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1

Hartwig, Benny, Christoph Meinerding, and Yves S. Schüler. "Identifying indicators of systemic risk." Journal of International Economics 132 (September 2021): 103512. http://dx.doi.org/10.1016/j.jinteco.2021.103512.

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Hristov, Nikolay, and Markus Roth. "Uncertainty shocks and systemic-risk indicators." Journal of International Money and Finance 122 (April 2022): 102573. http://dx.doi.org/10.1016/j.jimonfin.2021.102573.

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Arsov, Ivailo, Elie Canetti, Laura E. Kodres, and Srobona Mitra. "Near-Coincident Indicators of Systemic Stress." IMF Working Papers 13, no. 115 (2013): 1. http://dx.doi.org/10.5089/9781484343784.001.

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Gradojevic, Nikola, and Marko Caric. "Predicting Systemic Risk with Entropic Indicators." Journal of Forecasting 36, no. 1 (March 21, 2016): 16–25. http://dx.doi.org/10.1002/for.2411.

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Bezrodna, Olena, Zoia Ivanova, Yulia Onyshchenko, Volodymyr Lypchanskyi, and Serhii Rymar. "Systemic risk in the banking system: measuring and interpreting the results." Banks and Bank Systems 14, no. 3 (August 7, 2019): 34–47. http://dx.doi.org/10.21511/bbs.14(3).2019.04.

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Highly concentrated banking system risks and the cumulative effect due to their accumulation act as a driver for improving the macro-prudential policy implemented by central banks. For this reason, an effectively and comprehensively assessed systemic risk in the banking system is declared an express condition for the early detection of its production sources and blocking of potential spreading channels, reducing the possible implementation. In light of this, the article develops an approach to the aggregated systemic risk assessment and interpretation of its results. The proposed approach is based on the considered influence exerted by financial risks of systemically important banks on the destabilized banking system and interconnections between banks in the context of the possible crisis impulse spreading. The following steps should be accomplished to form an aggregated systemic risk indicator in the banking system. Firstly, the differentiation of systemically important banks by the degree of their systemic importance; secondly, an integral assessment of the bank operation riskiness within certain bank groups; thirdly, the cumulative composition of the corresponding integral indicators, taking into account their weighting coefficients based on two criteria, namely values of the systemic importance indicator differentiating the bank groups, and the correlation of their risks. Interpreting the quantitative measurement results with regard to the systemic risk in the banking system is followed by the recommendations below: the systemic risk grading into high, medium and low levels and the respective definition of the threshold aggregated systemic risk indicator value which informs about the possible systemic crisis when approached; justification of the selected supervision regime types (strengthened, moderate or weakened) for systemically important banks, depending on the riskiness level specific for their operation and the systemic importance degree. The developed approach to measuring the systemic risk by means of constructing an aggregated indicator and interpreting the obtained results was being tested considering the financial risk indicators of the systemically important banks in Ukraine during 2009–2018.
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Ye, Xingxing, and Raphael Douady. "Systemic Risk Indicators Based on Nonlinear PolyModel." Journal of Risk and Financial Management 12, no. 1 (December 20, 2018): 2. http://dx.doi.org/10.3390/jrfm12010002.

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The global financial market has become extremely interconnected as it demonstrates strong nonlinear contagion in times of crisis. As a result, it is necessary to measure financial systemic risk in a comprehensive and nonlinear approach. By establishing a large set of risk factors as the main bones of the financial market network and applying nonlinear factor analysis in the form of so-called PolyModel, this paper proposes two systemic risk indicators that can prognosticate the advent and trace the development of financial crises. Through financial network analysis, theoretical simulation, empirical data analysis and final validation, we argue that the indicators suggested in this paper are proved to be very effective in forecasting and tracing the financial crises from 1998 to 2017. The economic benefit of the indicator is evidenced by the enhancement of a protective put/covered call strategy on major stock markets.
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Fay, Gavin, Scott I. Large, Jason S. Link, and Robert J. Gamble. "Testing systemic fishing responses with ecosystem indicators." Ecological Modelling 265 (September 2013): 45–55. http://dx.doi.org/10.1016/j.ecolmodel.2013.05.016.

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Dumičić, Mirna. "Financial Stability Indicators – The Case of Croatia." Journal of Central Banking Theory and Practice 5, no. 1 (January 1, 2016): 113–40. http://dx.doi.org/10.1515/jcbtp-2016-0006.

