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Modeling stock index returns by means of partial least‐squares methods: An out‐of‐sample analysis for three stock markets
Author(s) -
Cengiz CetinBehzet,
Herwartz Helmut
Publication year - 2010
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.826
Subject(s) - predictability , econometrics , autoregressive model , stock market index , economics , stock market , stock (firearms) , partial least squares regression , conditional expectation , random walk , financial economics , mathematics , statistics , engineering , mechanical engineering , paleontology , horse , biology
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.