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The financial crisis of 2007-2009 has given way to the sovereign debt crisis of 2010-2012, yet many of the banking issues remain the same. We discuss a method to estimate the capital that a financial firm would need to raise if we have another financial crisis. This measure of capital shortfall is based on publicly available information but is conceptually similar to the stress tests conducted by US and European regulators. We argue that this measure summarizes the major characteristics of systemic risk and provides a reliable interpretation of the past and current financial crises.

In this paper, we develop a framework for measuring, allocating and managing systemic risk. SystRisk, our measure of total systemic risk, captures the a priori cost to society for providing tail-risk insurance to the financial system. Our allocation principle distributes the total systemic risk among individual institutions according to their size-shifted marginal contributions. To describe economic shocks and systemic feedback effects, we propose a reduced form stochastic model that can be calibrated to historical data. We also discuss systemic risk limits, systemic risk charges and a cap and trade system for systemic risk.

Despite the growing attention in the last years on the topic of systemic risk, a widely accepted definition of systemic crisis is missing. We use a theoretical scheme to subjectively define a systemic event. This permits the analysis of a financial crisis as a standard binary classification problem, providing an intuitive and useful framework to compare systemic risk measures defined in very different fields. Then we focus the empirical analysis on the comparison of the performance of correlation-based systemic risk measures using the standard tools for the evaluation of binary classifiers as the receiver operating characteristic (ROC) curve and the area under the curve (AUC). We show that the binary classification framework is useful but unable to capture some significant differences among the measures under comparison. The experimental approach, developed on real financial data, is divided in an in-sample exercise, able to evaluate the descriptive power of the different systemic risk measures, and an out-of-sample application to evaluate the capacity of the measures in preventing and predicting systemic events. The forecasting ability of a measure can be fundamental for policy makers and investors respectively to stabilize market fluctuations and to reduce the losses.

This study investigates the ESG performance–systemic risk (SR) nexus among Indian companies. Using the beta coefficient from the Capital Asset Pricing Model (CAPM) and statistical analysis, it explores how ESG performance affects SR. The findings reveal that firms with higher ESG scores have lower SR sensitivity. Notably, there is a significant difference in risk sensitivity between high- and low-ESG-rated companies, with ESG effects being less pronounced in high-cap firms compared to low-cap firms. Conversely, large firms, older firms, and those with lower borrowing costs show a diminished effect of ESG ratings on their SR sensitivity. These results underscore the importance of firm-specific characteristics in determining the efficacy of ESG strategies in risk mitigation. This study reveals that ESG performance reduces SR, with market valuation affecting this relationship.

Weaknesses in investor control over their investments and in warehousing systemic risk in modern Financial Market Infrastructure (FMI) are the result of a combination of market failures and of structural flaws deeply ingrained in modern financial markets. Yet the utility of complex FMI comprising long custodial chains and large global Central Counterparties (CCPs) for the operation of modern markets is not seriously disputed. The change in the technology paradigm with the introduction of DLT systems for securities and derivatives FMI can increase investor control, the efficiency of risk management and, to some extent, augment the distribution of systemic risk. It can thus create a more diverse and resilient financial ecosystem. This cross-disciplinary paper identifies a multitude of reasons that favour a paradigm shift in FMI technology. It also sketches a comprehensive blockchain-based framework for the development of permission-based platforms for derivatives clearing and settlement and the handling of liquidity shortages within DLT systems. Arguably, the impact of technological change should lead to a reduction of industry rents for the benefit of end investors and of the end users of finance (entrepreneurs and businesses) enhancing market welfare. Therefore, the use of blockchain technology in FMI can transform the structure and future direction of the financial services industry as a whole.

