Journal articles: 'Level of risk'

1

Titus, James G., and Vijay Narayanan. "The risk of sea level rise." Climatic Change 33, no. 2 (June 1996): 151–212. http://dx.doi.org/10.1007/bf00140246.

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Newman, Alan. "Low-level radioactive wastes, high-level risk?" Environmental Science & Technology 28, no. 11 (October 1994): 488A—491A. http://dx.doi.org/10.1021/es00060a004.

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Sayed Abd Elghaffar, Emad, Ahmed Mohamed Abotalib, and Manal Abdel Azeem Mohamed Khalil. "Determining factors that affect risk disclosure level in Egyptian banks." Banks and Bank Systems 14, no. 1 (March 26, 2019): 159–71. http://dx.doi.org/10.21511/bbs.14(1).2019.14.

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This study aims to measure the risk disclosure level in Egyptian banks and to investigate its determinants. The sample consisted of 28 banks during the period from 2010 to 2017. An unweighted risk disclosure index including six categories was used: credit risk, market risk, liquidity risk, capital structure and adequacy risk, operational risk, and other non-financial risks. Also, a content analysis approach was used to measure the actual level of risk disclosure. The findings demonstrated that there was an average level of total risk disclosure of all sample banks. The results showed that banks with a higher percentage of independent board membership, large board size, large audit committee size, duality, higher institutional ownership, and banks audited by one of big four audit firms were more motivated to increase risk disclosure. Also, the results showed that leverage, bad news, and bank social responsibility have a negative relationship with the level of risk disclosure. Overall, the results indicated that leverage, board size, audit committee size, auditor types, independence, duality, institutional ownership, bank social responsibility, and bad news are the main factors affecting the level of risk disclosure in Egyptian banks. The findings of this paper have a number of important implications. The risk disclosure in the banking sector is important for stakeholders such as investors and depositors. Also, risk disclosure index helps the regulatory bodies to evaluate the risk disclosure practice in Egyptian banks. This paper contributes to analyzing factors affecting banks managers’ decision to disclose risk information in emerging countries such as Egypt.

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Lavrushin, Oleg, and Natalia Sokolinskaya. "Retraction: Confidence level and credit risk analysis in Russian banks." Banks and Bank Systems 15, no. 2 (April 16, 2020): 38–46. http://dx.doi.org/10.21511/bbs.15(2).2020.04.

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Retracted on August 17, 2020 by the Journal’s owner and Publisher. Type of retraction – plagiarism.There wasn’t a request for this retraction, but the reason for investigation of plagiarism fact was the Russian Academy of Sciences Committee’s report “Predatory Journals at Scopus and WoS: Translation Plagiarism from Russian Sources”: https://kpfran.ru/wp-content/uploads/plagiarism-by-translation-2.pdf” dated August 12, 2020. The publishing house has familiarized itself with the report. The article by Alexey Mikhaylov, Natalia Sokolinskaya and Evgeniy Lopatin (2019). Asset allocation in equity, fixed-income and cryptocurrency on the base of individual risk sentiment. Investment Management and Financial Innovations, 16(2), 171-181. doi:10.21511/imfi.16(2).2019.15 was mentioned in this report. It is noted that translation plagiarism was detected in this article - http://wiki.dissernet.org/wsave/IMFI_2019_2_1publ.html. Due to this the publishing house carried out an investigation on possible cases of plagiarism of all articles of these authors (Alexey Mikhaylov, Natalia Sokolinskaya and Evgeniy Lopatin) published in “Business Perspectives” journals. When the manuscript "Confidence level and credit risk analysis in Russian banks" was submitted to the Journal for consideration, the authors signed the Cover letter and attested to the fact that their manuscript is an original research and has not been published before. Then, the manuscript was accepted for consideration by the Managing Editor and was tested for plagiarism using the iThenticate and Unicheck programs. Plagiarism was not detected. On August 12, 2020 the Russian Academy of Sciences Committee’s presented the report. Editorial staff decided to re-test all articles of mentioned authors for plagiarism using the iThenticate and Unicheck programs – the programs didn’t show the plagiarism, then the articles were tested for translation plagiarism by the experts of “Business Perspectives” and plagiarism was detected (plagiarism and paraphrases from Russian-language sources). According to the results of the investigation, the Publisher and owner of the journal decided to retract this article because of plagiarism on August 17, 2020.The authors were notified of such a decision.

