A 'peer reviewed' journal indexed on Cabell's Directory,
and also distributed by EBSCO and Proquest Database
It is a quarterly journal that focuses on Risk management, Forex markets, Retail banking, Banking-supervision and Regulatory mechanisms, Convergence of financial services and E-Banking, HRM banking, ICT in rendering banking solutions, Blockchain and Cyber security.
Leverage and Risk-Weighted Capital in Banking Regulation
This paper offers a critical survey of the swings in banking regulation, notably with reference to leverage and Risk-Weighted Ratios (RWR). At the outset, a distinction is made between economic and Regulatory Capital (ReC) and between private and social costs/benefits of equity finance for banking firms. The inherent limitations of the transformation process of assets into a combined size-risk metric, amplified by Negative Nominal Interest Rates (NNIRs), are brought to the fore, as well as the relative ease of circumventing the rules. The complexity of regulatory risk weighting creates significant (fixed) compliance costs. Unless appropriate tiering is adopted, a competitive distortion is created in favor of large banking institutions. These shortcomings were especially evident in the Basel II standard. With reference to the Basel III/IV framework, it is argued that the two regulatory ratios (leverage and risk-weighted capital) can be complementary, but require close and constant supervision, rather than the quest for an optimal (steady state) ex ante calibration, which may prove time inconsistent. Emphasis should be placed on corporate governance and on the effective interaction between supervisory activity and internal controls. This is usefully complemented by stress-testing techniques which are less model-dependent. Potential drawbacks inherent in recent regulatory changes in the US (community banks have now the option of abandoning tiered risk-weighted requirements and adopting exclusively a leverage constraint, higher than 9%) are indicated.
When and Why Cooperative Banks Fail? The Case of Urban Cooperative Banks in India
The financial system in India has been by and large robust, and there has been no major commercial bank failures. However, notwithstanding a well-regulated structure, several Urban Cooperative Banks (UCBs) have indeed failed and caused losses to depositors and other stakeholders. Therefore, the question as to when and why the UCBs fail is a critical issue to examine and evaluate. This study identifies the key factors for their failures, which can be monitored effectively to prevent any further instances of failure of UCBs in India.
Bank Nifty: Empirical Modeling of Returns vis-a-vis Leverage and Volatility
The Indian banking industry has been changing at a fast pace along with the change in the macro fundamentals of the country. The banking stockholding investors would always be interested in knowing the rate of return and its variance over the holding period. Domestic market returns contain the predictive information on bank Nifty returns. To analyze the return on banking stock, the authors have used the logarithm change in the bank Nifty index series consisting of the daily closing prices of the index over the period of January 2, 2012 to September 6, 2017. The series depicts the period from January 2, 2012 to February 2, 2014 with lower volatility, followed by higher volatility from February 3, 2014 to September 6, 2017. As asset prices tend to behave as random walks, the objective is to accurately capture the behavior of the conditional volatility. To nullify the impact of structural break in the variance series that can create the appearance of a highly persistent conditional volatility, the authors have conducted Bai-Perron test of sequentially determined breaks. Based on the Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC) values, the EGARCH model has been selected as the best fitted model. The authors have concluded that the EGARCH model better captures the leverage effect as bad news has greater impact than good news on bank Nifty stock returns. Investors are prone to shift their investments in case of high volatility, which can be adduced to bad events such as NPA ballooning effect, restructuring and waiver, and inflationary effect.
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