 10% value, accepted by UE standards for eligible reserve funds. Figure 1 presents the statistical information for the results.

The worst and best case scenarios

Sensitivity and risk analysis allows also a scenario analysis for the worst and the best case scenarios. From the values of statistical distributions obtained for "GENERAL DEVICE" (without VAT) result a probability value below 5% in order to obtain an amount over 1 350 thousands of [euro], also a probability value below 5% for an amount below 1240 thousands of [euro].

Conclusions for sensitivity and risk analysis

Sensitivity and risk analysis emphasize model integrity and stability for the social and economical analysis.

This leads in accepting the work examined hypothesis and the fact that under an unfavourable variation of influence factors, the investment will continue to be profitable (Chan, 2002).

Assumed risks are technical risk, financial risk, institutional risk, legal risks.

The project execution risks can be internal type or external type.

This is based on the three dedicated key systems of project management.

The supervising system

It consists in the permanent comparison of an actual situation with the project planning: natural evolution, financial expense, quality (the project objectives are identical with the created assets).

A suitable deviation from the supervising system (a programmed evolution) leads to a decision package from project managers who will decide if some recovering measures are possible or not.

The control system

This system will have to act fast and efficient when the supervising system indicates a deviation from its course.

Informational system

The informational system will support the control and supervising systems, providing the project team (in a short period of time) the necessary information.

For project supervision (the first key system of project management), the imperative information are the following:

* The measurement of physical evolution.

* The measurement of financial evolution.

* Quality control.

* Other particular information which offer specific interest.

[FIGURE 2 OMITTED]

The financial control mechanism

A financial control mechanism, which assures an optimum found utilization, is a circular conditions system which helps on achieving project objectives, avoiding the unforeseen events and notify, in time, about the risks which demand corrective measures (Petit, 2000).

The main effective tools will rely on quantity and quality analysis of results.

Accountancy and financial management

The accountancy and financial management will be handled by a specialist accountant who will manage three major tasks:

1. Operations planning, control and registration.

2. Information presentation (the first two items are tasks of the specialist accountant).

3. Financial decisions (management competence).

3. CONCLUSIONS

The analysis for risk distribution is a common way for project manager, showing where the risk resources can be found. There were marked several imperative ideas:

* Through time, the project has to be adaptable to changes

* The information regarding risks represents critical elements for analysis.

In its evolution, the risk assessment for industrial companies' investments gained flexibility and adaptability through modelling and simulation of economic processes and also, the inter-disciplinary nature has been dramatically emphasized.

This paper presents an alternative in analyzing different economic processes with a simulation model made with a system of software internationally recognized. This software uses the specific Microsoft Excel routines, presenting a big degree of accessibility and comprehensively, creating a useful and easy to understand language used by a large number of experts from developed countries.

The modern management for investment projects leads in merging the real investments theories with financial theories in their superior form, enabling project management models to be made and to be optimized with simulation and risk analysis.

The risk analysis and the sensitivity emphasize the integrity and stability of the social economic analysis. According to that, it means to accept the work proposed hypothesis and also the fact that, in the conditions of unfavorable factors of influence, the investment will remain profitable.

4. REFERENCES

Caouette, J.B., Altman, E.I., Narayanan, P.(1998). Managing Credit Risk, The Next Great Financial Challenge, John Wiley&Sons.

Chan S., Ronald P., Kenneth, C., Ming. J. Zuo (2002) Analyse economique en ingenierie Ed. Pearson Education Canada Inc, Toronto, Ontario, ISBN 2 84211 198 2.

Damodaran A. (2002) The Promise and Peril of Real Options, Stern School of Business 44 West Fourth Street New York, NY 10012.

Ispas C., Petre M., Mohora C., Balan E. (2005). Hedging and others financial derivatives, new instruments of risk management in Romania- Proceeding of the 7-th International Conference on: The Modern Information Technology in the Innovation process of the Industrial Enterprises pag. 64, Genoa, Italy September 8-9. ISBN: 88-7544-050

Petit J., Evaluation, Editura Stern Stewart & CO, Vars,ovia, 2000.

Fig. 1. Statistical information for distribution results

Detailed Statistics

Name TOTAL GENERAL In mii lei/mii euro
 (fara TVA)/ la cursul lei/e
 mi euro
Description Output Risk Triang
 (3,5; 3,75; 3,8)
Cell D41 C5
Minimum 1238,175 3,517032
Maximum 1366,757 3,882334
Mean 1234,03 3,71661
S td Deviation 23,12673 3,311274E-02
Variance 848,3665 6.307728E-03
Skewness 0,3425137 -0,2438258
Kurtosis 2,513871 2,450162
Errors Calculated 0 0
Mode 1275,267 3,722806
5X Perc 1250,076 3,568106
10% Perc 1256,834 3,53666
15% Perc 1262,808 3,620731
20% Perc 1267.518 3.638352