Abstract

The multiple techniques used for trying to predict the future prices of securities usually fall in two categories: statistical techniques and soft computing techniques. In the first category one can find ARIMA (autoregressive integrated moving average) or GARCH (generalized autoregressive conditional heteroskedasticity) models, and the former will be used in the present article. From the second category, the most important models are the artificial neural networks – ANN, and such a model will be compaired to ARIMA in order to see which one performs better in the goal of estimating Volkswagen’s future prices. It is widely known that this company was recently involved in a scandal which affected the company’s shares. Data used is comprised of daily prices for a period of 4,5 years, and the article’s main objective is to try and foresee the price for the next 6 months (the second semester of 2015). After this step, it can be observed which of the two models was more accurate, through comparison with the actual prices. The conclusion will confirm or will refute the superiority of a model over the other, in the mentioned context.

Authors and Affiliations