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Academic literature on the topic 'Systemic risk measure'

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Published: 9 March 2023
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Journal articles on the topic "Systemic risk measure"

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Engle, Robert. "Systemic Risk 10 Years Later." Annual Review of Financial Economics 10, no. 1 (November 2018): 125–52. http://dx.doi.org/10.1146/annurev-financial-110217-023056.

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Ten years ago, the financial crisis spurred research focused on systemic risk. This article examines the history and application of the SRISK measure, which was developed at that time and is now widely used in monitoring systemic risk around the globe. The concept is explained and a variety of ways to measure SRISK are developed. In this article, new results are presented on the uncertainty associated with the SRISK measure and on how it compares with other related measures from both academics and regulators. By focusing on the mechanism by which undercapitalization of the financial sector initiates a financial crisis, new research examines how the probability of a financial crisis is affected by the level of SRISK and, consequently, how much SRISK a country can stand without having a high probability of crisis. The model used to evaluate this probability recognizes the externalities between financial institutions that make an undercapitalized firm or country more fragile if other firms and countries are also undercapitalized.
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Nekhili, Ramzi. "Systemic risk and interconnectedness in Gulf Cooperation Council banking systems." Banks and Bank Systems 15, no. 1 (March 25, 2020): 158–66. http://dx.doi.org/10.21511/bbs.15(1).2020.15.

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Nowadays, financial interconnectedness is the main driver of systemic risk. Thus, there is a constant need for tools to assess and manage systemic risk. This paper offers an alternative model framework to measure systemic risk and examine interconnectedness between direct exposures across banking systems in the emerging markets of the Gulf Cooperation Council (GCC). To ensure consistency and efficiency of systemic risk estimates and to capture its multifaceted nature, the methodology measures systemic risk using a combination of Filtered Historical Simulation and nonparametric regression and then examines the interconnectedness using a network analysis. The results reveal that shocks originating in the banking systems in Saudi Arabia may potentially cause a cascade of failures in the banking systems of most GCC countries. The banking system in Oman, however, is robust enough to withstand any ripple effect from adverse shocks affecting GCC’s major banking systems. Such results present some policy implications for regulators and supervisors and may benefit asset managers and investors in making portfolio allocation decisions.
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Ivanov, Katerina, James Schulte, Weidong Tian, and Kevin Tseng. "An Equilibrium-Based Measure of Systemic Risk." Journal of Risk and Financial Management 14, no. 9 (September 2, 2021): 414. http://dx.doi.org/10.3390/jrfm14090414.

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This paper develops and implements an equilibrium model of systemic risk. The model derives a systemic risk measure, loss beta, in characterizing all too-big-to-fail banks using a capital insurance equilibrium. By constructing each bank’s loss portfolio with a recent accounting approach, we perform a comprehensive empirical study of this loss beta measure and document all TBTF banks from 2002 to 2019. Our empirical findings suggest a significant number of too-big-to-fail banks in 2018–2019.
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Hadad, Elroi, Tomer Shushi, and Rami Yosef. "Measuring Systemic Governmental Reinsurance Risks of Extreme Risk Events." Risks 11, no. 3 (February 23, 2023): 50. http://dx.doi.org/10.3390/risks11030050.

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This study presents an easy-to-handle approach to measuring the severity of reinsurance that faces a system of dependent claims, where the reinsurance contracts are of excess loss or proportional loss. The proposed approach is a natural generalization of common reinsurance methodologies providing a conservative framework that deals with the fundamental question of how much money should a government hold to prepare for natural or human-made extreme risk events that the government will cover? Although the ruin theory is commonly used for extreme risk events, we suggest a new risk measure to deal with such events in a new framework based on multivariate risk measures. We analyze the results for the log-elliptical model of dependent claims, which are commonly used in risk analysis, and illustrate our novel risk measure using a Monte Carlo simulation.
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Kritzman, Mark, Yuanzhen Li, Sébastien Page, and Roberto Rigobon. "Principal Components as a Measure of Systemic Risk." Journal of Portfolio Management 37, no. 4 (July 31, 2011): 112–26. http://dx.doi.org/10.3905/jpm.2011.37.4.112.

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Parker, Edgar. "The Relationship between the US Economy’s Information Processing and Absorption Ratios: Systematic vs Systemic Risk." Entropy 20, no. 9 (September 2, 2018): 662. http://dx.doi.org/10.3390/e20090662.

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After the 2008 financial collapse, the now popular measure of implied systemic risk called the absorption ratio was introduced. This statistic measures how closely the economy’s markets are coupled. The more closely financial markets are coupled the more susceptible they are to systemic collapse. A new alternative measure of financial market health, the implied information processing ratio or entropic efficiency of the economy, was derived using concepts from information theory. This new entropic measure can also be useful in predicting economic downturns and measuring systematic risk. In the current work, the relationship between these two ratios and types of risks are explored. Potential methods of the joint use of these different measures to optimally reduce systemic and systematic risk are introduced.
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Pârţachi, Ion, and Eugeniu Gârlă. "Economic Insecurity as Systemic Risk." Annals of the Alexandru Ioan Cuza University - Economics 62, s1 (October 1, 2015): 29–36. http://dx.doi.org/10.1515/aicue-2015-0034.

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Abstract Difficulties related to the problem of evaluating the economic security / insecurity, including the threshold of economic security / insecurity, namely the impossibility of giving an analytical description of a criterion entirely made up of a set of indicators describing the degree of economic security / insecurity, makes more and more researchers, including the authors, to seek indirect ways of finding solutions, for example considering systemic risk., as a measure of evaluation. Thus, starting from a new approach, and given the specific components of systemic risk to financial stability: the banking sector, corporate sector, public sector, volume of credits, economic activity index the threshold vector of economic security / insecurity can be developed. The study shows that systemic risk can be used to measure the threshold of economic security /insecurity.
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Brownlees, Christian, and Robert F. Engle. "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk." Review of Financial Studies 30, no. 1 (August 6, 2016): 48–79. http://dx.doi.org/10.1093/rfs/hhw060.

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Mwamba, John Weirstrass Muteba, and Serge Angaman. "Systemic risk and real economic activity: A South African insurance stress index of systemic risk." Asian Academy of Management Journal of Accounting and Finance 18, no. 1 (July 29, 2022): 195–218. http://dx.doi.org/10.21315/aamjaf2022.18.1.8.

