Goodness-of-fit test for the SVM based on noisy observations

Liang Ching Lin, Sangyeol Lee, Meihui Guo

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


In financial high frequency data analysis, the efficient price of an asset is commonly assumed to follow a continuous-time stochastic volatility model, contaminated with a microstructure noise. In this study, we consider a goodness-of-fit test problem for the efficient price models based on discretely observed samples and employ a goodness-of-fit test based on the empirical characteristic function. We show that the proposed test is asymptotically a weighted sum of products of centered normal random variables. To evaluate the proposed test, we conducted a simulation study using a bootstrap method. A data analysis is provided for illustration.

Original languageEnglish
Pages (from-to)1305-1329
Number of pages25
JournalStatistica Sinica
Issue number3
Publication statusPublished - 2016 Jul

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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