Reference : Asset Pricing under Rational Learning about Rare Disasters |
Scientific congresses, symposiums and conference proceedings : Unpublished conference | |||
Business & economic sciences : Finance | |||
Finance | |||
http://hdl.handle.net/10993/29921 | |||
Asset Pricing under Rational Learning about Rare Disasters | |
English | |
Koulovatianos, Christos ![]() | |
Wieland, Volker [] | |
7-Jan-2017 | |
No | |
International | |
American Economic Association 2017 Annual meeting | |
January 6-8, 2017 | |
American Economic Association / American Finance Association | |
Chicago | |
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. | |
http://hdl.handle.net/10993/29921 | |
http://www.aeaweb.org/conference/2017/upload/retrieve.php?pdfid=1798 |
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