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Stock Market Volatility and Learning

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dc.creator Marcet, Albert
dc.creator Adam, Klaus
dc.creator Nicolini, Juan Pablo
dc.date 2008-05-19T14:57:44Z
dc.date 2008-05-19T14:57:44Z
dc.date 2008-01-25
dc.date.accessioned 2017-01-31T01:22:22Z
dc.date.available 2017-01-31T01:22:22Z
dc.identifier http://hdl.handle.net/10261/4349
dc.identifier.uri http://dspace.mediu.edu.my:8181/xmlui/handle/10261/4349
dc.description Introducing bounded rationality in a standard consumption-based asset pricing model with time separable preferences strongly improves empirical performance. Learning causes momentum and mean reversion of returns and thereby excess volatility, persistence of price-dividend ratios, long-horizon return predictability and a risk premium, as in the habit model of Campbell and Cochrane (1999), but for lower risk aversion. This is obtained, even though our learning scheme introduces just one free parameter and we only consider learning schemes that imply small deviations from full rationality. The findings are robust to the learning rule used and other model features. What is key is that agents forecast future stock prices using past information on prices.
dc.description Marcet acknowledges support from CIRIT (Generalitat de Catalunya), DGES (Ministry of Education and Science, Spain), CREI, the Barcelona Economics program of XREA and the Wim Duisenberg fellowship from the European Central Bank.
dc.description Peer reviewed
dc.format 567796 bytes
dc.format application/pdf
dc.language eng
dc.relation UFAE and IAE Working Papers
dc.relation 732.08
dc.rights openAccess
dc.title Stock Market Volatility and Learning
dc.type Documento de trabajo

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