本文關(guān)鍵詞：基于分位數(shù)回歸方法的A股市場收益率影響因素的研究　出處：《哈爾濱工業(yè)大學》2012年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 股票收益率 聚類分析 分位數(shù)回歸 最小二乘法

【摘要】：關(guān)于股票收益率的影響因素的理論和模型一直是各國學者研究的重點問題，從最初的資本資產(chǎn)定價模型和套利定價理論到三因素模型等各種因素模型，學者們在探索影響因素的過程中發(fā)現(xiàn)了許多模型和理論并不完善。盡管學者們不斷的改變影響因素和完善模型，但所有的檢驗方法都是檢測收益率均值處的效應(yīng)，常常因模型和數(shù)據(jù)樣本的不同往往會得出不同的實證結(jié)果，尤其是很多在外國得到論證的結(jié)論在中國市場上并不成立。 本文立足中國股市并結(jié)合學者們的研究成果選取了26個可能影響收益率的影響因素。然后利用聚類分析方法從中篩選了12個代表性因素。最后以中國A股市場股票為研究對象，以最小二乘法和分位數(shù)回歸方法對12個影響因素進行全部數(shù)據(jù)和分行業(yè)的分析。 經(jīng)過分位數(shù)和最小二乘法兩種回歸分析方法的對比發(fā)現(xiàn)：（1）同一個影響因素與股票收益率在最小二乘法下的相關(guān)性和顯著性是唯一的，但在分位數(shù)回歸方法下不同分位點處的結(jié)果卻各不相同；另外，同一影響因素在不同行業(yè)中與收益率的關(guān)系在不同分位點處也是不同的，因此還要分行業(yè)利用分位數(shù)回歸方法分析二者之間的關(guān)系。（2）全部數(shù)據(jù)分析結(jié)果顯示在大多數(shù)分位點處分位數(shù)回歸的擬合效果好于最小二乘法的擬合效果，，但分行業(yè)分析后，最小二乘法的擬合效果更好。（3）無論是全部數(shù)據(jù)還是分行業(yè)分析，大多數(shù)財務(wù)指標對股票收益率的解釋力度遠不如一些公司外部的特殊因素對收益率的解釋，表明我國大多數(shù)投資者在進行價值和投資分析時更加重視那些反映公司市場表現(xiàn)的特殊指標對股票收益率的影響力，忽略了反映公司經(jīng)營業(yè)績的財務(wù)指標的影響力。 通過兩種回歸分析方法的結(jié)果對比可以看出來，最小二乘法下回歸系數(shù)、敏感性和擬合度都是唯一的；但在分位數(shù)回歸方法下，不同分位點處的回歸系數(shù)、敏感性和擬合度差異還是很明顯的，能深刻的刻畫這三個變量的變化及趨勢。為以后更加深入的研究股票收益率影響因素提供了更好的分析方法。
[Abstract]:On the impact of stock returns and the theory model of factors has been the focus of researchers all over the world, the model from the capital asset pricing model and arbitrage pricing theory to the original three factor model and other factors, the scholars in the exploration of the influencing factors were found in many models and theories are not perfect. Although the factors to affect the scholars continuous and perfect model, but the test methods are all effect detection yields at mean, often because of the model and data samples often have different empirical results obtained different, especially in many foreign get the conclusion of the argument does not hold in China market.
Based on the China stock market and the research results of the scholars selected 26 factors that may affect the rate of return. Then use the clustering analysis method is selected from 12 representative factors. At last China A shares stock market as the research object, analysis of all the data and industry of the 12 factors, using the least square method and the quantile regression method.
After comparing the two quantile and least squares regression analysis found that: (1) the same factors and the correlation of stock returns in the least squares method and is the only significant, but different in the quantile quantile regression method under the results are different; in addition, the relationship between the same factor effect of rate and yield in different industries in different sites is different, so the relationship between the industry and using the method of quantile regression analysis of the two. (2) all the data analysis results showed that the fitting effect of the fitting effect in most quantile quantile regression is better than the punishment of the least squares method, but the industry analysis after the fitting effect is better than the least square method. (3) whether all data and industry analysis, explanation of most financial indicators on stock returns than outside the company for some special The explanation of yield shows that most investors in China pay more attention to the influence of special indicators that reflect the company's market performance on the stock returns, ignoring the influence of financial indicators that reflect the company's performance.
Through the comparative analysis of two kinds of regression results we can see that the least squares regression coefficient, sensitivity and fitting degree is unique; but in the method of quantile regression, the regression coefficients of different sites, and the fitting degree of sensitivity difference is very obvious, which can describe the changes and trends of the three variables deep. For a more in-depth study of stock returns influencing factors analysis method is provided for the better.

【學位授予單位】：哈爾濱工業(yè)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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