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This study investigates the link between systemic risk in the South African insurance sector real economic activity in South Africa. To this end, we use six systemic risk measures, the Conditional Value at Risk (CoVaR), the Marginal Conditional Value at Risk (ΔCoVaR), the Comovement and Interconnectedness of the South African insurance sector (Eigen), the Dynamic Mixture Copula Marginal Expected Shortfall (DMC-MES), the Average Conditional Volatility (Ave-vol), and the South African Volatility Index (SAVI). We first evaluate the significance of each measure by assessing its ability to forecast future economic downturns in South Africa. We find that only two systemic risk measures possess the ability to predict future economic downturns in South Africa. We then use principal component quantile regression analysis to aggregate these measures into a composite stress index of systemic risk for the South African insurance sector and assess the ability of the proposed index to predict future economic downturns in South Africa. Our results reveal that the proposed index is a good predictor of future economic downturns in South Africa. Thus, our results suggest that regulators and risk managers must develop an analysis of systemic risk in the insurance sector with particular attention to its effects on real economic activity. In addition, our index can potentially be used as an instrument to monitor and mitigate systemic risk in the insurance sector in order to ensure the stability of the financial system and the economy in South Africa.
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Brunnermeier, Markus K., and Patrick Cheridito. "Measuring and Allocating Systemic Risk." Risks 7, no. 2 (April 26, 2019): 46. http://dx.doi.org/10.3390/risks7020046.

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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.
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Dissertations / Theses on the topic "Systemic risk measure"

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Bjarnadottir, Frida. "Implementation of CoVaR, A Measure for Systemic Risk." Thesis, KTH, Matematik (Inst.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-102684.

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Abstract In recent years we have witnessed how distress can spread quickly through the financial system and threaten financial stability. Hence there has been increased focus on developing systemic risk indicators that can be used by central banks and others as a monitoring tool. For Sveriges Riksbank it is of great value to be able to quantify the risks that can threaten the Swedish financial system CoVaR is a systemic risk measure implemented here with that with that purpose. CoVaR, which stands for conditional Value at Risk, measures a financial institutions contribution to systemic risk and its contribution to the risk of other financial institutions. The conclusion is that CoVaR can together with other systemic risk indicators help get a better understanding of the risks threatening the stability of the Swedish financial system.
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ARDUCA, MARIA. "Measures of Risk: valuation and capital adequacy in illiquid markets, and systemic risk." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2021. http://hdl.handle.net/10281/307643.

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In questa tesi studiamo problemi di pricing e misure di rischio in mercati con frizioni, e misure di rischio sistemico. Il contesto è quello di mercati uniperiodali. Nel primo capitolo consideriamo un modello con costi di transazione convessi all'istante iniziale, vincoli convessi sui portafogli, e insieme di accettazione convesso che riflette le preferenze di un agente che agisce da compratore sul mercato. Definiamo l'insieme dei "prezzi consistenti" per ogni possbile payoff, dove con consistenti intendiamo sia rispetto al mercato, sia rispetto alle preferenze dell'agente. Mostriamo che l'estremo superiore di questo insieme coincide con il noto prezzo di superreplicazione, e in questo modo diamo un'interpretazione a quest ultimo al di là di quella classica nei problemi di hedging. Estendiamo il Teorema Fondamentale dell'Asset Pricing a un contesto dove gli "accordi accettabili" sostituiscono gli arbitraggi (cioè l'insieme di accettazione sostituisce il cono positivo), e i prezzi non sono lineari. Questo consente, sotto opportune ipotesi, di caratterizzare l'insieme dei prezzi consistenti di un payoff. Nel secondo capitolo, consideriamo un'economia astratta con costi di transazione sia all'istante iniziale sia a scadenza, e vincoli sui portafogli. Non assumiamo convessità a priori, anche se alcuni risultati valgono solo sotto opportune ipotesi di convessità. Un regolatore esterno fissa l'insieme di accettazione, cioè l'insieme delle possibili posizioni a scadenza di un agente che lui ritiene accettabili dal punto di vista della rischiosità. Definiamo requisiti di capitale che generalizzano le misure di rischio coerenti di Artzner, Delbaen, Eber e Heath (1999) in quanto rappresentano il minimo importo di capitale che l'agente deve investire sul mercato per reggiungere i requisiti di accettabilità. Il capitolo si propone di studiare le proprietà di queste misure di rischio generalizzate. In particolare, stabiliamo delle condizioni sui portafogli che assicurano che la misura di rischio sia semicontinua dal basso, e confrontiamo queste condizioni con le assunzioni del tipo "no accordi accettabili". Nel caso convesso e quasi convesso, forniamo anche una rappresentazione duale di questi funzionali. Nel terzo capitolo stabiliamo rappresentazioni duali di misure di rischio sistemico. Modelliamo le interazioni tra un numero finito di istituzioni attraverso una funzione di aggegazione, e assumiamo che un regolatore decida l'insieme di posizioni aggregate accettabili. Il rischio sistemico è misurato come il minimo quantitativo di capitale che deve essere inserito nel sistema (prima o dopo l'aggregazione) per far sì che la posizione aggregata sia accettabile. Lavoriamo dunque con misure di rischio sistemico sia del tipo "prima allocare, poi aggregare", sia "prima aggregare, poi allocare". In entrambi i casi forniamo un'analisi dettagliata del corrispondente insieme di accettazione sistemico e della sua funzione di supporto. Lo stesso approccio fornisce una semplice dimostrazione della rappresentazione duale di misure di rischio per posizioni univariate indotte da funzioni di utilità.
In this thesis, we study pricing and risk measures in markets with frictions, and systemic risk measures. All along the thesis, we focus on uniperiodal market models. In the first chapter, we consider a model with convex transaction costs at initial time, convex portfolio constraints and convex acceptance set that reflects the preferences of an agent who acts as a buyer in the market. We define the set of market consistent prices for every conceivable payoff, where consistent is meant with respect to the market and the preferences of the buyer. We show that the supremum of this set coincides with the well-known superreplication price, this giving to this functional an interpretation that goes beyond the classical hedging explanation. We develop an extension of the Fundamental Theorem of Asset Pricing in a context where arbitrages are replaced by acceptable deals (i.e. the positive cone is replaced by the acceptance set) and prices are not linear. This allows to characterize, under suitable assumptions, the set of market consistent prices of any payoff. In the second chapter, we consider an abstract economy with transaction costs both at initial time and at maturity, and portfolio constraints. We do not assume convexity a priori, tough some results hold only under convexity assumptions. An external regulator fixes the acceptance set, that is the set of possible agent's capital positions that he deems acceptable from a risk perspective. We define capital adequacy rules that generalize the coherent risk measures of Artzner, Delbaen, Eber and Heath (1999) in that they represent the minimum amount that the agent has to invest in the market in order to reach the acceptability requirements. The chapter aims to study the properties of these generalized risk measures. In particular, we establish conditions on the portfolios ensuring that they are lower semicontinuous, and we compare these conditions with no-acceptable deal type assumptions. In convex and quasi convex case, we also provide a dual representation of the functionals of interest. In the third chapter we establish dual representations of systemic risk measures. We model interactions among a finite number of institutions through an aggregation function, and we assume that a regulator fixes a set of acceptable aggregated positions. Systemic risk is estimated as the minimum amount of capital that has to be injected in the system (before or after aggregation) in order to make the aggregated position acceptable. Hence, we deal with systemic risk measures of both ``first allocate, then aggregate'' and ``first aggregate, then allocate'' type. In both cases, we provide a detailed analysis of the corresponding systemic acceptance sets and their support functions. Our general results cover some specific cases already studied in literature. The same approach delivers a simple and self-contained proof of the dual representation of utility-based risk measures for univariate positions.
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DOLDI, ALESSANDRO. "EQUILIBRIUM, SYSTEMIC RISK MEASURES AND OPTIMAL TRANSPORT: A CONVEX DUALITY APPROACH." Doctoral thesis, Università degli Studi di Milano, 2021. http://hdl.handle.net/2434/812668.

