Next Article in Journal
Factors, Outcome, and the Solutions of Supply Chain Finance: Review and the Future Directions
Next Article in Special Issue
A Divisia User Cost Interpretation of the Yield Spread Recession Prediction
Previous Article in Journal
Asymmetric Effects of Policy Uncertainty on the Demand for Money in the United States
Previous Article in Special Issue
On the Rising Complexity of Bank Regulatory Capital Requirements: From Global Guidelines to their United States (US) Implementation
Article Menu

Export Article

Open AccessArticle
J. Risk Financial Manag. 2019, 12(1), 2;

Systemic Risk Indicators Based on Nonlinear PolyModel

Department of Applied Mathematics and Statistics, State University of New York at Stony Brook, Stony Brook, NY 11794-3600, USA
Authors to whom correspondence should be addressed.
Received: 1 December 2018 / Revised: 17 December 2018 / Accepted: 17 December 2018 / Published: 20 December 2018
(This article belongs to the Special Issue Financial Crises, Macroeconomic Management, and Financial Regulation)
Full-Text   |   PDF [2650 KB, uploaded 22 December 2018]   |  


The global financial market has become extremely interconnected as it demonstrates strong nonlinear contagion in times of crisis. As a result, it is necessary to measure financial systemic risk in a comprehensive and nonlinear approach. By establishing a large set of risk factors as the main bones of the financial market network and applying nonlinear factor analysis in the form of so-called PolyModel, this paper proposes two systemic risk indicators that can prognosticate the advent and trace the development of financial crises. Through financial network analysis, theoretical simulation, empirical data analysis and final validation, we argue that the indicators suggested in this paper are proved to be very effective in forecasting and tracing the financial crises from 1998 to 2017. The economic benefit of the indicator is evidenced by the enhancement of a protective put/covered call strategy on major stock markets. View Full-Text
Keywords: systemic risk crisis; financial indicator; network; nonlinear regression; PolyModel; validation systemic risk crisis; financial indicator; network; nonlinear regression; PolyModel; validation

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Ye, X.; Douady, R. Systemic Risk Indicators Based on Nonlinear PolyModel. J. Risk Financial Manag. 2019, 12, 2.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
J. Risk Financial Manag. EISSN 1911-8074 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top