Statistical model for forecasting uranium prices to estimate the nuclear fuel cycle cost

Abstract

This paper presents a method for forecasting future uranium prices that is used as input data to calculatethe uranium cost, which is a rational key cost driver of the nuclear fuel cycle cost. In other words, thestatistical autoregressive integrated moving average (ARIMA) model and existing engineering costestimation method, the so-called escalation rate model, were subjected to a comparative analysis. Whenthe uranium price was forecasted in 2015, the margin of error of the ARIMA model forecasting wascalculated and found to be 5.4%, whereas the escalation rate model was found to have a margin of errorof 7.32%. Thus, it was verified that the ARIMA model is more suitable than the escalation rate model atdecreasing uncertainty in nuclear fuel cycle cost calculation.