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This Thesis focuses on two main topics. Firstly, we introduce and analyze the novel concept of Systemic Optimal Risk Transfer Equilibrium (SORTE), and we progressively generalize it (i) to a multivariate setup and (ii) to a dynamic (conditional) setting. Additionally we investigate its relation to a recently introduced concept of Systemic Risk Measures (SRM). We present Conditional Systemic Risk Measures and study their properties, dual representation and possible interpretations of the associated allocations as equilibria in the sense of SORTE. On a parallel line of work, we develop a duality for the Entropy Martingale Optimal Transport problem and provide applications to problems of nonlinear pricing-hedging. The mathematical techniques we exploit are mainly borrowed from functional and convex analysis, as well as probability theory. More specifically, apart from a wide range of classical results from functional analysis, we extensively rely on Fenchel-Moreau-Rockafellar type conjugacy results, Minimax Theorems, theory of Orlicz spaces, compactness results in the spirit of Komlós Theorem. At the same time, mathematical results concerning utility maximization theory (existence of optima for primal and dual problems, just to mention an example) and optimal transport theory are widely exploited. The notion of SORTE is inspired by the Bühlmann's classical Equilibrium Risk Exchange (H. Bühlmann, "The general economic premium principle", Astin Bulletin, 1984). In both the Bühlmann and the SORTE definition, each agent is behaving rationally by maximizing his/her expected utility given a budget constraint. The two approaches differ by the budget constraints. In Bühlmann's definition the vector that assigns the budget constraint is given a priori. In the SORTE approach, on the contrary, the budget constraint is endogenously determined by solving a systemic utility maximization problem. SORTE gives priority to the systemic aspects of the problem, in order to first optimize the overall systemic performance, rather than to individual rationality. Single agents' preferences are, however, taken into account by the presence of individual optimization problems. The two aspects are simultaneously considered via an optimization problem for a value function given by summation of single agents' utilities. After providing a financial and theoretical justification for this new idea, in this research sufficient general assumptions that guarantee existence, uniqueness, and Pareto optimality of such a SORTE are presented. Once laid the theoretical foundation for the newly introduced SORTE, this Thesis proceeds in extending such a notion to the case when the value function to be optimized has two components, one being the sum of the single agents' utility functions, as in the aforementioned case of SORTE, the other consisting of a truly systemic component. This marks the progress from SORTE to Multivariate Systemic Optimal Risk Transfer Equilibrium (mSORTE). Technically, the extension of SORTE to the new setup requires developing a theory for multivariate utility functions and selecting at the same time a suitable framework for the duality theory. Conceptually, this more general setting allows us to introduce and study a Nash Equilibrium property of the optimizers. Existence, uniqueness, Pareto optimality and the Nash Equilibrium property of the newly defined mSORTE are proved in this Thesis. Additionally, it is shown how mSORTE is in fact a proper generalization, and covers both from the conceptual and the mathematical point of view the notion of SORTE. Proceeding further in the analysis, the relations between the concepts of mSORTE and SRM are investigated in this work. The notion of SRM we start from was introduced in the papers "A unified approach to systemic risk measures via acceptance sets" (Math. Finance, 2019) and "On fairness of systemic risk measures" (Finance Stoch., 2020) by F. Biagini, J.-P. Fouque, M. Frittelli, and T. Meyer-Brandis. SRM of Biagini et al. are generalized in this Thesis to a dynamic (namely conditional) setting, adding also a systemic, multivariate term in the threshold functions that Biagini et al. consider in their papers. The dynamic version of mSORTE is introduced, and it is proved that the optimal allocations of dynamic SRM, together with the corresponding fair pricing measures, yield a dynamic mSORTE. This in particular remains true if conditioning is taken with respect to the trivial sigma algebra, which is tantamount to working in the non-dynamic setting covered in Biagini et al. for SRM, and in the previous parts of our work for mSORTE. The case of exponential utility functions is thoroughly examined, and the explicit formulas we obtain for this specific choice of threshold functions allow for providing a time consistency property for allocations, dynamic SRM and dynamic mSORTE. The last part of this Thesis is devoted to a conceptually separate topic. Nonetheless, a clear mathematical link between the previous work and the one we are to describe is established by the use of common techniques. A duality between a novel Entropy Martingale Optimal Transport (EMOT) problem (D) and an associated optimization problem (P) is developed. In (D) the approach taken in Liero et al. (M. Liero, A. Mielke, and G. Savaré, "Optimal entropy-transport problems and a new Hellinger-Kantorovich distance between positive measures", Inventiones mathematicae, 2018) serves as a basis for adding the constraint, typical of Martingale Optimal Transport (MOT) theory, that the infimum of the cost functional is taken over martingale probability measures, instead of finite positive measures, as in Liero et al.. The Problem (D) differs from the corresponding problem in Liero et al. not only by the martingale constraint, but also because we admit less restrictive penalization terms D, which may not have a divergence formulation. In Problem (P) the objective functional, associated via Fenchel conjugacy to the terms D, is not any more linear, as in Optimal Transport or in MOT. This leads to a novel optimization problem which also has a clear financial interpretation as a non linear subhedging value. Our results in this Thesis establish a novel nonlinear robust pricing-hedging duality in financial mathematics, which covers a wide range of known robust results in its generality. The research for this Thesis resulted in the production of the following works: F. Biagini, A. Doldi, J.-P. Fouque, M. Frittelli, and T. Meyer-Brandis, "Systemic optimal risk transfer equilibrium", Mathematics and Financial Economics, 2021; A. Doldi and M. Frittelli, "Multivariate Systemic Optimal Risk Transfer Equilibrium", Preprint: arXiv:1912.12226, 2019; A. Doldi and M. Frittelli, "Conditional Systemic Risk Measures", Preprint: arXiv:2010.11515, 2020; A. Doldi and M. Frittelli, "Entropy Martingale Optimal Transport and Nonlinear Pricing-Hedging Duality", Preprint: arXiv:2005.12572, 2020.
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Scquizzato, Gianmarco <1989&gt. "Systemic Risk Measures." Master's Degree Thesis, Università Ca' Foscari Venezia, 2017. http://hdl.handle.net/10579/9570.

