Goodness-of-fit testing for fractional diffusions

Mark Podolskij () and Katrin Wasmuth ()
Additional contact information
Mark Podolskij: Heidelberg University and CREATES, Postal: Department of Mathematics, 69120 Heidelberg, Germany
Katrin Wasmuth: Heidelberg University, Postal: Department of Mathematics, 69120 Heidelberg, Germany

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: This paper presents a goodness-of-fit test for the volatility function of a SDE driven by a Gaussian process with stationary and centered increments. Under rather weak assumptions on the Gaussian process, we provide a procedure for testing whether the unknown volatility function lies in a given linear functional space or not. This testing problem is highly non-trivial, because the volatility function is not identifiable in our model. The underlying fractional diffusion is assumed to be observed at high frequency on a fixed time interval and the test statistic is based on weighted power variations. Our test statistic is consistent against any fixed alternative.

Keywords: central limit theorem; goodness-of-fit tests; high frequency observations; fractional diffusions; stable convergence. (search for similar items in EconPapers)
JEL-codes: C10 C13 C14 (search for similar items in EconPapers)
Pages: 13
Date: 2012-04-16
New Economics Papers: this item is included in nep-ecm and nep-ene
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://repec.econ.au.dk/repec/creates/rp/12/rp12_12.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2012-12

Access Statistics for this paper

More papers in CREATES Research Papers from Department of Economics and Business Economics, Aarhus University
Bibliographic data for series maintained by ().