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Abstract This paper considers financial stability through the processes of accumulation and materialisation of systemic risks. To this end, the method of principal component analysis on the example of Croatia has been used to construct two composite indicators – a systemic risk accumulation index and an index reflecting the consequences of systemic risk materialisation. In the construction of the indices, the features and risks specific to small open economies were considered. Such an approach to systemic risk analysis facilitates the monitoring and understanding of the degree of financial stability and communication of macroprudential policy makers with the public.
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9

Qi, Yuqing. "Financial Market and Inflation." International Journal of Economics and Finance 12, no. 6 (May 28, 2020): 90. http://dx.doi.org/10.5539/ijef.v12n6p90.

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Based on two dimensions of system risk, this paper studies the changes in the future inflation risk level, and uses the out-of-sample quantile R2  to further evaluate the predictive accuracy of different systemic risk indicators on inflation risk. Firstly, we compute two systemic risk indicators, MES and volatility, with data of Chinese financial institutions. And then we explore the amplification effect of these indicators on future inflation risk, under the framework of quantile regression. We find that systematic risk indicators have a strong predictive ability for the inflation level at various quantiles. MES indicator that reflects individual risk can better predict future deflation risk, while volatility index has a stronger ability to predict inflation risk. We also find that systemic risk indicators of different dimensions have different effects on inflation risk and deflation risk. In general, the MES index, which captures the individual risk of the organization, have a greater impact on the future inflation risk. While indicator that measures volatility in financial markets has more influence on the extreme lower tail of inflation rates. Finally, we predict the distribution of inflation in China from March 2020 to June 2021, and visually show the distribution trend of future inflation with forecast fan charts.
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Parfenova, M. V., and N. A. L'vova. "Assessment of Russian non-financial companies' systemic risk in financial stability monitoring." Finance and Credit 26, no. 4 (April 28, 2020): 724–43. http://dx.doi.org/10.24891/fc.26.4.724.

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Subject. The article addresses the issues of financial stability monitoring as part of macroprudental supervision and regulation. The study concerns non-financial companies as a source of systemic risk for the national financial system. There are a lot of discussions about monitoring of systemically important borrowers under the auspices of the Russian Regulator. Objectives. Research is aimed at developing a methodology for assessing the systemic risk of Russian non-financial companies. Methods. We propose a set of indicators to assess the systemic risk derived from non-financial companies in Russia. The sample of indicators corresponds with the leading international practice and available data. The dynamic analysis of the sampled indicators should be conducted. We should focus on separate indicators and for a comprehensive view using a new composite indicator of systemic risk. Results. We devised a methodology for assessing the systemic risk of Russian non-financial companies. The relevance of the methodology was proved with empirical data. The sample includes 3,766 companies per year. The proposed indicators were proved to reflect an adequate change in the tested period (the year before, during and after financial instability). Conclusions and Relevance. Our methodology contributes to the current scientific discussion on new directions for assessing the financial stability. The results can be applied to the analytical practice, including the macroprudential supervision and regulation.
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Lee, M. V., A. V. Martynova, M. V. Alenickaya, V. V. Skvarnik, B. V. Okun, and N. B. Afanasieva. "Peculiarities of system evaluation of polyclinics medical organization: optimization of availability by personnel." Manager Zdravoochranenia, no. 10 (January 17, 2023): 61–70. http://dx.doi.org/10.21045/1811-0185-2022-10-61-70.

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A model for the analysis of some indicators of a systemic assessment of the activities of a multidisciplinary medical organization is proposed: the integration of the indicator of staffing of a medical organization and the financial performance of medical organization is analyzed. The main performance indicators of the medical diversified organization are listed and the results of their c orrelation analysis with the indicators of the group of financial indicators are presented.
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Kurakina, Elena, Sergei Evtiukov, and Grigory Ginzburg. "SYSTEMIC INDICATORS OF ROAD INFRASTRUCTURE AT ACCIDENT CLUSTERS." Architecture and Engineering 5, no. 1 (2020): 51–58. http://dx.doi.org/10.23968/2500-0055-2020-5-1-51-58.

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13

Pokusaeva, D. P., I. A. Anikhovskaya, L. A. Korobkova, G. G. Enukidze, and M. Yu Yakovlev. "Prognostic Importance of Systemic Endotoxinemia Indicators in Atherogenesis." Human Physiology 45, no. 5 (September 2019): 543–51. http://dx.doi.org/10.1134/s036211971905013x.

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Schianetz, Karin, and Lydia Kavanagh. "Sustainability Indicators for Tourism Destinations: A Complex Adaptive Systems Approach Using Systemic Indicator Systems." Journal of Sustainable Tourism 16, no. 6 (December 1, 2008): 601. http://dx.doi.org/10.2167/jost766.0.

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Schianetz, Karin, and Lydia Kavanagh. "Sustainability Indicators for Tourism Destinations: A Complex Adaptive Systems Approach Using Systemic Indicator Systems." Journal of Sustainable Tourism 16, no. 6 (November 6, 2008): 601–28. http://dx.doi.org/10.1080/09669580802159651.

