Learning and Conditional Heteroscedasticity in Asset Returns
AbstractDespite the widespread use of the GARCH model, the specification of the heteroscedasticity is essentially ad hoc. This paper's contribution is to develop a model of asset pricing and learning where GARCH disturbances evolve naturally out of the decision problem of economic agents. An empirical example with the Italian-Lira German Deutschemark exchange rate supports the extended GARCH specification proposed in the paper.
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Bibliographic InfoPaper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 199526.
Date of creation: 24 Jul 1996
Date of revision:
Publication status: Forthcoming in "Learning and ARCH Disturbances in Asset Returns," in Catherine Kyrtsou (ed.), Progress in Financial Markets Research, New York: Nova Science.
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asset returns; GARCH; learning;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- F31 - International Economics - - International Finance - - - Foreign Exchange
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
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- Catherine Kyrtsou & Michel Terraza, 2003. "Is it Possible to Study Chaotic and ARCH Behaviour Jointly? Application of a Noisy Mackey–Glass Equation with Heteroskedastic Errors to the Paris Stock Exchange Returns Series," Computational Economics, Society for Computational Economics, vol. 21(3), pages 257-276, June.
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