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Considering the effects generated by the recent financial crisis, and, given the ease with which a situation of financial distress caused impact beyond and outwith financial system, the concept of systemic risk has gained even more attention in the worldwide community. Despite many studies, there is no recognised single definition of systemic risk and as demonstrated by the existence of numerose metrics in the relative literature, finding effective measures to assess systemic risk is one of the toughest challenges for many individuals and institutions. The aimo of this work is to provide a measure of systemic risk through the use of three econometric methods: principal component analysis, Granger causality test and nonlinear causality test of Diks and Panchenko.
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Mosmann, Gabriela. "Axiomatic systemic risk measures forecasting." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/178875.

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Neste trabalho, aprofundamos o estudo sobre risco sistêmico via funções de agregação. Consideramos três carteiras diferentes como proxy para um sistema econômico, estas carteiras são consistidas por duas funções de agregação, baseadas em todos as ações do E.U.A, e um índice de mercado. As medidas de risco aplicadas são Value at Risk (VaR), Expected Shortfall (ES) and Expectile Value at Risk (EVaR), elas são previstas através do modelo GARCH clássico unido com nove funções de distribuição de probabilidade diferentes e mais por um método não paramétrico. As previsões são avaliadas por funções de perda e backtests de violação. Os resultados indicam que nossa abordagem pode gerar uma função de agregação adequada para processar o risco de um sistema previamente selecionado.
In this work, we deepen the study of systemic risk measurement via aggregation functions. We consider three different portfolios as a proxy for an economic system, these portfolios are consisted in two aggregation functions, based on all U.S. stocks and a market index. The risk measures applied are Value at Risk (VaR), Expected Shortfall (ES) and Expectile Value at Risk (EVaR), they are forecasted via the classical GARCH model along with nine distribution probability functions and also by a nonparametric approach. The forecasts are evaluated by loss functions and violation backtests. Results indicate that our approach can generate an adequate aggregation function to process the risk of a system previously selected.
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FARINA, Gianluca. "Systemic risk measures and contagion models." Doctoral thesis, Università degli studi di Bergamo, 2014. http://hdl.handle.net/10446/30380.

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The main theme of the thesis is systemic risk measurement. This extremely young field of research has gained a lot of attention in recent times from academics and practioners alike because of global financial crises. The main contributions of the thesis can be grouped in four broad items. Firstly, we propose a novel categorization of the risk measures advanced in recent years based on the modeling assumptions they rely upon. We identified four categories: measures based on portfolio theory, econometric indicators, network analysis and measures based on multivariate default distribution. The second set of contributions regards the CIMDO framework, a methodology heavily used in systemic risk studies. We proved a new theoretical independence result that significantly extended previous ones. We also performed a comprehensive stability study where every input of the methodology was considered and whose conclusions should serve as guidance for future CIMDO users. The third contribution is a new contagion model that is both tractable and flexible enough to be used with heterogeneous portfolios. We provided several theoretical results with respect to both marginal and joint default distribution. We also detailed a recursive algorithm to calculate the portfolio loss distribution in an efficient way. An application to the problem of pricing and hedging CDO products is hence shown. Lastly, we introduced a new systemic risk measure in the context of contagion models called contagion loss ratio (CLR). It is based on attributing losses to either idiosyncratic or infection-driven events and represents the percentage of the total portfolio losses due to contagion. We showed how to calculate it in a variety of models and presented an application to the problem of banking stability.
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Oudghir, Mouad <1989&gt. "Analysis of systemic risk through entropy measures." Master's Degree Thesis, Università Ca' Foscari Venezia, 2015. http://hdl.handle.net/10579/6942.

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Cao, Zhili. "Systemic risk measures, banking supervision and financial stability." Thesis, Toulouse 1, 2013. http://www.theses.fr/2013TOU10014/document.

