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Observed and 'Fundamental' Price Earning Ratios: A Comparative Analysis of High-tech Stock Evaluation in the US and in Europe

Author

Listed:
  • Leonardo Becchetti

    (University of Rome II - Faculty of Economics)

  • Michele Bagella

    (University of Rome II - Faculty of Economics)

  • Fabrizio Adriani

    (University of Rome II - Centre for International Studies on Economic Growth (CEIS))

Abstract

By assuming that a large share of investors (which we call fundamentalists) follows a fundamental approach to stock picking, we build a discounted cash flow (DCF) model and test on a sample of high-tech stocks whether the strong and the weak version of the model are supported by data from the US and European stock markets. Empirical results show that "fundamental" earning price ratios explain a significant share of cross sectional variation of the observed E/P ratios, with other additional variables being only partially and weakly relevant. Within this general framework, valid both for Europe and the US, empirical results outline significant differences between the two markets. The most relevant of them is that the relationship between observed and fundamental E/P ratios is much weaker in Europe.

Suggested Citation

  • Leonardo Becchetti & Michele Bagella & Fabrizio Adriani, 2003. "Observed and 'Fundamental' Price Earning Ratios: A Comparative Analysis of High-tech Stock Evaluation in the US and in Europe," CEIS Research Paper 34, Tor Vergata University, CEIS.
    • Handle: RePEc:rtv:ceisrp:34
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    Cited by:

    1. Leonardo Becchetti & Stefania Di Giacomo, 2007. "Deviations from Fundamentals in US and EU Stock Markets: A Comparative Analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 13(3), pages 195-226.
    2. Michele Bagella & Leonardo Becchetti & Rocco Ciciretti, 2007. "Earning Forecast Error in US and European Stock Markets," The European Journal of Finance, Taylor & Francis Journals, vol. 13(2), pages 105-122.
    3. Ming-Chi Tsai & Ching-Hsue Cheng & Meei-Ing Tsai & Huei-Yuan Shiu, 2018. "Forecasting leading industry stock prices based on a hybrid time-series forecast model," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-24, December.
    4. Ahmed, Mohamed S. & Alhadab, Mohammad, 2020. "Momentum, asymmetric volatility and idiosyncratic risk-momentum relation: Does technology-sector matter?," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 355-371.
    5. Laura Arenas & Ana Maria Gil-Lafuente, 2021. "Regime Switching in High-Tech ETFs: Idiosyncratic Volatility and Return," Mathematics, MDPI, vol. 9(7), pages 1-25, March.
    6. Michele Bagella & Leonardo Becchetti & Rocco Ciciretti, 2007. "Market vs. analysts reaction: the effect of aggregate and firm-specific news," Applied Financial Economics, Taylor & Francis Journals, vol. 17(4), pages 299-312.

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    More about this item

    Keywords

    financial market microstructure; asset pricing;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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