Academic literature on the topic 'Risk analysis'
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Journal articles on the topic "Risk analysis"
Koza, Patrycja, and Jarosław Krzywański. "New method of occupational risk assessment – Risk Analysis." International Journal of Engineering and Safety Sciences 1 (2020): 69–84. http://dx.doi.org/10.16926/ijess.2020.01.05.
Full textKizilaslan, H., and N. Kizilaslan. "Risk analysis in Turkey milk production." Czech Journal of Food Sciences 25, No. 3 (January 7, 2008): 144–50. http://dx.doi.org/10.17221/743-cjfs.
Full textŘíhová Ambrožová, J., J. Říha, J. Hubáčková, and I. Čiháková. "Risk analysis in drinking water accumulation." Czech Journal of Food Sciences 28, No. 6 (December 13, 2010): 557–63. http://dx.doi.org/10.17221/98/2010-cjfs.
Full textK, Roopa. "Credit Risk Management - A Case Analysis." International Journal of Science and Research (IJSR) 12, no. 12 (December 5, 2023): 361–66. http://dx.doi.org/10.21275/sr231128152822.
Full textViscusi, W. Kip. "Risk-risk analysis." Journal of Risk and Uncertainty 8, no. 1 (January 1994): 5–17. http://dx.doi.org/10.1007/bf01064083.
Full textLund, Jay R. "A Risk Analysis of Risk Analysis." Journal of Contemporary Water Research & Education 140, no. 1 (September 2008): 53–60. http://dx.doi.org/10.1111/j.1936-704x.2008.00028.x.
Full textVan Groenendaal, Willem J. H. "Measuring Risk: Risk Analysis or Sensitivity Analysis?" IFAC Proceedings Volumes 28, no. 7 (July 1995): 443–50. http://dx.doi.org/10.1016/s1474-6670(17)47145-x.
Full textCizek, Milan, Miroslav Mimra, Miroslav Kavka, and Jaroslav Humpal. "Analysis of economic risk in potatoes cultivation." Agricultural Economics (Zemědělská ekonomika) 65, No. 7 (July 17, 2019): 331–39. http://dx.doi.org/10.17221/319/2018-agricecon.
Full textLiu, K. F. R., K. Yeh, M. J. Hung, C. W. Chen, and Y. S. Shen. "Health Risk Analysis of Indoor Air Pollution." International Journal of Environmental Science and Development 6, no. 6 (2015): 464–68. http://dx.doi.org/10.7763/ijesd.2015.v6.638.
Full textKapoor Laxmi Ahuja, Tanya. "Cryptocurrency Financial Risk Analysis using Machine Learning." International Journal of Science and Research (IJSR) 12, no. 4 (April 5, 2023): 1117–21. http://dx.doi.org/10.21275/sr23417141525.
Full textDissertations / Theses on the topic "Risk analysis"
Bergvall, Jacob, and Louise Svensson. "Risk analysis review." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-119379.
Full textPayne, Brad. "Project risk analysis." Thesis, Nottingham Trent University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263943.
Full textLiwång, Hans, Jonas W. Ringsberg, and Martin Norsell. "Quantitative risk analysis : Ship security analysis for effective risk control options." Försvarshögskolan, Militärtekniska avdelningen (MTA), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-3800.
Full textNelson, Laura Kathleen. "Risky business: social media metrics and political risk analysis." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/13626.
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Quantifying country risk – and in particular, political risk – poses great difficulties for business, institutions, and investors alike. As economic indicators are updated far less frequently than Facebook feeds, it can be challenging for political risk analysts to understand, and more importantly measure, what is taking place in real time on the ground. However, with the growing availability of big data from social media platforms such as Twitter, now is an opportune moment to examine the types of social media metrics that are available and the limitations to applying them to country risk analysis, particularly during episodes of political upheaval. This study, using the qualitative method of bibliographical research, identifies the current landscape of data available from Twitter, analyzes the current and potential methods of analysis, and discusses their possible application to the field of political risk analysis. After a thorough review of the field to date, and given the expected near- to medium-term technological advancements, this study concludes that despite obstacles like the cost of data storage, limitations of real-time analysis, and the potential for data manipulation, the potential benefits of the application of social media metrics to the field of political risk analysis, particularly for structured-qualitative and quantitative models, outweigh the challenges.
