The Relationship Between Risk and Capital: Evidence from Indian Public Sector Banks

The study investigates the relationship between changes in risk and capital in the public sector banking system in India, using both the seemingly unrelated regression (SUR) and the two stage least square (2SLS) method of estimation. Empirical findings establish a negative and significant impact of size on capital, indicating that large banks increased their ratio of capital to risk weighted assets less than other banks. Regulatory pressure is also found to have a negative and significant impact on the ratio of capital to risk weighted assets. Ceteris paribus, adequately capitalised banks decrease their capital ratio more prominently than other banks.

Expected returns and liquidity risk: Does entrepreneurial income matter?

This paper studies the effects of jointly incorporating liquidity risk and non-tradeable wealth in a single asset pricing equation. First, I propose an overlapping-generations model with random endowment shocks and liquidity risk, evaluating their joint impact on expected returns. The model presents a single-factor asset pricing equation, with a new term capturing the covariance between assets' liquidities and non-tradeable wealth. In this economy, assets with higher liquidity or returns when non-tradeable wealth is low command lower expected returns. Second, I investigate whether risks associated with liquidity are priced after including non-tradeable wealth due to entrepreneurial income. I test the model on equally weighted and value-weighted portfolios, sorted by illiquidity levels, illiquidity variation and size, using US stock data from January 1962 to December 2004. The extra terms due to entrepreneurial income reduce liquidity risk premium by almost 40%, with an impact of -0.45% per year on expected returns of value-weighted illiquidity-sorted portfolios. Overall, liquidity risk as a whole has a yearly premium equal to 1.06%. However, liquidity levels are much more important and have a premium of 6.14% per year, contributing to most of the explanatory gains of the model.Asset Pricing; Liquidity Risk; Human Capital; Labor Income;

Capital ratios as predictors of bank failure

The current review of the 1988 Basel Capital Accord has put the spotlight on the ratios used to assess banks’ capital adequacy. This article examines the effectiveness of three capital ratios—the first based on leverage, the second on gross revenues, and the third on risk-weighted assets—in forecasting bank failure over different time frames. Using 1988-93 data on U.S. banks, the authors find that the simple leverage and gross revenue ratios perform as well as the more complex risk-weighted ratio over one- or two-year horizons. Although the risk-weighted measures prove more accurate in predicting bank failure over longer horizons, the simple ratios are less costly to implement and could function as useful supplementary indicators of capital adequacy.Bank failures ; Bank capital ; Banks and banking - Ratio analysis

Banks' regulatory capital buffer and the business cycle: evidence for German savings and cooperative banks

This paper analyzes the effect of the business cycle on the regulatory capital buffer of German savings and cooperative banks in the period 1993-2003. The capital buffer is found to fluctuate anticyclically over the business cycle. The fluctuation is stronger for savings banks than for cooperative banks, as, for savings banks, risk-weighted assets fluctuate more strongly with the business cycle. Further, low-capitalized banks do not catch up with their wellcapitalized peers. The gap between low-capitalized and well capitalized banks even widened over the observation period. Finally, low-capitalized banks do not decrease risk-weighted assets in a business cycle downturn by more than well-capitalized banks. This finding seems to imply that their low capitalization does not force them to retreat from lending. --Capital Regulation,Bank Capital,Business Cycle Fluctuations

Australian Bank Capital and the Regulatory Framework

The amount and quality of the Australian banking sector’s capital has increased considerably over the past couple of years. As in a number of other countries, this is because the recent global financial crisis has prompted both markets and regulators to reappraise their views on acceptable levels and forms of capital. National and international regulatory bodies have proposed a number of major changes to existing capital regulations, details of which will be finalised later this year.banks; capital; bank capital; capital regulation; capital standards; Basel I; Basel II; Basel III; Tier 1 capital; credit risk; market risk; risk-weighted assets

Total assets versus risk weighted assets: Does it matter for MREL?

The European Union's Bank Recovery and Resolution Directive foresees a "minimum requirement for own funds and eligible liabilities" (known as MREL) that banks need to comply with in order to ensure the effectiveness of the bail-in tool. The details of how MREL should be constructed in practice are under discussion. We look at alternative ways to compute MREL, showing how the choice of the benchmark metric (risk weighted assets, total assets or leverage exposure) can change the allocation of requirements across banks. We also review MREL in light of the global effort to ensure future resolvability of banks, highlighting some differences with, and inconsistencies in relation to, the Financial Stability Board's total loss-absorption capacity (TLAC) measure

Hedge fund portfolio selection with modified expected shortfall

Modified Value-at-Risk (VaR) and Expected Shortfall (ES) are recently introduced downside risk estimators based on the Cornish-Fisher expansion for assets such as hedge funds whose returns are non-normally distributed. Modified VaR has been widely implemented as a portfolio selection criterion. We are the first to investigate hedge fund portfolio selection using modified ES as optimality criterion. We show that for the EDHEC hedge fund style indices, the optimal portfolios based on modified ES outperform out-of-sample the EDHEC Fund of Funds index and have better risk characteristics than the equal-weighted and Fund of Funds portfolios.portfolio optimization, modified expected shortfall, non-normal returns

Dynamic Optimal Portfolio Selection in a VaR Framework

We propose a dynamic portfolio selection model that maximizes expected returns subject to a Value-at-Risk constraint. The model allows for time varying skewness and kurtosis of portfolio distributions estimating the model parameters by weighted maximum likelihood in a increasing window setup. We determine the best daily investment recommendations in terms of percentage to borrow or lend and the optimal weights of the assets in the risky portfolio. Two empirical applications illustrate in an out-of-sample context which models are preferred from a statistical and economic point of view. We find that the APARCH(1,1) model outperforms the GARCH(1,1) model. A sensitivity analysis with respect to the distributional innovation hypothesis shows that in general the skewed-t is preferred to the normal and Student-t.Portfolio Selection; Value-at-Risk; Skewed-t distribution; Weighted Maximum Likelihood.

Effect of rollover risk on default risk: evidence from bank financing

We study the effect of rollover risk on the risk of default using a comprehensive database of U.S. industrial firms during 1986–2013. Dependence on bank financing is the key driver of the impact of rollover risk on default risk. Default risk and rollover risk present a significant positive relation in firms dependent on bank financing. In contrast, rollover risk is uncorrelated with default probability in the case of firms that do not rely on bank financing. Our measure of rollover risk is the amount of long-term debt maturing in one year, weighted by total assets. In the case of a firm that depends on bank financing, an increase of one standard deviation in this measure leads to a significant increase of 3.2% in its default probability within one year. Other drivers affecting the interaction between rollover risk and default risk are whether a firm suffers from declining profitability and has poor credit. Additionally, rollover risk's impact on default probability is stronger during periods when credit market conditions are tighter