Ekonometrinių modelių pritaikymas OMXV indekso pokyčių prognozavimui
APPLICATION OF ECONOMETRIC MODELS FOR FORECASTING OF OMXV INDEX CHANGES

Summary/Abstract: Time series models are increasingly widely used for predicting future stock prices. Advancing information technology and data analysis tools allow traders and investors to use these models easily for forecasting risk reduction and profits increase. The authors use classical decomposition, exponential smoothing and ARIMA models to forecast the OMXV index. Multivariate regression is also used to estimate the short-term impact of industrial production, inflation, interest rates, exchange rates, oil price and unemployment on OMXV index. The study finds that exponential smoothing an ARIMA models have good accuracy using one-step ahead forecast. Only oil prices seem to have a small positive impact and inflation – a negative impact on the index.

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