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16

Powis, Melanie Lynn, Nathan Taback, Christina Diong, Katherine Enright, Christopher M. Booth, Maureen E. Trudeau, and Monika K. Krzyzanowska. "Reliability of administrative data for evaluating the quality of systemic treatment for cancer." Journal of Clinical Oncology 35, no. 8_suppl (March 10, 2017): 208. http://dx.doi.org/10.1200/jco.2017.35.8_suppl.208.

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208 Background: There is ongoing interest in leveraging administrative data to examine quality but methodological concerns persist. We evaluated the reliability of a previously established panel of administrative data derived quality measures for systemic cancer treatment. Methods: The study cohort consisted of women diagnosed with early stage (stage I-III) breast cancer (ESBC) in Ontario, Canada, in 2010. Performance on 11 quality indicators evaluated using deterministically linked healthcare administrative databases has been reported previously. The sensitivity and specificity of these 11 indicators were examined using the chart as the gold standard. Results: The administrative cohort consisted of 6,795 women with ESBC from which a validation cohort of 705 patients was randomly selected from among patients who underwent cancer surgery at one of five hospitals chosen to balance feasibility and institutional characteristics.Sensitivity and specificity varied by indicator (Table). Reliability of some indicators may have been affected by suboptimal chart documentation in instances where care spanned multiple settings or the medical record was fragmented, or where the number of eligible patients for that indicator was low. Conclusions: Administrative data can be used to evaluate quality of systemic cancer therapy but understanding the reliability characteristics of individual indicators is essential to inform their appropriate use and interpretation. [Table: see text]
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Krzyzanowska, Monika K., Melanie Lynn Powis, Nathan Taback, Christina Diong, Katherine Enright, Christopher M. Booth, and Maureen E. Trudeau. "Reliability of administrative data for evaluating quality of systemic cancer treatment." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): e18269-e18269. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e18269.

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e18269 Background: There is ongoing interest in leveraging administrative data to examine quality but methodological concerns persist. We evaluated the reliability of a previously established panel of administrative data derived quality measures for systemic treatment. Methods: The cohort consisted of women diagnosed with early stage (stage I-III) breast cancer (ESBC) in Ontario, Canada, in 2010. Performance on 11 quality indicators evaluated using deterministically linked healthcare administrative databases has been reported previously. Sensitivity and specificity were examined using the chart as the gold standard. Results: The administrative cohort consisted of 6,795 women with ESBC from which a validation cohort of 705 patients was randomly selected from among patients who underwent cancer surgery at one of five hospitals chosen to balance feasibility and institutional characteristics.Sensitivity and specificity varied by indicator (Table 1). Reliability of some indicators may have been affected by suboptimal chart documentation in instances where care spanned multiple settings or the medical record was fragmented, or where the number of eligible patients for that indicator was low. Conclusions: Administrative data can be used to evaluate quality of systemic cancer therapy but understanding the reliability characteristics of individual indicators is essential to inform their appropriate use and interpretation. [Table: see text]
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18

Mokiy, M. S., and E. K. Borzenko. "SYSTEMIC CAUSES OF THE APPEARANCE OF “COBRA EFFECT” IN THE MANAGEMENT OF SOCIO-ECONOMIC DEVELOPMENT." Economics of Contemporary Russia 86, no. 3 (October 2, 2019): 51–61. http://dx.doi.org/10.33293/1609-1442-2019-3(86)-51-61.

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The article on the basis of extrapolation of system laws of management of social and economic development illustrates the system reason of the Cobra effect, that is, a situation where, despite the rather attractive goals that managers formulate, the result of the activities of subordinates is opposite to what was intended. The main problem of management is the development of a system of indicators, in which, working on the indicator, employees would change the state in the right direction. The reason for the Cobra effect is the manifestation of systemic patterns of socio-economic development. The main system regularity is the desire of the system for stability and self-preservation. This state of the system is achieved using the least energy-consuming way. It is shown that any worker, realizing system regularities, aspires to stability and self-preservation. Therefore, the employee is always forced to work for achieving the indicator. The article analyzes the manifestation of these laws at the level of enterprises and state. When managers understand these patterns explicitly or covertly, changes in the economic system are moving in the right direction. It is shown that the existing system of target indicators used as indicators to assess the effectiveness of management does not meet the goals and objectives of socio-economic development. At the meso- and macrolevel, absolute, volumetric indicators, such as gross national product and others, reduce the range of benefits to the population. The article defines the vector of change in the system of indicators for assessing the effectiveness of management at the regional and state levels, based on the fact that the key element is the family. At the same time, the targets should be indicators to assess the availability of benefits for households.
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Yu, Jia-Wei, Qin-Qin Huang, Yong-Han Guo, Zhi-Qiang Jiang, and Wen-Jie Xie. "Systemic Risk and Trading Strategy Based on Correlation-Based Networks in Stock Markets." Fluctuation and Noise Letters 19, no. 03 (February 7, 2020): 2050028. http://dx.doi.org/10.1142/s0219477520500285.

