TY - GEN
T1 - Predicting Chinese bond market turbulences
T2 - 2nd International Conference on Big Data Engineering, BDE 2020
AU - Wang, Peiwan
AU - Zong, Lu
AU - Yang, Yurun
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/5/29
Y1 - 2020/5/29
N2 - The study aims to construct an effective early warning system (EWS) to predict the crisis triggered turbulence in Chinese bond market by integrating the volatility regime switching model, SWARCH, to improve the crisis classifying precision, and the stylized predictive model, Attention-BiLSTM of attention mechanism based deep neural networks, to resolve the predicting hysteresis. The model versatility and comparability are investigated and testified by applying multiple prominent EWS models to bonds with different credit rating levels. The hybrid EWS also specifies the leading factors relating to the bond credit rating, that will practically instruct governors and market participants to focus on either the national economy associated or the corporate finance concerned factors according to the bond varying credit risks to make more effective predictions.
AB - The study aims to construct an effective early warning system (EWS) to predict the crisis triggered turbulence in Chinese bond market by integrating the volatility regime switching model, SWARCH, to improve the crisis classifying precision, and the stylized predictive model, Attention-BiLSTM of attention mechanism based deep neural networks, to resolve the predicting hysteresis. The model versatility and comparability are investigated and testified by applying multiple prominent EWS models to bonds with different credit rating levels. The hybrid EWS also specifies the leading factors relating to the bond credit rating, that will practically instruct governors and market participants to focus on either the national economy associated or the corporate finance concerned factors according to the bond varying credit risks to make more effective predictions.
KW - Attention mechanism
KW - Deep neural networks
KW - Early warning system
KW - Regime switching ARCH
KW - Volatility classified crisis
UR - http://www.scopus.com/inward/record.url?scp=85089587547&partnerID=8YFLogxK
U2 - 10.1145/3404512.3404521
DO - 10.1145/3404512.3404521
M3 - Conference Proceeding
AN - SCOPUS:85089587547
T3 - ACM International Conference Proceeding Series
SP - 91
EP - 104
BT - Proceedings of the 2020 2nd International Conference on Big Data Engineering, BDE 2020
PB - Association for Computing Machinery
Y2 - 29 May 2020 through 31 May 2020
ER -