Identifying Bull and Bear Markets in Stock Returns.
This article uses a Markov-switching model that incorporates duration dependence to capture non-linear structure in both the conditional mean and the conditional variance of stock returns. The model sorts returns into a high-return stable state and a low-return volatile state. We label these as bull and bear markets, respectively. The filter identifies all major stock-market downturns in over 160 years of monthly data. Bull markets have a declining hazard function although the best market gains come at the start of a bull market. Volatility increases with duration in bear markets. Allowing volatility to vary with duration captures volatility clustering.
Year of publication: |
2000
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Authors: | Maheu, John M ; McCurdy, Thomas H |
Published in: |
Journal of Business & Economic Statistics. - American Statistical Association. - Vol. 18.2000, 1, p. 100-112
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Publisher: |
American Statistical Association |
Saved in:
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