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Nadraga, Vasiliy, and Anatoliy Balanda. "Macro-level Modelling of Budget Support for Social Risk Management." Central Ukrainian Scientific Bulletin. Economic Sciences, no. 2(35) (2019): 144–51. http://dx.doi.org/10.32515/2663-1636.2019.2(35).144-151.

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Prasad, Kedar N., William C. Cole, and Gerald M. Haase. "Low-Level Radiation Risk." American Journal of Roentgenology 181, no. 1 (July 2003): 278–79. http://dx.doi.org/10.2214/ajr.181.1.1810278a.

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Filipović, Damir. "Multi-Level Risk Aggregation." ASTIN Bulletin 39, no. 2 (November 2009): 565–75. http://dx.doi.org/10.2143/ast.39.2.2044648.

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AbstractIn this paper we compare the current Solvency II standard and a genuine bottom-up approach to risk aggregation. This is understood to be essential for developing a deeper insight into the possible differences between the diversification assumptions between the standard approach and internal models.

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Hinkel, Jochen, Carlo Jaeger, Robert J. Nicholls, Jason Lowe, Ortwin Renn, and Shi Peijun. "Sea-level rise scenarios and coastal risk management." Nature Climate Change 5, no. 3 (February 25, 2015): 188–90. http://dx.doi.org/10.1038/nclimate2505.

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Zagursky, O. M. "Assessment model of risk tolerability level of perishable agricultural products transportation." Naukovij žurnal «Tehnìka ta energetika» 11, no. 2 (July 5, 2020): 59–66. http://dx.doi.org/10.31548/machenergy2020.02.059.

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KURISAKA, Kenichi, and Shigeki OKAMURA. "ICONE19-43802 PRELIMINARY EVALUATION OF JSFR ACHIEVEMENT LEVEL TO RISK TARGETS." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2011.19 (2011): _ICONE1943. http://dx.doi.org/10.1299/jsmeicone.2011.19._icone1943_310.

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Hassan, Tarek A., Stephan Hollander, Laurence van Lent, and Ahmed Tahoun. "Firm-Level Political Risk: Measurement and Effects*." Quarterly Journal of Economics 134, no. 4 (August 26, 2019): 2135–202. http://dx.doi.org/10.1093/qje/qjz021.

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AbstractWe adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual U.S. firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing that it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firm’s actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. These results continue to hold after controlling for news about the mean (as opposed to the variance) of political shocks. Interestingly, the vast majority of the variation in our measure is at the firm level rather than at the aggregate or sector level, in the sense that it is captured neither by the interaction of sector and time fixed effects nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.

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Kim, Sung-Yul, Sang-Kun Moon, and Jin-O. Kim. "A Study on Evaluation for Risk Level in Transmission Network Connected with Renewable Energy." Journal of the Korean Institute of Illuminating and Electrical Installation Engineers 25, no. 2 (February 28, 2011): 87–95. http://dx.doi.org/10.5207/jieie.2011.25.2.087.

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Covi, Michelle Peppina, and Donna Jean Kain. "Sea-Level Rise Risk Communication: Public Understanding, Risk Perception, and Attitudes about Information." Environmental Communication 10, no. 5 (August 12, 2015): 612–33. http://dx.doi.org/10.1080/17524032.2015.1056541.

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Sajjad, Joe. "Managing Risk at Ground Level." Journal of Petroleum Technology 65, no. 08 (August 1, 2013): 18–21. http://dx.doi.org/10.2118/0813-0018-jpt.

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15

Watts, John M. "Acceptable level of fire risk." Fire Technology 28, no. 4 (November 1992): 289. http://dx.doi.org/10.1007/bf01873398.

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Shin, Je-Seok, Jin-O. Kim, and Sung-Yul Kim. "Transmission network expansion planning considering risk level assessment and scenario-based risk level improvement." IET Generation, Transmission & Distribution 12, no. 5 (March 13, 2018): 1081–88. http://dx.doi.org/10.1049/iet-gtd.2017.1210.

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17

Hardy, R. Dean, and Mathew E. Hauer. "Social vulnerability projections improve sea-level rise risk assessments." Applied Geography 91 (February 2018): 10–20. http://dx.doi.org/10.1016/j.apgeog.2017.12.019.

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Graham, Sonia, Jon Barnett, Ruth Fincher, Anna Hurlimann, Colette Mortreux, and Elissa Waters. "The social values at risk from sea-level rise." Environmental Impact Assessment Review 41 (July 2013): 45–52. http://dx.doi.org/10.1016/j.eiar.2013.02.002.