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In this paper, we construct five systemic risk indicators and test their performances based on four different datasets. It is observed that the five indicators can accurately indicate the increment of systemic risks during the periods of sub-prime crisis and European debt crisis. Trading strategies based on the risk indicators are further designed to test the warning ability of future price drops. The backtests reveal that trading based on the five indicators provides satisfied excess returns when the trading costs are included. Our results provide insights to find new network-based risk indicators to early warn the systemic risks in financial markets.
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Nguyen, Phuong T., Sam Wells, and Nam Nguyen. "A Systemic Indicators Framework for Sustainable Rural Community Development." Systemic Practice and Action Research 32, no. 3 (April 27, 2018): 335–52. http://dx.doi.org/10.1007/s11213-018-9456-9.

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Stratmann, Heidi, Maria Hellmund, Ulrich Veith, Nicole End, and Wera Teubner. "Indicators for lack of systemic availability of organic pigments." Regulatory Toxicology and Pharmacology 115 (August 2020): 104719. http://dx.doi.org/10.1016/j.yrtph.2020.104719.

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Shaprynskyy, V. O., V. F. Kryvetskyy, V. H. Suleymanova, B. O. Mityuk, and T. A. Khmelevska. "Systemic inflammatory response indicators in patients with neck phlegmons." Modern medical technologies 41 part 3, no. 2 (2019): 25–28. http://dx.doi.org/10.34287/mmt.2(41).2019.35.

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Purpose of the study. To study systemic inflammatory response indexes in patients with neck phlegmons. Materials and methods. All patients were divided on two groups. In general group (84 people) treatment included vulnerosorption with modern composition. The control group consisted of 57 patients taking hydrophilic ointments. To investigate the severity of endotoxicosis, Morozova’s scales and predictors of leukocyte index of intoxication, the index of the ratio of neutrophils and lymphocytes, lymphocytic-granulocyte index, were used.Results. The most frequent complications included sepsis (64,5%), toxic myocarditis (60%), toxic nephritis (68%) and mediastinitis (48,2%). Morozov's index of 113 (80%) patients was 41,5 ± 5 (severe endogenous intoxication); among the last 28 (20%) it showed 29,7 ± 2,6 (the average degree of intoxication). Changes of leukocyte index of intoxication, the index of the ratio of neutrophils and lymphocytes, lymphocytic-granulocyte index in patients treated with sorption composition showed more positive dynamics compared with the control group. The mortality in general group was 4,8% vs 14% in the control group.Conclusions.Deep neck phlegmons are characterized by severe endotoxicosis and lead to sepsis in 64,5% and mediastinitis in 48,2% cases. Morozova’s scales are useful to study the level of endotoxicosis in patients with neck phlegmons. Investigated sorption composition is more effective than a hydrophilic ointment, what confirms the dynamics of leukocyte index of intoxication, the index of the ratio of neutrophils and lymphocytes, ymphocytic-granulocyte index.Keywords: neck phlegmon, endogenous intoxication, leukogram, mediastinitis,vulnerosorption.
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Zhang, Junzhi, and Lei Chen. "Evaluating the Systemic Importance of China’s Banks via Adjacency Information Entropy." Discrete Dynamics in Nature and Society 2022 (April 15, 2022): 1–12. http://dx.doi.org/10.1155/2022/6979176.

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Information entropy can be utilized to assess the complexity of the Banking System and the uncertainty of association information between banks. Based on information entropy and the balance sheet data of 167 banks from 2011 to 2020, we proposed a centrality indicator based on Adjacency Information Entropy, then applied it to directed weighted and directed unweighted interbank networks to identify banks with systemically important status, and compared the results with those of traditional centrality indicators. The outcomes show that the results of centrality indicator based on Adjacency Information Entropy are more accurate than those of traditional centrality indicators in identifying banks with systemically important status in interbank networks. Six large state-owned commercial banks, nine joint-stock commercial banks, two policy banks, and two urban commercial banks with large assets are identified as systemically important banks based on the proposed centrality indicator, which is highly consistent with the list of systemically important banks published by the Chinese banking regulator. Among the systemically important banks, changes in systemic risk levels of joint-stock commercial banks and urban commercial banks are more susceptible to national policies than those of large state-owned commercial banks. The findings of this paper have certain reference significance for strengthening the supervision of banks with systemically important status in interbank networks and formulating targeted policies for regulating large commercial banks and small- and medium-sized commercial banks.
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Burra, Pravin, Pieter Juriaan De Jongh, Helgard Raubenheimer, Gary Van Vuuren, and Henco Wiid. "Implementing the countercyclical capital buffer in South Africa: Practical considerations." South African Journal of Economic and Management Sciences 18, no. 1 (March 4, 2015): 105–27. http://dx.doi.org/10.4102/sajems.v18i1.956.

