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On the statistical and economic performance of stock return predictive regression models: An international perspective

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Giot, Pierre [UCL] Petitjean, Mikael [FUCAM]

The predictability of stock returns is assessed in 10 countries using the linear predictive regression framework. We use recently developed out-of-sample statistical tests and include both valuation ratios and interest rates as predictive variables. Contrary to previous studies, we explicitly address the issue of the small-sample bias, deal with trading profitability, and employ several risk-adjusted metrics. When statistical forecastability is found, it cannot be exploited to consistently deliver abnormal returns across countries and investment horizons. We hold the view that returns are predictable to some extent, but show that such forecasts are not useful for portfolio advice.

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès libre
Publication date 2011
Language Anglais
Journal information "Quantitative Finance" - Vol. 11, no. 2, p. 175-193 (2011)
Peer reviewed yes
issn 1469-7688
e-issn 1469-7696
Affiliations UCL - SSH/LIDAM/CORE - Center for operations research and econometrics
Louvain School of Management - Accounting & Finance
Louvain School of Management - Accounting & Finance
FUCaM - Sciences de gestion
Keywords Predictability ; Profitability ; Efficiency ; Out-of-sample ; 4323 ; 4391
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Bibliographic reference Giot, Pierre ; Petitjean, Mikael. On the statistical and economic performance of stock return predictive regression models: An international perspective. In: Quantitative Finance, Vol. 11, no. 2, p. 175-193 (2011)
Permanent URL http://hdl.handle.net/2078/69138