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Cette thèse analyse les sources d’inefficacité qui peuvent générer un risque systémique au sein du système financier et étudie les différentes mesures associées. Le premier article présente une revue de la littérature sur le risque systémique et la politique macroprudentielle : 1) les effets négatifs de la procyclicité pour le système financier dans son ensemble ainsi que pour l’économie réelle; 2) le risque de contagion entre institutions financières. Le second article de la thèse propose une nouvelle mesure du risque systémique visant à capturer efficacement l’importance systémique de chaque institution financière au sein d’un système donné. Le troisième article de la thèse analyse la structure de la dette des banques. Les banques choisissent la maturité de leur dette à court et/ou long terme. Les externalités négatives générées par l’excès de financement de court terme n’apparaissent que lorsque la probabilité d’un choc macroéconomique est suffisamment large
This thesis analysis the inefficiencies which may trigger the systemic risks in the financial system and studies the related measures to quantify such risks. The first article surveys the systemic risk in the financial system and the related macro-prudential policy: 1) the pro-cyclicality effect is harmful to the whole financial system as well as to the real economy; 2) the contagion risk among financial institutions. The second article of thesis proposes a new systemic risk measure to efficiently capture the systemic importance of each financial institution within a given system. The term systemic risk refers to the contagion risk to which each bank contributes to the financial system. The third article of thesis analysis the debt structure in the banking sector. Banks choose their debt maturity structure by weighting short term against long term debt. The externalities caused by over borrowing in short term debt exist only when the probability of macro shock is large
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Pellegrinet, Sarah <1988&gt. "Systemic Risk Measures and Connectedness: a network approach." Master's Degree Thesis, Università Ca' Foscari Venezia, 2015. http://hdl.handle.net/10579/6009.

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The main objective of the thesis is the construction of a systemic risk indicator based on the dispersion of the risk measures of the individual institutions of the system. The thesis presents a brief introduction to the literature on systemic risk measures, focusing on the Marginal Expected Shortfall (MES) and the delta CoVaR, which consider not only the yield of an individual firm, but also the effect of its performance on the whole system, and on the connectedness measure between the financial institutions, which measures the relationship between the institutions. We apply the systemic risk and the connectedness measures to the daily returns of the European financial institutions from the 1St January 1985 to 12th May 2014. Finally, to aggregate the risk measures and build a systemic risk indicator, we estimate the measure entropy and find that the indicator has good forecasting abilities for the financial crisis.
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Monti, Alice <1986&gt. "Essays in the Econometric Analysis of Systemic Risk Measures." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amsdottorato.unibo.it/7782/7/monti_alice_tesi.pdf.

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This thesis aims at the study of systemic risk measurement, which became crucial after the 2007 − 2009 financial crisis. The objective of the thesis is twofold: (i) we address the issue of assessing the accuracy of systemic risk measures, (ii) we investigate the role of the long-range dependence in systemic risk forecasting, under both methodological and empirical perspectives. From the methodological point of view, we propose two appropriate loss functions, the Tail Tick Loss function and the Tail Mean Square Error, specifically designed to evaluate the CoVaR and MES accuracy, respectively. Moreover, we introduce a comprehensive model called Asymmetric-Component-GARCH (ACGARCH), which is able to capture both the leverage effect and long-range dependence. An empirical analysis of different bivariate volatility models to the daily returns of 91 US financial institutions in the period 2000 − 2012 confirms the need of employing appropriate loss functions to evaluate systemic risk accuracy and to discriminate among different competing models. Moreover, empirical results encourage the usage of the ACGARCH model in the systemic risk framework.
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Books on the topic "Systemic risk measure"

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Duffey, Romney B. The quantification of systemic risk and stability: New methods and measures. Cambridge, MA: National Bureau of Economic Research, 2011.

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Thomas, Norman. Risk analysis and security countermeasure selection. Boca Raton, FL: CRC Press, 2010.

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Thomas, Norman. Risk analysis and security countermeasure selection. Boca Raton, FL: CRC Press, 2010.

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Norman, Thomas. Risk analysis and security countermeasure selection. Boca Raton, FL: CRC Press, 2010.

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Norman, Thomas L. Risk analysis and security countermeasure selection. Boca Raton: CRC Press, 2010.

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Canadian Institute for International Peace and Security., ed. The risk of accidental nuclear war: A conference report. Ottawa: Canadian Institute for International Peace and Security, 1986.

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Practical risk management for the CIO. Boca Raton, FL: Auerbach Publications, 2011.

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service), SpringerLink (Online, ed. Linear-Quadratic Controls in Risk-Averse Decision Making: Performance-Measure Statistics and Control Decision Optimization. New York, NY: Springer New York, 2013.

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Ou, Xinming. Quantitative security risk assessment of enterprise networks. New York, NY: Springer, 2012.

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Company, R. S. Means, ed. Building security: Strategies & costs : risk assessment, security planning, cost data for construction & security systems. Kingston, MA: Reed Construction Data, 2003.

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Book chapters on the topic "Systemic risk measure"

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Karaś, Marta, and Witold Szczepaniak. "Towards a Generalized Measure of Systemic Risk: Systemic Turbulence Measure." In Contemporary Trends and Challenges in Finance, 11–23. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15581-0_2.

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Challet, Damien, and David Morton de Lachapelle. "A Robust Measure of Investor Contrarian Behaviour." In Econophysics of Systemic Risk and Network Dynamics, 105–18. Milano: Springer Milan, 2013. http://dx.doi.org/10.1007/978-88-470-2553-0_7.

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Lunkov, Alexey, Sergei Sidorov, Alexey Faizliev, Alexander Inochkin, and Elena Korotkovskaya. "Quantifying the Impact of External Shocks on Systemic Risks for Russian Companies Using Risk Measure $$\varDelta \text {CoVaR}$$." In Transactions on Engineering Technologies, 31–42. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0746-1_3.

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Radev, Deyan. "Systemic Fragility Measures." In Measuring Systemic Risk, 23–45. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94281-6_4.

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Basilio, Jorge, and Amilcar Oliveira. "A Critical Discussion on Systemic Risk Measures." In Mindful Topics on Risk Analysis and Design of Experiments, 18–36. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06685-6_2.

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Moix, Pierre-Yves. "Risk and Risk Measures." In Lecture Notes in Economics and Mathematical Systems, 21–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56481-9_2.

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Nyre, Åsmund Ahlmann, and Martin Gilje Jaatun. "Seeking Risks: Towards a Quantitative Risk Perception Measure." In Availability, Reliability, and Security in Information Systems and HCI, 256–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40511-2_18.

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Balbás, Alejandro, Beatriz Balbás, and Raquel Balbás. "Minimizing Vector Risk Measures." In Lecture Notes in Economics and Mathematical Systems, 55–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-10354-4_4.

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Xu, Chunhui, and Takayuki Shiina. "Market Risk Measures in Financial Investments." In Translational Systems Sciences, 13–34. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0317-3_2.

