Author(s)

Zongxuan Chai ¹, Tingting Zheng ¹

Affiliation(s)

¹ School of Electrical and Control Engineering, North China University of Technology, Beijing, 100144, China

Corresponding Author

Tingting Zheng

ABSTRACT

Forecasting financial systemic risk has always been an important element of financial research. Despite being a key component of our country's financial market, the bond market has received relatively less systematic research attention from scholars in terms of singular market risk warnings. This paper draws on established research to construct a systemic risk stress index for the bond market. Innovatively, it utilizes the Empirical Mode Decomposition (EEMD) method to decompose the pressure index of the Chinese bond market from 2010 to 2023 into individual IMF sequences. Then, it employs the LSTM algorithm for ensemble forecasting, conducting systematic risk warning research. According to the simulation results, China's bond market will show a trend of declining pressure or low pressure in the long term, and the systemic risk will fluctuate less under effective regulation. Meanwhile, the EEMD-LSTM model has higher risk prediction accuracy compared with single LSTM model prediction.

KEYWORDS

Systemic risk; Bond Markets; Ensemble Empirical Mode Decomposition; Long Short-Term Memory

CITE THIS PAPER

Zongxuan Chai, Tingting Zheng, Systematic Risk Stress Prediction in Bond Market Based on EEMD-LSTM. Financial Engineering and Risk Management (2023) Vol. 6: 181-186. DOI: http://dx.doi.org/10.23977/ferm.2023.061126.

REFERENCES

[1] Zhao, W.; Meng, X.; Xiang, X. Research on the Mechanism and Measurement of Systemic Risk Formation in China's Bond Market. Journal of Financial Development Research 2022, 10, 82-87. 
[2] Illing, M.; Y, Liu. Measuring Financial Stress in a Developed Country: an Application to Canada. Journal of Financial Stability 2006, 2(3), 243-265. 
[3] Balakrishnan, R.; Danninger, S.; Tytell, I. The Transmission of Financial Stress from Advanced to Emerging Economies. Emerging Markets Finance and Trade 2011, 47, 40-68. 
[4] Tao, L.; Zhu, Y. On China's Financial Systemic Ｒisks. Journal of Financial Research 2016, 6, 18-36. 
[5] Li, M.; Liang, S. Monitoring Systemic Financial Risks: Construction and State Identification of China's Financial Market Stress Index. Journal of Financial Research 2021, 6, 21-38. 
[6] Wu, H.; Han, Y.; Zheng Z. An Experimental Construction of the Monitoring System of Bond Market Fragility in China. Financial Regulation Research 2018, 6, 31-47. 
[7] Li, X.; Zhao, G.; Wang Y. Improved Internet of Things Intrusion Detection Model for CNN and RNN. Computer Engineering and Applications 2023, 59(14), 242-250. 
[8] Elman, J. L.Finding Structure in Time. Cognitive Science 1990, 14(2), 179-211. 
[9] Hochreiter, S.; Schmidhuber, J. Long short-term memory. Neural Computation 1997, 9(8), 1735-1780.
[10] Huang, N E.; Shen, Z.; Long, S R.; et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 1998, 454(1971), 903-995.
[11] Wu, Z.; Huang, N E. Ensemble empirical mode decomposition: a noise-assisted data analysis method. Advances in Adaptive Data Analysis 2009, 1(1), 1-41. 
[12] Tang, Z.; Wu, J.; Zhang, T.; et al. An EEMD-LSTM Model Based Research on Early Warning of the Systematic Risk in China Insurance Industry. Management Review 2022, 9, 14. 
[13] Li, Z.; Fang, M.; Zhang, M. Research on the Cross-Market Spillover Effect of Financial Stress in China——From the Perspective of Systemic Risk Management. Financial Forum 2022, 27(8), 7-18. 
[14] Wang, S.; Yu, L.; Lai, K. TEl@I Methodology and Its Application to Exchange Rates Prediction. Chinese Journal of Management 2007, 1, 21-27. 
[15] Chen, Y.; Dong, Z.; Wang, Y.; et al. Short-term wind speed predicting framework based on EEMD-GA-LSTM method under large scaled wind history. Energy Conversion and Management 2021,227, 113559. 

Sponsors, Associates, and Links

---

• Information Systems and Economics
  
  
• Accounting, Auditing and Finance
  
  
• Industrial Engineering and Innovation Management
  
  
• Tourism Management and Technology Economy
  
  
• Journal of Computational and Financial Econometrics
  
  
• Accounting and Corporate Management
  
  
• Social Security and Administration Management
  
  
• Population, Resources & Environmental Economics
  
  
• Statistics & Quantitative Economics
  
  
• Agricultural & Forestry Economics and Management
  
  
• Social Medicine and Health Management
  
  
• Land Resource Management
  
  
• Information, Library and Archival Science
  
  
• Journal of Human Resource Development
  
  
• Manufacturing and Service Operations Management
  
  
• Operational Research and Cybernetics