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Bullwhip effect is undesirable in the supply chains, exacerbating its performance. Various factors can cause bullwhip effect, one of which is customer demand forecasting. In this paper, impact of forecasting methods on the bullwhip effect has been considered. A simulation study is implemented considering a supply chain consisting of one supplier and four retailers. A time series procedure (ARMA) is used as the forecasting method and is compared with two of the most applicable forecasting methods (moving average (MA) and exponential smoothing (ES)), from both bullwhip effect and forecasting accuracy point of view. Our findings show that having more accurate forecasting method is not equivalent to creating less bullwhip effect.