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Xu, Chunhui, and Takayuki Shiina. "Market Risk Measures for Flexible Investments." In Translational Systems Sciences, 59–78. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0317-3_4.

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Conference papers on the topic "Systemic risk measure"

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Dai, Dehao, and Desheng Wu. "An Innovative Decision Support Approach to Measure the Propagation of Systemic Risk Using Granger Causality Networks." In 2022 International Conference on Computers, Information Processing and Advanced Education (CIPAE). IEEE, 2022. http://dx.doi.org/10.1109/cipae55637.2022.00094.

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Feng, Yichen, Ming Min, and Jean-Pierre Fouque. "Deep Learning for Systemic Risk Measures." In ICAIF '22: 3rd ACM International Conference on AI in Finance. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3533271.3561669.

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Basilio, Jorge, Amilcar Oliveira, and Rahim Mahmoudvand. "An overview of the systemic risk measures." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2019. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0027053.

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Mosoiu, Ovidiu, Catalin Cioaca, and Ion Balaceanu. "USING THE CAPITAL ASSET PRICING MODEL IN INFORMATION SECURITY INVESTMENTS." In eLSE 2018. Carol I National Defence University Publishing House, 2018. http://dx.doi.org/10.12753/2066-026x-18-220.

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Interest in real option theory has intensified over the last decade due to the high uncertainty faced by some private and public organizations when deciding to make a strategic investment (competitive environment) or when faced with an external requirement of the organizational environment (ensuring security standards). Traditional methods of investment analysis define the existence of investment opportunity by net present value (NPV), ignoring the possibility that an investment will start from a certain moment in the future. In this way, it is not possible to capture the phenomenon in dynamics, which leads to limiting the possibility of solving the existing uncertainty over the time regarding the optimal use of resources. The need to optimize managerial strategies and give some flexibility to decision-makers in relation to the changes in the organization's external environment has triggered the real options analysis (ROA). By using ROA, a win-win situation is created in which the available policy options mitigate uncertainty fluctuations of updated net worth (based on new information available) and, at the same time, by applying the best strategy, maximize earnings. Information security systems are designed on a layered architecture and the decision to improve performance on each layer is the responsibility of strategic management. Being a modular system, it is recommended to build the architecture by stages, depending on the value of the assets. Also, the relatively long duration and costs of implementation, limited resources, irreversible character, and project risks determine the value and evaluation of the investment, involving its representation as a combined option associated with a succession of decisions. The proposed model is inspired from the theory of financial and real options, but also from the fuzzy logic. This approach seeks to anchor specific mechanisms for the study of asymmetric risk events in the security market (perfect market assumptions are of course limiting but provide a quick overview, which is essential for the proposed application). Using the capital asset pricing model (CAPM), the return on investments in the security of IT & C systems, by reference to the investment risk as the estimated value, is defined. Investors can take risks that can be broken down into two components: systematic risks and non-systemic risks. Systematic risk refers to the variability of income caused by external factors (macroeconomic conditions), being a measure of the relative market volatility of relative incomes. Unsystematic risk refers to income variability caused by unpredictable factors (mismanagement decisions, abrupt technologies overtaken). The depreciation of security investments is inherent and leads to the dilemma of small and frequent investments or major and rare investments. On this issue, the proposed model can provide solutions to decision-makers. Uncertainty, irreversibility, growth potential and competition are factors that influence the behavior and investment decision. We consider that by using the capital asset pricing model in the security investments associated with eLerning training systems, we can increase the precision of optimal investment in terms of risk and opportunity balancing.
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Sevcik, A., and O. T. Gudmestad. "A systematic approach to risk reduction measures in the Norwegian offshore oil and gas industry." In RISK ANALYSIS 2014. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/risk140251.

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Drummond, Barbara M., and Raphael C. S. Machado. "Cyber Security Risk Management for Ports - A Systematic Literature Review." In 2021 International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea). IEEE, 2021. http://dx.doi.org/10.1109/metrosea52177.2021.9611569.

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Lachey, Jeffrey, Keith Vanderlee, Robert Jewell, and Tony Alfano. "Optimizing Preventative and Mitigative Measure Selection." In 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64638.

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As risk assessment methodologies, tools, and processes continue to evolve in the industry, utilizing risk outputs to not only identify high risk locations, but to also understand the driver(s) behind the elevated risks for those locations is paramount. The ideal scenario for reducing pipeline risk is utilizing a risk-driven mitigation plan as this ensures the optimal use of company dollars, but also inherently means that a company has a firm understanding of their data and pipeline system. When the company understands their data and the implications for its inaccuracies, whether it be improper data alignment or incorrect application of data, they can effectively employ a campaign for preventative and mitigative measures (P&MM). However, if suspect data is used during a risk assessment, P&MM cannot accurately target risk drivers and high risk locations, making it challenging for the company to maximize their resources. For well over a year, an on-going partnership between AGL Resources Inc. (AGL) and Det Norske Veritas (U.S.A.), Inc. (DNV GL) has ensued to tailor a GIS-based risk management software solution for AGL. Through this collaboration among Integrity Management, Risk Management, IT, GIS, and Operations & Maintenance subject matter experts (SMEs) on both sides, one central hub of cross-functional pipeline knowledge was created. As a result, countless opportunities were exploited to identify supplementary data sources to employ new data manipulation techniques and processes, providing AGL with the foundation for such a risk-based Preventative & Mitigative Measure program. With the foundation laid and the proper risk elements present, AGL can now execute optimized risk-informed responses to identified high risk locations, pipeline segments, or pipeline systems. These optimized responses require an understanding of the types of P&MM available to reduce the threats and consequences, the costs involved for each P&MM implemented, and the utilization of a tool to allow various ‘what-if’ risk analyses to be conducted. Adopting and integrating this process as part of AGL’s risk management program allows them to capitalize on the maintenance dollars they spend while also reducing the potential hazards to the surrounding people, places and environment.
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Liang, Jiaqi, Linjing Li, Daniel Zeng, and Yunwei Zhao. "Correlation-based Dynamics and Systemic Risk Measures in the Cryptocurrency Market." In 2018 IEEE International Conference on Intelligence and Security Informatics (ISI). IEEE, 2018. http://dx.doi.org/10.1109/isi.2018.8587395.

