Abstract
Based on stochastic discount factor theory, this paper proposes a method to convert the traditional systemic risk measures of financial markets, such as VaR, ES, MES and SES, into risk-neutral measures. We proposed a novel way to neutralize the returns without relying on option price information. Then, we empirically analyzed and compared the systemic risks and changes between the A-shares in Shanghai and H-shares in Hong Kong before and after a stock market crash, and we found that systematic risk measures under risk neutrality could more accurately determine market system risks than traditional systemic risk measures. Moreover, these systemic risk measures have a certain market risk warning effect.
Highlights
Systemic risk is the most important risk that must be faced and managed in the financial market
Based on stochastic discount factor theory, we proposed a new method to calculate the financial system risk measurement under risk-neutral conditions, namely, VaR, expected losses (ES), Marginal Expected Shortfall (MES) and SES
Using these systemic risk measures, we empirically analyzed the changes in the systemic risks of the Chinese stock market and the Hong Kong stock market from 2014 to 2016
Summary
Systemic risk is the most important risk that must be faced and managed in the financial market. [5] and [6] used the CoVAR method to propose a profit distribution model for the entire financial system based on the risk of a particular financial institution, namely, the “bottom-up” approach. Based on the S&P 500 Index Options, Paper [19] pointed out that risk-neutral indicators have a good predictive effect on future market returns. Based on the stochastic discount factor, this paper proposes a method for conducting systemic risk measurements under risk-neutral conditions. It uses this method to analyze the changes of the systemic risk in China’s Shanghai stock market and Hong Kong stock market and compares it with traditional risk measures. The second section is the introduction of the models and methods, the third section is the empirical results, and the final section is the conclusion
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