THE PREDICTING OF AUDITOR CHANGES BY USING FINANCIAL DISTRESS VARIABLES: DATA MINING APPROACH

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ETEMADI HOUSSEIN; LOTFI SALMAN

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: The Financial Accounting and Auditing Researches Year:2016 | Volume:8 | Issue:29 Page(s): 125-148

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

1,529

Download:

Cites:

Information Journal Paper

Title

THE PREDICTING OF AUDITOR CHANGES BY USING FINANCIAL DISTRESS VARIABLES: DATA MINING APPROACH

Author(s)

ETEMADI HOUSSEIN | LOTFI SALMAN | Issue Writer Certificate

Keywords

AUDITOR CHANGEQ2

FINANCIAL DISTRESSQ1

DATA MININGQ1

Abstract

Independence auditing contributes to optimization of financial reports in capital markets through improving reliability and increasing process validity. Auditing quality is a function of many different factors, particularly auditor autonomy. Therefore, any decline in auditor autonomy directly affects the process of auditing. A close analysis of AUDITOR CHANGE is urgent, for it is related to auditor autonomy. Thus, the present study undertakes to investigate predictability of FINANCIAL DISTRESS for predicting AUDITOR CHANGEs in companies listed at Tehran Stock Exchange during 2002-2011. It also proposes a model for this process using FINANCIAL DISTRESS and techniques of Data- mining.Data mining methods, Bayesian network, Classification and Regression Tree (CART) and Logistic Regression are used for testing the four hypotheses of the study. Results of logistic regression analysis indicate a significant relationship between AUDITOR CHANGE and FINANCIAL DISTRESS at confidence level of 95%. Results also show 89% and 84% for precision and true positive rates, respectively. Our results reveal that FINANCIAL DISTRESS arising from audited financial statements are good sources of information for predicting AUDITOR CHANGEs in active companies listed at Tehran Stock Exchange, which can be used, along with data-mining techniques, for designing effective models for predicting AUDITOR CHANGEs.

Cites

No record.

References

Cite

APA: Copy

ETEMADI, HOUSSEIN, & LOTFI, SALMAN. (2016). THE PREDICTING OF AUDITOR CHANGES BY USING FINANCIAL DISTRESS VARIABLES: DATA MINING APPROACH. THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES, 8(29), 125-148. SID. https://sid.ir/paper/198152/en

Vancouver: Copy

ETEMADI HOUSSEIN, LOTFI SALMAN. THE PREDICTING OF AUDITOR CHANGES BY USING FINANCIAL DISTRESS VARIABLES: DATA MINING APPROACH. THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES[Internet]. 2016;8(29):125-148. Available from: https://sid.ir/paper/198152/en

IEEE: Copy

HOUSSEIN ETEMADI, and SALMAN LOTFI, “THE PREDICTING OF AUDITOR CHANGES BY USING FINANCIAL DISTRESS VARIABLES: DATA MINING APPROACH,” THE FINANCIAL ACCOUNTING AND AUDITING RESEARCHES, vol. 8, no. 29, pp. 125–148, 2016, [Online]. Available: https://sid.ir/paper/198152/en

Related Journal Papers