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The purpose of this paper is to incorporate risk in technical efficiency of ASEAN banks in a panel data framework for the period 2000 to 2015.

The directional distance function and semi-parametric framework are employed to estimate efficiency scores for two scenarios, one with only good outputs and the other with a combination of good and bad outputs.

The findings show there is no evidence of technological progress for banks in ASEAN and concerns about the outperformance of Vietnam’s banks. In addition, performance of Vietnam’s banks tends to be distorted by low level of loan loss reserves.

To reflect the true performance and shorten the period of removing bad assets, the State Bank of Vietnam can request banks in Vietnam to book more loan loss reserves.

By examining such a new approach, this study makes an early attempt to incorporate credit risk into the banking efficiency in ASEAN region.

This paper aims to assess to what extent the COVID-19 shock is expected to create a debt crisis in emerging markets and developing economies (EMDEs) through two main questions: what are the main determinants of EMDEs external vulnerability? How vulnerable are EMDEs to the current COVID-19 shock compared to the global financial crisis (GFC)?

In addition to a descriptive analysis of the determinants of EMDEs external vulnerability, this paper designs two sub-indices of overindebtedness and financial fragility that capture EMDEs’ distinct characteristics. The two sub-indices together illustrate the overall external vulnerability to the current shock.

EMDEs are more vulnerable compared to the GFC era. Current debt threats arise mainly from debt architecture and the domination of volatile debt forms – primarily foreign currency-denominated bonds. Excessive fear of debt-deflation spirals after the GFC prompted EMDEs to expand their growth trajectories through a pattern of cheap private lending, loose measures and unmonitored fiscal expansion.

Conclusive post-crisis data are still unavailable.

EMDEs need to balance between temporary accommodative measures and a post-shock policy mix that prevent a deflation spiral without worsening indebtedness and financial fragility. Moreover, financial prudence in face of growing credit demand is crucial, particularly in light of the monetary expansion and injected liquidity.

The indices offer a framework for examining external vulnerability in EMDEs based on theoretical and historical revisions, IMF benchmarks and EMDEs specific debt characteristics. The indices components can be offered for empirical examination in separate future research once conclusive data become available.

This study aims to examine and compare the credit risk management (CRM) scenario of Islamic banks (IBs) and conventional banks (CBs) in Pakistan, keeping in view the phenomenal growth of Islamic banking and its future implications.

A sample of five CBs and four IBs was chosen out of the whole banking industry for the study. Secondary data obtained from the banks’ annual financial reports for 13 years, starting from 2004 to 2016, were analyzed. Multiple regression, correlation and descriptive analysis were used in the examination of the data.

The results show that loan quality (LQ) has a positive and significant impact on CRM for both IBs and CBs. Asset quality (AQ), on the other hand, has a negative impact on CRM in the case of IBs, but has a significantly positive relation with CRM in the case of CBs. The impact of 16 ratios measuring LQ and AQ have also been individually checked on CRM, by making use of a regression model using a dummy variable of financial crises for robust comparison among CBs and IBs. The model proved significant, and CRM performance of IBs was observed to be better than that of CBs. Moreover, the mean average value of financial ratios used as a measuring tool for these variables shows that the CRM performance of IBs operating in Pakistan was better than that of CBs over the period of the study.

The research findings are expected to facilitate bankers, investors, academics and policy makers to build a better understanding of CRM practices as adopted by CBs and IBs. The findings would be useful in formulating policy measures for the progress of the banking industry in Pakistan.

This research is unique in terms of its approach toward analyzing and comparing CRM performance of CBs and IBs. Such work has not been carried out before in the Pakistani banking industry.

Basel III regulations require banks to protect themselves against strategic risk. This paper aims to provide a comprehensive and measurable definition of this risk and proposes a framework to estimate economic capital requirements.

The paper studies the literature and solicits expert opinion in formulating a comprehensive and measurable definition of strategic risk. The paper postulates that the economic capital for a bank’s strategic risk should be estimated using the cost of equity as the profitability threshold, rather than zero and develops a simulation-based framework to estimate economic capital.

The framework closely matches the actual economic capital outlay for strategic risk from our case study of ABN AMRO. It is shown that a bank’s strategic growth plans can fall into one of two scenarios based on risk-return characteristics. In one scenario, the required economic capital outlay will increase, and decrease in the other.

This framework is generalizable and makes use of widely accepted and used practices in banks, making it readily implementable in practice. It does not introduce errors resulting from model selection, parameterizations or complex calculations.

Society would be worse off in the absence of banking and lending services. Banks need to take risks to grow and stay competitive. The framework facilitates better strategic risk management, protecting banks from collapse and reducing the need for taxpayer-funded bailouts.

The paper provides a measurable and practitioner-verified definition of strategic risk and proposes a simple framework to estimate economic capital requirements, a crucial topic, given the threats and increased levels of strategic risk facing banks.

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 paper aims to obtain a recent estimate of the cost of precautionary foreign reserve accumulation that emerging market and developing economies (EMDEs) had to endure to protect themselves against the risks of financial globalization. In addition, the study estimates the cost of excess reserves in emerging market economies (EMEs) using various reserve adequacy indicators that reflect potential sources of foreign exchange drains and vulnerability in EMEs' balance of payments.

