Maternal haemoglobin concentrations before and during pregnancy and stillbirth risk: A population-based case-control study

Background: Results of previous studies on the association between maternal haemoglobin concentration during pregnancy and stillbirth risk are inconclusive. It is not clear if haemoglobin concentration before pregnancy has a role. Using prospectively collected information from pre-pregnancy and antenatal visits, we investigated associations of maternal haemoglobin concentrations before and during pregnancy and haemoglobin dilution with stillbirth risk. Methods: In a population-based case-control study from rural Golestan, a province in northern Iran, we identified 495 stillbirths (cases) and randomly selected 2,888 control live births among antenatal health-care visits between 2007 and 2009. Using logistic regression, we estimated associations of maternal haemoglobin concentrations, haemoglobin dilution at different stages of pregnancy, with stillbirth risk. Results: Compared with normal maternal haemoglobin concentration (110-120g/l) at the end of the second trimester, high maternal haemoglobin concentration (≥140g/l) was associated with a more than two-fold increased stillbirth risk (OR = 2.31, 95% CI [1.30-4.10]), while low maternal haemoglobin concentration (<110g/l) was associated with a 37% reduction in stillbirth risk. Haemoglobin concentration before pregnancy was not associated with stillbirth risk. Decreased haemoglobin concentration, as measured during pregnancy (OR = 0.61, 95% CI [0.46, 0.80]), or only during the second trimester (OR = 0.75, 95% CI [0.62, 0.90]), were associated with reduced stillbirth risk. The associations were essentially similar for preterm and term stillbirths. Conclusions: Haemoglobin concentration before pregnancy is not associated with stillbirth risk. High haemoglobin level and absence of haemoglobin dilution during pregnancy could be considered as indicators of a high-risk pregnancy. © 2016 The Author(s)

Measuring concentration risk for regulatory purposes

The measurement of concentration risk in credit portfolios is necessary for the determination of regulatory capital under Pillar 2 of Basel II as well as for managing portfolios and allocating economic capital. Existing multi-factor models that deal with concentration risk are often inconsistent with the Pillar 1 capital requirements. Therefore, we adjust these models to achieve Basel II-compliant results. Within a simulation study we test the impact of sector concentrations on several portfolios and contrast the accuracy of the different models. In this context, we also compare Value at Risk and Expected Shortfall regarding their suitability to assess concentration risk. --Concentration Risk,Pillar 2,Multi-Factor Models,Economic Capital,Simulation Study,Value at Risk,Expected Shortfall

Analysis of cyber risk and associated concentration of research (ACR)² in the security of vehicular edge clouds

Intelligent Transportation Systems (ITS) is a rapidly growing research space with many issues and challenges. One of the major concerns is to successfully integrate connected technologies, such as cloud infrastructure and edge cloud, into ITS. Security has been identified as one of the greatest challenges for the ITS, and security measures require consideration from design to implementation. This work focuses on providing an analysis of cyber risk and associated concentration of research (ACR2). The introduction of ACR2 approach can be used to consider research challenges in VEC and open up further investigation into those threats that are important but under-researched. That is, the approach can identify very high or high risk areas that have a low research concentration. In this way, this research can lay the foundations for the development of further work in securing the future of ITS

Impact of ownership structure and ownership concentration on credit risk of Chinese commercial banks

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose- The purpose of this study is to examine the effects of bank ownership structure and ownership concentration on credit risk. Design/methodology/approach- Using panel data on a sample of 88 Chinese commercial banks with 1194 observations over a period of 2003-2018, this study employs system generalised method of moments regression to examine the impact of bank ownership structure and ownership concentration on credit risk. Two measures of credit risk, namely, non-performing loan ratio and loan loss provision ratio are used to ensure the robustness of the results. Findings– The results show that ownership type (both government and private ownership) exert positive and significant impact on credit risk. However, our results indicate that concentration of ownership in the hands of government has negative and significant effect on credit risk while private ownership concentration positively impacts on credit risk. Overall our findings suggest that concentration of ownership in government hands reduces risk, whilst private ownership concentration exacerbates credit risks. Our results are invariant to alternative measures of credit risk and financial crisis. Practical implications – The findings provide useful insight to guide policy decisions in Chinese banks’ lending policies and bank ownership. Originality/value– Using hand collected data on ownership structure and governance from annual reports this study deepens our understanding on the effectiveness of Chinese banks’ corporate governance reforms on managing credit risks

Concentration risk under Pillar 2: When are credit portfolios infinitely fine grained?

The ongoing debate concerning credit concentration risk is mainly driven by the requirements on credit risk management due to Pillar 2 of Basel II since risks (e.g. concentration risk) that are not fully captured by Pillar 1 should be adequately considered in the banks' risk management. This instruction is indeed relevant since quantifying credit portfolio risk in Pillar 1 is based on an Asymptotic Single Risk Factor (ASRF) framework in which concentration risk is not covered. Against the background of the ASRF model, we determine the number of credits up to which concentration risk leads to a significant estimation error so that the assumption of an infinitely fine grained portfolio is inadequate. We conclude that the critical portfolio size varies from 22 up to 35,986 debtors, dependent on assets correlation and probability of default. Using a modified valuation function (granularity adjustment) it is possible to reduce the critical number of credits by averaged 83.04 %. --Basel II,Pillar 2,Concentration Risk,Granularity Adjustment