An alternative methodological approach to assess the predictive performance of the moving average trading rule in financial markets: application to the london stock exchange

Abstract

In this work a modification of the Box-Tiao methodology for the assessment of the impact of external events on time series is proposed as an alternative statistical approach of assessing the predictive performance of the moving average trading rule in financial markets. With the proposed methodology measures of the predictive performance of the moving average trading rule can be simultaneously estimated, while at the same time controlling for autocorrelation in the series of asset returns. The potential advantages of the proposed methodology over the existing ones are discussed. Application of this alternative methodology to the returns of the FT30 Index of the London Stock Exchange shows good agreement with the empirical findings of other methods.

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