A quantificação do risco país – e do risco político em particular – levanta várias dificuldades às empresas, instituições, e investidores. Como os indicadores econômicos são atualizados com muito menos freqüência do que o Facebook, compreender, e mais precisamente, medir – o que está ocorrendo no terreno em tempo real pode constituir um desafio para os analistas de risco político. No entanto, com a crescente disponibilidade de 'big data' de ferramentas sociais como o Twitter, agora é o momento oportuno para examinar os tipos de métricas das ferramentas sociais que estão disponíveis e as limitações da sua aplicação para a análise de risco país, especialmente durante episódios de violência política. Utilizando o método qualitativo de pesquisa bibliográfica, este estudo identifica a paisagem atual de dados disponíveis a partir do Twitter, analisa os métodos atuais e potenciais de análise, e discute a sua possível aplicação no campo da análise de risco político. Depois de uma revisão completa do campo até hoje, e tendo em conta os avanços tecnológicos esperados a curto e médio prazo, este estudo conclui que, apesar de obstáculos como o custo de armazenamento de informação, as limitações da análise em tempo real, e o potencial para a manipulação de dados, os benefícios potenciais da aplicação de métricas de ferramentas sociais para o campo da análise de risco político, particularmente para os modelos qualitativos-estruturados e quantitativos, claramente superam os desafios.
Zhang, Minhao. "Managerial perception of supply chain quality risk : risk analysis and decision analysis." Thesis, University of York, 2017. http://etheses.whiterose.ac.uk/20715/.
Full textPenha, Ricardo Miguel do Brito. "Default risk : analysis of a credit risk model." Master's thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/12902.
Full textUma parte considerável do negócio bancário inclui naturalmente o empréstimo de dinheiro. Inerentemente, o risco de não receber de volta o montante emprestado é assumido pela instituição bancária. Neste trabalho, o risco de incumprimento é estudado através da função de distribuição das perdas agregadas. Depois de feita a ponte entre as características de uma carteira de empréstimos de um banco e as características de uma carteira de apólices de seguros vida, os resultados da Teoria de Risco podem ser aplicados à carteira em estudo. O CreditRisk+, geralmente classificado como o modelo actuarial, é um modelo de risco de crédito que tem por base esta ponte. Para aplicação deste modelo, é necessária informação relativa às probabilidades de incumprimento de cada devedor e a exposição ao risco, que no nosso caso é igual ao montante em dívida. Na primeira parte deste trabalho é estimada a probabilidade de incumprimento através de um modelo logit, tendo em conta alguns indicadores financeiros da empresa. Seguidamente, no contexto de um modelo de risco coletivo, é aplicado o método iterativo de Panjer. Seguindo a metodologia proposta pelo modelo CreditRisk+, a carteira é seguidamente dividida em setores e, em cada setor, é introduzida volatilidade à probabilidade de incumprimento. No final, conclui-se que conseguem ser obtidos resultados semelhantes utilizando métodos de aproximação menos dispendiosos, nomeadamente com a aproximação NP. Finalmente, a taxa de juro média que o banco deveria aplicar aos empréstimos em carteira é calculada, assim como a reserva que deveria ter sido constituída.