The Covid-19 pandemic has brought about a heavy impact on the world economy, which arouses growing concerns about potential systemic risk, taking place in countries and regions. At this critical moment, it makes sense to interpret the systemic risk from the perspective of the financial crisis framework. By combing the latest research on systemic risks, we may arrive at some precautions relating to the current events. This literature review verifies the origin of systemic risk research. By comparing the retrieved and screened systemic literature with the relevant research on the financial crisis, more focus on the micro-foundations of systemic risk has been discovered. Besides, the measurement methods of systemic risks and the introduction of interdisciplinary methods have made the research in this field particularly active. This paper synthesizes the previous research conclusions to find the appropriate definition of systemic risk and combs the research literature of systemic risk from two lines: Firstly, conducting the division according to the sub-branch fields within the financial discipline and the relevant interdisciplinary research methods, which is helpful for scholars within and outside the discipline to have a more systematic understanding of the research in this field. Secondly predicting the research direction that can be expanded in this field.

The financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. Using results from cryptography, we develop computationally tractable protocols for sharing and aggregating such risk exposures that protect the privacy of all parties involved, without the need for trusted third parties. Financial institutions can share aggregate statistics such as Herfindahl indexes, variances, and correlations without revealing proprietary data. Potential applications include: privacy-preserving real-time indexes of bank capital and leverage ratios; monitoring delegated portfolio investments; financial audits; and public indexes of proprietary trading strategies.

This research belongs focuses on the effects of financial instability on the rest of the economy. The article observes the dynamic changes of the shock spillovers between systemic stress and the rest of the German economy. In that way, the net emitters and receivers of shocks are observed throughout time, as previous research found that systemic stress is not always the predictor of other economic activity. The analysis utilizes Diebold and Yilmaz (2009, 2012) spillover index approach within the vector autoregression model. One step further is taken as well, as the changes of dynamics are observed throughout the entire period. As the macroprudential and monetary policymakers have to track the interrelationships between these variables over time, the approach in the study is straightforward and easy to interpret. The timing and intensity of the specific measures are important in practice, and such an approach enables the policymakers to meet these criteria.

Brazil has a large share of hydropower in its electricity matrix. Since hydropower depends on water availability, it is particularly vulnerable to drought events, making the Brazilian electricity matrix vulnerable to climate change. Starting in 2005, Brazil opened the matrix to new renewable sources, including sugarcane-based electricity. Sugarcane is known for its resilience to short dry spells. Over the last decades, its production area moved from the coastal plains of the Atlantic Forest biome to the savannahs of the Cerrado biome, which is characterised by a five- to six month-long dry season. The sugarcane-based electricity system is highly dynamic and complex due to the interlinkages, dependencies, and cascading impacts between its agricultural and industrial subsystems. This paper applies the risk framework proposed by the IPCC to assess climate-change-driven drought risks to sugarcane electricity generation systems to identify their strengths and weaknesses, considering the system dynamics and linkages. Our methodology aims to understand and characterize drought in the agriculture as well as industrial subsystems and offers a specific understanding of the system by using indicators tailored to sugarcane-based electricity generation. Our results underline the relevance of actions at different levels of management. Initiatives, such as regional weather forecasts specifically for agriculture, and measures to increase industrial water-use efficiency were identified to be essential to reduce the drought risk. Actions from farmers and mill owners, supported and guided by the government at different levels, have the potential to increase the resilience of the system. For example, the implementation of small dams was identified by local actors as a promising intervention to adapt to the long dry seasons; however, they need to be implemented based on a proper technical assessment in order to locate these dams in suitable places. Moreover, the results show that creating and maintaining small water reservoirs to enable the adoption of deficit-controlled irrigation technology contribute to reducing the overall drought risk of the sugarcane-based electricity generation system.

This research deals with several approaches to constructing a composite indicator of cyclical systemic risk accumulation with a specific focus on Croatia. Such indicators are important in macroprudential policymaking, in order to track the position of the economy in the financial cycle. Moreover, the countercyclical capital buffer (CCyB) depends on the timely and accurate estimation of cyclical risk accumulation. The credit gap as defined in the BCBS (Basel Committee on Banking Supervision) and the ESRB (European Systemic Risk Board) guidance and recommendation has shown many flaws in practice. Thus, there is a need for improvement of the methodology. That is why this paper deals with the advantages and shortfalls of existing composite indicators of cyclical systemic risks and the possibilities of introducing them in Croatia. This research contributes to a critical oven'iew of the methodological approaches, with suggestions for their improvement, focusing particularly on the specifics of Croatian data.