The Bickel–Rosenblatt test for continuous time stochastic volatility models

• Liang-Ching Lin ^[1] ; Sangyeol Lee ^[2] ; Meihui Guo ^[1]
  1. [1] National Sun Yat-sen University

     National Sun Yat-sen University

     Taiwán

     
  2. [2] Seoul National University

     Seoul National University

     Corea del Sur

     
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 23, Nº. 1, 2014, págs. 195-218
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • 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