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The Basel II regulatory framework significantly increased the resilience of the banking system, but proved ineffective in preventing the 2008/9 financial crisis. The subsequent introduction of Basel III aimed, inter alia, to supplement bank capital using buffers. The countercyclical buffer boosts existing minimum capital requirements when systemic risk surges are detected. Bolstering capital in favourable economic conditions cushions losses in unfavourable conditions, thereby addressing capital requirement procyclicality. This paper contains an overview of the countercyclical capital buffer and a critical discussion of its implementation as proposed in Basel III. Consequences of the buffer's introduction for South African banks are explored, and in particular, potential systemic risk indicator variables are identified that may be used by the South African Reserve Bank (SARB) as early warning indicators of imminent systemic financial distress. These indicators may be of value to the SARB, which could use them in taking decisions on the build-up and release of the countercyclical buffer for South African banks.
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Roger D. Mitchell, Felix Ayala-Fier. "SYSTEMIC INDICATORS OF INORGANIC ARSENIC TOXICITY IN FOUR ANIMAL SPECIES." Journal of Toxicology and Environmental Health, Part A 59, no. 2 (January 28, 2000): 119–34. http://dx.doi.org/10.1080/009841000157014.

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Hussein, Rugzan Jameel, Robert Krohn, Petra Kaufmann-Kolle, and Gerald Willms. "Quality indicators for the use of systemic antibiotics in dentistry." Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen 122 (May 2017): 1–8. http://dx.doi.org/10.1016/j.zefq.2017.04.007.

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Stoevesandt, Johanna, Gunter J. Sturm, Patrizia Bonadonna, Joanna N. G. Oude Elberink, and Axel Trautmann. "Risk factors and indicators of severe systemic insect sting reactions." Allergy 75, no. 3 (July 16, 2019): 535–45. http://dx.doi.org/10.1111/all.13945.

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Tedeschi, Gabriele, Fabio Caccioli, and Maria Cristina Recchioni. "Taming financial systemic risk: models, instruments and early warning indicators." Journal of Economic Interaction and Coordination 15, no. 1 (December 30, 2019): 1–7. http://dx.doi.org/10.1007/s11403-019-00278-x.

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Powis, Melanie, Alejandro Gonzalez, Rinku Sutradhar, Katherine Enright, Nathan Taback, Christopher M. Booth, Maureen E. Trudeau, and Monika K. Krzyzanowska. "Establishing achievable benchmarks for quality improvement in systemic therapy for early-stage breast cancer." Journal of Clinical Oncology 34, no. 7_suppl (March 1, 2016): 263. http://dx.doi.org/10.1200/jco.2016.34.7_suppl.263.

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263 Background: Setting realistic targets for performance on quality indicators (QI) is a consistent challenge in quality improvement. The purpose of this study was to utilize administrative data to define achievable targets for QI in the early stage breast cancer (EBC) population in relation to systemic therapy (ST) delivery based on best performers. Methods: Deterministically linked administrative healthcare databases were used to identify EBC cases diagnosed 2006 – 2010 in Ontario, Canada. Panel of previously established QIs for systemic therapy was applied to patients who met eligibility criteria for the individual indicators. Institutions with less than 10 eligible patients for a specific indicator were excluded. An empiric benchmark was defined as the proportion of patients meeting the indicator from institutions accounting for the top decile of eligible patients. Results: We identified 28,303 EBC patients who received surgery of which 12,252 received adjuvant chemotherapy. Benchmark results are summarized in Table. Conclusions: Many institutions fell considerably below the benchmark. Further analysis of institution-level drivers of high quality care is required to help characterize high performing institutions. [Table: see text]
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Asanović, Željka. "Predicting Systemic Banking Crises Using Early Warning Models: The Case of Montenegro." Journal of Central Banking Theory and Practice 6, no. 3 (September 26, 2017): 157–82. http://dx.doi.org/10.1515/jcbtp-2017-0025.

