Search results

Financial stability has become a focal point for central banks since the global financial crisis. However, the optimal mix between monetary and financial stability policies remains unclear. In this study, the “soft” approach to such policy mix was tested – how often monetary policy (in inflation reports) analyses financial stability issues. This paper aims to discuss the aforementioned objective.

A total of 648 inflation reports published by 11 central banks from post-communist countries in 1998-2019 were reviewed using a text-mining method.

Results show that financial stability topics (mainly cyclical aspects of systemic risk) on average account for only 2%of inflation reports’ content. Although this share has grown somewhat since the global financial crisis (in CZ, HU and PL), it still remains at a low level. Thus, not enough evidence was found on the use of a “soft” policy mix in post-communist countries.

Given the strong interactions between price and financial stability, this paper emphasizes the need to increase the attention of monetary policymakers to financial stability issues.

The study combines two research areas, i.e. monetary policy and modern text mining techniques on a sample of post-communist countries, something which to the best of the authors’ knowledge has not been sufficiently explored in the literature before.

Despite the sophisticated regulatory regime established in Solvency II, analysts should be able to consider other less complex indicators of the soundness of insurers. The Z-score measure, which has traditionally been used as a proxy of individual risk in the banking sector, may be a useful tool when applied in the insurance sector. However, different methods for calculating this indicator have been proposed in the literature. This paper compares six different Z-score approaches to examine which one best fits insurance companies. The authors use a final dataset of 183 firms (1,382 observations) operating in the Spanish insurance sector during the period 2010–2017.

In the first stage, the authors opt for a root mean squared error (RMSE) criterion to evaluate which of the various mean and SD estimates that are used to compute the Z-score best fits the data. In the second stage, the authors estimate and compare the explanatory power of the six Z-score measures that are considered by using an ordinary least squares (OLS) regression model. Finally, the authors report the results of the baseline equation using the system-GMM estimator developed by Arellano and Bover (1995) and Blundell and Bond (1998) for dynamic panel data models.

The authors find that the best formula for calculating the Z-score of insurance firms is the one that combines the current value of the return on assets (ROA) and capitalization with the SD of the returns calculated over the full sample period.

The main limitation of the research is that it addresses only the Spanish insurance sector, and consequently, the implications of the findings must be framed in this institutional context. However, the authors think that the results could be extrapolated to other countries. Future research should consider including different countries and analyzing the usefulness of aggregated insurer-level Z-scores for macroprudential monitoring.

The Z-score may be a useful early warning indicator for microprudential supervision. In addition to being an indicator of the soundness of insurers simpler than those established in the current regulation, the information provided by this accounting-based measure may help analysts and investors obtain a better understanding of insurance firms' risk factors.

To the best of the authors’ knowledge, this study is the first to examine and compare different approaches to calculating Z-scores in the insurance sector. The few available results on the predictive power of the Z-score are mixed and focus on the banking sector.

雖然在償付能力標準II 內已建立了精密的監管制度，但分析人員應可以考慮以不太複雑的指標，來分析保險公司的穩健程度。Z-分數的估量在銀行業一向作為是個體風險的代理而使用，而Z-分數如應用於保險業，或許會成為有用的工具。唯在文獻裏，學者和研究人員提出了不同的方法來計算這個指標。本文比較六個不同的Z-分數估量方法，以研究出最適合保險公司的方法。我們使用一個最終數據集，包括在2010年至2017年期間在西班牙保險業界營運的183間公司（1382 個觀察）。

在首個階段，我們選擇使用一個方均根誤差(RMSE) 標準來衡量用來計算Z-分數的各個平均值和標準差估量中哪個最適合使用於有關的數據。在第二個階段， 我們以普通最小平方 (OLS) 迴歸模型，去估計並比較被考慮的六個Z-分數估量的解釋力。最後，我們以Arellano與Bover (1995), 以及Blundell與Bond (1998) 為動態追蹤資料模型而發展出來的系統-廣義動差估計推定量，來發表我們基線方程式的結果。

