Reference : Asset Pricing under Rational Learning about Rare Disasters
Scientific congresses, symposiums and conference proceedings : Unpublished conference
Business & economic sciences : Finance
Asset Pricing under Rational Learning about Rare Disasters
Koulovatianos, Christos mailto [University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Center for Research in Economic Analysis (CREA) >]
Wieland, Volker []
American Economic Association 2017 Annual meeting
January 6-8, 2017
American Economic Association / American Finance Association
United States of America
[en] beliefs ; Bayesian learning ; filtering ; De Finetti's theorem ; price-dividend ratios ; excess stock-price volatility
[en] Why is investment in stocks so persistently weak after a rare disaster? Connecting disaster episodes with post-disaster expectations seems crucial for such post-disaster forecasting and also policymaking, but rational-expectations models with variable disaster risk often fail to achieve this connection. To this end, while retaining full rationality, we introduce limited information and learning about rare-disaster risk and show that the resulting stock-investment behavior seems similar to persistent investor fear after a rare disaster. We study, (a) rational learning for state verification (RLS), with investors knowing the data-generating process of disaster riskiness but being unable to observe whether the economy is in a riskier state (regime) or not, and (b) rational learning about the data-generating process (RLP) of disaster risk, with investors also being unaware of the data-generating process of disaster riskiness. We analytically show that both RLS and RLP synchronize disaster events with post-disaster expectations and asset prices, and create persistence in price-dividend ratios even if data-generating processes of disaster risk have no persistence. Using De Finetti's theorem we show that RLP offers an explanation for global spells of pessimism and weak investment after a disaster.

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