Linear and nonlinear models for the analysis of the relationship between stock market prices and macroeconomic and financial factors
AbstractThe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0411018.
Length: 18 pages
Date of creation: 26 Nov 2004
Date of revision:
Note: Type of Document - pdf; pages: 18
Contact details of provider:
Web page: http://126.96.36.199
nonlinear dependence; stock market; financial and macroeconomic factors;
Find related papers by 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
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-77, December.
- Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
- 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.
- Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-28, September.
- 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, 09.
- 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.
- 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.
- Stutzer, Michael, 1995. "A Bayesian approach to diagnosis of asset pricing models," Journal of Econometrics, Elsevier, vol. 68(2), pages 367-397, August.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).
If references are entirely missing, you can add them using this form.