我們發現，計算保險公司Z-分數的最佳公式是把資產收益率及資本總額的現值，和在整個樣本期間計算出來的囘報的標準差結合起來的公式。

我們研究主要的局限為：研究只涉及西班牙的保險業；因此，研究結果的含意，必須在這個體制的背景框架下來闡釋。唯我們相信研究結果或許可外推至其它國家。未來的研究，應考慮納入不同國家作為研究對象，並分析保險公司層面的集成Z-分數的功用，以求達到宏觀審慎監控的目的。

Z-分數或許就微觀審慎監管而言是一個有用的早期警告器。這些以會計為基礎的估量而提供的資訊，除了較現時規例内已建立顯示保險公司穩健程度的各個指標更簡單外，還會幫助分析人員和投資者更了解保險公司的風險因素。

據我們所知，本研究為首個研究，去探討並比較保險業內的Z-分數的計算方法。以前關於Z-分數預測能力的，為數不多並可供取閱的研究結果均不統一；而且，這些研究都聚焦探討銀行業。

This study aims to analyze the impact of cooperation between banking supervisory entities on maintaining financial stability, using Single Supervisory Mechanism evolution and performance as instance. Then banking supervisory cooperation and financial stability in Egypt are reviewed.

The qualitative method is used to study and analyze the practices that contributed to financial instability and raised the need for supervisory cooperation. Descriptive qualitative method is used to study the interrelations between supervisory authorities on various levels and its impact on financial stability.

Findings show that maintaining financial stability through strong, consistent complete or semi unified supervisory framework faces challenges. Providing cooperation between different supervisory authorities, effective information sharing, gained experience in the long run contributes to financial stability.

The originality of this research paper arises from the fact that it encompasses the academic aspect through interpreting the developments that occurred to the cooperation in banking supervision in relation to the financial instability times in the Eurozone that led to the establishment of Single Supervisory mechanism, and the challenges it faced. The supervisory cooperation in Egypt is studied as well at international, regional levels and its role in contributing to financial stability. To the best of the authors' knowledge this is the first study that studies the banking supervisory cooperation between Egyptian supervisory authorities and other international and regional authorities.

This paper aims to investigate the nonlinear effects of bank regulation stringency on bank lending in 23 sub-Saharan African (SSA) countries over the period 1997–2017.

This study employs the dynamic panel threshold regression (PTR) model, which addresses endogeneity and heterogeneity problems within a nonlinear framework. It also uses indices of entry barriers, mixing of banking and commerce restrictions, activity restrictions and capital regulatory requirements from the updated databases of the World Bank's Bank Regulation and Supervision Surveys as measures of bank regulation.

The linearity test results support the existence of nonlinear effects in the relationship between bank lending and entry barriers or capital regulations in the selected SSA economies. The dynamic PTR estimation results reveal that bank lending responds positively when the stringency of entry barriers is below the threshold of 62.8%. However, once the stringency of entry barriers exceeds that threshold level, bank credit reacts negatively and significantly. By contrast, changes in capital regulation stringency do not affect bank lending, either below or above the obtained threshold value of 76.5%.

These results can help policymakers design bank regulatory measures that will promote the resilience and safety of the banking system but at the same time not bring unintended effects to bank lending.

To the best of the authors’ knowledge, this is the first study to examine the nonlinear effects of bank regulatory measures on bank lending using the dynamic PTR model and SSA context.

This work analyzes, through social-environmental reports, whether banks with higher transparency in social-environmental policies better safeguard financial stability in Brazil.

The analysis is carried out through a panel database analysis of the 42 largest Brazilian banks, representing 98% of the Brazilian financial system. Seeking to avoid spurious results, we followed rigorous methodological standards. Hence, we conducted an empirical analysis using a dynamic panel data model, we used the difference generalized method of moments (D-GMM) and the system generalized method of moments (S-GMM).

The results show that the higher the transparency of social-environmental policies, the lower the chance of possible stress on the financial stability of Brazilian banks. In sum, this study builds evidence that disclosing risks related to policies about sustainability can enhance financial stability. It is essential to highlight that social-environmental transparency does not have as direct objective financial stability.

The manuscript submitted represents an original work that analyzes whether banks with higher transparency in social-environmental policies better safeguard financial stability. Some countries, such as Brazil, have their potential for sustainable policies spotlighted due to their green territory and diverse natural ecosystems. Besides having green potential, Brazil is a developing country with a well-developed financial system. These characteristics make Brazil one of the best laboratories for studying the relationship between transparency in social-environmental policies and financial stability.

