Nowadays the Stock Exchange plays an important role in everyday's life. People can be rich in a short time, but they can lose everything as well. But one can benefit from a well-defined stock strategy. In the world there are a lot of methods to define an appropriate stock strategy, there are people who believe in the success of the fundamental analysis, people who trust more the technical analysis, and there are some who think that they take a chance by using an algorithm.
From the end of the Twentieth Century forecasting financial time series (stock prices for instance) has focused a lot of attention. The Box-Jenkins autoregressive integrated moving average (ARIMA) models are one of the most widely used linear models in time series forecasting, however there are other algorithms, that are available to us for predicting a future value.
In my thesis after an extensive historical summary I studied the different methods, and afterwards I chose the ARIMA model for the prediction. I used the R statistical software to work with and I predicted the future value of the stock of the five biggest Hungarian companies. After defining them I analyzed them and by using a proper comparison I have drawn the conclusions.