Author/Authors
ÇOŞKUN, Ali Atatürk Üniversitesi - Pasinler Meslek Yüksekokulu - İşletme Bölümü, Turkey , GÜNGÖR, Bener Atatürk Üniversitesi - İktisadi ve İdari Bilimler Fakültesi (İİBF) - İşletme Bölümu, Turkey , ÇODUR, M. Yasin Erzurum Teknik Üniversitesi, Turkey
Title Of Article
Determining Factors Affecting the Capital Structure with Artificial Neural Network Method
شماره ركورد
43297
Abstract
The aim of this study is to identify in what degree and how leverage ratios of industrial sectors of business are operating in Turkey and traded in Istanbul Stock Exchange (BIST), regarding capital structure, are affected by company-specific factors. 110 industrial sectors that operate between the years 2003 to 2013 were used in the study of business data. For this purpose, while total liabilities of the leverage ratio as the output variable / equity, total debt / total assets and long-term liabilities / equity ratio are used, as input variables, the growth, profitability, non-debt tax shield, cash flow ratio, fixed assets / total assets, current ratio, financial risk, net working capital and the tax rate is used.While as a result of the study it has been identified that in artificial Neural Network Model, CR, DVTV and NCS variables to be important variables in predicting the capital structure.
From Page
333
NaturalLanguageKeyword
Capital Structure , Industrial Sector , Artificial Neural Network ,
JournalTitle
Journal Of Graduate School Of Social Sciences
To Page
350
JournalTitle
Journal Of Graduate School Of Social Sciences
Link To Document