Monte-Carlo simulations

Forecasting an ARIMA (0,2,1) using the random walk model with drift, MPRA Paper 31841, University Library of Munich, Germany. Ιn common with Ι. Kevork.

In this paper we show that the random walk model with drift behaves like an ARIMA (0,2,1) when its parameter θ is greater but close to –1. Using the random walk for predicting future values of an ARIMA (0,2,1) process, we find out that when θ is not so close to –1, the performance of the prediction interval for the period forecast is not satisfactory. Particularly, for large, the achieved coverage, namely, the probability the prediction interval to include the future value is quite low.