ICDSBA 18
Measuring Systemic Risk in the Chinese Financial System Based on Asymmetric Exponential Power Distribution
H. Li, T. Luo, L. Li, T. Liu
Recent Developments in Data Science and Business Analytics (Springer Proceedings in Business and Economics), pp. 225-232, 2018
Abstract
We propose an extension of CoVaR approach by employing the Asymmetric Exponential Power Distribution (AEPD) to capture the properties of financial data series such as fat-tailedness and skewness. We prove the new model with AEPD has better goodness-of-fit than traditional model with Gaussian distribution, which means a higher precision. Basing on the Chinese stock market data and the new model, we measure the contribution of 29 financial institutions in bank, security, insurance and other industries.
financial-risk
BibTeX
@InProceedings{Li2018SystemicRisk,
author = {Li, Helong and Luo, Tianqi and Li, Liuling and Liu, Tiancheng},
editor = {Tavana, Madjid and Patnaik, Srikanta},
title = {Measuring Systemic Risk in the Chinese Financial System Based on Asymmetric Exponential Power Distribution},
booktitle = {Recent Developments in Data Science and Business Analytics},
year = {2018},
publisher = {Springer International Publishing},
address = {Cham},
pages = {225--232},
isbn = {978-3-319-72745-5},
doi = {10.1007/978-3-319-72745-5_24}
}