Goodness-of-fit test for stochastic volatility models

Liang Ching Lin, Sangyeol Lee, Meihui Guo

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

In this paper, we propose a goodness of fit test for continuous time stochastic volatility models based on discretely sampled observations. The proposed test is constructed by measuring deviations between the empirical and true characteristic functions obtained from the hypothesized stochastic volatility model. In this study, both the test statistics based on the fixed and decreasing sampling schemes are taken into consideration. It is shown that under the null, the proposed tests asymptotically follow a weighted sum of products of centered normal random variables. In order to evaluate the proposed tests, a simulation study is performed, in which a bootstrap method is also considered. Finally, a real data analysis is conducted for illustration.

Original languageEnglish
Pages (from-to)473-498
Number of pages26
JournalJournal of Multivariate Analysis
Volume116
DOIs
Publication statusPublished - 2013 Apr

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

Fingerprint

Dive into the research topics of 'Goodness-of-fit test for stochastic volatility models'. Together they form a unique fingerprint.

Cite this