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Learning and Conditional Heteroscedasticity in Asset Returns

Author

Listed:
  • Bruce Mizrach

    () (Rutgers University)

Abstract

Despite 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.

Suggested Citation

  • Bruce Mizrach, 1996. "Learning and Conditional Heteroscedasticity in Asset Returns," Departmental Working Papers 199526, Rutgers University, Department of Economics.
  • Handle: RePEc:rut:rutres:199526
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    Cited by:

    1. 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, Springer;Society for Computational Economics, vol. 21(3), pages 257-276, June.

    More about this item

    Keywords

    asset returns; GARCH; learning;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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