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Hardy, R. Dean, and Bryan L. Nuse. "Global sea-level rise: weighing country responsibility and risk." Climatic Change 137, no. 3-4 (May 27, 2016): 333–45. http://dx.doi.org/10.1007/s10584-016-1703-4.

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20

Demirci, Ebru, and Ian Young. "ESTIMATING GLOBAL SEA LEVEL VARIATIONS AND RESULTING INUNDATION EXPOSURE." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 71. http://dx.doi.org/10.9753/icce.v36.risk.71.

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Concerns about climate change highlights the needs to understand extreme sea levels and the resulting flood exposure in coastal areas on a global scale. The combined impacts of storm surge, tide, breaking wave setup and potential sea level rise will pose many economic, societal and engineering challenges in coming years. In order to predict the global coastal flood risk, a global sea level dataset of sufficiently long duration is required to undertake extreme value analysis. This presentation will outline the development and application of such a dataset.

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Wauters, E., F. van Winsen, Y. de Mey, and L. Lauwers. "Risk perception, attitudes towards risk and risk management: evidence and implications." Agricultural Economics (Zemědělská ekonomika) 60, No. 9 (September 30, 2014): 389–405. http://dx.doi.org/10.17221/176/2013-agricecon.

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The comprehensive risk analysis of a business such as farming entails questions on what is at stake, how important is the risk concern and how to deal with it. We performed a sequential mixed method, with the in-depth interviews in the first stage (n = 35), followed by a survey on the Flemish FADN (n = 614) in the second, to investigate the farmers’ risk perception, the attitudes towards risk and the perceived usefulness of the risk management strategies. We find that, rather than the short-term volatility in prices, the longer term co-evolution of expenses versus receipts is of a major concern to farmers, next to the land availability and the policy risks. Farmers are shown to be only slightly risk averse, rather risk neutral even. Further, our results suggest that farmers do not consider extensively studied risk management strategies such as contracts, futures and insurances, a valid option for their farm, and put more faith in internal strategies such as the debt management, the liquidity management and diversification. Last, risk management is to a substantial degree performed at the household level, rather than at the farm level, with strategies such as cutting the private expenses and the off-farm employment. These results hardly differ according to the farm and farmer characteristics.  

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22

Chen, Yao-Tien. "A Level Set Method Based on Bayesian Risk for Textured Image Segmentation." International Journal of Machine Learning and Computing 7, no. 4 (October 2017): 89–93. http://dx.doi.org/10.18178/ijmlc.2017.7.4.626.

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23

Dittmar, Robert F., and Christian T. Lundblad. "Firm characteristics, consumption risk, and firm-level risk exposures." Journal of Financial Economics 125, no. 2 (August 2017): 326–43. http://dx.doi.org/10.1016/j.jfineco.2017.05.002.

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Diez Roux, Ana V., Kiarri Kershaw, and Lynda Lisabeth. "Neighborhoods and cardiovascular risk: Beyond individual-level risk factors." Current Cardiovascular Risk Reports 2, no. 3 (May 2008): 175–80. http://dx.doi.org/10.1007/s12170-008-0033-0.

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Schedel, Angela, and John Schedel. "THE ECONOMICS OF SEA LEVEL RISE: FORECASTING FLOOD DAMAGE COST." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 79. http://dx.doi.org/10.9753/icce.v36.risk.79.

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Globally, sea levels are rising. As property owners decide whether and how to protect their assets to minimize future damage, a comprehensive understanding of potential damage costs is vital to making informed, cost-effective decisions. These estimates, when combined with probabilistic modeling of future flood events and sea level rise, can be used to forecast the future costs of flood inundation. Using this information, the economic benefits of different adaptation measures are compared to select the most cost-effective option. This study describes a methodology using Expected Monetary Value (EMV) to make risk-informed decisions for adapting vulnerable assets to sea level rise.

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Hudson, Paul. "The Affordability of Flood Risk Property‐Level Adaptation Measures." Risk Analysis 40, no. 6 (February 26, 2020): 1151–67. http://dx.doi.org/10.1111/risa.13465.

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27

White, Thomas E. "ADAPTATION MEASURES TO SEA-LEVEL RISE & SUBSIDENCE FOR COASTAL STRUCTURES." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 68. http://dx.doi.org/10.9753/icce.v36.risk.68.