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Tóth, Marián, Ivan Holúbek, and Roman Serenčéš. "Applying Markowitz portfolio theory to measure the systematic risk in agriculture." In International Scientific Days 2016 :: The Agri-Food Value Chain: Challenges for Natural Resources Management and Society. Slovak University of Agriculture in Nitra, Slovakia, 2016. http://dx.doi.org/10.15414/isd2016.s12.10.

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Nass, David, Boris Belousov, and Jan Peters. "Entropic Risk Measure in Policy Search." In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019. http://dx.doi.org/10.1109/iros40897.2019.8967699.

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Reports on the topic "Systemic risk measure"

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Arias, Mauricio, Juan Carlos Mendoza-Gutiérrez, and David Perez-Reyna. Applying CoV aR to measure systemic market risk : the colombian case. Bogotá, Colombia: Banco de la República, March 2010. http://dx.doi.org/10.32468/tef.47.

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Garvey, Paul R., and Chien-Ching Cho. An Index to Measure a System's Performance Risk. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada423527.

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Billio, Monica, Mila Getmansky, Andrew Lo, and Loriana Pelizzon. Econometric Measures of Systemic Risk in the Finance and Insurance Sectors. Cambridge, MA: National Bureau of Economic Research, July 2010. http://dx.doi.org/10.3386/w16223.

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Duffey, Romney. The Quantification of Systemic Risk and Stability: New Methods and Measures. Cambridge, MA: National Bureau of Economic Research, May 2011. http://dx.doi.org/10.3386/w17022.

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TARAKANOVA, V., A. ROMANENKO, and O. PRANTSUZ. MEASURES TO PREVENT POSSIBLE EMERGENCIES AT THE ENTERPRISE. Science and Innovation Center Publishing House, 2022. http://dx.doi.org/10.12731/2070-7568-2022-11-1-4-32-43.

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In the article, the authors consider emergency situations at the enterprise of the Joint-Stock Company “Scientific and Production Complex “Alternative Energy” (JSC “NPK “ALTEN”), consider measures to prevent emergency situations at the enterprise, readiness to eliminate them consequences. Compliance with these measures will improve the efficiency of the company’s industrial safety management system. The relevance of the research is aimed at an effective system of organization and management of industrial safety, which allows you to manage risks and helps to ensure favorable working conditions for the health of employees at the enterprise. A mobile emergency and emergency response system was created. The system can also be used for accounting and accident investigation, based on the use of corporate communication devices and applications for mobile operating systems.
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Jalil, Yorschua, and Ruvistay Gutierrez. Myokines secretion and their role in critically ill patients. A scoping review protocol. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, September 2021. http://dx.doi.org/10.37766/inplasy2021.9.0048.

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Review question / Objective: 1-How and by which means stimulated muscle from critically ill patients can liberate myokines?, 2-Which are the main characteristics of the critically ill population studied and if some of these influenced myokine´s secretion?, 5-Can myokines exert local or distant effects in critically ill patients?, 5-Which are the potential effects of myokines in critically ill patients? Eligibility criteria: Participants and context: We will include primary studies (randomized or non-randomized trials, observational studies, case series or case report) that consider hospitalized critically ill adult patients (18 years or older) in risk for developing some degree of neuromuscular disorders such as ICU-AW, diaphragmatic dysfunction, or muscle weakness, therefore the specific setting will be critical care. Concept: This review will be focused on studies regarding the secretion or measure of myokines or similar (exerkines, cytokines or interleukin) by any mean of muscle activation or muscle contraction such as physical activity, exercise or NMES, among others. The latter strategies must be understood as any mean by which muscle, and there for myocytes, are stimulated as result of muscle contraction, regardless of the frequency, intensity, time of application and muscle to be stimulated (upper limb, lower limb, thoracic or abdominal muscles). We also will consider myokine´s effects, local or systemic, over different tissues in terms of their structure or function, such as myocytes function, skeletal muscle mass and strength, degree of muscle wasting or myopathies, among others.
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Daudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe, and Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, December 2021. http://dx.doi.org/10.53328/uxuo4751.

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The report provides a review of how risk is conceived of, modelled, and mapped in studies of infectious water, sanitation, and hygiene (WASH) related diseases. It focuses on spatial epidemiology of cholera, malaria and dengue to offer recommendations for the field of WASH-related disease risk mapping. The report notes a lack of consensus on the definition of disease risk in the literature, which limits the interpretability of the resulting analyses and could affect the quality of the design and direction of public health interventions. In addition, existing risk frameworks that consider disease incidence separately from community vulnerability have conceptual overlap in their components and conflate the probability and severity of disease risk into a single component. The report identifies four methods used to develop risk maps, i) observational, ii) index-based, iii) associative modelling and iv) mechanistic modelling. Observational methods are limited by a lack of historical data sets and their assumption that historical outcomes are representative of current and future risks. The more general index-based methods offer a highly flexible approach based on observed and modelled risks and can be used for partially qualitative or difficult-to-measure indicators, such as socioeconomic vulnerability. For multidimensional risk measures, indices representing different dimensions can be aggregated to form a composite index or be considered jointly without aggregation. The latter approach can distinguish between different types of disease risk such as outbreaks of high frequency/low intensity and low frequency/high intensity. Associative models, including machine learning and artificial intelligence (AI), are commonly used to measure current risk, future risk (short-term for early warning systems) or risk in areas with low data availability, but concerns about bias, privacy, trust, and accountability in algorithms can limit their application. In addition, they typically do not account for gender and demographic variables that allow risk analyses for different vulnerable groups. As an alternative, mechanistic models can be used for similar purposes as well as to create spatial measures of disease transmission efficiency or to model risk outcomes from hypothetical scenarios. Mechanistic models, however, are limited by their inability to capture locally specific transmission dynamics. The report recommends that future WASH-related disease risk mapping research: - Conceptualise risk as a function of the probability and severity of a disease risk event. Probability and severity can be disaggregated into sub-components. For outbreak-prone diseases, probability can be represented by a likelihood component while severity can be disaggregated into transmission and sensitivity sub-components, where sensitivity represents factors affecting health and socioeconomic outcomes of infection. -Employ jointly considered unaggregated indices to map multidimensional risk. Individual indices representing multiple dimensions of risk should be developed using a range of methods to take advantage of their relative strengths. -Develop and apply collaborative approaches with public health officials, development organizations and relevant stakeholders to identify appropriate interventions and priority levels for different types of risk, while ensuring the needs and values of users are met in an ethical and socially responsible manner. -Enhance identification of vulnerable populations by further disaggregating risk estimates and accounting for demographic and behavioural variables and using novel data sources such as big data and citizen science. This review is the first to focus solely on WASH-related disease risk mapping and modelling. The recommendations can be used as a guide for developing spatial epidemiology models in tandem with public health officials and to help detect and develop tailored responses to WASH-related disease outbreaks that meet the needs of vulnerable populations. The report’s main target audience is modellers, public health authorities and partners responsible for co-designing and implementing multi-sectoral health interventions, with a particular emphasis on facilitating the integration of health and WASH services delivery contributing to Sustainable Development Goals (SDG) 3 (good health and well-being) and 6 (clean water and sanitation).
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Hilbrecht, Margo, Sally M. Gainsbury, Nassim Tabri, Michael J. A. Wohl, Silas Xuereb, Jeffrey L. Derevensky, Simone N. Rodda, McKnight Sheila, Voll Jess, and Gottvald Brittany. Prevention and education evidence review: Gambling-related harm. Edited by Margo Hilbrecht. Greo, September 2021. http://dx.doi.org/10.33684/2021.006.

