The thesis focuses on how to find a probability local optimal solution that maximizes relative benefits in the ever-changing stock market, and establishes a stock model for future expected trends and an investment analysis model that optimizes returns. First of all, the background and error analysis at that time should be obtained through the establishment of each stock market value and sector index, and the relevant information should be inquired, and the functional relationship between the corrected value and the original value should be obtained, to build three different models of related moving averages. For different model analysis and data processing, use ARIMA model and grey model to simulate its future expected trend, and use third-order difference to improve images and data, and compare some major events that have occurred recently to make an artificial background. Correction, and finally get a time-dependent model of it. For the establishment of the investment model, the relevant knowledge of probability theory is used to carry out continuous linear combination of high-quality solutions, the high-temperature annealing model is used to narrow the scope, and lingo is used to solve the local optimal solution, so that the risks and benefits can be optimized.

Shaocheng Hu, Shang Li, Yizhou Wang, Huayu Xue, Chen Gao. Development Trend Analysis and Prediction of Photovoltaic Building Integration Plate Index. Academic Journal of Business & Management (2022) Vol. 4, Issue 5: 6-9. https://doi.org/10.25236/AJBM.2022.040502.

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