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USING ARIMA MODELS FOR TURNOVER PREDICTION IN INVESTMENT PROJECT APPRAISAL
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Abstract

In the contemporary investment project analyses, most critical point is how to estimate daily turnover of production, or service, based system. In order to make prediction, for investment in certain type of equipment more accurate, daily turnover in the system for automated car wash was observed, along with weather conditions.  According to observation,  ARIMA model for daily turnover and weather condition is created, according to Box-Jenkins procedure. Conclusion was made that daily turnover can be analytically expressed through daily weather conditions. Validity of observation is checked on second system that is installed in different town in Serbia. According to compared results, conclusion was made that ARIMA model of system daily turnover, predicted by dependent variable,  can be generally used as good predictor in investment analyses, or selective criteria for investment decisions.

 

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DOI: 10.5937/jaes10-2617

References

Box, G.E.P., Jenkins, G.M., 1987. Time Series Analyses, Forecasting and Control. 2nd ur. San Francisco: Holden-Day.

Ho, S.L., 1998. The use of ARIMA models for reliability forecasting and analyses. Computers and industrial engineering, 35 (1-2), 213-216

Jiang, B., Heise, D.R., 2004. The Eye Diagram: New Perspective on the Project Life Cycle. Journal of education for Business, pp. 10-16

Morris, P. W., 1998. Managing Project interfaces: Key Points for Project Success. Englewood Cliffs, New Jersey: Prentice-Hall.

Newell, M.W., Grashina, M.N., 2004. The Project Management Question and Answer Book. New York: AMACOM.

Tabachnik, B.G., Fidell, L.S., 2007. Using multivariate statistics (5th edn.). Boston: Pearson Education

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