by Qianhe Gao
2025,7(2);
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Abstract
This paper conducts an study on the relationship between financial market and the real economy,
systematically exploring the methods of financial market risk analysis and prediction, risk management strategies,
and the two-way interaction mechanism between them. In the field of risk analysis and prediction, research
methods have evolved from traditional statistical models to machine learning and deep learning technologies.
Although progress has been made in predicting market trends, challenges still remain in predicting extreme
events and data application. Risk management strategies have gone through iterations from traditional theories
such as the Capital Asset Pricing Model (CAPM) to modern models like Value at Risk (VaR) and Conditional
Value at Risk (CVaR), and have formed segmented practices in the management of the electricity financial
market, operational risks, and the global market. There is a close two-way interaction between the financial
market and the real economy: financial market risks impact the real economy through fluctuations in interest rates
and exchange rates; the state of the real economy, in turn, affects the financial market. The two form a vicious
cycle through the risk transmission mechanism. Based on this, the paper proposes collaborative governance
strategies such as constructing a dynamic risk monitoring system, innovating policy coordination mechanisms,
strengthening the ability of finance to serve the real economy, and improving the risk isolation mechanism,
aiming to enhance the stability of the financial market and promote a virtuous interaction and sustainable
development between the real economy and the financial market.
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