Goodness-of-fit tests for parametric specification of diffusion coefficients
Abstract/Contents
- Abstract
- With wide range of models for volatility in continuous-time finance, we propose a test for the parametric specification of local volatility models. We provide two approaches to this problem with a focus on a few key properties for the tests. Our first approach is based on deriving an asymptotically independent and identically distributed (IID) sequence through a variance stabilizing transformation. We analyze and employ the generalized runs tests of Cho and White (2011) for testing the IID hypothesis to derive a statistic with universal limit law regardless of estimation method for the parametric volatility function. We perform a simulation study to evaluate the finite sample performance of the test. Our second approach is a variations-based test using the existing limit theory for variations processes and functionals of normalized increments of observed diffusion processes covered in Jacod and Protter (2012). We utilize a local normalization and introduce an orthogonality condition which leads to a unified framework for a universal limit law in univariate and multivariate models. This avoids the necessity for a bootstrap procedure that reduces performance and leads to complications associated with the structure of the diffusion process. The test has good finite sample performance as we demonstrate in numerical simulations and extends to multivariate diffusions as well.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2013 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Papanicolaou, Alex |
|---|---|
| Associated with | Stanford University, Institute for Computational and Mathematical Engineering. |
| Primary advisor | Giesecke, Kay |
| Thesis advisor | Giesecke, Kay |
| Thesis advisor | Glynn, Peter W |
| Thesis advisor | Lai, T. L |
| Advisor | Glynn, Peter W |
| Advisor | Lai, T. L |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Alex Papanicolaou. |
|---|---|
| Note | Submitted to the Institute for Computational and Mathematical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2013. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2013 by Alex George Papanicolaou
Also listed in
Loading usage metrics...