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RISS 인기검색어
- 검색키워드
- 저자 : Umeair SHAHZAD (검색결과 2 건)
- 무료
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Reliable and Advanced Predictors for Corporate Financial Choices in Pakistan
SHAHZAD, Umeair,FUKAI, Luo,MAHMOOD, Faisal,JING, Liu,AHMED, Zahoor Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.7
Existing studies disagree over the core predictors of firm-level financial choices in developing countries. The general practice only validates the traditional capital structure model, which leads to inconsistency and a lack of novelty. This study removed overfitting issues among existing factors and presented the most reliable and advanced capital structure model in Pakistani firms. The panel data include 368 Pakistani companies from 19 non-financial sectors over the period 2004 to 2017. We apply Akaike and Bayesian Information Criteria to remove overfitting issues among inconsistent proxies in the capital structure model. The fixed effects regression is used for basic results and the Generalized Method of Moments is applied to control the endogeneity. Besides the conventional proxies, we report that credit rating, distance from bankruptcy, managerial concentration, and institutional quality are the most advanced capital structure determinants in Pakistan. These predictors remain significant across firm size and growth levels. Also, the findings confirm that new predictors are reliable to define capital structure dynamics and improve the speed of adjustment in overall and sub-sample analysis. The major findings suggest that managers and policymakers should consider these advanced predictors to design their financial settings in firms.
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Association of Financial Distress and Predicted Bankruptcy: The Case of Pakistani Banking Sector
Hafeez ULLAH,Zhuquan WANG,Muhammad Ghazanfar ABBAS,Fan ZHANG,Umeair SHAHZAD,Memon Rafait MAHMOOD 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.1
The banking sector is one of the most important sectors in Pakistan’s struggling economy. Recent studies have recommended that suitable methods can be applied to predict bankruptcy. In this context, this work analyzes Pakistan’s banking sector’s financial status through the five-factor Altman Z-score model, which determines the probability of bankruptcy for an organization. Banking data has been collected through the Pakistan Stock Exchange (PSX) in the period 2013-2017. The Z-score assessment criteria is defined as: Z> 2.99 - “safe” zone; Z> 1.8 Z>2.98- “grey” zone; and Z <1.8 - “distress” zone. Results show good predictions for the local banking industry, while most foreign Pakistani banks were found bankrupt with the Z-score below 1.1. One of the financial risks investors face when investing in any company is the risk of bankruptcy. One of the most used models for predicting financial distress for any company is Altman’s Z-score model. On the other hand, the Z-score analysis suggests that all banking establishments are not bankrupt because they have sufficient ability to control bankruptcy. At the same time, foreign banks failed financially and would not be able to be sustained in the future because they do not have the ability to pay the short-term and long-term debt.
ScienceON
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