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Linear and nonlinear models for the analysis of the relationship between stock market prices and macroeconomic and financial factors

Author

Listed:
  • Andreia Dionisio

    (University of Evora, Portugal)

  • Rui Menezes

    (ISCTE, Portugal)

  • Diana A. Mendes

    (ISCTE, Portugal)

  • Jacinto Vidigal da Silva

    (University of Evora, Portugal)

Abstract

The main objective of this paper is to assess how mutual information as a measure of global dependence between stock markets and macroeconomic factors can overcome some of the weaknesses of the traditional linear approaches commonly used in this context. One of the advantages of mutual information is that it does not require any prior assumption regarding the specification of a theoretical probability distribution or the specification of the dependence model. This study focuses on the Portuguese stock market where we evaluate the relevance of the macroeconomic and financial variables as determinants of the stock prices behaviour.

Suggested Citation

  • Andreia Dionisio & Rui Menezes & Diana A. Mendes & Jacinto Vidigal da Silva, 2004. "Linear and nonlinear models for the analysis of the relationship between stock market prices and macroeconomic and financial factors," Econometrics 0411018, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0411018
    Note: Type of Document - pdf; pages: 18
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    References listed on IDEAS

    as
    1. Darbellay, Georges A & Wuertz, Diethelm, 2000. "The entropy as a tool for analysing statistical dependences in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 429-439.
    2. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    3. Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
    4. Asprem, Mads, 1989. "Stock prices, asset portfolios and macroeconomic variables in ten European countries," Journal of Banking & Finance, Elsevier, vol. 13(4-5), pages 589-612, September.
    5. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    6. C. W. Granger & E. Maasoumi & J. Racine, 2004. "A Dependence Metric for Possibly Nonlinear Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 649-669, September.
    7. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    8. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    9. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    10. Fama, Eugene F, 1990. "Stock Returns, Expected Returns, and Real Activity," Journal of Finance, American Finance Association, vol. 45(4), pages 1089-1108, September.
    11. Haugen, Robert A. & Baker, Nardin L., 1996. "Commonality in the determinants of expected stock returns," Journal of Financial Economics, Elsevier, vol. 41(3), pages 401-439, July.
    12. Stutzer, Michael, 1995. "A Bayesian approach to diagnosis of asset pricing models," Journal of Econometrics, Elsevier, vol. 68(2), pages 367-397, August.
    13. McQueen, Grant & Roley, V Vance, 1993. "Stock Prices, News, and Business Conditions," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 683-707.
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    More about this item

    Keywords

    nonlinear dependence; stock market; financial and macroeconomic factors;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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