Starting from the theoretical mechanism of profit sharing between finance and the real economy, this paper reviews and analyzes the profitability of China's banking industry and makes a horizontal comparison with the banking industry of the United States, Japan, and Germany.

Based on the panel threshold model, it is found that there is a dual-threshold asymmetric effect between banking profit and the growth of real economy. When the net profit rate of the banking industry is lower than 0.491%, the increase in banking profitability will inhibit the growth of real economy due to profit grabbing; when the rate falls within the range of 0.491–0.801%, the increase in bank profitability is conducive to the growth of real economy.

Finance and the real economy are in the most comfortable symbiotic state; when the rate is higher than 0.801%, the continued increase in bank profitability will weaken the promotion effect of finance on the real economy, but bank profitability and the growth of real economy are still in a symbiotic state of positive promotion.

The promotion effect of China's bank profitability to the growth of real economy has shifted from the suboptimal state to the optimal range as a whole, which is attributed to the strong deleveraging and strict supervision of the Chinese government after 2016, the timely and decisive “stepping on the brakes”, pulling the financial sector back from the “illusion” caused by “self-circulated” profits and preventing it from harming the real economy.

In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.

By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.

The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.

Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.

This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.

Using cross-country data on the 1,000 largest global banks for 2019, the paper aims to examine the response of bank risk and returns to the pandemic.

The author employs weighted least squares (WLS) techniques for the purposes of analysis.

The findings suggest that banks with Islamic windows increased their riskiness in response to the pandemic, although there was not much impact on profitability. Additionally, the author categorizes banks based on certain major characteristics and find that these findings are manifest primarily for well-capitalized and less liquid banks.

Research as to the impact of the pandemic on banks' balance sheets has been an unaddressed area of research. By focusing on a large sample of banks across countries with both Islamic and conventional banking presence, the analysis sheds light on the balance sheet response of banks to the pandemic, an aspect that has not been addressed earlier.

This study aims to identify European positioning on the use of remote customer onboarding solutions in combating financial crime.

This study is a desktop research that examines European Banking Authority (EBA) policy statements relating to the use of innovative solutions in combating financial crime.

Technological advancements in biometric data and software tools provide a unique opportunity to address potential paper customer onboarding process deficiencies. Electronic remote customer onboarding solutions equip credit, financial institutions and investment firms with an alternative FTE cost-saving solution, in their pursuit of revenue generation. Whilst the EBA and Financial Action Task Force have provided approval for the utilisation of innovative solutions and AML technologies in combatting financial crime. Hesitancy remains on the ability of credit and financial institutions to use technological solutions as a “magic solution” in preventing the materialisation of money laundering/terrorist financing related risks. Analysis of policy suggests a gravitation towards the increased use of the aforementioned technologies in the interim.

Capitalisation of European banking authority.

This paper aims to discuss the main characteristics of the Middle East North Africa (MENA) region's capital inflows volatility. It also examines the effect of institutional quality and information availability on capital inflows volatility in selected MENA countries (Bahrain, Egypt, Israel, Jordan, Kuwait, Libya, Morocco, Oman, Saudi Arabia and Tunisia) in the period 1996–2017.

The study's assessments are based on the International Country Risk Guide (ICRG) and globalization indices. It also employs an updated data set of balance of payments indicators released by the International Monetary Fund. Moreover, the study uses econometric panel modeling of random effect model, with Driscoll-Kraay robust standard error, to analyze the relationship between capital inflows volatility, institutional quality and information availability.

The paper finds that both institutional quality and information availability are in an inverse relationship with the total capital inflows volatility in the MENA region. However, the findings vary across the different components of total capital inflows. For example, the volatility of foreign direct investment (FDI) declines, like total capital flows, as the two factors improve. However, the volatility of foreign portfolio investment (FPI) is negatively related to institutional quality but does not have any significant relationship with information availability. While the volatility of foreign other investments (FOI) decreases with the availability of information, but does not have any significant relationship with institutional quality.

This paper expands the limited literature regarding the determinants of capital inflows volatility. Furthermore, it is the first study that investigates the effect of institutional quality and information availability on capital inflows volatility in the MENA region.