Suchergebnisse

The Basel Committee on Banking Supervision (BCBS) states that in addition to the fact that it lacks simplicity, the Advanced Measurement Approach (AMA) must be discarded because the flexibility of AMAs does not narrow as envisioned prior. This paper discusses whether this judgment of the BCBS holds for the Chinese banking industry. We first review the development of operational risk data collection and AMAs in China over the past decade. Then, capital requirement results for Chinese banks based on these datasets and approaches are summarized and analyzed. It is shown that along with the accumulation of operational risk data and the refinement of AMAs, operational risk results for the Chinese banking industry have shown a clear trend of convergence that is exactly opposed to judgments of the BCBS. Therefore, the removal of the AMA from regulatory frameworks may not be reasonable.

AbstractRisk matrices have been widely used as a risk evaluation tool in many fields due to their simplicity and intuitive nature. Designing a rating scheme, i.e., determining the number of ratings used in a risk matrix and assigning different ratings to different cells, is an essential part of risk matrix construction. However, most of the related literature has focused on applying a risk matrix to various fields, instead of researching how to design risk matrices. Based on the analysis of several current rules, we propose a new approach, namely, the sequential updating approach (SUA), to design the rating scheme of a risk matrix in a reliable way. In this article, we propose three principles and a rating algorithm based on these principles. The three principles, namely, adjusted weak consistency, consistent internality, and continuous screening, characterize a good rating scheme. The resulting rating scheme has been proven to be unique. A global rating algorithm is then proposed to create the design that satisfies the three principles. We then explore the performance of the SUA. An illustrative application is first given to explain the feasibility of our approach. The sensitivity analysis shows that our method captures a resolution‐reliability tradeoff for decisionmakers in choosing an appropriate rating scheme for a risk matrix. Finally, we compare the designs based on the SUA and Cox's axioms, highlighting the advantages of the SUA.

ABSTRACTFor the balance between risk and return under the energy geopolitics, this paper attempts to investigate the energy geopolitical attraction rather than the general geopolitical risk of energy‐exporting countries and focus on selecting and ranking the countries characterized by multiple geopolitical determinants. We identify the major determinants of energy geopolitics and construct the energy geopolitical climate index to capture the common underlying characteristics of the energy geopolitical attraction. Then, the energy geopolitical climate index values are extracted from multiple geopolitical determinants using a multiple‐attribute analysis, factor analysis. Finally, 35 energy‐exporting countries are selected to test the effectiveness of the model from the perspective of Chinese energy‐supply security. Empirical results account for the relationship between energy geopolitics and energy‐security strategy of China and indicate that it is an effective solution to strengthen energy cooperation with the peripheral energy‐exporting countries besides the Middle East for improving Chinese energy‐supply security. By comparing empirical results with the real situation of international energy geopolitics, we confirmed the effectiveness and usefulness of the proposed methodology. Copyright © 2011 John Wiley & Sons, Ltd.

AbstractComplicated interaction between risk events is the critical obstacle preventing accurate risk aggregation, which is an important issue in risk management. Recent research integrates interaction into risk aggregation with different perspectives and lacks a comprehensive discussion of this issue, making the risk aggregation process not universal for diverse cases, especially in subjective risk assessment contexts. Therefore, this article proposes a theoretically convincing risk aggregation method embedding different types of interaction to support decision analysis more effectively. The main contributions of this article are as follows: (a) more in‐depth and stricter definitions, measures, and graphical descriptions of different types of interaction are developed to ensure the accuracy of risk aggregation; (b) a formal risk aggregation approach that could apply in both objective and subjective risk assessment contexts while elegantly embedding risk interactions is proposed; (c) the additivity of risks and risk sets in the risk aggregation process is discussed in detail and the conditions for additivity are clarified; (d) the quasi‐two/three‐additive measures, which approximately obtain the aggregate risk value within sufficient reliability, are proposed to greatly reduce the computational cost. To examine the applicability of the proposed general risk aggregation method, a case study is finally presented to show the complete risk aggregation process and its application in the decision‐making stage.

AbstractExisting studies on the environmental Kuznets curve (EKC) neglect the inverse effect of pollution transfer from environmental regulation interactions on pollution reduction from a risk analysis perspective. Based on the regional differentiated attitudes on the environmental regulation reached in risk communication by the risk awareness biases of multiple interest groups, this article clarifies the causality between risk communication and risk transfer based on multistakeholder engagement processes; furthermore, the article incorporates the simultaneous action of the technological innovation effect and pollution risk transfer effect to construct a spatial environmental hyperbolic model with a bidirectional correlation between pollution emissions and economic growth in different regions. To verify our model, we select the pollution from agricultural watersheds in China as a sample to examine the two inverse effects. The results demonstrate that (1) agricultural watershed pollution and economic growth show an inverted U‐shaped relation and a U‐shaped relation in the local region and adjacent regions, respectively; (2) the pollution reduction assessment of the classical EKC model can be largely attributed to pollution risk transfer behavior; and (3) the turning point of the U‐shaped curve appears earlier than that of the inverted U‐shaped curve in the spatial hyperbola model. The findings suggest that stakeholders should consider the risk awareness bias caused by the imbalance of regional economic development and the scenarios that provide a "haven" for pollution risk transfer. Moreover, our study expands the theoretical connotation of the classical EKC hypothesis and is more suitable for pollution reduction scenarios in developing countries.