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Abstract Very high costs of systemic banking crises emphasize the importance of early warning models for these crises. In order to create an early warning model for systemic banking crises a combined approach is implemented. The first approach applied in this paper is signal approach, however, with some modifications as compared with its standard application in the literature. On the basis of individual indicators two composite indices are created. Unlike other papers in this field, the author has chosen a 24-month period before the beginning of the crisis as a signal horizon, while the signal horizon in the literature is usually considered to be a period of 12 months before and 12 months after the crisis onset. The second approach represents logit model whereas the independent variables are actually the indicators with the best performances obtained within the signal approach. In order to check the robustness of indicators, the Bayesian model averaging technique is used. The indicator that represents the credit growth rate, besides being a part of the composite index, is statistically significant in all estimated specifications of the logit model, including the technique of Bayesian model averaging. Additionally, trends in the international market have a significant influence on the domestic banking system and its stability, and hence also on the probability of occurrence of a systemic banking crisis.
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Sum, Katarzyna. "Basic Indicators of Systemic Risk in the EU Banking Sector. Implications for Banking Regulation." International Journal of Management and Economics 47, no. 1 (September 1, 2015): 36–55. http://dx.doi.org/10.1515/ijme-2015-0027.

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Abstract The issue of systemic risk regulation and management has gained substantial attention following the latest financial crisis. In the case of the EU it became crucial to deal with the systemic risk problem on a supranational level since the banking sectors of the member countries are highly integrated. While substantial measures have been undertaken to mitigate systemic risk in the EU, the discussion of further reforms continues. This study’s goal is to assess basic indicators of systemic risk in the EU banking sector by using three complementary methods: a forward-looking stock market data analysis, an EU-stress test analysis for systemically important banks, and an empirical investigation of the relation between banking regulation and systemic risk as measured by bank balance sheet indicators. The results lead to a recommendation of further necessary regulatory reforms, which appear in the conclusion.
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Gillis, JoAnn Zell, Pantelis Panopalis, Gabriela Schmajuk, Rosalind Ramsey-Goldman, and Jinoos Yazdany. "Systematic review of the literature informing the systemic lupus erythematosus indicators project: Reproductive health care quality indicators." Arthritis Care & Research 63, no. 1 (December 28, 2010): 17–30. http://dx.doi.org/10.1002/acr.20327.

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Schmajuk, Gabriela, Edward Yelin, Eliza Chakravarty, Lorene M. Nelson, Pantelis Panopolis, and Jinoos Yazdany. "Osteoporosis screening, prevention, and treatment in systemic lupus erythematosus: application of the systemic lupus erythematosus quality indicators." Arthritis Care & Research 62, no. 7 (February 23, 2010): 993–1001. http://dx.doi.org/10.1002/acr.20150.

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Zozulya, S., I. Oleichik, I. Otman, M. Yakovlev, and T. Klyushnik. "Association between markers of inflammation and indicators of systemic endotoxemia in endogenous psychosis." European Psychiatry 65, S1 (June 2022): S699—S700. http://dx.doi.org/10.1192/j.eurpsy.2022.1801.

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Introduction The clinical and biological studies indicate the involvement of inflammation in the pathogenesis of endogenous mental disorders. The inflammation markers leukocyte elastase, α1-proteinase inhibitor, and autoantibodies to neuroantigens reflect the severity of the pathological process in the brain. Systemic endotoxemia is a pathological process caused by an excess of endotoxins in the systemic circulation, can be considered as one of the components of the inflammatory process in endogenous psychosis. Objectives To evaluate the association between systemic inflammation markers and indicators of systemic endotoxemia in patients with endogenous psychosis. Methods The study included 25 patients aged 23-49 with endogenous psychoses (F20, F25) and 25 healthy people. The severity of symptoms was assessed using PANSS. We detected the activity of leukocyte elastase and a1-proteinase inhibitor, antibodies to neuroantigens, endotoxin (ET) concentration, and antibodies to endotoxin (aEТ) in serum. Results In 24% of cases, an increase of inflammation markers activity, ET concentration, and aET deficiency were observed (p<0.05), which is an unfavorable factor that aggravates the clinical course of the disease. In 76% of cases, ET concentration remained within control values (p>0.05) but associated with different levels of aET, which is likely to be a consequence of previous endotoxin aggression. There were correlations between ET concentration and antibodies to neuroantigens S-100B and MBP. We also revealed the association between the activity of the inflammatory marker with the severity of clinical symptoms in patients. Conclusions Results suggest the relationship between systemic inflammation markers and indicators of systemic endotoxemia and their involvement in the pathogenesis of endogenous psychosis. Disclosure No significant relationships.
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Gladman, Dafna D. "Indicators of disease activity, prognosis, and treatment of systemic lupus erythematosus." Current Opinion in Rheumatology 5, no. 5 (September 1993): 587–95. http://dx.doi.org/10.1097/00002281-199305050-00006.

