本文選題：預(yù)測(cè) + 審計(jì)意見　； 參考：《重慶理工大學(xué)》2017年碩士論文

【摘要】：上市公司定期公布的財(cái)務(wù)報(bào)告是利益相關(guān)者進(jìn)行決策的依據(jù),注冊(cè)會(huì)計(jì)師作為獨(dú)立的第三方對(duì)被審計(jì)單位財(cái)務(wù)報(bào)告進(jìn)行審計(jì)出具的鑒證性審計(jì)意見,對(duì)增強(qiáng)上市公司財(cái)務(wù)信息的可信性起著至關(guān)重要的作用,經(jīng)審計(jì)后的財(cái)務(wù)報(bào)表更可靠,使信息使用者能更加有信心,能減少投資決策失誤,注冊(cè)會(huì)計(jì)師出具的審計(jì)意見類型對(duì)公司利益相關(guān)者的投資決策行為具有重大影響,因此對(duì)上市公司審計(jì)意見預(yù)測(cè)模型的研究具有一定的現(xiàn)實(shí)意義。本文構(gòu)建了基于灰色神經(jīng)網(wǎng)絡(luò)的上市公司審計(jì)意見預(yù)測(cè)模型,為保證預(yù)測(cè)效果,在以往研究大多使用財(cái)務(wù)指標(biāo)的基礎(chǔ)上,建立了包括財(cái)務(wù)指標(biāo)和公司治理、會(huì)計(jì)師事務(wù)所等非財(cái)務(wù)指標(biāo)的預(yù)測(cè)指標(biāo)體系。選取2013-2015年滬深兩市全部A股制造業(yè)被出具非標(biāo)準(zhǔn)審計(jì)意見的上市公司作為研究樣本,根據(jù)公司的資產(chǎn)規(guī)模、行業(yè)以及1:1配比原則,并剔除缺失值之后,最終得到訓(xùn)練組、檢驗(yàn)組以及預(yù)測(cè)組樣本;為降低訓(xùn)練的復(fù)雜性,保證預(yù)測(cè)效果,采用鄰域粗糙集方法對(duì)樣本指標(biāo)進(jìn)行篩選,在不影響預(yù)測(cè)效果的情況下,剔除次要指標(biāo),以保留相對(duì)重要指標(biāo);利用BP神經(jīng)網(wǎng)絡(luò)方法對(duì)訓(xùn)練組樣本數(shù)據(jù)進(jìn)行訓(xùn)練建模及回判仿真,并利用檢驗(yàn)組數(shù)據(jù)對(duì)所建立的模型進(jìn)行檢驗(yàn);選取預(yù)測(cè)組樣本時(shí)點(diǎn)數(shù)據(jù),構(gòu)建基于灰色神經(jīng)網(wǎng)絡(luò)方法的審計(jì)意見預(yù)測(cè)模型,該模型綜合了灰色預(yù)測(cè)模型建模所需信息較少及神經(jīng)網(wǎng)絡(luò)模型自適應(yīng)、自學(xué)習(xí)的優(yōu)點(diǎn)。研究結(jié)果表明,加入非財(cái)務(wù)指標(biāo)的綜合預(yù)測(cè)模型的預(yù)測(cè)準(zhǔn)確度高于僅用財(cái)務(wù)指標(biāo)建模的預(yù)測(cè)準(zhǔn)確度,構(gòu)建的基于灰色神經(jīng)網(wǎng)絡(luò)方法的審計(jì)意見預(yù)測(cè)模型具有較好的預(yù)測(cè)能力。
[Abstract]:The financial reports issued regularly by listed companies are the basis for stakeholders to make decisions. Certified public accountants, as independent third parties, audit the financial reports of audited units and issue an authenticated audit opinion. It plays an important role in enhancing the credibility of financial information of listed companies. The audited financial statements are more reliable, so that the information users can have more confidence and can reduce the mistakes in investment decisions. The type of audit opinion issued by CPA has great influence on the investment decision-making behavior of corporate stakeholders, so it is of practical significance to study the prediction model of audit opinion of listed companies. In this paper, a forecasting model of audit opinion of listed companies based on grey neural network is constructed. In order to ensure the forecasting effect, the financial indexes and corporate governance are established on the basis of the financial indicators used in most previous studies. Accounting firms and other non-financial indicators of the forecast index system. From 2013 to 2015, all the A-share manufacturing companies in Shanghai and Shenzhen stock markets were selected as the research samples. According to the company's asset size, industry and 1:1 matching principle, and after eliminating the missing value, the training group was finally obtained. In order to reduce the complexity of training and ensure the prediction effect, the neighborhood rough set method is used to screen the sample index, and the secondary index is eliminated without affecting the prediction effect, so as to retain the relative important index. BP neural network method is used for training modeling and simulation of training group sample data, and the test group data is used to test the established model, and the prediction group sample time point data is selected. An audit opinion prediction model based on grey neural network is constructed. The model combines the advantages of less information needed in grey prediction model and adaptive and self-learning of neural network model. The research results show that the prediction accuracy of the comprehensive forecasting model with non-financial indexes is higher than that of only using the financial indicators, and the prediction model based on the grey neural network method has a better forecasting ability.
【學(xué)位授予單位】：重慶理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F239.4

