本文關鍵詞： 股票板塊 股票分類 聚類分析 蟻群算法　出處：《復旦大學》2012年碩士論文　論文類型：學位論文

【摘要】：隨著中國股票市場不斷發(fā)展,正確對股票進行分類,以構建投資組合降低投資風險的重要性也不斷提高。根據(jù)現(xiàn)代投資組合理論,通過構建投資組合,可以起到分散非系統(tǒng)性風險的作用。投資組合的風險程度與組合內各股票之間的相關性有關,各股票之間的相關性越小,組合起到的風險分散效應越明顯。現(xiàn)階段投資者常按照行業(yè)對股票進行分類。因此,如果同一行業(yè)內的股票收益率之間的相關性高于不同行業(yè)的股票收益率間的相關性,不同行業(yè)間資產的搭配也應該能起到更好的效果。 但是,本文通過實證研究證明了中國股市行業(yè)之間股票價格波動具有很高的相關性,按行業(yè)分類構建投資組合以降低風險的效果較差。因此,提出一種行業(yè)之外的有效分類股票的方法就顯得非常重要。 本文提出使用優(yōu)化的蟻群聚類算法,對中國A股市場上所有的兩千多支股票進行聚類分析。分別采用財務指標和個股收益率波動對股票進行聚類,通過對聚類結果的分析驗證了使用蟻群聚類算法對大樣本量數(shù)據(jù)進行聚類分析的可行性和良好效果。為在中國市場進行股票分類提供了新的思路,為投資決策和風險控制提供了理論和數(shù)據(jù)基礎。 本文共分為五章：第一章為研究背景、文獻綜述及論文框架介紹；第二章介紹了中國股票市場行業(yè)分類及其存在問題：第三章提出了基于優(yōu)化的蟻群聚類算法的股票分類方法；第四章就第三章提出的方法進行了實證研究；最后提出了結論和展望。
[Abstract]:With the continuous development of China's stock market, the importance of correctly classifying stocks in order to build a portfolio to reduce investment risk is also increasing. According to modern portfolio theory, through the construction of portfolio. The degree of risk in the portfolio is related to the correlation between the stocks in the portfolio, and the smaller the correlation among the stocks. Portfolio plays a more obvious risk dispersion effect. At this stage, investors often classify stocks according to the industry. Therefore. If the correlation between stock returns in the same industry is higher than the correlation between stock returns in different industries, asset matching among different industries should also play a better role. However, through empirical research, this paper proves that stock price volatility among Chinese stock market industries has a high correlation, according to the industry classification of investment portfolio to reduce the effect of risk is poor. It is very important to propose an effective method of classifying stocks outside the industry. In this paper, we use the optimized ant colony clustering algorithm to cluster all the more than 2,000 stocks in the A-share market of China. We use the financial index and the volatility of individual stock return to cluster the stocks. The analysis of clustering results verifies the feasibility and good effect of using ant colony clustering algorithm to cluster large sample data, which provides a new idea for stock classification in Chinese market. It provides theoretical and data basis for investment decision and risk control. This paper is divided into five chapters: the first chapter is the research background, literature review and the introduction of the paper framework; The second chapter introduces the industry classification of Chinese stock market and its existing problems. In chapter 3, we propose a stock classification method based on ant colony clustering algorithm. Chapter 4th makes an empirical study on the methods proposed in the third chapter. Finally, the conclusion and prospect are put forward.
【學位授予單位】：復旦大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F832.51;F224

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本文編號：1493097