Information flows around the globe: predicting opening gaps from overnight foreign stock price patterns
Central European Journal of Economic Modelling and Econometrics
Faculty of Economics and Business (FEB)
Amsterdam School of Economics Research Institute (ASE-RI)
This paper describes a forecasting exercise of close-to-open returns on major global stock indices, based on high-frequency
price patterns that have become available in foreign markets overnight. Generally speaking, out-ofsample forecast performance
depends on the forecast method as well as the information that the forecasts are based on. In this paper both aspects are
considered. The fact that the close-to-open gap is a scalar response variable to a functional variable, namely an overnight
foreign price pattern, brings the prediction exercise in the realm of functional data analysis. Both parametric and non-parametric
functional data analysis are considered, and compared with a simple linear benchmark model. The information set is varied
by dividing global markets into three clusters, Asia-Pacific, Europe and North-America, and including or excluding price patterns
on a per-cluster basis. The overall best performing forecast is nonparametric using all available information, suggesting
the presence of nonlinear relations between the overnight price patterns and the opening gaps.
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