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Short term stock price forecasting with application of neural network

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thesis
posted on 24.05.2021, 18:27 by Jiayin Liu
With the world’s rapid economic growth and the expansion of stock market, it produced a large amount of valuable data information. That data become an important investors in stock investment analysis subject Thorough analysis the short-term stock price forecast problem and comparing a variety of stock price forecasting method, on the basis of BP neural network (BPNN) [1] and principal component analysis (PCA)[2] and genetic algorithm and the feasibility of short-term prediction of stock price .BP neural network can use the study of historical stock market data, find out the inherent law of development and change of the stock market, so as to realize the future stock price data changes over a period of time.

History

Degree

Master of Engineering

Program

Electrical and Computer Engineering

Granting Institution

Ryerson University

LAC Thesis Type

Thesis