本文關(guān)鍵詞：數(shù)據(jù)挖掘方法在股票分析中的應(yīng)用與研究　出處：《西南財(cái)經(jīng)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： 數(shù)據(jù)挖掘 決策樹 神經(jīng)網(wǎng)絡(luò) logistic回歸 財(cái)務(wù)指標(biāo) 股票投資

【摘要】：改革開放以來,隨著我國經(jīng)濟(jì)的快速發(fā)展,股市應(yīng)運(yùn)而生。我國股市自成立以來,歷經(jīng)了風(fēng)風(fēng)雨雨之后,伴隨著成長,逐步發(fā)展壯大。并且隨著人民生活水平的日益提高,人們手頭閑置的資金也越來越多,投資需求日益旺盛,投資意識(shí)和金融意識(shí)也日益增長,投資方式也越來越多樣化。股票市場(chǎng)由于其高風(fēng)險(xiǎn)高回報(bào)的特性,長期以來,不斷吸引人們投入到其中,逐漸成為許多人投資的重要手段之一。越來越多的人將手頭的資金投入到股市,以期獲得較為可觀的回報(bào)。然而由于專業(yè)知識(shí)的缺乏、信息的不對(duì)稱性等等原因,人們對(duì)于股市的投資往往帶有盲目性、投機(jī)性,很難獲得可觀的收益。因此,對(duì)于股票市場(chǎng),尋求一套有效的方法,降低人們投資的風(fēng)險(xiǎn),同時(shí)提高人們投資的收益就顯得非常重要。在股票市場(chǎng)中,時(shí)刻都會(huì)誕生大量的數(shù)據(jù),上市公司也會(huì)定期發(fā)布大量的財(cái)務(wù)數(shù)據(jù),如何有效地利用這些數(shù)據(jù),減少投資者的投資風(fēng)險(xiǎn),從而給投資者帶來較高的回報(bào)便成為了一個(gè)非常值得分析研究的問題。 上市公司定期發(fā)布的財(cái)務(wù)報(bào)告數(shù)據(jù)具有較大的信息含量,這些信息含量包括各種財(cái)務(wù)比率指標(biāo)。綜合這些財(cái)務(wù)指標(biāo),能夠一定程度上反映公司整體的經(jīng)營運(yùn)行狀況,有利于投資者判斷公司的內(nèi)在價(jià)值,從而有助于投資者更好地判斷上市公司股票的投資價(jià)值。對(duì)于中長期的投資者來說,如何利用這些信息來判斷股票的未來投資價(jià)值,顯得尤為重要。而本文試圖通過數(shù)據(jù)挖掘技術(shù),來研究上市公司公布的財(cái)務(wù)比率指標(biāo)和股票投資價(jià)值的內(nèi)在聯(lián)系,期望挖掘出財(cái)務(wù)數(shù)據(jù)中有用的信息,從而對(duì)股票的投資價(jià)值作出更好的判斷。傳統(tǒng)的統(tǒng)計(jì)模型對(duì)于數(shù)據(jù)有較高的要求,對(duì)于數(shù)據(jù)的假定較多,要求過于嚴(yán)格,實(shí)際中的數(shù)據(jù)往往很難達(dá)到這種要求,而數(shù)據(jù)挖掘技術(shù)對(duì)于數(shù)據(jù)的要求相對(duì)較低,能夠相對(duì)較好地處理非正態(tài)、非平穩(wěn)、高噪聲的數(shù)據(jù)。數(shù)據(jù)挖掘通過結(jié)合統(tǒng)計(jì)學(xué)、機(jī)器學(xué)習(xí)和人工智能等技術(shù)對(duì)于處理海量數(shù)據(jù)和高頻數(shù)據(jù)往往能夠達(dá)到不錯(cuò)的效果。另外數(shù)據(jù)挖掘還能夠?qū)Σ粩喃@得的新數(shù)據(jù)進(jìn)行模型的動(dòng)態(tài)更新,非常適合應(yīng)用于新環(huán)境。數(shù)據(jù)挖掘是當(dāng)今國際上統(tǒng)計(jì)學(xué)、人工智能和數(shù)據(jù)庫研究方面最富活力的新興領(lǐng)域,從大型數(shù)據(jù)庫中挖掘有效信息的問題已經(jīng)成為近年來數(shù)據(jù)分析研究領(lǐng)域中的一個(gè)新熱點(diǎn)。股票投資風(fēng)險(xiǎn)與機(jī)遇并存,如何把握風(fēng)險(xiǎn),使投資回報(bào)最大化是投資者追求的目標(biāo)。在上市公司公布的財(cái)務(wù)數(shù)據(jù)以及股票行情數(shù)據(jù)庫中積累了大量的歷史數(shù)據(jù),如何充分利用這些歷史數(shù)據(jù),為投資者提供決策依據(jù),把數(shù)據(jù)挖掘方法運(yùn)用于股市投資研究和探索變得很有意義。因此,本文嘗試用數(shù)據(jù)挖掘中的方法來對(duì)上市公式財(cái)務(wù)數(shù)據(jù)進(jìn)行分析,目的是發(fā)現(xiàn)公司財(cái)務(wù)數(shù)據(jù)和股票投資價(jià)值的聯(lián)系,為投資者提供參考。 本文基于國內(nèi)外研究成果,介紹了數(shù)據(jù)挖掘的相關(guān)理論,并且引入數(shù)據(jù)挖掘的相關(guān)方法對(duì)上市公司定期公布的財(cái)務(wù)比率指標(biāo)和股票價(jià)格變化之間的關(guān)系進(jìn)行了研究分析。文章中用到的數(shù)據(jù)挖掘技術(shù)包括決策樹分類、神經(jīng)網(wǎng)絡(luò)模型以及l(fā)ogistic回歸模型三種方法,將三種方法運(yùn)用于股票價(jià)值投資分析中,通過三種方法來研究上市公司公布的財(cái)務(wù)比率指標(biāo)與股票投資價(jià)值之間的內(nèi)在聯(lián)系,并試圖尋找哪些財(cái)務(wù)指標(biāo)對(duì)于上市公司的股價(jià)的變化有較大的影響,并且對(duì)三種方法取得的結(jié)果進(jìn)行評(píng)估和對(duì)比分析,比較各種模型進(jìn)行實(shí)證分析時(shí)取得的效果,從而更好地判斷股票的投資價(jià)值。文中建立模型時(shí)以上市公司公布的財(cái)務(wù)指標(biāo)作為輸入變量,為便于不同上市公司的比較,財(cái)務(wù)指標(biāo)均選取財(cái)務(wù)比率指標(biāo)。并為了綜合反映公司的運(yùn)行狀況,從公司盈利能力、償債能力、發(fā)展能力、運(yùn)營能力以及現(xiàn)金流五個(gè)大的方面來選取指標(biāo),以更為準(zhǔn)確的反映公司的內(nèi)在價(jià)值。此外,以個(gè)股贏率作為目標(biāo)變量建立模型。其中個(gè)股贏率為二元變量,當(dāng)股票一年期的漲跌幅大于大盤指數(shù)的漲跌幅時(shí)取“1”,否則便取“O”。文章的思路便是以綜合反映上市公司運(yùn)行狀況的財(cái)務(wù)比率指標(biāo)為輸入變量,以個(gè)股贏率為目標(biāo)變量,來研究分析上市公司公布的財(cái)務(wù)比率指標(biāo)和上市公司個(gè)股贏率是不是存在關(guān)系,如果存在關(guān)系,哪些財(cái)務(wù)比率指標(biāo)對(duì)個(gè)股贏率的影響較大以及哪種模型預(yù)測(cè)效果較好,這些都是文章中要研究和解決的問題。
[Abstract]:Since the reform and opening up, with the rapid development of China's economy, the stock market. China's stock market since its inception, after the groundless talk, along with the growth, gradually growing. And with the increasing of people's living standard, people idle funds on hand is increasing, investment demand is increasingly vigorous, consciousness and awareness of financial investment is growing, investment is becoming more and more diversified. The stock market because of its high risk and high return characteristics, long time, continue to attract people into it, has gradually become the important measure to many investment. More and more people would put money into the stock market, in order to obtain a more substantial returns. However due to the lack of professional knowledge, information asymmetry and other reasons, the people to invest in the stock market often with blindness, speculation, it is difficult to obtain benefits. Therefore view, For the stock market, to seek an effective method to reduce the risk of investment in people, it is very important to improve the return on investment. At the same time, people in the stock market, the moment will be the birth of a large number of data, listed companies will regularly publish financial data, how to use these data effectively, decrease the risk of investment thus, to give investors higher returns will become a very worthy of study.
