Search results

This paper aims to improve the debate linking the business models of banks to their riskiness by checking if diversification exerts different impacts on the probability of bank distress depending on the level of capital buffers.

The paper focuses on a sample of listed bank holding companies observed between 2007:Q3 and 2022:Q4. The authors use three subindexes of bank diversification. The authors estimate a dynamic model specification using a system generalized method of moments with robust standard errors and consistent estimators under heteroskedasticity and autocorrelation within a panel. Sensitivity and robustness checks are performed.

Asset and income diversification increase the probability of distress in low-capitalized banks during normal periods (excluding periods of crises and high uncertainty). Concerning crisis periods, a marginal increase in asset diversification during the global financial crisis (GFC) and the COVID-19 pandemic crisis induces a more important increase in the probability of failure of well-capitalized banks relative to low-capitalized ones. Contrary to the results obtained for the GFC period, well-capitalized banks were found to pursue more careful funding diversification in reaction to the sudden increase of uncertainty during the Russia–Ukraine war.

Prudential supervision should concentrate on well-capitalized banks to encompass unexpected excessive risk-taking during crisis periods. Regulatory requirements should constrain fragile banks to avoid pursuing assets and income diversification strategies that increase earnings volatility.

The main originality of this paper is to consider the interaction between three different dimensions of bank diversification and capital regulation during stable and unstable periods using the marginal effect analysis. Moreover, this paper uses, initially, the GFC as the reference crisis period to study the impact of capital buffers and diversification interactions on the probability of bank distress. Then, the authors extend the observation period until 2022:Q4 to include two additional major events, namely, the COVID-19 pandemic and the Russia-Ukraine war.

This study aims to investigate the effect of income and asset diversification on earnings management using discretionary loan loss provisions (LLP) in banks, and the role of risk level in mediating this effect.

A sample of banks operating in Middle East and North Africa countries was used to test the mediation model of Baron and Kenny (1986) with different measures of diversification and risk.

The results show that bank income and asset diversification have unique and combined effects on earnings management. The results also support the idea that a risk-mediating effect contributes to explaining this relationship among banks. Specifically, bank diversification strategies positively affect LLP-based earnings management by increasing bank risk. This result is relevant for conventional banks. However, only a direct and positive effect of diversification strategies on LLP-based earnings management can be observed in Islamic banks, and the indirect effect is not supported.

This study extends previous research by examining the unique and combined effects of income and asset diversification strategies on earnings management in the banking sector. Specifically, it provides new evidence that diversification strategies increase LLP-based earnings management, both directly and indirectly, through bank risk.

The purpose of this paper is to examine the financial factors across multiple levels of analysis that influence the performance effects of the unrelated diversification strategy, including institutional-, industry- and firm-levels.

Using a unique panel dataset of Italian firms from 1980 to 2010, the paper tests hypotheses on how industry external financial dependence and the firm's financial constraints both separately and jointly alter the performance benefits of unrelated diversification in contexts with financial market inefficiencies.

Unrelated diversification increases performance in weak financial contexts and such positive effect is enhanced by greater industry external financial dependence and greater firm financial constraints. However, as financial markets develop, the moderating effects of firm financial constraints shrink.

The study highlights the importance of recognizing the multiple financial contingencies that may alter the benefits of the unrelated diversification strategy, suggesting caution in its pursuit to boost firm performance.

The authors develop a theoretical framework that explains the performance outcomes of unrelated diversification, linking the benefits of an internal capital market (ICM) with the financial context of the firm and offering a fine-grained analysis that moves beyond the advanced/emerging economy dichotomy. Furthermore, leveraging on the unprecedented time frame of the empirical analysis, the paper highlights the crucial role of industry- and firm-level financial contingencies and demonstrates that their effects change at varying levels of development of the financial context.

Following the traditions of stakeholder salience theory, this paper aims to contend that some institutional investor activists and tactics have more power, legitimacy and urgency than others.

The author undertakes an empirical test of a saliency table looking at the effects of institutional investor heterogeneity on portfolio firm responses using ordinal logistic regression.

This study found heterogeneity for institutional investor type to drive firm responses but not tactic type raising the importance of the attributes of each type of investor activist. The author found a rank ordering of public pension plans, hedge funds and then private multiemployer funds in saliency to portfolio firms. In addition, the use of proxy-based tactics did not help or hurt each investor type. Both findings challenge prior empirical work.

The rank ordering based upon the heterogeneity of institutional investor activists and their tactical interactions are tested providing empirical evidence of the most influential activist investors and tactics in one study, which is rare in the literature.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

This paper delves into the ex ante rates of return demanded by the private sector in Indonesian public–private partnership (PPP) infrastructure projects and the manifold factors emanating from project attributes that can influence these rates.

This paper analyzes feasibility studies of 37 PPP projects across different sectors. The studies were carefully selected based on relevance, completeness and validity of data. The analysis uses statistical techniques, including Levene’s tests, t-tests, ANOVA tests, Cohen’s effect size and Pearson correlations, to explore differences in cost of capital and excess returns across various attributes.

Based on the statistical analysis, no significant difference exists between the excess return of 200 basis points (bps) and the equity excess return of 0 bps. This suggests that the eligibility criteria for PPP projects require an internal rate of return (IRR) equal to the weighted average cost of capital plus 200 bps or an equity IRR equal to the cost of equity. The variations in the tested variables among diverse project attributes do not exhibit statistically significant disparities, even though specific attributes display moderate to high effect sizes.

