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This paper has used account-level data of corporate and retail borrowers, assessed their credit risk through the risk-neutral principle and examined its implication on loan pricing.

It derives the capital charge and credit risk-premium for expected and unexpected losses through a risk-neutral approach. It estimates the risk-adjusted return on capital as the pricing principle for loans. Using GMM regression, the article has assessed the determinants of risk-based pricing.

It has been found that risk-premium is not reflected in the current loan pricing policy as per Basel II norms. However, the GMM estimation on RAROC can price risk premium and probability of default, LGD, risk weight, bank beta and capital adequacy, which are the prime determinants of loan pricing. The average RAROC for retail loans is more than that of corporate loans despite the same level of risk capital requirement for both categories of loans. The robustness tests indicate that the RAROC method of loan pricing and its determinants are consistent against the time and type of borrowers.

The RAROC method of pricing effectively assesses the inherent risk associated with loans. Though the empirical findings are confined to the sample bank, the model can be used for any bank implementing the Basel principle of risk and capital assessments.

The article has developed and validated the model for estimating RAROC, as per Basel II guidelines, for loan pricing that any bank can use.

It has developed the risk-based loan pricing model for retail and corporate borrowers. It has significant practical utility for banks to manage their risk, reduce their losses and productively utilise the public deposits for societal developments.

The article empirically validated the risk-neutral pricing principle using a unique 1,520 retail and corporate borrowers dataset.

This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms.

This study makes use of the bivariate cross-quantilogram methodology recently developed by Han et al. (2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states.

The study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market.

The findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns.

This study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.

This study aims to investigate factors that influence the attitudes and intentions of investors towards environmental, social and governance (ESG) stocks in the presence of perceived risk as a moderator.

Data was collected through an online survey method from 341 investors with more than three years of investing experience. Smart PLS was used to analyse the data using two-stage structural equation modelling. First, a measurement model was performed for construct reliability and validity, followed by path analysis (structural model) for hypothesis testing and overall model predictability.

The findings show that both environmental concern (altruistic value) and economic concern (egoistic value) are crucial for the attitude and intention of investors to invest in ESG-backed stocks; however, environmental concern was found to be a more significant predictor of their behaviour, showing evidence of pro-environmental values in the decision-making of utility-seeking individuals. No significant impact of perceived risk was evident as a moderator of the relationship between attitude and intention towards ESG stocks.

The study's findings have implications for fund managers, policymakers, and the government. Values as antecedents were found to be influential in shaping investors’ attitudes and intentions towards the environmental cause. Fund managers could include more ESG-compliant companies in their portfolios, and the government can play an important role in encouraging investors by providing financial incentives. Corporates should also take strategic steps to adopt green production processes to secure long-term, sustainable capital funding.

To the best of the authors’ knowledge, there has been no research done in the field of ESG investing that takes into account the values (both altruistic and egoistic) of investors as potential antecedents of their attitudes and intentions.

This paper aims to examine the weak form of efficiency for price series of four precious metals, i.e. gold, silver, platinum and palladium, using a generalized spectral method.

The method has the advantage of detecting both linear and non-linear serial dependence in the conditional mean, and it is robust to various forms of conditional heteroscedasticity. The authors use three different rolling windows for the purpose of robustness.

The authors report weak form of efficiency across metals series for almost all rolling windows. The optimum efficiency for Gold and Palladium is achieved through 250 days rolling window estimates whereas it is 500 days rolling window for silver. Platinum has similar efficiency levels across rolling windows. The degree of efficiency for metal prices is observed to be varying over time with silver market possessing highest levels of efficiency. The efficiency synchronization also varies across rolling windows and metals.

The results reveal that metal markets are efficient for most times implying the low predictability and the low likelihood of earning abnormal returns by speculating in these markets.

The study uses a relatively new statistical technique, the generalized spectral test, to capture linear and non-linear serial dependence. Therefore, the results possess adequate power against departure from market efficiency.

This study aims at identifying critical success factors of a sustainable mobile banking application using text mining approach.

A total of 6,073 consumer reviews relating to a mobile banking application were collected and analyzed to meet the study objective. Latent Semantic Analysis (LSA) was done to identify the critical success factors of a sustainable mobile banking application.

The results indicated that privacy and security, navigation, customer support, convenience and efficiency are the key factors.

The study findings enrich the mobile banking and sustainable service delivery channel literature.

The results are expected to benefit the bankers in delivering effective banking services through a mobile banking application.

Studies in the sustainability are few yet promising particularly the ones that use rigorous statistics suitable on thousands of data points to accomplish the study objectives.

This study aims to investigate the dynamic co-movement and interconnection among 69 security investment indices in China using the multi-time scale framework.

The authors first use the multiple coherence analysis method to exhibit the degree of relationships among the variables under study. In addition, the wavelet multiple correlation and wavelet multiple cross-correlation analyses are used to examine the time-frequency synchronization interdependence structure among the variables.

From the empirical findings, one may infer less opportunity for portfolio diversification at higher time scales. Obviously, at these scales, the authors find that the 69 Chinese investment indices generate a simple security investment class, as indicated by higher interconnection between the indices.

Further research can increase the sample size to re-investigate the empirical relationship for security investment indices.

In the nutshell, the results demonstrate the potential for Chinese investors to invest in security investment indices to earn from portfolio diversification at lower time frequencies. The Chinese investment market indices under study yield further opportunities of portfolio diversification toward the short-term investors than the long-term investors.

To the best of the authors’ knowledge, this is the first paper to examine the dynamic co-movement and interconnection for security investment indices in China.

The current study aims to analyze the linkage among bank competition, liquidity and loan price in an interconnected bank network system.

The study employs the Lerner index to estimate bank power; Granger non-causality for estimating competition, liquidity and loan price network structure; principal component for developing competition network index, liquidity network index and price network index; and panel VAR and LASSO-VAR for analyzing the dynamics of interactive network effect. Current work considers 33 Indian banks, and the duration of the study is from 2010 to 2020.

Network structures are concentrated during the economic upcycle and dispersed during the economic downcycle. A significant interaction among bank competition, liquidity and loan price networks exists in the Indian banking system.

The study meaningfully contributes to the existing literature by adding new insights concerning the interrelationship between bank competition, loan price and bank liquidity networks. While enhancing competition in the banking system, the regulator should also pay attention toward making liquidity provisions. The interactive network framework provides direction to the regulator to formulate appropriate policies for managing competition and liquidity while ensuring the solvency and stability of the banking system.

The study contributes to the limited literature concerning interactive relationship among bank competition, liquidity and loan price in the Indian banks.