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On the Volatility of High Frequency Stock Index Based on SV Model of MCMC

  • Y. X. Zheng
  • Y. H. ZhangEmail author
  • X. H. Lu
Conference paper
  • 42 Downloads
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 302)

Abstract

By using of 5-min high-frequency data in CSI 300 index stock high-frequency data from 15th Jan. 2018 to 5th Mar. 2018, basing on Bayesian Analysis simulated by MCMC, this paper adopts the Stochastic Volatility model to do empirical researches on China’s stock market and utilizes DIC criterion to do model fitting comparison. The result shows that China’s stock market has higher volatility persistence, and the fitting effect for SV model to 5-min high-frequency data is better than the low-frequency data, and the standard stochastic volatility model (SV-N) is more suitable for high frequency-data of 5-min than the heavy-tail finance stochastic volatility model (SV-T).

Keywords

SV model Gibbs sampling Bayesian analysis Monte Carlo method 

Notes

Acknowledgements

The work was partly supported by National Natural Science Foundation of China (Grant No. 11971042) and National Science Foundation of Beijing Municipality (Grant No. 1182008).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Technology Support GroupMigu Culture Technology Com., LtdBeijingChina
  2. 2.Department of MathematicsBeijing Technology and Business UniversityBeijingChina
  3. 3.School of Statistics and MathematicsCentral University of Finance and EconomicsBeijingChina

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