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This report supports an evidence-based approach to the prevention and education objective of the National Strategy to Reduce Harm from Gambling. Applying a public health policy lens, it considers three levels of measures: universal (for the benefit of the whole population), selective (for the benefit of at-risk groups), and indicated (for the benefit of at-risk individuals). Six measures are reviewed by drawing upon a range of evidence in the academic and grey literature. The universal level measures are “Regulatory restriction on how gambling is provided” and “Population-based safer gambling/responsible gambling efforts.” Selective measures focus on age cohorts in a chapter entitled, “Targeted safer gambling campaigns for children, youth, and older adults.” The indicated measures are “Brief internet delivered interventions for gambling,” “Systems and tools that produced actual (‘hard’) barriers and limit access to funds,” and “Self-exclusion.” Since the quantity and quality of the evidence base varied by measure, appropriate review methods were selected to assess publications using a systematic, scoping, or narrative approach. Some measures offered consistent findings regarding the effectiveness of interventions and initiatives, while others were less clear. Unintended consequences were noted since it is important to be aware of unanticipated, negative consequences resulting from prevention and education activities. After reviewing the evidence, authors identified knowledge gaps that require further research, and provided guidance for how the findings could be used to enhance the prevention and education objective. The research evidence is supplemented by consultations with third sector charity representatives who design and implement gambling harm prevention and education programmes. Their insights and experiences enhance, support, or challenge the academic evidence base, and are shared in a separate chapter. Overall, research evidence is limited for many of the measures. Quality assessments suggest that improvements are needed to support policy decisions more fully. Still, opportunities exist to advance evidence-based policy for an effective gambling harm prevention and education plan.
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Mwebe, Robert, Chester Kalinda, Ekwaro A. Obuku, Eve Namisango, Alison A. Kinengyere, Moses Ocan, Ann Nanteza, Savino Biryomumaisho, and Lawrence Mugisha. Epidemiology and effectiveness of interventions for Foot and Mouth Disease in Africa: A protocol for systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2022. http://dx.doi.org/10.37766/inplasy2022.11.0039.

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Review question / Objective: What is the epidemiology and effectiveness of control measures for foot and mouth disease in African countries?’ PICOS: Description of elements Population/ problem/Setting: Artiodactyla (cloven ungulates), domestic (cattle, sheep, goats, and pigs), camels and wildlife (buffaloes, deer, antelope, wild pigs, elephant, giraffe, and camelids) affected by Foot and Mouth Disease (FMD) or Hoof and Mouth Disease (HMD) caused by the Foot and Mouth Disease Virus (FMDV) in Africa. Intervention: Prevention measures: vaccination, ‘biosafety and biosecurity’, sensitization of the public. Control measures: quarantine, movement control, closure of markets and stock routes, mouth swabbing of animals with infected materials (old technique that is no long applicable), culling, mass slaughter, stamping out and any other interventions or control measures generally accepted by the ‘community of practice’ of animal health practitioners. Comparator: areas that did not have any control activities for FMD, in head-to-head comparisons in the same study. Outcome: epidemiological outcomes: incidence, prevalence, patterns or trends, clinical symptoms, and risk factors. Effectiveness outcomes: success, and usefulness of the interventions measured as averted deaths, illness and infections, and costs associated with the interventions (cost–effectiveness). Study design: epidemiological designs include cohort design for incidence, cross sectional for prevalence and case-control for clinical symptoms and risk factors. Interventional designs include randomized controlled trials, cluster randomized trials, quasi-experimental designs – controlled before and after, interrupted time series, [regression discontinuity design, difference-in-difference, and propensity score matching]. Timelines: 1900 – 2022.
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Soloviev, Vladimir N., Andrii O. Bielinskyi, and Natalia A. Kharadzjan. Coverage of the Coronavirus Pandemic through Entropy Measures. CEUR Workshop Proceedings, March 2021. http://dx.doi.org/10.31812/123456789/4427.

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The rapidly evolving coronavirus pandemic brings a devastating effect on the entire world and its economy as awhole. Further instability related to COVID-19will negatively affect not only on companies and financial markets, but also on traders and investors that have been interested in saving their investment, minimizing risks, and making decisions such as how to manage their resources, how much to consume and save, when to buy or sell stocks, etc., and these decisions depend on the expectation of when to expect next critical change. Trying to help people in their subsequent decisions, we demonstrate the possibility of constructing indicators of critical and crash phenomena on the example of Bitcoin market crashes for further demonstration of their efficiency on the crash that is related to the coronavirus pandemic. For this purpose, the methods of the theory of complex systems have been used. Since the theory of complex systems has quite an extensive toolkit for exploring the nonlinear complex system, we take a look at the application of the concept of entropy in finance and use this concept to construct 6 effective entropy measures: Shannon entropy, Approximate entropy, Permutation entropy, and 3 Recurrence based entropies. We provide computational results that prove that these indicators could have been used to identify the beginning of the crash and predict the future course of events associated with the current pandemic.
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