本文關(guān)鍵詞：部分線性模型在股票價(jià)格預(yù)測(cè)中的應(yīng)用研究　出處：《遼寧師范大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 股票價(jià)格 預(yù)測(cè) 部分線性模型 主成分分析

【摘要】：隨著我國(guó)經(jīng)濟(jì)的快速發(fā)展和完善，證券投資特別是股票交易正逐漸發(fā)展成為當(dāng)今經(jīng)濟(jì)社會(huì)的重要環(huán)節(jié)。股票是市場(chǎng)經(jīng)濟(jì)的產(chǎn)物，股票的發(fā)行與交易促進(jìn)著市場(chǎng)經(jīng)濟(jì)的發(fā)展。股票預(yù)測(cè)分析是指以準(zhǔn)確的統(tǒng)計(jì)資料和股市信息為依據(jù)，從股市的歷史、現(xiàn)狀和規(guī)律出發(fā)，運(yùn)用科學(xué)的方法對(duì)股票未來(lái)發(fā)展?fàn)顩r進(jìn)行測(cè)定。從我國(guó)目前股票交易市場(chǎng)情況出來(lái)看，，中國(guó)股票交易市場(chǎng)存在著很多的不確定因素。同時(shí)股票預(yù)測(cè)還是理性投資、科學(xué)投資的重要前提。根據(jù)這些具體情況，本文主要工作如下： 第一，本文介紹了股票的相關(guān)基礎(chǔ)知識(shí)，特別介紹了影響股票價(jià)格的公司主要財(cái)務(wù)指標(biāo)。在這些基礎(chǔ)知識(shí)之上，介紹了已有的股票價(jià)格預(yù)測(cè)方法，并分析了每種方法的優(yōu)缺點(diǎn)。 第二，闡述了本文所應(yīng)用于股票預(yù)測(cè)的統(tǒng)計(jì)模型。本文的統(tǒng)計(jì)模型，主要包括部分線性模型和主成分分析兩部分。首先對(duì)部分線性模型進(jìn)行概述，并且討論了部分線性模型的最小二乘估計(jì)，最后介紹了主成分分析原理。 第三，本文通過(guò)中國(guó)銀河證券海王星股票分析軟件，得到傳統(tǒng)能源板塊的66支股票，去除3支ST股票和數(shù)據(jù)缺失、異常的11支股票，剩余的52支股票的2010年12月30日公布的公司財(cái)務(wù)指標(biāo)和個(gè)只股票的收盤(pán)價(jià)作為回歸分析的樣本數(shù)據(jù)。先運(yùn)用相關(guān)性分析、單元回歸等方法對(duì)個(gè)只股票的公司財(cái)務(wù)指標(biāo)進(jìn)行篩選篩選，其次利用主成分分析方法對(duì)篩選出的財(cái)務(wù)指標(biāo)數(shù)據(jù)進(jìn)行降維處理，最后基于降維后的數(shù)據(jù)擬合部分線性模型。并且根據(jù)2011年9月30日公布的財(cái)務(wù)指標(biāo)，應(yīng)用本文統(tǒng)計(jì)模型對(duì)當(dāng)日股票收盤(pán)價(jià)進(jìn)行預(yù)測(cè)，通過(guò)與實(shí)際股票收盤(pán)價(jià)相比較。同時(shí)還應(yīng)用線性模型對(duì)股票價(jià)格進(jìn)行預(yù)測(cè)，將兩種方法的預(yù)測(cè)結(jié)果相對(duì)比說(shuō)明本文方法具有一定的應(yīng)用價(jià)值。
[Abstract]:With the rapid development and improvement of China's economy, securities investment, especially stock trading, is gradually developing into an important part of the economic society. Stock is the product of market economy. Stock issue and trading promote the development of market economy. Stock prediction and analysis is based on accurate statistical data and stock market information, starting from the history, current situation and law of stock market. Using scientific methods to determine the future development of stocks. From the current stock market situation in China to see. There are many uncertain factors in China's stock market. At the same time, stock forecasting is also an important prerequisite for rational investment and scientific investment. According to these specific conditions, the main work of this paper is as follows: First, this paper introduces the basic knowledge of the stock, especially the main financial indicators that affect the stock price. On the basis of these knowledge, the paper introduces the existing methods of stock price prediction. The advantages and disadvantages of each method are analyzed. Secondly, this paper describes the statistical model used in stock forecasting. The statistical model of this paper mainly includes two parts: partial linear model and principal component analysis. Firstly, the partial linear model is summarized. The least square estimation of partial linear model is discussed, and the principle of principal component analysis is introduced. Thirdly, through the software of Neptune stock analysis of China Galaxy Securities, this paper obtains 66 stocks of traditional energy plate, removes 3 St stocks and missing data, and 11 abnormal stocks. The financial indexes of the remaining 52 stocks published on December 30th 2010 and the closing price of each stock were used as the sample data of regression analysis. First, the correlation analysis was used. The unit regression method is used to screen the financial index of a stock, and the principal component analysis method is used to reduce the dimension of the selected financial index data. Finally, based on the reduced dimension data fitting partial linear model, and according to the financial indicators published on September 30th 2011, this paper uses the statistical model to forecast the closing price of the stock on that day. Compared with the actual stock closing price, the linear model is also used to predict the stock price. The comparison of the results of the two methods shows that this method has certain application value.
【學(xué)位授予單位】：遼寧師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F224;F832.51

【參考文獻(xiàn)】

相關(guān)期刊論文 前3條

1 丁雪梅,李英梅,倫立軍;基于神經(jīng)網(wǎng)絡(luò)的證券預(yù)測(cè)技術(shù)研究[J];哈爾濱師范大學(xué)自然科學(xué)學(xué)報(bào);2003年04期

2 吳如海,宋逢明;基金分離下中國(guó)股市交易量模型的實(shí)證研究[J];管理科學(xué)學(xué)報(bào);2000年01期

3 國(guó)琳;楊寶臣;;利用財(cái)務(wù)指標(biāo)預(yù)測(cè)股票價(jià)格及財(cái)務(wù)風(fēng)險(xiǎn)預(yù)警[J];科學(xué)技術(shù)與工程;2005年23期

本文編號(hào)：1371643