本文關(guān)鍵詞： 證券分析師 上市公司 盈利預(yù)測(cè) 誤差　出處：《浙江工商大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：我國(guó)證券市場(chǎng)雖歷經(jīng)近20年的發(fā)展,但仍處于“弱式有效市場(chǎng)”之中,對(duì)于中小投資者更是如此。多數(shù)中小投資者因缺乏有效信息和專業(yè)知識(shí),他們對(duì)上市公司的分析更多依賴于證券分析師的業(yè)績(jī)預(yù)測(cè)。由于證券分析師具有分析能力優(yōu)勢(shì)以及信息渠道優(yōu)勢(shì),他們的預(yù)測(cè)結(jié)果往往成為許多中小投資者的決策依據(jù),尤其隨著近幾年國(guó)內(nèi)宏觀經(jīng)濟(jì)的大幅波動(dòng),越來(lái)越多的中小投資者關(guān)注他們的預(yù)測(cè)分析。那么,專業(yè)分析人員的預(yù)測(cè)結(jié)果可靠嗎?他們預(yù)測(cè)的誤差有多大?他們的預(yù)測(cè)是否存在誘導(dǎo)行為?對(duì)于這些問(wèn)題,目前國(guó)內(nèi)鮮有學(xué)者進(jìn)行系統(tǒng)研究,相關(guān)研究?jī)H局限于個(gè)別行業(yè)和較短的時(shí)間跨度,這使得其研究結(jié)論缺乏實(shí)質(zhì)性指導(dǎo)意義。 基于上述背景,本研究通過(guò)對(duì)以往文獻(xiàn)的系統(tǒng)梳理,確定了盈利預(yù)測(cè)誤差的度量標(biāo)準(zhǔn),并歷經(jīng)兩個(gè)多月的時(shí)間從國(guó)泰安數(shù)據(jù)庫(kù)(CSMAR)、長(zhǎng)城證券軟件、國(guó)家統(tǒng)計(jì)局網(wǎng)站、中國(guó)證券業(yè)協(xié)會(huì)網(wǎng)站中收集了2007-2011年證券分析師對(duì)十大行業(yè)上市公司當(dāng)年上半年的盈利預(yù)測(cè)數(shù)據(jù),運(yùn)用統(tǒng)計(jì)軟件EXCEL和EViews6.0對(duì)這些盈利預(yù)測(cè)誤差進(jìn)行了系統(tǒng)分析,在此基礎(chǔ)上探討影響各行業(yè)預(yù)測(cè)誤差差異的原因,從而為中小投資者進(jìn)行合理的投資決策提供必要的指導(dǎo)。 本研究結(jié)論主要包括以下幾點(diǎn)：(1)證券分析師的盈利預(yù)測(cè)關(guān)注度主要集中于鋼鐵業(yè)、銀行業(yè)、房地產(chǎn)業(yè)等市值大的行業(yè),而對(duì)農(nóng)業(yè)等市值較小的行業(yè)的關(guān)注度明顯偏低；(2)宏觀經(jīng)濟(jì)形勢(shì)會(huì)影響證券分析師對(duì)上市公司的盈利預(yù)測(cè)誤差,經(jīng)濟(jì)形勢(shì)較好的年份的預(yù)測(cè)誤差明顯低于不好的年份；(3)證券分析師對(duì)不同行業(yè)的預(yù)測(cè)誤差具有-定的差異性,其中,銀行業(yè)、公路管理及養(yǎng)護(hù)業(yè)的盈利預(yù)測(cè)更準(zhǔn)確,而對(duì)鋼鐵業(yè)、電力生產(chǎn)業(yè)、汽車制造業(yè)的預(yù)測(cè)誤差波動(dòng)幅度較大；(4)參股券商的預(yù)測(cè)從總體上要比同公司其他非參股券商的更準(zhǔn)確,但與其對(duì)同行業(yè)其它非參股公司的預(yù)測(cè)并沒(méi)有明顯的差異。 本研究的創(chuàng)新點(diǎn)主要體現(xiàn)在三個(gè)方面：(1)在研究?jī)?nèi)容上深入分析近五年來(lái)證券分析師對(duì)我國(guó)上市公司盈利預(yù)測(cè)誤差情況,豐富了我國(guó)專業(yè)分析人員對(duì)上市公司盈利預(yù)測(cè)的研究；(2)系統(tǒng)研究了證券分析師對(duì)不同行業(yè)的盈利預(yù)測(cè)誤差,從而在一定程度上填補(bǔ)了國(guó)內(nèi)對(duì)證券分析師盈利預(yù)測(cè)行業(yè)差異研究的空白；(3)在度量證券分析師對(duì)上市公司進(jìn)行的盈利預(yù)測(cè)誤差標(biāo)準(zhǔn)上首次加入了股權(quán)的指標(biāo),排除了因股權(quán)變動(dòng)而造成了非人為預(yù)測(cè)誤差。 盡管本研究進(jìn)行了大量數(shù)據(jù)搜集和分析,但仍存在一些局限性：(1)本研究并未選取我國(guó)所有的上市公司作為樣本,只是選取其中具有代表性的10個(gè)行業(yè)以及每個(gè)行業(yè)中規(guī)模最大的前10家公司；(2)由于數(shù)據(jù)收集困難,本研究很難搜集過(guò)去20年的預(yù)測(cè)數(shù)據(jù),而只選擇2007-2011年期間五年預(yù)測(cè)數(shù)據(jù)。這些一定程度上會(huì)影響研究結(jié)論的準(zhǔn)確性。
[Abstract]:Although China's securities market has been developing for nearly 20 years, it is still in the "weak efficient market", especially for the small and medium-sized investors, most of whom lack effective information and professional knowledge. Their analysis of listed companies depends more on the performance forecasts of securities analysts, who have the advantage of analytical ability and information channel. Their prediction results often become the basis for many small and medium-sized investors to make decisions, especially with the domestic macroeconomic fluctuations in recent years, more and more small and medium-sized investors pay attention to their prediction and analysis. Are professional analysts' predictions reliable? How much error are they predicting? Does their prediction have induced behavior? At present, few domestic scholars do systematic research on these problems, and the related research is limited to individual industries and a short time span, which makes the