Research on CSI 300 Index Price Prediction Based on LSTM Algorithm
Abstract
irregular linear characteristic trajectories. Some traditional sequential prediction methods have subtly revealed their limitations and shortcomings in the process of stock price fluctuations. Practical results show that this paper selects CSI 300 original data as the foundation, constructs
an extremely complex prediction technology system through the long short-term memory (LSTM) network series, and discusses the adaptability of hierarchical algorithms in processing continuous time series data. The current pattern of “integration of information and computing
power” is subtly permeating the specific operational links of the industry, and more cross-border attempts and very complete and complex
organizational system construction may emerge in the future.
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DOI: http://dx.doi.org/10.18686/fm.v10i6.14341
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