【摘要】：隨著我國(guó)資本市場(chǎng)的快速發(fā)展,上市公司的并購(gòu)越來(lái)越活躍,并購(gòu)目標(biāo)公司的識(shí)別對(duì)于投資者、收購(gòu)方和管理者來(lái)說(shuō)都具有重要意義。在并購(gòu)目標(biāo)公司的可預(yù)測(cè)性研究方面,前人的研究往往年限較短,沒(méi)有考慮行業(yè)差異產(chǎn)生的影響,且僅用一年或者某幾年的預(yù)測(cè)準(zhǔn)確性來(lái)說(shuō)明并購(gòu)目標(biāo)公司的可預(yù)測(cè)性是片面的。 本文對(duì)2001-2010年的樣本逐年進(jìn)行分析,每年都建立并購(gòu)目標(biāo)公司預(yù)測(cè)模型,并用下一年的并購(gòu)事件對(duì)該預(yù)測(cè)模型進(jìn)行檢驗(yàn),通過(guò)每年模型指標(biāo)及準(zhǔn)確率的變化,對(duì)我國(guó)控制權(quán)轉(zhuǎn)移市場(chǎng)的并購(gòu)目標(biāo)公司可預(yù)測(cè)性問(wèn)題做出相對(duì)全面、系統(tǒng)和客觀的分析。本文采用通過(guò)實(shí)證分析得到以下結(jié)論： (1)目標(biāo)公司具有盈利能力較差、償債能力較差、營(yíng)運(yùn)能力較差、成長(zhǎng)能力較差、獲取現(xiàn)金能力較差及規(guī)模小的特點(diǎn),對(duì)并購(gòu)動(dòng)機(jī)具有一定解釋力；(2)通過(guò)單因素方差分析可以發(fā)現(xiàn),在股權(quán)分置改革之前股權(quán)分散的上市公司容易被并購(gòu),而股權(quán)分置改革之后股權(quán)結(jié)構(gòu)對(duì)成為并購(gòu)目標(biāo)公司的概率影響不顯著；(3)通過(guò)三種方式建模并對(duì)預(yù)測(cè)模型進(jìn)行檢驗(yàn),表明并購(gòu)目標(biāo)公司具有一定可預(yù)測(cè)性；(4)通過(guò)三種建模方式的對(duì)比,可以發(fā)現(xiàn),采用逐年累計(jì)建模方式得到的預(yù)測(cè)模型擬合效果較好,也比較穩(wěn)定,模型中較為穩(wěn)定的指標(biāo)包括總資產(chǎn)對(duì)數(shù)、經(jīng)營(yíng)產(chǎn)生的現(xiàn)金流量?jī)纛~對(duì)數(shù)、扣除非經(jīng)營(yíng)性損益后的凈利潤(rùn)對(duì)數(shù)及營(yíng)運(yùn)資金對(duì)數(shù),這些指標(biāo)的系數(shù)均為負(fù)。(5)通過(guò)三種建模方式的對(duì)比可以發(fā)現(xiàn),按照各年樣本建模的方式易受宏觀因素影響,連續(xù)三年樣本及逐年累計(jì)樣本建模的方式建立的預(yù)測(cè)模型比較穩(wěn)定,受宏觀因素影響不明顯,且逐年累計(jì)樣本建模方式的預(yù)測(cè)結(jié)果及模型的穩(wěn)定性最好,由此表明隨著建模樣本數(shù)量的增加可以有效降低宏觀因素的影響。
[Abstract]:With the rapid development of China's capital market, M & A of listed companies is becoming more and more active. The identification of target companies is of great significance to investors, acquirers and managers. In the research of the predictability of M & A target companies, previous studies tend to have a short period of time and do not take into account the impact of industry differences. And the prediction accuracy of only one year or several years to explain the target company M & A predictability is one-sided. In this paper, the samples of 2001-2010 are analyzed year by year, and the forecast model of target company is established every year, and the forecast model is tested by the next year's M & A event, and the change of the index and accuracy of the model is made every year. This paper makes a relatively comprehensive, systematic and objective analysis on the predictability of M & A target companies in the market of control transfer in China. In this paper, the following conclusions are obtained by empirical analysis: (1) the target company has the characteristics of poor profitability, poor solvency, poor operating capacity, poor growth capacity, poor ability to obtain cash and small scale. It has certain explanatory power to the motive of M & A; (2) through the analysis of variance of single factor, it can be found that the listed companies with dispersed shares are easy to be merged before the split share structure reform, but the ownership structure has no significant effect on the probability of becoming the target company after the split share structure reform; (3) through modeling and testing the prediction model in three ways, it shows that the target company of M & A has certain predictability; (4) through the comparison of the three modeling methods, it can be found that the prediction model obtained by the cumulative modeling method has good fitting effect and stability, and the more stable indexes in the model include the logarithm of total assets. The logarithm of net cash flow generated by operation, the logarithm of net profit after deducting non-operating profit and loss and the logarithm of working capital, the coefficients of these indexes are all negative. (5) through the comparison of three modeling methods, we can find that, According to the method of sample modeling in each year, it is easy to be influenced by macroscopical factors. The prediction model established by the method of sample modeling for three consecutive years and accumulative sample year by year is relatively stable, but not obviously influenced by macro factors. Moreover, the prediction results and the stability of the model are the best, which shows that with the increase of the number of modeling samples, the influence of macroscopic factors can be effectively reduced.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F271;F832.51;F224

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