Solving OLG Models with Asset Choice
Michael Reiter
No 1509, 2015 Meeting Papers from Society for Economic Dynamics
Abstract:
The paper presents a computationally efficient method to solve overlapping generations models with asset choice. The method is used to study an OLG economy with many cohorts, up to 3 different assets, stochastic volatility, short-sale constraints, and subject to rather large technology shocks. On the methodological side, the main findings are that global projection methods with polynomial approximations of degree 3 are sufficient to provide a very precise solution, even in the case of large shocks. Globally linear approximations, in contrast to local linear approximations, are sufficient to capture the most important financial statistics, including not only the average risk premium, but also the variation of the risk premium over the cycle. However, global linear approximations are not sufficient to reliably pin down asset choices. With a risk aversion parameter of only 4, the model generates a price of risk, measured as the Sharpe ratio, that is about two thirds of that of US stocks. Being subject to three types of shocks, the equilibiurm allocation, even with 3 assets, differs substantially from an allocation under sequentially complete markets. In particular, the oldest cohorts are more more heavily exposed to negative shocks.
Date: 2015
New Economics Papers: this item is included in nep-dge and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://red-files-public.s3.amazonaws.com/meetpapers/2015/paper_1509.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:red:sed015:1509
Access Statistics for this paper
More papers in 2015 Meeting Papers from Society for Economic Dynamics Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christian Zimmermann ().