The financial report data of the listed companies has regularly published information content is big, the information content including financial ratios. These financial indicators, to a certain extent reflect the company's overall business operation status, intrinsic value for investors to judge companies, and help investors to better judge the listed company stock investment value. For long-term investors, the future investment value of how to use the information to judge the stock, is particularly important. This paper through the data mining technology, internal relations of financial ratio index and stock investment value of listed companies released, expected to dig out the useful information in the financial data, so as to make better judgment the stock investment value. The traditional statistical model has a higher requirement for the data, the data is assumed to. Pray too strict, actual data is often difficult to meet this requirement, the technology of data mining for data requirements are relatively low, relatively better treatment of non normal, non smooth, high noise data. Data mining by combining statistics, machine learning and artificial intelligence technology for processing massive data and high frequency data tend to be able to achieve good results. Data mining can also dynamically update the model of new data obtained continuously, very suitable for the new environment. Data mining is one of the emerging field of statistics, artificial intelligence and database of the most dynamic, mining useful information from large databases has become a problem data analysis is a new hotspot in the research field in recent years. The stock investment risks and opportunities, how to grasp the risk, to maximize the return on investment is investment The pursuit of the goal. In the financial data released by the listed company and the stock market database has accumulated a lot of historical data, how to make full use of the historical data, to provide decision-making basis for investors, the data mining method is used to study and explore the stock market investment becomes very significant. Therefore, this paper attempts to use the method of data mining to to analyze the financial data of listed formula, the purpose is to find the financial data and stock investment value, provide a reference for investors.
Based on the research results at home and abroad, introduces the related theory of data mining, the relationship between financial ratios and stock price changes and the introduction of related methods of data mining to regularly publish listed companies were analyzed. The data used in the article mining technology including decision tree classification, neural network model and logistic regression model three methods the three methods applied to stock value investment analysis, to study the relationship between financial ratios and stock investment value of listed companies published by the three methods, and try to find out what changes in financial indicators for the stock prices of listed companies have a great effect, and get the results of three methods were analysis of evaluation and comparison, made empirical analysis and comparison of various models of the effect, so as to judge the investment value of stock better in this paper. To set up the model to the listed companies announced financial indicators as input variables, to facilitate comparisons of different companies, financial indicators are selected financial ratios. And in order to reflect the operation status of the company, from the company's profitability, solvency, development ability, operation ability and cash flow five aspects of selection index, to more accurately reflect the intrinsic value of the company. In addition, the stocks win rate as the target variable model. The stocks win rate of two yuan a year variable, when the stock price is greater than the market index rose from "1", otherwise it will take the "O". It is thought to reflect the financial ratios of listed companies operating conditions as input variables, in order to win stock rate as target variable, to study the listed companies announced the financial ratios of listed companies and stocks win rate is not saved In relation, if there is a relationship, which financial ratios index has a greater impact on the winning rate of stocks and what models predict better? These are the problems to be studied and solved in the article.

