Predicting returns in financial markets
Predicting returns in financial markets
This paper attempts to reproduce the time series properties of nominal excess returns in a variety of financial markets using a representative agent cash-in-advance model, modified to allow for time variation in the conditional variances of the exogenous processes. The exogenous fundamental processes of the model are estimated from the data and the remaining free parameters are estimated with a simulated method of moments technique. Simulations demonstrate that the model can replicate some of the predictability features of observed excess returns for the period 1978–1991, but that it fails to account for the serial correlation and for the joint properties of one and three months excess returns.
excess returns, financial markets, cash-in-advance model
35-69
Canova, Fabio
d700bd9a-5f63-4782-9eda-64c5b8fe2dc5
Marrinan, Jane
f0d18ef0-4c27-46d4-80e6-54a967105860
January 1995
Canova, Fabio
d700bd9a-5f63-4782-9eda-64c5b8fe2dc5
Marrinan, Jane
f0d18ef0-4c27-46d4-80e6-54a967105860
Abstract
This paper attempts to reproduce the time series properties of nominal excess returns in a variety of financial markets using a representative agent cash-in-advance model, modified to allow for time variation in the conditional variances of the exogenous processes. The exogenous fundamental processes of the model are estimated from the data and the remaining free parameters are estimated with a simulated method of moments technique. Simulations demonstrate that the model can replicate some of the predictability features of observed excess returns for the period 1978–1991, but that it fails to account for the serial correlation and for the joint properties of one and three months excess returns.
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Published date: January 1995
Keywords:
excess returns, financial markets, cash-in-advance model
Identifiers
Local EPrints ID: 32935
URI: http://eprints.soton.ac.uk/id/eprint/32935
ISSN: 0014-2921
PURE UUID: 5661e073-1ccd-44cd-bbe1-24630194a636
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Date deposited: 11 Dec 2007
Last modified: 15 Mar 2024 07:40
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Author:
Fabio Canova
Author:
Jane Marrinan
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