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28

Janová, J. "Crop plan optimization under risk on a farm level in the Czech Republic." Agricultural Economics (Zemědělská ekonomika) 60, No. 3 (March 27, 2014): 123–32. http://dx.doi.org/10.17221/77/2013-agricecon.

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The precise agricultural operations research models claiming complex solutions and specialized software tools may appear too complicated to truly support the decision making process on the farm level. The specific balance between the simplifications made and the correspondence to the real problem must be found when building decision support for a local farmer. In this paper, a decision support model for agricultural production planning in the Czech Republic is developed covering both the randomness of parameters entering the problem and the complex crop succession requirements. Crucially, the model can be approached using software tools commonly available to farmers. The structure of the simplified model is described in detail, its validity proved by the recently suggested simulation procedures and the general applicability of the model structuring for a local agriculture decision support is discussed.  

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29

Stoltz, Amanda Daria, Manoj Shivlani, and Robert Glazer. "Fishing Industry Perspectives on Sea-Level Rise Risk and Adaptation." Water 13, no. 8 (April 20, 2021): 1124. http://dx.doi.org/10.3390/w13081124.

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Sea-level rise, already occurring over Florida’s coast, stands to generate a significant impact on the state’s fishing industry and coastal communities, exposing vulnerable areas and populations to extreme events and disrupting established patterns of fishery and marine resource use. Using a semi-structured interview approach, this study evaluated fishing industry perspectives on sea-level rise risk and adaptation in three Florida coastal communities. The results showed that adaptation responses vary across industry sectors and communities and are strongly influenced by experience, community dynamics, and age. Generally, older fishers are less willing to relocate due to social factors, such as strong place attachment, compared to younger fishers, who are more likely to retreat and/or work from a less vulnerable location. These findings suggest that adaptation responses, while influenced by experience, are mediated by age, attachment to place, and worldviews, and that these factors need to be accounted for when crafting adaptation strategies across coastal communities.

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30

Freestone, David, and Clive Schofield. "Sea Level Rise and Archipelagic States: A Preliminary Risk Assessment." Ocean Yearbook Online 35, no. 1 (July 20, 2021): 340–87. http://dx.doi.org/10.1163/22116001_03501011.

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31

Cohen, Bernard L. "Cancer Risk from Low-Level Radiation." American Journal of Roentgenology 179, no. 5 (November 2002): 1137–43. http://dx.doi.org/10.2214/ajr.179.5.1791137.

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32

Gándelman, Néstor, and Rubén Hernández-Murillo. "Risk Aversion at the Country Level." Review 97, no. 1 (2015): 53–66. http://dx.doi.org/10.20955/r.2015.53-66.

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33

Ardillah, Yustini. "RISK FACTORS OF BLOOD LEAD LEVEL." Jurnal Ilmu Kesehatan Masyarakat 7, no. 3 (November 15, 2016): 150–55. http://dx.doi.org/10.26553/jikm.2016.7.3.150-155.

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34

Brown, Alan. "Low level outlets 2: risk assessment." Dams and Reservoirs 19, no. 1 (March 2009): 11–14. http://dx.doi.org/10.1680/dare.2009.19.1.11.

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35

Travis, Curtis C., and Holly A. Hattemer-Frey. "Determining an acceptable level of risk." Environmental Science & Technology 22, no. 8 (August 1988): 873–76. http://dx.doi.org/10.1021/es00173a003.

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36

Goldman, M. "Cancer Risk of Low-Level Exposure." Science 271, no. 5257 (March 29, 1996): 1821–22. http://dx.doi.org/10.1126/science.271.5257.1821.

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37

Abelson, P. "Risk assessments of low-level exposures." Science 265, no. 5178 (September 9, 1994): 1507. http://dx.doi.org/10.1126/science.7832844.

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Smith, S., A. Chen, S. Caudill, S. Wetterhall, and L. Sever. "Risk assessments of low-level exposures." Science 267, no. 5198 (February 3, 1995): 603–4. http://dx.doi.org/10.1126/science.7839131.

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39

Mann, J. "Risk assessment of low-level exposures." Science 267, no. 5198 (February 3, 1995): 604–5. http://dx.doi.org/10.1126/science.7839132.

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40

İmrohoroğlu, Ayşe, and Şelale Tüzel. "Firm-Level Productivity, Risk, and Return." Management Science 60, no. 8 (August 2014): 2073–90. http://dx.doi.org/10.1287/mnsc.2013.1852.

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41

Rogach, Yu P. "Integral index of occupational risk level." Geo-Technical mechanics, no. 143 (2018): 31–39. http://dx.doi.org/10.15407/geotm2018.143.031.

