Generally, the capital ratios are in the form of a risk-based capital ratio or a leverage ratio. The Basel III framework has suggested a regulatory minimum leverage ratio that defines a stand-alone Tier 1 capital ratio (Tier 1 capital overexposure) as a supplement to the prevailing capital adequacy ratio. The leverage ratio is expressed as the percent of Tier 1 Capital to the Total Consolidated Assets. Simply put, Basel III suggested that leverage ratio determines the level of a bank's core capital to its total assets. Essentially, the Basel III-proposed leverage ratio acts as a ring-fence to the risk-based capital measure. While the leverage ratio connotes the level of loss that the bank equity can absorb, the risk-based capital ratio indicates the maximum capacity of a bank to withstand the potential losses.

The main purpose of the leverage ratio is to offset the systemic risk by restraining the impacts of risk-weight density during boom periods. In a way, it is envisaged to act as a countercyclical regulatory instrument, being tighter during boom periods and flexible during periods of busts. It is expected that when the bank capital is regulated to behave in this pattern during the business cycles, the likelihood of the crisis as well as the magnitude of the impact of the possible crisis can be minimized.

In India, the Reserve Bank of India (RBI) has stipulated a leverage ratio of 4.5% for Systematically Important Banks (SIBs) and 3.5% for other banks. In the case of well-capitalized banks, as their Capital Adequacy Ratio (CAR) is higher than the RBI stipulated regulatory requirement, it encourages increasing the exposure. On the other hand, for capital-starved banks, the additional exposure needs to be of lower risk-weights.

It is desirable to recognize how the leverage ratio evolves over the cycle as against the CAR. Further, it is essential to know how excessive leverage in the banking system can be restrained to enhance bank stability.

The first paper of this issue, "Leverage and Risk-Weighted Capital in Banking Regulation", offers a critical review of banking regulation in the context of the leverage ratio and risk-weighted capital. The paper highlights the potential drawbacks of the recent regulatory changes in the US. The author, Rainer Masera, claims that though the two regulatory measures (i.e., leverage ratio and CAR) seem to be complementary, there is a need for rigorous supervision, instead of looking for an optimal ex ante standardization that might turn out to be time-inconsistent. The paper underscores the importance of effective corporate governance and efficient interaction between banking supervision and internal control mechanisms in ensuring sensible banking regulation.

In India, recently, an Urban Cooperative Bank (UCB) failed to honor the claims of a large number of its depositors, leading to a crisis situation that forced the RBI to limit the amount a customer could withdraw from their deposit accounts to 1,000 for some time. This incident led to concerns among the general public on the safety of their deposits with the cooperative banks. In the second paper, "When and Why Cooperative Banks Fail? The Case of Urban Cooperative Banks in India", the authors, Ajit Kumar and Ashish Srivastava, analyze the key factors that lead to the failure of cooperative banks, particularly the UCBs, in India. According to the study, the instrumental factors for such a failure of the UCBs are poor governance benchmarks, frauds, regulatory breaches, liquidity constraints and bad asset quality. More particularly, the paper states that governance and managerial malpractices lead to such causative factors that lead to cooperative bank failures. The authors suggest that implementation of proper governance standards, integrity in financial disclosures, effective management controls, continuous regulatory scrutiny and supervisory oversight of the banking processes would help minimize bank failures.

The third paper, "Bank Nifty: Empirical Modeling of Returns vis-a-vis Leverage and Volatility", by Neelam Tandon, Deepak Tandon and Navneet Saxena, explores the bank Nifty closing price time series to explicate the past and predict the future of a return series. In doing so, the study estimates the volatility and leverage effect in bank Nifty returns over the study period. As mean and variance may not adequately explain the distribution of returns, the authors claim that the degree of symmetry in return distribution is useful for investor's asset holding. In the backdrop of the transition of Indian banking into a higher trajectory with the incorporation of new technologies and innovative products, the authors analyze the bank Nifty returns, the extent of volatility and the leverage effect. The authors employ ARCH, GARCH, and EGARCH models and find that EGARCH is the best fitting model to measure the performance of bank Nifty returns over the study period. The findings suggest that the higher the leverage effect, the greater the risk or volatility or variance of banking stock. Further, during periods of high volatility, bank's exposure increases and investors shift their funds to less risk-prone investments.