Multi-model subject matter market prediction method and device

Abstract

The invention provides a multi-model subject matter market prediction method and device, and belongs to artificial intelligence, and the method comprises the steps: obtaining the historical data of a subject matter; preprocessing the historical data of the subject matter to determine preprocessed data; performing feature extraction on the preprocessed data, and establishing a prediction model; dividing the preprocessed data into a training set and a test set, and determining a market condition prediction model based on technical indexes, a market condition prediction model based on information and a user guessing rise and fall transaction emotion model by using the training set; respectively determining respective prediction result accuracy of the three models according to the test set; and according to respective prediction result accuracy rates of the three models, distributing weights to the market condition prediction model based on the technical indexes, the market condition prediction model based on the information and the user guessing rise and fall transaction emotion model, predicting the market condition of the current subject matter after weighted averaging, and determining a market condition prediction result of the current subject matter. According to the invention, the prediction accuracy of the subject matter is effectively improved.

Description

technical field [0001] The invention relates to the technical field of computer data processing, in particular to a method and device for predicting a multi-model target stock market. Background technique [0002] This section is intended to provide a background or context for implementations of the invention that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section. [0003] In recent years, with the development of big data, distributed, and artificial intelligence technologies, major financial industry-related companies have also made efforts to research the market forecast of the subject matter in this technology field. [0004] At present, the existing technology mainly collects the historical technical index information of the subject matter and conducts machine learning modeling analysis to predict the market trend of the subject matter. Since the market trend of the subject matter has great uncertainty, it i...

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Problems solved by technology

[0004] At present, the existing technology mainly collects the historical technical index information of the subject matter and conducts machine learning modeling analysis to predict the market trend of the subject matter. Since the market trend of the subject matter has great uncertainty, it is not only affected by the historical trend of the subject matter itself, technology Influenced by objective factors such as indicators, it will also be affected by key factors such as public opinion and human emotions. Therefore, it is difficult to restore the complexity of the target market forecast by relying solely on the historical trend of the subject matter and technical index data to model and predict the market, which affects the accuracy of the forecast. Rate

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