By a News Reporter-Staff News Editor at Investment Weekly News -- Fresh data on Statistical Mechanics are presented in a new report. According to news reporting from Kunming, People’s Republic of China, by VerticalNews journalists, research stated, “Using intraday data of the CSI300 index, this paper discusses value-at-risk (VaR) forecasting of the Chinese stock market from the perspective of high-frequency volatility models. First, we measure the realized volatility (RV) with 5-minute high-frequency returns of the CSI300 index and then model it with the newly introduced heterogeneous autoregressive quarticity (HARQ) model, which can handle the time-varying coefficients of the HAR model.”
Financial supporters for this research include National Natural Science Foundation of China, Fundamental research funds for the central universities, China.
The news correspondents obtained a quote from the research from Yunnan University, “Second, we forecast the out-of-sample VaR of the CSI300 index by combining the HARQ model and extreme value theory (EVT). Finally, using several popular backtesting methods, we compare the VaR forecasting accuracy of HARQ model with other traditional HAR-type models, such as HAR, HAR-J, CHAR, and SHAR.”
According to the news reporters, the research concluded: “The empirical results show that the novel HARQ model can beat other HAR-type models in forecasting the VaR of the Chinese stock market at various risk levels.”
For more information on this research see: Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory. Physica A-Statistical Mechanics and Its Applications , 2018;499():288-297. Physica A-Statistical Mechanics and Its Applications can be contacted at: Elsevier Science Bv, PO Box 211, 1000 Ae Amsterdam, Netherlands.
Our news journalists report that additional information may be obtained by contacting Y. Wei, Yunnan Univ Finance & Econ, Sch Finance, Kunming, Yunnan, People’s Republic of China. Additional authors for this research include G.Q. Liu, Y.F. Chen, J. Yu and Y. Hu.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.physa.2018.02.033. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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CITATION: (2018-05-05), Findings in the Area of Statistical Mechanics Reported from Yunnan University (Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory), Investment Weekly News, 516, ISSN: 1945-8185, BUTTER® ID: 015578493
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