USING ARIMA MODELS FOR TURNOVER PREDICTION IN INVESTMENT PROJECT APPRAISAL
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.
Keywords
References
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