Forecasting UK stock prices

Roy Boyd

25 citations0/0 files storedApplied Financial Economics

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Forecasting Techniques and Applications

Abstract

The Vector Autoregressive (VAR) model, the Error Correction Model (ECM), and the Kalman Filter Model (KFM) are used to forecast UK stock prices. The forecasting performance of the three models is compared using out of sample forecasting. The results show that the forecasting performance of the ECM is better than that of the VAR and the KFM, and that the VAR performs a forecasting better than the KFM. It seems that the ECM outperforms the VAR and the KFM, since the ECM allows for dynamic updating via an error correction term.

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References

1987Co-Integration and Error Correction: Representation, Estimation, and Testing 1970EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*1988Statistical analysis of cointegration vectors 1981Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root 1990MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY 1990Econometric Models and Economic Forecasts 1986The theory and practice of econometrics 1990Forecasting, Structural Time Series Models and the Kalman Filter

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