This paper represents one of the first attempts to examine the rates of return demanded by the private sector in the context of Indonesian PPP projects. It comprehensively explores the factors that influence these rates, drawing on insights derived from feasibility studies.

This study is the first to investigate the causal relationship between Bitcoin and equity price returns by sectors. Previous studies have focused on aggregated indices such as S&P500, Nasdaq and Dow Jones, but this study uses mixed frequency and disaggregated data at the sectoral level. This allows the authors to examine the nature, direction and strength of causality between Bitcoin and equity prices in different sectors in more detail.

This paper utilizes an Unrestricted Asymmetric Mixed Data Sampling (U-AMIDAS) model to investigate the effect of high-frequency Bitcoin returns on a low-frequency series equity returns. This study also examines causality running from equity to Bitcoin returns by sector. The sample period covers United States (US) data from 3 Jan 2011 to 14 April 2023 across nine sectors: materials, energy, financial, industrial, technology, consumer staples, utilities, health and consumer discretionary.

The study found that there is no causality running from Bitcoin to equity returns in any sector except for the technology sector. In the tech sector, lagged Bitcoin returns Granger cause changes in future equity prices asymmetrically. This means that falling Bitcoin prices significantly influence the tech sector during market pullbacks, but the opposite cannot be said during market rallies. The findings are consistent with those of other studies that have established that during market pullbacks, individual asset prices have a tendency to decline together, whereas during market rallies, they have a tendency to rise independently. In contrast, this study finds evidence of causality running from all sectors of the equity market to Bitcoin.

The findings have significant implications for investors and fund managers, emphasizing the need to consider the asymmetric causality between Bitcoin and the tech sector. Investors should avoid excessive exposure to both Bitcoin and tech stocks in their portfolio, as this may lead to significant drawdowns during market corrections. Diversification across different asset classes and sectors may be a more prudent strategy to mitigate such risks.

The study's findings underscore the need for investors to pay close attention to the frequency and disaggregation of data by sector in order to fully understand the true extent of the relationship between Bitcoin and the equity market.

This paper investigates the impact of financial integration on the capital structure of the firms operating in mainland China, examining the firm-level and country-level integrating variables for 2,878 listed Chinese firms over the period of 1991–2016 in regard to the firms' capital structures. Finally, the study revisits the associations for the state-owned and multinational firms in the context of China.

A large sample of unbalanced data from firms were used to explore the relationship firm-level and country-level integrating variables has with firm leverage and maturity; this is accomplished using the fixed effect model. For robustness, a system-generalised method of moments was used.

The results indicate that internationalisation positively impacts the leverage and debt maturity of all listed Chinese firms and multinational firms and that state-owned firms are financed mainly by the state. For country-level integration, the authors find that credit and equity markets are negatively related to a firm's leverage. A negative relation with credit markets suggests that Chinese firms have much cheaper financing options than the benefits that arise from credit market integration. Moreover, the effect of equity market integration is more pronounced on Chinese firms' capital structure and debt maturity than credit market integration.

The results provide valuable implications of financial integration for policymakers as well as capital structure decision-making for managers in China.

Few studies have examined the impact of integration on firms' capital structures in developing countries. After controlling for unobserved heterogeneity and endogeneity, this study adds new multilevel integration evidence on the capital structure of Chinese firms.

This chapter investigates the cost of public debt for firms using a comprehensive sample consisting of 17,368 industrial bond issues from 1970 to 2011. The empirical evidence shows that yield spreads for seasoned bond issues are significantly lower than those for initial bond issues. This seasoning effect is robust across different sample periods, subsamples, and model specifications. On average, the yield spreads for seasoned bond issues are around 50 bps lower than those for initial bond issues. This difference cannot be explained by other bond and firm characteristics. The seasoning effect is more pronounced for firms with higher levels of uncertainty, lower information disclosure quality, and longer time intervals between the first and subsequent issues. Our empirical findings provide supportive evidence for the extant theories that aim to rationalize the information role in determining the cost of capital.

This study aims to explore the determinants (bank-specific, industry-specific and macroeconomic) of income diversification across interest income and non-interest income as well as for non-traditional income sources (non-interest income) from 2004–2005 to 2021–2022.

An unbalanced data set comprising 110 Indian commercial banks with 1480 observations is sampled in this study. Because of the bounded nature of the dependent variables (proxies of income diversification), the panel Tobit regression model is used.

The findings reveal that income diversification is positively influenced by bank size, technological advancements, cost–income ratio, return on assets, market competition and inflation in the economy. However, the decision to diversify income sources is adversely impacted by the capital ratio, GDP and financial intermediation ratio. Moreover, factors such as asset quality (loan loss provisions) and liquidity ratio do not directly influence the diversification strategies in the Indian banking industry.

The present study uses an extensive set of variables to provide insights into key factors for bank managers, regulators and policymakers to consider before developing diversification strategies.

To the best of the authors’ knowledge, this is the first study to examine the various bank-specific and macroeconomic determinants that affect income diversification in the Indian banking sector. The current study also investigates new variables such as technological advancements and a market concentration index for measuring competition, which have not been investigated in existing literature concerning bank income diversification in the Indian context.