A study of loan loss provisioning of Hong Kong banks

This study is an investigation of the loan loss provisioning (LLP) behaviour of Hong Kong commercial banks during the period 2011–2016. Hong Kong, being one of the largest financial hubs in the world, contains a massive circulation of capital in the banking system. However, it also suffered from sig...

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Bibliographic Details
Main Author: Ng, Ue Tung
Format: Dissertation (University of Nottingham only)
Language:English
Published: 2017
Subjects:
Online Access:https://eprints.nottingham.ac.uk/45676/
Description
Summary:This study is an investigation of the loan loss provisioning (LLP) behaviour of Hong Kong commercial banks during the period 2011–2016. Hong Kong, being one of the largest financial hubs in the world, contains a massive circulation of capital in the banking system. However, it also suffered from significant economic fluctuation during unanticipated financial events. Therefore, this study aims to improve the performance of Hong Kong banks by studying its loan loss provisioning performance and situation. Three main hypothesis are tested, including capital, income-smoothing and cyclical management hypotheses. In this paper, the influence of X-efficiencies and other risk control variables on loan loss provisioning activities is investigated and analyzed. SFA model is adopted for deducing the x-efficiency of various local commercial banks’ x-efficiency. It is then combined with other potential variables to study the factors of high significance that affects loan loss provision. Loan loss provisioning, as the key contributor of fluctuations in bank profitability and capital levels, allows banks to recognize their estimated loss of loan portfolios performance ahead of the actual loss. In this research, several variables were successfully proved to be interrelated with the loan loss provisioning level of Hong Kong banks, including Net total income to total asset, Gross domestic product growth rate, Customer deposit to total funding rate, total common equity to total asset and x-efficiency. These results are expected to provide banking industry with a clearer direction for future analysis of banking system determinants.