Predictive Modeling of US Winter Apparel Sales using Time Series Forecasting Method

Engy Shafik

Abstract


Fashion and apparel sales have always been an interesting aspect of study due to the immense number of controllable and uncontrollable variables that contributes to the total sales. In order to develop a sound predictive model for forecasting apparel sales a lot of factors can be incorporated to enhance the results and minimize the forecast error. This paper will present a Time Series Forecasting model of US Apparel and accessories sales for the winter season. This model is generated to shed the light on the unexpected loss incurred by retailers for the winter season of 2015 by incorporating weather variation as an influencer on the sales. This paper is also going to discuss some important managerial approaches which empower firms to deal better with unforeseen variabilities.

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