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Price dividend ratio and long-run stock returns : a score driven state space model
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Delle Monache, Davide, Venditti, Fabrizio and Petrella, Ivan (2021) Price dividend ratio and long-run stock returns : a score driven state space model. Journal of Business and Economic Statistics, 39 (4). pp. 1054-1065. doi:10.1080/07350015.2020.1763805 ISSN 0735-0015.
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WRAP-price-dividend-ratio-long-run-stock-returns-score-driven-state-space-model-Petrella-2020.pdf - Accepted Version - Requires a PDF viewer. Download (2603Kb) | Preview |
Official URL: https://doi.org/10.1080/07350015.2020.1763805
Abstract
In this article, we develop a general framework to analyze state space models with time-varying system matrices, where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying matrices. We use this method to study the time-varying relationship between the price dividend ratio, expected stock returns and expected dividend growth in the United States since 1880. We find a significant increase in the long-run equilibrium value of the price dividend ratio over time, associated with a fall in the long-run expected rate of return on stocks. The latter can be attributed mainly to a decrease in the natural rate of interest, as the long-run risk premium has only slightly fallen.
| Item Type: | Journal Article | ||||||||
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| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HC Economic History and Conditions H Social Sciences > HG Finance |
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| Divisions: | Faculty of Social Sciences > Warwick Business School > Finance Group Faculty of Social Sciences > Warwick Business School |
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| Library of Congress Subject Headings (LCSH): | State-space methods -- Econometric models, Time-series analysis -- Econometric models, Stock price forecasting -- Econometric models, Rate of return -- Forecasting -- Econometric models | ||||||||
| Journal or Publication Title: | Journal of Business and Economic Statistics | ||||||||
| Publisher: | Taylor & Francis Inc. | ||||||||
| ISSN: | 0735-0015 | ||||||||
| Official Date: | 2021 | ||||||||
| Dates: |
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| Volume: | 39 | ||||||||
| Number: | 4 | ||||||||
| Page Range: | pp. 1054-1065 | ||||||||
| DOI: | 10.1080/07350015.2020.1763805 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Reuse Statement (publisher, data, author rights): | This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Business and Economic Statistics on 02/06/2020, available online: http://www.tandfonline.com/10.1080/07350015.2020.1763805 | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Date of first compliant deposit: | 27 April 2020 | ||||||||
| Date of first compliant Open Access: | 2 December 2021 | ||||||||
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