Abstract
In the paper an in-depth analysis of individual stock returns on the Helsinki Stock Exchange (Finland) and the Stockholm Stock Exchange (Sweden) is carried out using univariate time series methodology. The need for such a research effort is clearly indicated by the results obtained previously. The models are derived by a Cartesian ARIMA Search Algorithm (CARIMA), developed by Östermark and Höglund. In the study we demonstrate that the majority of stock prices in both markets are predictable with seasonal and/or nonseasonal ARIMA-models of a fairly simple structure. The stock markets are seen to differ in complexity of time series models as well as in predictability of individual asset prices.
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