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Stationary bootstrap test for jumps in high-frequency financial asset data

  • Hwang, Eunju (Department of Applied Statistics, Gachon University) ;
  • Shin, Dong Wan (Department of Statistics, Ewha University)
  • Received : 2016.01.01
  • Accepted : 2016.02.17
  • Published : 2016.03.31

Abstract

We consider a jump diffusion process for high-frequency financial asset data. We apply the stationary bootstrapping to construct a bootstrap test for jumps. First-order asymptotic validity is established for the stationary bootstrapping of the jump ratio test under the null hypothesis of no jump. Consistency of the stationary bootstrap test is proved under the alternative of jumps. A Monte-Carlo experiment shows the advantage of a stationary bootstrapping test over the test based on the normal asymptotic theory. The proposed bootstrap test is applied to construct continuous-jump decomposition of the daily realized variance of the KOSPI for the year 2008 of the world-wide financial crisis.

Keywords

stationary bootstrap;jump diffusion process;ratio test;realized variation;realized bipower variation

Acknowledgement

Supported by : National Research Foundation of Korea

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