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Modeling stock index returns by means of partial least‐squares methods: An out‐of‐sample analysis for three stock markets

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  • Cetin‐Behzet Cengiz
  • Helmut Herwartz

Abstract

We analyze the underlying economic forces of the stock markets in Germany, the U.K. and the U.S. Identifying a number of variables evincing return predictability, we follow a partial least‐squares (PLS) approach to combine these observables into a few latent factors. Conditional on European markets, our findings indicate (i) superior prediction performance of PLS‐based schemes in comparison with both, a random walk and a first‐order autoregressive benchmark model, (ii) consistent profitable trading on the German and British market, (iii) profitable linear forecast combinations, (iv) the U.S. stock market is diagnosed as informationally efficient. Copyright © 2010 John Wiley & Sons, Ltd.

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  • Cetin‐Behzet Cengiz & Helmut Herwartz, 2011. "Modeling stock index returns by means of partial least‐squares methods: An out‐of‐sample analysis for three stock markets," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(3), pages 253-266, May.
    • Handle: RePEc:wly:apsmbi:v:27:y:2011:i:3:p:253-266
    DOI: 10.1002/asmb.826
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    Cited by:

    1. Barua, Ronil & Sharma, Anil K., 2023. "Using fear, greed and machine learning for optimizing global portfolios: A Black-Litterman approach," Finance Research Letters, Elsevier, vol. 58(PC).

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