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:
Arima / Box-Jenkins / investments / predictions / turnoverSource:
Journal of Applied Engineering Science, 2012, 10, 4, 197-200Collections
Institution/Community
Mašinski fakultetTY - JOUR AU - Petrović, Zoran AU - Bugarić, Uglješa AU - Petrović, Dušan PY - 2012 UR - https://machinery.mas.bg.ac.rs/handle/123456789/5806 AB - 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. T2 - Journal of Applied Engineering Science T1 - Using ARIMA models for turnover prediction in investment project appraisal EP - 200 IS - 4 SP - 197 VL - 10 DO - 10.5937/jaes10-2617 ER -
@article{ author = "Petrović, Zoran and Bugarić, Uglješa and Petrović, Dušan", year = "2012", 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.", journal = "Journal of Applied Engineering Science", title = "Using ARIMA models for turnover prediction in investment project appraisal", pages = "200-197", number = "4", volume = "10", doi = "10.5937/jaes10-2617" }
Petrović, Z., Bugarić, U.,& Petrović, D.. (2012). Using ARIMA models for turnover prediction in investment project appraisal. in Journal of Applied Engineering Science, 10(4), 197-200. https://doi.org/10.5937/jaes10-2617
Petrović Z, Bugarić U, Petrović D. Using ARIMA models for turnover prediction in investment project appraisal. in Journal of Applied Engineering Science. 2012;10(4):197-200. doi:10.5937/jaes10-2617 .
Petrović, Zoran, Bugarić, Uglješa, Petrović, Dušan, "Using ARIMA models for turnover prediction in investment project appraisal" in Journal of Applied Engineering Science, 10, no. 4 (2012):197-200, https://doi.org/10.5937/jaes10-2617 . .