發(fā)布時(shí)間：2018-02-23 07:54

  本文關(guān)鍵詞： 聚類(lèi)分析 模糊C-均值聚類(lèi) β-KFCM 粗糙模糊C-均值聚類(lèi)　出處：《東北石油大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：聚類(lèi)分析是重要數(shù)據(jù)挖掘算法之一。近年來(lái),隨著數(shù)據(jù)庫(kù)技術(shù)的飛速發(fā)展和廣泛應(yīng)用,人們的生產(chǎn)活動(dòng)產(chǎn)生大量的多元化數(shù)據(jù)。面對(duì)大規(guī)模的數(shù)據(jù),數(shù)據(jù)挖掘的一項(xiàng)重要任務(wù)就是將其進(jìn)行合理的歸類(lèi)。聚類(lèi)分析就是一種有效的將數(shù)據(jù)合理歸類(lèi)的方法,它可以從大量數(shù)據(jù)中發(fā)現(xiàn)隱含在其中的數(shù)據(jù)結(jié)構(gòu)。隨著我國(guó)資本市場(chǎng)的發(fā)展,中國(guó)股市已經(jīng)具有一定規(guī)模,上市公司數(shù)量也有了很大提升。在股市發(fā)展初期,股民的投資具有較強(qiáng)的投機(jī)性,基本面和技術(shù)面的分析已經(jīng)明顯失去了有效性,投資無(wú)法獲得收益甚至嚴(yán)重虧損,運(yùn)用會(huì)計(jì)指標(biāo)進(jìn)行理智的選擇股票就需要對(duì)股票自身的品質(zhì)進(jìn)行評(píng)價(jià),放眼全球目前能夠在資本市場(chǎng)占有一席之地的只有量化投資。本文系統(tǒng)的介紹了模糊聚類(lèi)方法的國(guó)內(nèi)外研究情況、研究的目的及意義,并且將理論研究與實(shí)證研究相結(jié)合,分層次介紹數(shù)據(jù)結(jié)構(gòu)理論、數(shù)據(jù)樣本間相似屬性和聚類(lèi)準(zhǔn)則函數(shù)。研究了的模糊聚類(lèi)理論,以模糊聚類(lèi)分析算法及實(shí)現(xiàn)過(guò)程為主線(xiàn);首先研究模糊C-均值理論中數(shù)據(jù)集C劃分方法和模糊C-均值分類(lèi)法;模糊C-均值聚類(lèi)算法理論中對(duì)模糊核聚類(lèi)算法和高斯核模糊C-均值目標(biāo)函數(shù)進(jìn)行求解;結(jié)合投資組合理論將投資組合中單個(gè)資產(chǎn)對(duì)組合貢獻(xiàn)率考慮其中同時(shí)解釋了β的投資意義,提出加權(quán)模糊核聚類(lèi)算法β-KFCM模糊分類(lèi)法;最后研究了粗糙模糊C-均值基本理論,并簡(jiǎn)化了粗糙模糊C-均值聚類(lèi)算法。本文實(shí)證部分,選取2015年第四季度和2016年第三季度流動(dòng)比率、現(xiàn)金比率、營(yíng)業(yè)收入同比增長(zhǎng)率、總資產(chǎn)報(bào)酬率、銷(xiāo)售凈利率和資產(chǎn)負(fù)債率六個(gè)財(cái)務(wù)指標(biāo)對(duì)A股市場(chǎng)不同板塊50支股票進(jìn)行實(shí)證分析,結(jié)合股票收益率將50支股票分為三類(lèi)投資等級(jí),其中Ⅰ類(lèi)為建議的優(yōu)質(zhì)投資品種,Ⅱ類(lèi)和Ⅲ類(lèi)次之。
[Abstract]:Clustering analysis is one of the important data mining algorithms. In recent years, with the rapid development and wide application of database technology, people's production activities produce a large number of diversified data. One of the important tasks of data mining is to classify the data reasonably, and clustering analysis is an effective method to classify the data reasonably. With the development of China's capital market, the Chinese stock market has already had a certain scale, and the number of listed companies has also greatly increased. In the early stage of the stock market development, The investors' investment is highly speculative, the analysis of fundamental and technical aspects has obviously lost its effectiveness, and the investment has not been able to obtain income or even a serious loss. The use of accounting indicators for rational selection of stocks requires evaluation of the quality of the stock itself. At present, there is only quantitative investment in the capital market. This paper systematically introduces the domestic and foreign research situation of fuzzy clustering method, the purpose and significance of the research, and combines the theoretical research with empirical research. This paper introduces the theory of data structure, similar attributes and clustering criterion functions among data samples. The fuzzy clustering theory is studied, and the main line is fuzzy clustering analysis algorithm and its implementation process. Firstly, the methods of data set C partition and fuzzy Cmean classification in fuzzy Cmean theory are studied, and the fuzzy kernel clustering algorithm and Gao Si kernel fuzzy Cmean objective function are solved in fuzzy Cmean clustering algorithm theory. Combined with portfolio theory, the contribution rate of single asset to portfolio in portfolio is considered, and the significance of 尾 investment is explained at the same time, a weighted fuzzy kernel clustering algorithm 尾 -KFCM fuzzy classification is proposed, and the basic theory of rough fuzzy C- mean is studied. In the empirical part of this paper, we choose the liquidity ratio, cash ratio, annual growth rate of operating income, total return rate of assets in in the fourth quarter of 2015 and in the third quarter of 2016. The six financial indexes of net interest rate of sale and asset-liability ratio are used to analyze 50 stocks in different sectors of A-share market. The 50 stocks are divided into three types according to the stock return rate. Class 鈪，

本文編號(hào)：1526505