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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Cash Holding,Investment inefficiency,CEO turnover
- چکیده:
- چکیده انگلیسی: The purpose of this study is to investigate the effective of investment inefficiency and cash holding on CEO turnover.
This study applies logistic regression method estimator to investigate the relationship between examine the effective of investment inefficiency and cash holding on CEO turnover of 1,309 firm-year observations in Iran for the period of 2009-2019.
According to positive relation between mentioned variables, the managers' opportunism increases investment inefficiency and cash holdings of the company because inappropriate managerial decisions lead to increased risk of wrong selection for investors.
In the present study, the weaknesses caused by the ambiguity of investment efficiency in market performance-based statistical models are compensated and partially covered by quantifying the relationships and implementing models. The Results will aid policy makers to evaluate disclosure rules and firms to managing their information. The study is based on the corporate accounting and financial literature and examines CEO behavioral changes that can be applied to investors, managers, standardization committees, and legislators.
Unlike other research, CEO turnover has also been addressed with regard to the origin and distribution of information. This study also considers the effect of information asymmetry and market constraints by considering the cash holding to transmit firm information- انتشار مقاله: 02-06-1399
- نویسندگان: Masoud Taherinia,Masoud Taherinia,Masoud Taherinia
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Mathematical Finance and Application
- نوع مقاله: Journal Article
- کلمات کلیدی: Artificial Neural Networks,Earning quality,Prediction
- چکیده:
- چکیده انگلیسی: Time changes of return, inefficiency studies performed and presence of effective factors on share return rate are caused development modern and intelligent methods in estimation and evaluation of share return in stock companies. Aim of this research is prediction of return using financial variables with artificial neural network approach. Therefore, the statistical population of this study includes 120 listed companies in Tehran stock securities during 2005 to 2017. Independent variables in this research are market variables (Earning quality, free cash flow) and dependent variable is share return. The obtained outputs from estimation of the artificial neural networks and results obtained from estimation, using of this method with evaluation scales concerning random amount and comparing it with adjusted R, we found that there is meaningful relation between the associated variables and return. However, such network has the least error than other networks.
- انتشار مقاله: 16-09-1397
- نویسندگان: Masoud Taherinia,Mohsen Rashidi Baghi
- مشاهده