本文關(guān)鍵詞：利用BP神經(jīng)網(wǎng)絡(luò)系統(tǒng)對(duì)股票市場(chǎng)進(jìn)行預(yù)測(cè)與分析的研究　出處：《天津大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 股票市場(chǎng) BP神經(jīng)網(wǎng)絡(luò) 股票預(yù)測(cè)

【摘要】：股票市場(chǎng)是一個(gè)充滿了機(jī)遇與陷阱的地方。自從1990年起，股票公開(kāi)在上海、深圳兩地發(fā)行以來(lái)，炒股票已經(jīng)成為國(guó)人日常經(jīng)濟(jì)行為的中的一部分。雖然股票的收益可以非常高，但是股票同樣具有著高風(fēng)險(xiǎn)。在這種形勢(shì)下，越來(lái)越的投資人和投資機(jī)構(gòu)開(kāi)始關(guān)注于對(duì)于股市行情的走向，試圖通過(guò)股票背后大量的數(shù)據(jù)來(lái)實(shí)現(xiàn)對(duì)股票走勢(shì)的預(yù)測(cè)。在這種形勢(shì)下，對(duì)股票市場(chǎng)內(nèi)在規(guī)律的研究和預(yù)測(cè)具有著極其重要的理論意義和實(shí)用價(jià)值。 本文試圖通過(guò)利用BP（Back Propagation）神經(jīng)網(wǎng)絡(luò)進(jìn)行對(duì)股票的分析和預(yù)測(cè)。股市是一個(gè)非常復(fù)雜的非線性的動(dòng)力學(xué)系統(tǒng)，而神經(jīng)網(wǎng)絡(luò)具有很強(qiáng)的非線性逼近能力和自學(xué)、自適應(yīng)等特性。通過(guò)整理股票價(jià)格歷史數(shù)據(jù)，并使BP神經(jīng)網(wǎng)絡(luò)訓(xùn)練學(xué)習(xí)歷史數(shù)據(jù)，可以有效的找到股票市場(chǎng)價(jià)格變動(dòng)的規(guī)律，，來(lái)達(dá)到預(yù)測(cè)股票未來(lái)價(jià)格趨勢(shì)的目的。 本文分析了使用BP網(wǎng)絡(luò)對(duì)股市價(jià)格進(jìn)行預(yù)測(cè)分析中的原理，建立三層前饋神經(jīng)網(wǎng)絡(luò)建立對(duì)股票的預(yù)測(cè)模型。在實(shí)驗(yàn)中，通過(guò)對(duì)BP網(wǎng)絡(luò)參數(shù)的調(diào)整，以達(dá)到比較好的學(xué)習(xí)效果。再以五只納斯達(dá)克股票為例，應(yīng)用已經(jīng)實(shí)現(xiàn)的預(yù)測(cè)模型對(duì)其股價(jià)的未來(lái)走勢(shì)進(jìn)行預(yù)測(cè)，取得了比較好的效果。通過(guò)過(guò)往的理論研究和BP神經(jīng)網(wǎng)絡(luò)的特點(diǎn)，可以證明可以使用BP神經(jīng)網(wǎng)絡(luò)對(duì)股票價(jià)格進(jìn)行有效預(yù)測(cè)。
[Abstract]:The stock market is a place full of opportunities and pitfalls. Since 1990, stocks have been publicly issued in Shanghai and Shenzhen. Stock speculation has become a part of people's daily economic behavior. Although the return of stocks can be very high, but stocks also have high risk. In this situation. More and more investors and investment institutions are focusing on the direction of the stock market, trying to achieve the prediction of the stock market through a lot of data behind the stock. In this situation. The research and prediction of the inherent law of stock market is of great theoretical significance and practical value. This paper attempts to analyze and predict stocks by using BP(Back Propagation neural network. Stock market is a very complex nonlinear dynamic system. The neural network has strong ability of nonlinear approximation, self-learning, self-adaptation and so on. Through sorting out historical data of stock price, BP neural network is trained to learn historical data. We can find the law of stock market price change effectively to predict the stock price trend in the future. In this paper, the principle of using BP neural network to predict the stock price is analyzed, and the three-layer feedforward neural network is established to build the forecasting model of stock. In the experiment, the parameters of BP network are adjusted. In order to achieve a better learning effect. Then take five NASDAQ stocks as an example, using the realized prediction model to predict the future trend of its stock price. Through the past theoretical research and the characteristics of BP neural network, it can be proved that the BP neural network can be used to predict the stock price effectively.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP183;F832.51

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相關(guān)期刊論文 前1條

1 徐迪,馬大軍,李元熹;神經(jīng)元網(wǎng)絡(luò)在股價(jià)預(yù)測(cè)中的應(yīng)用[J];系統(tǒng)工程理論與實(shí)踐;1998年11期

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