This paper begins by explaining the accumulation of foreign reserves in EMDEs as a self-protection strategy against the risks of financial globalization. Next, it sheds light on the different types of economic costs of foreign reserve accumulation. Finally, it estimates the cost of foreign reserve accumulation in EMEs during the period (1990–2018) and in EMDEs during the period (1990–2015) due to data availability.

Results indicate that the cost of accumulating foreign reserves as a self-protection strategy in EMDEs and EMEs' was huge compared to their development financing needs. Applying various reserve adequacy measures demonstrates that many of the EMEs were holding inadequate precautionary reserves in 2018. Actually, this reflects the significant increase in external short term debt that many of the EMEs have witnessed since the eruption of the global financial crisis (2008). Thus increasing reserves in EMEs with weak reserve buffers and higher external debt is critical as they are more vulnerable to external shocks and capital flow reversals. Also given the estimated huge costs of accumulating foreign reserves, EMDEs should accompany it by other complementary self-protection policies and liquidity management policies to free up resources for productive investment.

The study contributes to the literature by estimating the cost of precautionary foreign reserve accumulation imposed on EMDEs during an extended period of time that covers a decade after the onset of the global financial crisis. Also to the authors' knowledge, this is the first study that estimates the cost of excess reserves in EMEs using various reserve adequacy indicators including the International Monetary Fund (IMF) assessing reserve adequacy (ARA) approach.

This study aims to develop a high-quality impairment loss allowance model in conformity with Indonesian Financial Accounting Standards 71 (PSAK 71) that has significant contribution to national interests and the banking industry.

The determination of the impairment loss allowance model is settled through 7 stages, using integration of some statistical methods such as Markov chain, exponential smoothing, time series analysis of behavioral inherent trends of probability of default, tail conditional expectation and Monte Carlo simulation.

The model which is developed by the authors is proven to be a high-quality and reliable model. By using the model, it can be shown that the implementation of the expected credit losses model on Indonesian Financial Accounting Standards 71 is more prudent than the implementation of the incurred loss model on Indonesian Financial Accounting Standards 55.

Determination of defaults was based on days past due, and the analysis in this study did not touch the aspects of hedge accounting in general.

This developed model will contribute significantly to national interests as a source of reference for other banks operating in Indonesia in calculating impairment loss allowance (CKPN) and can be used by the Financial Services Authority of Indonesia (OJK) as a guideline in assessing the formation of impairment loss allowance for banks operating in Indonesia.

As so far there is not yet an available standardized model for calculating impairment loss allowance on the basis of Indonesian Financial Accounting Standards 71, the model developed by the authors will be a new breakthrough in Indonesia.

This paper aims to study the impact of (regulatory and nonregulatory) liquidity on contingent convertible (CoCo) issuance and the relationship between CoCos and asset quality.

The analysis of this study comprises two stages. In the first stage, the authors used a logit model to test whether banks with riskier assets as well as lower solvency and (regulatory and nonregulatory) liquidity are more likely to issue CoCos. In the second stage, the authors used univariate analysis and fixed effects regression to measure the impact of Additional Tier 1 (AT1) CoCos on the quality of the issuer’s assets.

The study shows that regulatory liquidity ratios are negatively related to CoCo issuance. This study also finds that the likelihood to issue CoCo is higher when banks have lower regulatory capital or are less risky. Asset quality is found to not change significantly after the issuance. All in all, these results suggest that while solvency regulation is primarily regarded as the main motivation for CoCo issuance, liquidity regulation also matters.

Despite the fact that CoCos have been emerging as an alternative way to help banks meet regulatory capital requirements, the paper argues that the relation between liquidity regulation and CoCos should be taken into account.

This study presents an empirical analysis on the CoCos instrument, focusing on the relationship between AT1 CoCos and liquidity regulation. Therefore, it serves to fill a gap in the literature on the underlying forces behind CoCo issuance. Moreover, this study measures the impact of AT1 CoCos issuance on bank risk, particularly on the quality of the issuer’s assets.

The European Parliament and Commission are considering introducing a green supporting factor (GSF) or brown penalty (BP) for capital reserve requirements. This paper aims to estimate the potential impact such a policy intervention may have on both capital reserves of European banks and the cost and availability of capital to “green” and “brown” investments.

The paper draws on the existing empirical and theoretical literature on the impacts of changes to capital reserve requirements on the real economy. It applies these estimates on the particular policy intervention currently being discussed at EU level to estimate the potential range of impacts on the cost of capital – measured in basis points – and the availability of capital – measured in per cent changes to lending.

A GSF would have a limited effect on overall capital requirements of banks compared to a BP – given the larger universe of assets on which such a penalty would be applied. The estimated effect is a reduction in capital requirements associated with a GSF of around €3-4bn based on baseline “green” definitions. In terms of cost of capital, the paper estimates a reduction of 5 to 26 basis points for green projects (with inverse expected effects for a BP). In terms of availability of capital, analysing a BP suggests a potential reduction in lending to brown assets of up to 8 per cent.

The paper provides direct evidence, with the first quantitative analysis of the potential impact of the current policy proposition discussed at EU-level.