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36

Chang, M. C., M. X. Cheatham, E. J. Rutherford, L. D. Nelson, J. A. Moms, and J. A. Morris. "GASTRIC TONOMETRY SUPPLEMENTS INFORMATION PROVIDED BY SYSTEMIC INDICATORS OF OXYGEN TRANSPORT." Journal of Trauma: Injury, Infection, and Critical Care 36, no. 1 (January 1994): 153. http://dx.doi.org/10.1097/00005373-199401000-00049.

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37

Chang, Michael C., Michael L. Cheatham, Loren D. Nelson, Edmund J. Rutherford, and John A. Morris. "GASTRIC TONOMETRY SUPPLEMENTS INFORMATION PROVIDED BY SYSTEMIC INDICATORS OF OXYGEN TRANSPORT." Journal of Trauma: Injury, Infection, and Critical Care 37, no. 3 (September 1994): 488–94. http://dx.doi.org/10.1097/00005373-199409000-00026.

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38

Schneider, R., B. A. Lang, and B. J. Reilly. "PROGNOSTIC INDICATORS OF JOINT DESTRUCTION IN SYSTEMIC-ONSET JUVENILE RHEUMATOID ARTHRITIS." Journal of Pediatric Orthopaedics 12, no. 4 (July 1992): 559. http://dx.doi.org/10.1097/01241398-199207000-00073.

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39

Schneider, Rayfel, Blanca A. Lang, Bernard J. Reilly, Ronald M. Laxer, Earl D. Silverman, Dominique Ibanez, Claire Bombardler, and Chaim M. Roifman. "Prognostic indicators of joint destruction in systemic-onset juvenile rheumatoid arthritis." Journal of Pediatrics 120, no. 2 (February 1992): 200–205. http://dx.doi.org/10.1016/s0022-3476(05)80427-5.

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40

Rossi, Sabrina, Michele Basso, Antonia Strippoli, Giovanni Schinzari, Ettore D'Argento, Mario Larocca, Alessandra Cassano, and Carlo Barone. "Are Markers of Systemic Inflammation Good Prognostic Indicators in Colorectal Cancer?" Clinical Colorectal Cancer 16, no. 4 (December 2017): 264–74. http://dx.doi.org/10.1016/j.clcc.2017.03.015.

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41

Nazarov, B. D., Yor Umarovich Saidov, D. A. Khalilova, R. N. Zubaidov, and B. R. Shodiyev. "RHEUMATOID ARTHRITIS WITH SYSTEMIC MANIFESTATIONS: DIAGNOSIS, INDICATORS OF AN UNFAVORABLE COURSE." Rheumatology Science and Practice, no. 6 (December 15, 2012): 45. http://dx.doi.org/10.14412/1995-4484-2012-1293.

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42

Gladman, Dafna D. "Indicators of disease activity, prognosis, and treatment of systemic lupus erythematosus." Current Opinion in Rheumatology 6, no. 5 (September 1994): 487–92. http://dx.doi.org/10.1097/00002281-199409000-00006.

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43

Gaitanidis, Apostolos, Mustapha El Lakis, Douglas Wiseman, Naris Nilubol, Electron Kebebew, and Dhaval Patel. "Preoperative Systemic Inflammatory Markers as Prognostic Indicators for Recurrent Adrenocortical Carcinoma." Journal of the American College of Surgeons 227, no. 4 (October 2018): e121-e122. http://dx.doi.org/10.1016/j.jamcollsurg.2018.08.328.

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44

Mazzocchetti, Andrea, Eliana Lauretta, Marco Raberto, Andrea Teglio, and Silvano Cincotti. "Systemic financial risk indicators and securitised assets: an agent-based framework." Journal of Economic Interaction and Coordination 15, no. 1 (October 4, 2019): 9–47. http://dx.doi.org/10.1007/s11403-019-00268-z.

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45

Balla, Eliana, Ibrahim Ergen, and Marco Migueis. "Tail dependence and indicators of systemic risk for large US depositories." Journal of Financial Stability 15 (December 2014): 195–209. http://dx.doi.org/10.1016/j.jfs.2014.10.002.

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46

Gaitanidis, Apostolos, Douglas Wiseman, Mustapha el Lakis, Naris Nilubol, Electron Kebebew, and Dhaval Patel. "Preoperative systemic inflammatory markers are prognostic indicators in recurrent adrenocortical carcinoma." Journal of Surgical Oncology 120, no. 8 (November 16, 2019): 1450–55. http://dx.doi.org/10.1002/jso.25760.

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47

Sprincean, Nicu. "Early warning indicators for macrofinancial activity in romania." Review of Economic and Business Studies 12, no. 1 (June 1, 2019): 137–62. http://dx.doi.org/10.1515/rebs-2019-0087.