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 許陽;;基于財(cái)務(wù)指標(biāo)的上市公司審計(jì)意見類型預(yù)測(cè)[J];中國內(nèi)部審計(jì);2015年02期

2 白憲生;續(xù)飛;張新;;可操控應(yīng)計(jì)利潤、審計(jì)意見和審計(jì)收費(fèi)[J];財(cái)會(huì)通訊;2014年36期

3 張曉莉;劉大為;;一種基于灰色神經(jīng)網(wǎng)絡(luò)的企業(yè)財(cái)務(wù)風(fēng)險(xiǎn)預(yù)警模型[J];企業(yè)經(jīng)濟(jì);2013年12期

4 房琳琳;;財(cái)務(wù)困境上市公司財(cái)務(wù)報(bào)告舞弊預(yù)警模型研究[J];經(jīng)濟(jì)與管理研究;2013年10期

5 王旭;孔玉生;;基于BP神經(jīng)網(wǎng)絡(luò)模型的持續(xù)經(jīng)營不確定性審計(jì)意見預(yù)測(cè)[J];財(cái)會(huì)月刊;2012年36期

6 劉霄侖;郝臣;褚玉萍;;公司治理對(duì)上市公司審計(jì)意見類型影響的研究——基于2007-2011年中國民營上市公司的面板數(shù)據(jù)[J];審計(jì)研究;2012年05期

7 鄭斯日古楞;;灰色神經(jīng)網(wǎng)絡(luò)在股票價(jià)格預(yù)測(cè)中的應(yīng)用[J];計(jì)算機(jī)仿真;2012年02期

8 葛少云;賈鷗莎;劉洪;;基于遺傳灰色神經(jīng)網(wǎng)絡(luò)模型的實(shí)時(shí)電價(jià)條件下短期電力負(fù)荷預(yù)測(cè)[J];電網(wǎng)技術(shù);2012年01期

9 蘇瑾;周健勇;;灰色神經(jīng)網(wǎng)絡(luò)在預(yù)測(cè)企業(yè)經(jīng)營活動(dòng)現(xiàn)金流中的應(yīng)用[J];科技與管理;2011年03期

10 周楊;;我國上市公司審計(jì)意見影響因素的實(shí)證研究——基于2008年滬深A(yù)股年報(bào)數(shù)據(jù)的分析[J];會(huì)計(jì)之友;2011年04期

相關(guān)碩士學(xué)位論文 前3條

1 郭磊;我國上市公司審計(jì)意見預(yù)測(cè)研究[D];暨南大學(xué);2008年

2 陳X;基于擴(kuò)展粗糙集的屬性約簡(jiǎn)的研究[D];合肥工業(yè)大學(xué);2008年

3 魯豫;基于財(cái)務(wù)指標(biāo)的上市公司審計(jì)意見類型預(yù)測(cè)[D];吉林大學(xué);2007年

，

本文編號(hào)：2110438