No abstract

The current relevant models for the analysis of Shanghai Stock Exchange (SSE) options, whether for the study of theoretical algorithms or the application of verification, are still at the beginning of the research stage. Based on this, we combine the status quo of China's SSE options to construct a state-space model with a certain flexibility and combine image processing technology to extract model features. At the same time, we obtained the experimental data of this study through the network data collection method and analyzed the performance of the algorithm by comparison method, recorded the data obtained by the model operation, and turned the result into a visually identifiable feature result through image processing. The research indicates that the state-space model has certain effects on the analysis of the SSE option and can provide theoretical reference for subsequent related research.

The current relevant models for the analysis of SSE options, whether for the study of theoretical algorithms or for the application of verification, are still at the beginning of the research stage. Based on this, this study combines the status quo of China’s SSE options to construct a state space model with certain flexibility and combines image processing technology to extract model features. At the same time, this study obtained the experimental data of this study through network data collection method and analyzed the performance of the algorithm by comparison method, recorded the data obtained by the model operation, and turned the result into a visually identifiable feature result through image processing. The research indicates that the state space model has certain effects in the analysis of SSE option and can provide theoretical reference for subsequent related research.