A study on systematic risk among financial sub-markets based on the SETAR-Copula model

Xi Xue; Yingzi Fu; Siqin Xia; Xuesha Li

doi:10.1117/12.2656781

13 January 2023 A study on systematic risk among financial sub-markets based on the SETAR-Copula model

Xi Xue, Yingzi Fu, Siqin Xia, Xuesha Li

Proceedings Volume 12510, International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022); 1251016 (2023) https://doi.org/10.1117/12.2656781
Event: International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), 2022, Qingdao, China

Abstract

Along with the gradual development of the international oil market in the direction of financialization, more and more investors are investing and trading oil as a financial asset, resulting in crude oil price fluctuations affecting the transfer of input funds between stock markets. In turn, the transfer of funds in stock markets will trigger changes in a country's exchange rate. Therefore, crude oil is an essential strategic resource, and its price fluctuations are bound to move the country's stock and currency markets, thus bringing systemic risk. Therefore, based on the industry perspective, the SETAR-Copula model is used to portray the nonlinear characteristics between the exchange rate, WTI crude oil futures price index and SSE index, and the sample data are divided into different intervals according to the threshold parameters in the model. The Vine Copula function is combined to measure the conditional value-at-risk CoVaR and risk spillover ΔCoVaR under various combinations of intervals. The study shows that the stability of the exchange market and the stock market in China can weaken the impact of the volatility of the international crude oil market when it is in a fast-rising stage.

Citation Download Citation

Xi Xue, Yingzi Fu, Siqin Xia, and Xuesha Li "A study on systematic risk among financial sub-markets based on the SETAR-Copula model", Proc. SPIE 12510, International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), 1251016 (13 January 2023); https://doi.org/10.1117/12.2656781

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KEYWORDS

Data modeling

Statistical modeling

Fourier transforms

Statistical analysis

Autoregressive models

Mathematical modeling

Analytical research

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