Predictability of the Siss Stock Market ith Respect to Style [Paperback]

Patrick Scheurle investigates refined market segments such as small value stocks or large growth stocks with respect to return predictability. The empirical research reveals significant positive first-order serial correlation in the returns of large value stocks, large neutral stocks, small neutral stocks, and small growth stocks.Literature Review.- Return Predictability and the Real Economy.- Study Design and Data.- Empirical Part I  Testing for Predictability.- Forecasting Models.- Empirical Part II  Investment Strategies.- Conclusion.Dr. Patrick Scheurle obtained his doctorate with Prof. Dr. Dr. h.c. Klaus Spremann at the University of St. Gallen.There is evidence of fairly strong serial correlation in small caps and a lead-lag relationship between large caps and small caps. Moreover, the discussion of a risk premium for cyclical risks which are captured by small caps and value stocks make style portfolios particularly interesting for research. Patrick Scheurle investigates refined market segments such as small value stocks or large growth stocks with respect to return predictability. The empirical research reveals significant positive first-order serial correlation in the returns of large value stocks, large neutral stocks, small neutral stocks, and small growth stocks. The evidence found supports the view that time-varying risk premia for cyclical risks might induce return predictability.There is evidence of fairly strong serial correlation in small caps and a lead-lag relationship between large caps and small caps. Moreover, the discussion of a risk premium for cyclical risks which are captured by small caps and value stocks make style portfolios particularly interesting for research. Patrick Scheurle investigates refined market segments such as small value stocks or large growth stocks with respect to return predictability. The empirical research reveals significant positive first-order serial correlation in the returns of large value stocks, large neutral lƒ$