research conclusions lack of substantive significance. Based on the above background, this study through a systematic review of previous literature, determine the measurement of profit prediction error, and after more than two months from the Cathay Pacific database CSMAR). The Great Wall Securities Software, the website of the National Bureau of Statistics, and the website of the China Securities Association collected profit forecasts for the first half of the year from 2007 to 2011. This paper makes a systematic analysis of these profit prediction errors by using statistical software EXCEL and EViews6.0, and then discusses the reasons that affect the difference of forecast errors in various industries. So as to provide necessary guidance for small and medium investors to make reasonable investment decisions. The main conclusions of this study include the following points: 1) the focus of earnings forecast of securities analysts is mainly focused on the steel industry, banking, real estate and other big industries such as market value. But to the agriculture and so on market value small industry's attention degree is obviously low; (2) the macroeconomic situation will affect the profit forecast error of the securities analysts, and the forecast error in the year of better economic situation is obviously lower than that in the bad year; (3) the forecast error of securities analysts to different industries has definite difference, among them, the profit forecast of banking, highway management and maintenance industry is more accurate, but to steel industry and electric power industry. The prediction error of automobile manufacturing industry fluctuates greatly; 4) the forecast of stockholders is more accurate than that of other non-equity firms, but there is no obvious difference between the forecast of other non-equity companies in the same industry and that of other non-equity companies in the same industry. The innovation of this study is mainly reflected in three aspects: 1) in the content of the research in-depth analysis of the recent five years securities analysts on the earnings forecast error of listed companies in China. It enriches the research on earnings forecast of listed companies by professional analysts in our country. (2) this paper systematically studies the profit forecast error of securities analysts to different industries, thus filling the gap of domestic research on the industry difference of securities analysts' profit forecast to some extent; For the first time, the index of equity is added to measure the error standard of stock analysts' earnings forecast to listed companies, which excludes the non-artificial forecast error caused by the change of stock rights. Although this study has conducted a lot of data collection and analysis, there are still some limitations in this study. Only select the representative of 10 industries and each industry in the largest 10 companies; 2) due to data collection difficulties, it is difficult for this study to collect forecast data for the past 20 years. Only five-year projections for the period 2007-2011 were selected, which in part affected the accuracy of the study's findings.
【學(xué)位授予單位】：浙江工商大學(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10條

