Conditional Style Rotation Model on Enhanced Value and Growth Portfolios: The European Experience
AbstractAcademic and professional attention has been devoted in the past to the analysis of the potential value-enhancement generated by strategies based on macroeconomic models and applied to portfolios or indexes of style classes. In this paper, we analyse the extent of the excess returns that can be potentially generated by rotating a portfolio between value and growth stocks in the European markets. We extend the results obtained by Bird and Casavecchia (Bird, R. and Casavecchia. L. (2007) Sentiment and financial health indicators for value and growth stocks: the European experience, European Journal of Finance, 13, pp. 769-793) when applying market sentiment and financial health indicators to stocks and document the extent to which macroeconomic factors convey information that is not already impounded in these indicators. We find that a strategy to rotate between portfolios, constructed on either single valuation metrics or their enhancement by market sentiment and a company’s financial strength, is typically consistent, monotonic, and in the expected direction. This highlights the proposition that the macroeconomic factors capture a cross-sectional variation that is not typically impounded in unconditional regression models on value and growth portfolios.
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Bibliographic InfoPaper provided by The Paul Woolley Centre for Capital Market Dysfunctionality, University of Technology, Sydney in its series Working Paper Series with number 2.
Length: 24 pages
Date of creation: 01 May 2008
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style rotation; financial health; market sentiment; asset pricing anomalies;
Find related papers by JEL classification:
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
- F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
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