The Bickel-Rosenblatt test for continuous time stochastic volatility models

Liang-Ching Lin, Sangyeol Lee, Meihui Guo

研究成果: Article

1 引文 (Scopus)

摘要

In this paper, we consider the Bickel-Rosenblatt test for continuous time stochastic volatility models. The test is constructed based on discretely observed samples by measuring integrated squared deviations between the nonparametric kernel density estimate from the observations and a parametric fit of the density. It is shown that under the null, the proposed test is asymptotically normal. To evaluate the proposed test, a simulation study is performed for illustration.

原文English
頁(從 - 到)195-218
頁數24
期刊Test
23
發行號1
DOIs
出版狀態Published - 2014 一月 1

指紋

Stochastic Volatility Model
Continuous Time
Kernel Density Estimate
Null
Deviation
Simulation Study
Continuous time
Stochastic volatility model
Evaluate

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

引用此文

Lin, Liang-Ching ; Lee, Sangyeol ; Guo, Meihui. / The Bickel-Rosenblatt test for continuous time stochastic volatility models. 於: Test. 2014 ; 卷 23, 編號 1. 頁 195-218.
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The Bickel-Rosenblatt test for continuous time stochastic volatility models. / Lin, Liang-Ching; Lee, Sangyeol; Guo, Meihui.

於: Test, 卷 23, 編號 1, 01.01.2014, p. 195-218.

研究成果: Article

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