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Application and Innovation in Financial Market Risk Management Based on Big Data and Artificial Intelligence

  
21 mar 2025

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Figure 1.

Modeling process of ARFIMA model
Modeling process of ARFIMA model

Figure 2.

Series model prediction flow chart
Series model prediction flow chart

Figure 3.

The trend of the closing price
The trend of the closing price

Figure 4.

Yield of Shangzhen 50 index day yield
Yield of Shangzhen 50 index day yield

Figure 5.

Yield squared
Yield squared

Figure 6.

Ljung-box check the p value
Ljung-box check the p value

Figure 7.

Control of volatility and financial crisis
Control of volatility and financial crisis

Figure 8.

Nonlinear component error self-associated function diagram
Nonlinear component error self-associated function diagram

Figure 9.

Nonlinear component network training result diagram
Nonlinear component network training result diagram

Figure 10.

Series hybrid model prediction
Series hybrid model prediction

Figure 11.

Residual difference fabric histogram
Residual difference fabric histogram

Figure 12.

Standard deviation
Standard deviation

Figure 13.

Risk value var trend diagram
Risk value var trend diagram

Figure 14.

Risk alert diagram
Risk alert diagram

Figure 15.

Stock yield range column chart
Stock yield range column chart

Residual description

Variable Numerical value
Mean value -0.0011645
Standard deviation 0.0245188
Maximum value 0.1445756
Minimum value -0.1678244
Degree of bias -0.025
Kurtosis 3.312

Series hybrid model predictive energy index

Model MSE RMSE MAE
ARFIMA-GARCH-LSTM 0.000386 0.019559 0.014479

Descriptive statistics

Mean Median Maximum value Minimum value Standard deviation Kurtosis Degree of bias Adf test
2.78e-4 4.62e-4 7.82e-2 -9.35e-2 1.52e-2 6.475 -0.588 -7.625(0.000)

Descriptive statistics of the price data

Variable Mean Median Maximum value Minimum value
Opening price 2619.061 2642.19 2597.586 2621.28
Maximum price 2614.54 2640.291 2591.675 2623.009
Lowest price 1915.107 1953.378 1874.166 1912.711
Closing price 3494.843 3494.713 3403.695 3458.697
Volume 339.332 341.808 334.741 338.293
Turnover amount 2619.051 2642.2 2597.486 2621.25