Eszközök árazása ritka katasztrófákhoz kapcsolódó racionális tanulás mellett

Date: 2023-11-20, Monday  
Time: 11:40-13:00 (Budapest time)  
Venue: Corvinus Main Building, E.III. (ground floor) 

Organizer: Institute of Finance  

Event: Research Seminar by Dr. Christos Koulovatianos 

Title: Asset Pricing under Rational Learning about Rare Disasters 

Abstract: 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. 
Joint paper with Volker Wieland (Goethe U Frankfurt). 

Click here to access the author’s website. 

Please note that this Microsoft Teams link is only in case you are unable to join the seminar at the Corvinus University of Budapest, Institute of Finance, E.III. However, the meeting will be generally held offline. 

Consult the list of upcoming seminars on our website.