Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/97775
Authors: 
Koulovatianos, Christos
Wieland, Volker
Year of Publication: 
2011
Series/Report no.: 
IMFS Working Paper Series 46
Abstract: 
This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors’ information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the likelihood of rare disasters drop to a much more pessimistic level once a disaster has occurred. Such a shift in beliefs can trigger massive declines in price-dividend ratios. Pessimistic beliefs persist for some time. Thus, belief dynamics are a source of apparent excess volatility relative to a rational expectations benchmark. Due to the low frequency of disasters, even an infinitely-lived investor will remain uncertain about the exact probability. Our analysis is conducted in continuous time and offers closed-form solutions for asset prices. We distinguish between rational and adaptive Bayesian learning. Rational learners account for the possibility of future changes in beliefs in determining their demand for risky assets, while adaptive learners take beliefs as given. Thus, risky assets tend to be lower-valued and price-dividend ratios vary less under adaptive versus rational learning for identical priors. Keywords: beliefs, Bayesian learning, controlled diffusions and jump processes, learning about jumps, adaptive learning, rational learning.
Subjects: 
beliefs
Bayesian learning
controlled diffusions and jump processes
learning about jumps
adaptive learning
rational learning
JEL: 
D83
G11
C11
D91
E21
D81
C61
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
442.72 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.