This paper compares the power in small samples of different tests for conditional heteroscedasticity. Two new tests, based on neural networks, are proposed: the main interest in them arises from the fact that they do not require the exact specification of the conditional variance under the alternative.
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Paper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number
99a22.
Length: 13 pages Date of creation: 1999 Date of revision: Handle: RePEc:fth:aixmeq:99a22
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Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
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