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42

Abelson, P. H. "Risk assessment of low-level exposures." IEEE Power Engineering Review 14, no. 12 (1994): 40. http://dx.doi.org/10.1109/mper.1994.334485.

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43

Bao, May Xiaoyan, and Yixin Liu. "Level 3 Assets and Credit Risk." Review of Pacific Basin Financial Markets and Policies 21, no. 01 (January 18, 2018): 1850003. http://dx.doi.org/10.1142/s0219091518500030.

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We examine the impact of Level 3 assets held by nonfinancial companies on credit risk. Specifically, we investigate how the pricing uncertainty of Level 3 assets is reflected in credit ratings, corporate bond yield spreads, and incidences of bond covenants. We find that higher holdings of Level 3 assets are associated with lower credit ratings, higher yield spreads, especially for Level 3 assets sample, and incidences of bondholder-friendly covenants in the bond issues. Our findings are robust to the treatment of sample selection bias and the influence of macroeconomic factors. In addition, our direct test on the relation between the holdings of Level 3 assets and a firm’s distance-to-default shows that higher holdings of Level 3 assets reduce a firm’s distance-to-default. Overall, our findings support the view that Level 3 assets are perceived as increasing credit risk in the bond market.

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Lim, Gregory B. "Vitamin D level and surgical risk." Nature Reviews Cardiology 10, no. 3 (January 29, 2013): 118. http://dx.doi.org/10.1038/nrcardio.2013.6.

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ESPINOZA, NICOLAS, and MARTIN PETERSON. "RISK AND MID-LEVEL MORAL PRINCIPLES." Bioethics 26, no. 1 (March 24, 2010): 8–14. http://dx.doi.org/10.1111/j.1467-8519.2010.01813.x.

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Goseva-Popstojanova, K., A. Hassan, A. Guedem, W. Abdelmoez, D. E. M. Nassar, H. Ammar, and A. Mili. "Architectural-level risk analysis using uml." IEEE Transactions on Software Engineering 29, no. 10 (October 2003): 946–59. http://dx.doi.org/10.1109/tse.2003.1237174.

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47

Billi, Roberto M. "Price level targeting and risk management." Economic Modelling 73 (June 2018): 163–73. http://dx.doi.org/10.1016/j.econmod.2018.03.013.

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48

Song, Fei. "Rights Against High-Level Risk Impositions." Ethical Theory and Moral Practice 22, no. 3 (June 2019): 763–78. http://dx.doi.org/10.1007/s10677-019-09994-6.

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49

Jacobs, DR. "Cholesterol level and risk of death." Biomedicine & Pharmacotherapy 44, no. 5 (January 1990): 291. http://dx.doi.org/10.1016/0753-3322(90)90156-4.

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50

Weber, Ron, Wilm Fecke, Imke Moeller, and Oliver Musshoff. "Meso-level weather index insurance." Agricultural Finance Review 75, no. 1 (May 5, 2015): 31–46. http://dx.doi.org/10.1108/afr-12-2014-0045.

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Purpose – Using cotton yield, and rainfall data from Tajikistan, the purpose of this paper is to investigate the magnitude of weather induced revenue losses in cotton production. Hereby the authors look at different risk aggregation levels across political regions (meso-level). The authors then design weather index insurance products able to compensate revenue losses identified and analyze their risk reduction potential. Design/methodology/approach – The authors design different weather insurance products based on put-options on a cumulated precipitation index. The insurance products are modeled for different inter-regional and intra-regional risk aggregation and risk coverage scenarios. In this attempt the authors deal with the common problem of developing countries in which yield data is often only available on an aggregate level, and weather data is only accessible for a low number of weather stations. Findings – The authors find that it is feasible to design index-based weather insurance products on the meso-level with a considerable risk reduction potential against weather-induced revenue losses in cotton production. Furthermore, the authors find that risk reduction potential increases on the national level the more subregions are considered for the insurance product design. Moreover, risk reduction potential increases if the index insurance product applied is designed to compensate extreme weather events. Practical implications – The findings suggest that index-based weather insurance products bear a large risk mitigation potential on an aggregate level. Hence, meso-level insurance should be recognized by institutions with a regional exposure to cost-related weather risks as part of their risk-management strategy. Originality/value – The authors are the first to investigate the potential of weather index insurance for different risk aggregation levels in developing countries.

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Journal articles on the topic 'Level of risk'

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