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Method for model building, forecasting and decision-making of stock market based on BP neural net

A BP neural network and decision-making technology, applied in biological neural network models, neural learning methods, instruments, etc., can solve the problems of complex correlation, unsatisfactory modeling and prediction results, etc., and achieve effective and easy-to-operate methods Effect

Inactive Publication Date: 2008-10-01
ZHONGYUAN ENGINEERING COLLEGE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the correlation among various factors in the stock market is intricate, and it is a multivariable nonlinear system. The modeling of the multivariable nonlinear system has not yet reached a mature level, and there are still uncertainties in the stock market, which makes Some modeling and forecasting results are often unsatisfactory

Method used

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  • Method for model building, forecasting and decision-making of stock market based on BP neural net
  • Method for model building, forecasting and decision-making of stock market based on BP neural net
  • Method for model building, forecasting and decision-making of stock market based on BP neural net

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Experimental program
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Embodiment Construction

[0024] The first step: determine the input of the BP neural network.

[0025] The input of the BP neural network is the market information of the stock on the day, using eight input signals X 1 、X 2 、X 3 、X 4 、X 5 、X 6 、X 7 、X 8 ,in:

[0026] x 1 : closing price of the day

[0027] x 2 : Trading volume of the day

[0028] x 3 : Turnover of the day

[0029] x 4 : The highest price of the day divided by the average highest price of the previous 5 days

[0030] x 5 : The trading volume of the day divided by the average trading volume of the previous 5 days

[0031] x 6 : The highest price of the day divided by the average highest price of the previous 15 days

[0032] x 7 : The trading volume of the day divided by the average trading volume of the previous 15 days

[0033] x 8 : The highest price of the year minus the closing price of the current day.

[0034] The second step: determine the output of the BP neural network.

[0035] The output of the BP neur...

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Abstract

The invention relates to a method for stock market modeling, forecasting and making decisions based on BP neural network; according to 8 easily-obtained messages: closing price, turnover, volume of transaction, value obtained by dividing the average maximum price of former 5 days by maximum price today, value obtained by dividing the average turnover of the former 5 days by turnover today, value obtained by dividing the average maximum price of former 15 days by maximum price today, value obtained by dividing the average turnover of the former 15 days by turnover today, and the value obtained by subtracting the closing price today by the maximum price in this year, the method forecast the highs and lows information of afternoon market via establishing the BP neural network forecast model of the market information today and the mapping relation ship of highs and lows of afternoon market, and the method makes the trade decision about the next stock-trading day according to the forecasting highs and lows information; the method is easily operable to efficiently forecast the stock market and make the decisions.

Description

technical field [0001] The present invention relates to a stock market modeling, forecasting and decision-making method based on BP neural network. The method only needs to input eight easily obtained stock information such as the closing price and trading volume of the day, and the system can give the stock market information of the next trading day. Buying and selling decisions, this method is effective and easy to operate. Background technique [0002] The stock market is a market where risks and benefits coexist. The modeling and forecasting of the stock market is of great significance to the economic development and financial construction of our country. However, the correlation among various factors in the stock market is intricate, and it is a multivariable nonlinear system. The modeling of the multivariable nonlinear system has not yet reached a mature level, and there are still uncertainties in the stock market, which makes Some modeling and forecasting results are...

Claims

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Application Information

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IPC IPC(8): G06Q40/00G06N3/06G06N3/08G06Q40/04
Inventor 禹建丽
Owner ZHONGYUAN ENGINEERING COLLEGE
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