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AbstractOverheating of economic and financial activities leads to macrofinancial imbalances that may disrupt financial stability, and can be detected by studying relevant indcators. In this study we developed an aggregate early warning index of macrofinancial activity for Romania over the 1998q1-2020q4 period, employing data from six categories: (i) macroeconomic risks, (ii) bank risks, (iii) activity of corporations and households, (iv) monetary and financial conditions, (v) risk appetite and (vi) external shocks. We determine the utility of these variables from two perspectives: (i) whether these indicators are able to detect overheating of macrofinancial activity in Romania in two periods characterized by systemic crises and (ii) whether these variables successfully minimize various statistical errors involved in forecasting future events. Comparing the evolution of our index with a series of indicators that measure investors’ perception of macrofinancial stability or the probability of default of Romanian economy, we note the positive correlation between these two, but our index exhibits a more pronounced early warning component, making it extremely useful in anticipating future systemic crises.
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48

Eratalay, Mustafa Hakan, and Ariana Paola Cortés Ángel. "The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms." Journal of Risk and Financial Management 15, no. 4 (March 28, 2022): 153. http://dx.doi.org/10.3390/jrfm15040153.

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There are diverging results in the literature on whether engaging in ESG related activities increases or decreases the financial and systemic risks of firms. In this study, we explore whether maintaining higher ESG ratings reduces the systemic risks of firms in a stock market context. For this purpose we analyse the systemic risk indicators of the constituent stocks of S&P Europe 350 for the period of January 2016–September 2020, which also partly covers the COVID-19 period. We apply a VAR-MGARCH model to extract the volatilities and correlations of the return shocks of these stocks. Then, we obtain the systemic risk indicators by applying a principle components approach to the estimated volatilities and correlations. Our focus is on the impact of ESG ratings on systemic risk indicators, while we consider network centralities, volatilities and financial performance ratios as control variables. We use fixed effects and OLS methods for our regressions. Our results indicate that (1) the volatility of a stock’s returns and its centrality measures in the stock network are the main sources contributing to the systemic risk measure, (2) firms with higher ESG ratings face up to 7.3% less systemic risk contribution and exposure compared to firms with lower ESG ratings and (3) COVID-19 augmented the partial effects of volatility, centrality measures and some financial performance ratios. When considering only the COVID-19 period, we find that social and governance factors have statistically significant impacts on systemic risk.
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Huang, Yunying, Wenlin Gui, Yixin Jiang, and Fengyi Zhu. "Types of systemic risk and macroeconomic forecast: Evidence from China." Electronic Research Archive 30, no. 12 (2022): 4469–92. http://dx.doi.org/10.3934/era.2022227.

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<abstract> <p>The macroeconomic forecast is of great significance to the government macroeconomic policy formulation and micro-agent operational decisions. The individual systemic risk measurement has a certain scope of application and application conditions and, therefore, it is difficult for the individual indicator to reflect the systemic risk comprehensively. In this paper, the systemic risk is divided into four types: institution-specific risk, comovement and contagion, financial vulnerability, liquidity and credit. Next, the optimal combination is selected from multiple individual systemic risk indicators through dominance analysis to forecast the macroeconomic performance. The macroeconomic performance selects consumer price index (CPI), producer price index (PPI), industrial growth value (IVA), growth rate of broad money supply (M2) and gross domestic product (GDP) as proxies to compare the forecast effect of systemic risk, with the period considered spans from 2003M4 to 2022M7. The results of immediate forecasts of different macroeconomic performance proxies demonstrate the individual indicator cannot cover all the information of systemic risk, can only reflect the specific aspect of macroeconomic performance, or is only highly relevant in a given period. The contribution of systemic risk to the forecast of different macroeconomic performance proxies in different terms is diverse, and show various types of results. This paper uses the optimal combination of systemic risk to forecast the macroeconomic performance, which provides a valuable reference for improving the macro prudential supervision mechanism.</p> </abstract>
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50

Asanović, Željka. "An Analysis of the Determinants of Systemic Banking Crises in Southeast European Countries." Journal of Central Banking Theory and Practice 7, no. 2 (May 1, 2018): 165–86. http://dx.doi.org/10.2478/jcbtp-2018-0017.

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Abstract The purpose of this paper is to determine potential indicators of systemic banking crises in five Southeast European countries. Although signal horizon in the literature usually implies a period of 12 months before and 12 months after a crisis outbreak, models in this paper imply a 24-month pre-crisis period. Probability of a banking crisis occurrence is calculated using logit regression. Results have shown that banking system indicators have higher impact on probability of systemic banking crisis occurrence compared to macroeconomic indicators, and that the banking systems of these countries are significantly exposed to global trends.
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