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Hybrid quantile estimation for asymmetric power GARCH models. (English) Zbl 07491159

Summary: Asymmetric power GARCH models have been widely used to study the higher order moments of financial returns, while their quantile estimation has been rarely investigated. This paper introduces a simple monotonic transformation on its conditional quantile function to make the quantile regression tractable. The asymptotic normality of the resulting quantile estimators is established under either stationarity or non-stationarity. Moreover, based on the estimation procedure, new tests for strict stationarity and asymmetry are also constructed. This is the first try of the quantile estimation for non-stationary ARCH-type models in the literature. The usefulness of the proposed methodology is illustrated by simulation results and real data analysis.

MSC:

62-XX Statistics
91-XX Game theory, economics, finance, and other social and behavioral sciences

Software:

CAViaR
PDFBibTeX XMLCite
Full Text: DOI arXiv

References:

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