A Bayesian Inference Approach to Testing Mean Reversion in the Swedish Stock Market
AbstractIn this paper we use a Bayesian approach to test for mean reversion in the Swedish stock market on monthly data 1918-1998. By simply account for the heteroscedasticty of the data with a two state hidden Markov model of normal distributions and taking estimation bias into account via Gibbs sampling we can find no support of mean reversion. This is a contradiction to previous result from Sweden. Our findings suggest that the Swedish stock market can be characterized by two regimes, a tranquil and a volatile, and within the regimes the stock market is random. This finding of randomness is in line with recent evidence for the U.S stock market.
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Bibliographic InfoPaper provided by Lund University, Department of Economics in its series Working Papers with number 2000:8.
Length: 21 pages
Date of creation: 03 Oct 2000
Date of revision: 09 Nov 2000
Contact details of provider:
Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden
Phone: +46 +46 222 0000
Fax: +46 +46 2224613
Web page: http://www.nek.lu.se/en
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Market efficency; variance ratio; Gibbs sampling; hidden markov Chains;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
This paper has been announced in the following NEP Reports:
- NEP-ECM-2000-11-14 (Econometrics)
- NEP-ETS-2000-11-08 (Econometric Time Series)
- NEP-FMK-2000-11-08 (Financial Markets)
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.:
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