scholarly journals A Study on the Detectability of Earnings Management via a Normal Accrual Prediction Model

2019 ◽  
Vol 13 (4) ◽  
pp. 41-49
Author(s):  
Ryota Takahashi ◽  
Ling Feng
2005 ◽  
Vol 173 (4S) ◽  
pp. 427-427
Author(s):  
Sijo J. Parekattil ◽  
Udaya Kumar ◽  
Nicholas J. Hegarty ◽  
Clay Williams ◽  
Tara Allen ◽  
...  

Author(s):  
Vivek D. Bhise ◽  
Thomas F. Swigart ◽  
Eugene I. Farber
Keyword(s):  

2009 ◽  
Author(s):  
Christina Campbell ◽  
Eyitayo Onifade ◽  
William Davidson ◽  
Jodie Petersen

2019 ◽  
Author(s):  
Zool Hilmi Mohamed Ashari ◽  
Norzaini Azman ◽  
Mohamad Sattar Rasul

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Qianqian Liang ◽  
Xiaodong Zhang ◽  
Jinliang Xu ◽  
Yang Zhang

2018 ◽  
Vol 16 (2) ◽  
pp. 30
Author(s):  
Dwikky Darmawan ◽  
Weny Putri

The purpose of this study is to determine the effects of political connection toward the earnings management of service sector companies with control variables firm size and audit quality. Firm�s political connection measured by using dummy variable. Earnings management is proxied by discretionary accrual which is measured by using Modified Jones Model. The research data applied in this study are the secondary data which are taken from the annual reports of service sector companies that listed in Indonesian Stock Exchange of 2016-2017 periods. There are 330 observations fit as sample, which are taken by using purposive sampling method. Data are processed by applying the multiple linear regression test. The result show that the political connection had positive but not significant influence to earnings management. Firm size had negative but not significant influence to earnings management. Whereas the audit quality had a negative and significant influence to earnings management.


Author(s):  
Karunesh Makker ◽  
Prince Patel ◽  
Hrishikesh Roy ◽  
Sonali Borse

Stock market is a very volatile in-deterministic system with vast number of factors influencing the direction of trend on varying scales and multiple layers. Efficient Market Hypothesis (EMH) states that the market is unbeatable. This makes predicting the uptrend or downtrend a very challenging task. This research aims to combine multiple existing techniques into a much more robust prediction model which can handle various scenarios in which investment can be beneficial. Existing techniques like sentiment analysis or neural network techniques can be too narrow in their approach and can lead to erroneous outcomes for varying scenarios. By combing both techniques, this prediction model can provide more accurate and flexible recommendations. Embedding Technical indicators will guide the investor to minimize the risk and reap better returns.


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