【學(xué)位授予單位】：西南財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.51;F224

【參考文獻(xiàn)】

相關(guān)期刊論文 前7條

1 陸璇,張嶺松,陳小悅;利用上市公司公開的財(cái)務(wù)信息預(yù)測(cè)未來的銷售[J];當(dāng)代經(jīng)濟(jì)科學(xué);2003年01期

2 趙宇龍;會(huì)計(jì)盈余披露的信息含量——來自上海股市的經(jīng)驗(yàn)證據(jù)[J];經(jīng)濟(jì)研究;1998年07期

3 陳曉,陳小悅,劉釗;A股盈余報(bào)告的有用性研究——來自上海、深圳股市的實(shí)證證據(jù)[J];經(jīng)濟(jì)研究;1999年06期

4 朱紹文,胡宏銀,王泉德,張大斌,黃浩,陸玉昌;決策樹采掘技術(shù)及發(fā)展趨勢(shì)[J];計(jì)算機(jī)工程;2000年10期

5 陳光華;;人工神經(jīng)網(wǎng)絡(luò)在證券價(jià)格預(yù)測(cè)中的應(yīng)用[J];計(jì)算機(jī)仿真;2007年10期

6 劉新勇,賀江峰,孟祥澤,陳增強(qiáng),袁著祉;基于神經(jīng)網(wǎng)絡(luò)的股市預(yù)測(cè)[J];南開大學(xué)學(xué)報(bào)(自然科學(xué)版);1998年03期

7 陸璇;劉慧霞;陳曉;;中國上市公司未來收益預(yù)測(cè)的實(shí)證研究——貝葉斯動(dòng)態(tài)模型及其預(yù)測(cè)[J];中南大學(xué)學(xué)報(bào)(社會(huì)科學(xué)版);2003年02期

，

本文編號(hào)：1394645