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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Khan, K. I., Qadeer, F., Mata, M. N., Neto, J. C., Sabir, Q. A., Martins, J. N....Filipe, J. (2021). Core predictors of debt specialization: A new insight to optimal capital structure. Mathematics. 9 (9)
Exportar Referência (IEEE)
K. I. Khan et al.,  "Core predictors of debt specialization: A new insight to optimal capital structure", in Mathematics, vol. 9, no. 9, 2021
Exportar BibTeX
@article{khan2021_1656984425602,
	author = "Khan, K. I. and Qadeer, F. and Mata, M. N. and Neto, J. C. and Sabir, Q. A. and Martins, J. N. and Filipe, J.",
	title = "Core predictors of debt specialization: A new insight to optimal capital structure",
	journal = "Mathematics",
	year = "2021",
	volume = "9",
	number = "9",
	doi = "10.3390/math9090975",
	url = "https://www.mdpi.com/journal/mathematics"
}
Exportar RIS
TY  - JOUR
TI  - Core predictors of debt specialization: A new insight to optimal capital structure
T2  - Mathematics
VL  - 9
IS  - 9
AU  - Khan, K. I.
AU  - Qadeer, F.
AU  - Mata, M. N.
AU  - Neto, J. C.
AU  - Sabir, Q. A.
AU  - Martins, J. N.
AU  - Filipe, J.
PY  - 2021
SN  - 2227-7390
DO  - 10.3390/math9090975
UR  - https://www.mdpi.com/journal/mathematics
AB  - Debt structure composition is an essential topic of discussion for the management of capital structure decisions. Researchers made extensive efforts to understand the criteria for selecting debts, specifically, to know about the reasons for debt specialization, concealed in identifying its predictors. This question is essential not only for establishing the field of debt structure but also for the financial managers to design corporate financial strategy in a way that leads to attaining an optimal debt structure. Sophisticated financial modeling is applied to identify the core predictors of debt specialization, influencing the strategic choices of optimal debt structure to address this issue. Data were collected from 419 non-financial companies listed at the Karachi Stock Exchange from 2009 to 2015. This study has validated debt specialization by showing that short-term debts maintain their position over the years and remain the most popular type of loan among Pakistani firms. Further, it provides a comprehensive view of the cross-sectional differences among the firms involved in debt specialization by applying a holistic approach. Results show that small, growing, dividend-paying companies, having high expense and risk ratios, followed the debt specialization strategy. This strategy enables firms to reduce their agency conflicts, transaction costs, information asymmetry, risk management and building up their good market reputation. Conclusively, we have identified the gross profit margin, long-term debt to asset ratio, firm size, age, asset tangibility, and long-term industry debt to asset ratio as reliable and core predictors of debt specialization for sustainable business growth.

ER  -