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Modelling the Impact of Overnight Surprises on Intra-daily Stock Returns

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Author Info
Giampiero M. Gallo () (Università degli Studi di Firenze, Dipartimento di Statistica "G. Parenti")
Yongmiao Hong (Cornell University, Departments of Economics & Statistical Science)
Tae-Why Lee (University of California, Riverside, Department of Economics)

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Abstract

In this paper we examine under what circumstances the information accumulated during market closing time and conveyed to the price formation at market opening may be exploited to predict where the stock price will be at the end of the trading day. In our sample of three financial time series, we find that, in spite of linear uncorrelatedness, there exists a strong nonlinear dependence structure in the conditional mean of the intra-daily returns. To model this structure we use the functional-coefficient (FC) model of Cai, Fan, and Yao (2000) where the coefficients are time-varying and dependent on the state of stock return volatility. Out-of-sample forecast performances of the FC models and linear models where the coefficients are constant are also compared using the criteria of mean square forecast errors, trading returns, and directional forecasts.

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Publisher Info
Paper provided by Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti" in its series Econometrics Working Papers Archive with number wp2001_03.

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Length: 17 pages
Date of creation: 24 Oct 2001
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Handle: RePEc:fir:econom:wp2001_03

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Related research
Keywords: Functional-coefficient model; Nonlinearity; Predictive ability; Volatility.;

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Find related papers by JEL classification:
C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
C5 - Mathematical and Quantitative Methods - - Econometric Modeling
F3 - International Economics - - International Finance

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