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Study of Stock Price Estimating Method

Author: WeiZhongQian
Tutor: ChenZhaoJiang
School: Beijing
Course: Technical Economics and Management
Keywords: Stock Capital Asset Pricing Model Artificial Neural Networks BP algorithm
CLC: F830.9
Type: Master's thesis
Year: 2002
Downloads: 382
Quote: 0
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The stock market , especially China 's stock market , it seems that is always a spectacular cloud wave sly deceitful lies elusive precisely the reason of its charm . We come into contact with many theoretical models and securities investment in actual combat operations evaluation results are different degrees of deviation from the actual situation of China's securities market , and its significance to play a larger discount . Therefore, I would like from a new perspective , a new approach to modeling , to guide investment . This paper attempts to single exponential smoothing valuation , the effect is not very satisfactory ; recent years , artificial neural network theory to study the rise again worldwide , has been widely used in the field of computer science, medicine and the military , aerospace industries , and the the introduction of this approach to stock valuation is just emerging in academia soon . I also tried to apply this new approach to try and explore . Due to a lot of factors that affect the stock price , they are non - linear , complex coupling relationship happens to the neural network to process large amounts of raw data , rather than using rules or formulas to describe the problem , showing a great deal of flexibility and adaptability . Theoretically , this method is more practical . The theoretical basis , I for one stock - the Three Gorges Water Conservancy ( 600116 ) , using BP network established for this stock valuation models , and of Zhezhi stocks estimated price and the actual price curve fitting in practice also achieved satisfactory results . Fitting results and analysis of its causes , and pointed out the strengths and weaknesses of this model lies . And stock investment decision support system is developed using DELPHI database .

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CLC: > Economic > Fiscal, monetary > Finance, banking > Finance, banking theory > Financial market
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