1 李冬昕;李心丹;張兵;;分析師的盈利預(yù)測(cè)偏差與本地優(yōu)勢(shì)[J];財(cái)經(jīng)科學(xué);2011年03期

2 王原,徐宗宇;盈利預(yù)測(cè)信息及其規(guī)范制度──兼論我國(guó)盈利預(yù)測(cè)信息披露的若干問(wèn)題[J];財(cái)經(jīng)論叢(浙江財(cái)經(jīng)學(xué)院學(xué)報(bào));1998年06期

3 公言磊;;公司因素對(duì)財(cái)務(wù)分析師盈余預(yù)測(cè)特性影響的實(shí)證研究[J];財(cái)經(jīng)問(wèn)題研究;2010年03期

4 石桂峰;蘇力勇;齊偉山;;財(cái)務(wù)分析師盈余預(yù)測(cè)精確度決定因素的實(shí)證分析[J];財(cái)經(jīng)研究;2007年05期

5 李睿,趙靖杰;滬深股市首發(fā)新股盈利預(yù)測(cè)的實(shí)證研究[J];財(cái)會(huì)通訊(學(xué)術(shù)版);2004年12期

6 邵清芳;;上市公司盈利預(yù)測(cè)可靠性實(shí)證研究綜述[J];財(cái)會(huì)通訊;2010年15期

7 張志強(qiáng);王曉燕;吳懋亮;;財(cái)務(wù)分析師盈利預(yù)測(cè)可靠性淺析[J];當(dāng)代經(jīng)濟(jì);2007年12期

8 劉陽(yáng);;中國(guó)證券市場(chǎng)投資者羊群行為研究[J];當(dāng)代經(jīng)濟(jì);2011年04期

9 徐宗宇;財(cái)務(wù)預(yù)測(cè)的實(shí)證研究及其對(duì)我國(guó)的借鑒意義[J];當(dāng)代經(jīng)濟(jì)科學(xué);1997年04期

10 郝東洋;;證券分析師盈利預(yù)測(cè)研究綜述：行為、可靠性及價(jià)值相關(guān)性[J];福建財(cái)會(huì)管理干部學(xué)院學(xué)報(bào);2008年03期

相關(guān)碩士學(xué)位論文 前6條

1 胡锫;我國(guó)證券分析師盈利預(yù)測(cè)的有效性研究[D];太原科技大學(xué);2011年

2 阮瑋仕;賣方分析師的盈利預(yù)測(cè)大膽程度與預(yù)測(cè)準(zhǔn)確性[D];清華大學(xué);2010年

3 戚佳;我國(guó)證券分析師盈余預(yù)測(cè)準(zhǔn)確度的影響因素研究[D];燕山大學(xué);2011年

4 陳劍挺;分析師盈利預(yù)測(cè)的實(shí)證研究[D];西南財(cái)經(jīng)大學(xué);2007年

5 羅穎;會(huì)計(jì)信息質(zhì)量與證券分析師盈利預(yù)測(cè)的實(shí)證研究[D];廈門(mén)大學(xué);2008年

6 袁琴;銀行業(yè)證券分析師盈利預(yù)測(cè)研究[D];河南大學(xué);2009年

，

本文編號(hào)：1456868