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On the volatility of high frequency stock index based on SV model of MCMC. (English) Zbl 07224877
Roy, Priti Kumar (ed.) et al., Mathematical analysis and applications in modeling. Selected papers presented at the international conference, ICMAAM 2018, Kolkata, India, January 9–12, 2018. Singapore: Springer (ISBN 978-981-15-0421-1/hbk; 978-981-15-0422-8/ebook). Springer Proceedings in Mathematics & Statistics 302, 271-278 (2020).
Summary: 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).
For the entire collection see [Zbl 1446.65004].
91G60 Numerical methods (including Monte Carlo methods)
65C05 Monte Carlo methods
91G15 Financial markets
Full Text: DOI
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