A considerable part of the banking business includes the lending of money. Inherently, a bank incurs the risk of not receiving back the money lent. In this work, default risk is studied through the distribution function of the aggregate losses. After making the link between the characteristics of a portfolio of loans and of a life insurance policies portfolio, Risk Theory results are applied to the portfolio of loans under study. CreditRisk+, usually classified as the actuarial model, is a credit risk model which uses this link. As an input to this model, both the individual probabilities of default for each obligor and the exposure at risk are needed. The first part of this work focus on the estimation of the probability of default through a logit model, taking into account some financial indicators of the company. Then, in the context of a collective risk model, Panjer?s recursive algorithm is applied. Following the methodology of CreditRisk+, the portfolio is then divided into sectors and default volatility is introduced in each sector, reaching a different aggregate loss distribution function. At the end, we find that similar results are obtained with less time consuming approximation methods, particularly with NP approximation. Finally, the average interest rate that the bank should have charged to the loans in the portfolio is found as well as the amount of money that should have been reserved to account for losses.
info:eu-repo/semantics/publishedVersion
Gallagher, Elisabeth. "Studies in risk analysis, with an emphasis on risk assessment and risk communication." Thesis, Royal Veterinary College (University of London), 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.419975.
Full textLaukka, Lucas, and Carl Fransson. "Cloud risk analysis using OCTAVE Allegro : Identifying and analysing risks of a cloud service." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176731.
Full textL, Sousa Rita. "Risk analysis for tunneling projects." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/58282.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 574-589).
Tunnel construction is increasing world wide. Although the majority of tunnel construction projects have been completed safely, there have been several incidents that have resulted in delays, cost overruns, and sometimes more significant consequences such as injury and loss of life. To help eliminate these accidents, it is necessary to systematically assess and manage the risks associated with tunnel construction. In order to better understand the conditions under which accidents occur, a database of 204 tunnel construction accidents was assembled. This is the most comprehensive database known to date. The database was analyzed to better understand the causes of accidents. Influence diagrams were constructed containing the main factors, and the interactions between them. These served as the basis of the risk assessment methodology presented in this work. The risk assessment methodology consists of combining a geologic prediction model that allows one to predict geology ahead of the tunnel construction, with a decision support model that allows one to choose amongst different construction strategies the one that leads to minimum risk. The geologic prediction model is based on Bayesian networks because of their ability to combine domain knowledge with data, encode dependencies among variables, and their ability to learn causal relationships.
(cont.) The combined geologic prediction - decision support model was then applied to the Porto Metro, in Portugal. The results of the geologic prediction model were in good agreement with the observed geology, and the results of the decision support model were in good agreement with the construction methods used. More significant, however, is the ability of the model to predict changes in geology and consequently changes in construction strategy. This was shown in two zones of the tunnel were accidents occurred, where the model predicted an abrupt change in geology, and the construction method should have been changed but was not. Using the model could have possibly avoiding the accidents. This risk assessment methodology provides a powerful tool with which planners and engineers can systematically assess and mitigate the inherent risks associated with tunnel construction.
by Rita L. Sousa.
Ph.D.
Engelmann, Josh. "Dairy price risk management analysis." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/13209.
Full textDepartment of Agricultural Economics
Kevin Dhuyvetter
The size of our dairy operation increased from 300 milk cows to 1,700 milk cows in 2003. Once the dairy operation increased, the dependency on milk price to support the entire operation also increased. This was due to the fact that the cropping side of the operation became more devoted to growing feed for the livestock as opposed to producing cash crops. Thus, the increase in the number of milk cows led to decreased diversity in our income potentially increasing the financial risk of the operation. The purpose of this thesis is to study different risk management tools and strategies to aid in the formulation of a risk management plan for milk sales in our operation. Risk management strategies using forward contracts, futures, put options, and cash were analyzed at different time periods and various minimum price levels. The strategies were analyzed over the last ten years (2001-2010) of available price data. Twenty-five risk management strategies were analyzed both with and without set minimum milk prices. Minimum price levels ranged from $14/cwt to $17/cwt in $1 increments. The time frame for the transaction ranged from zero to twelve months prior to production in three-month increments. Based on historical data, risk management strategies can be used to decrease the price risk faced by an operation. The risk management strategies did not affect the average price received at statistically significant levels typically considered. Different risk management opportunities are highlighted that need to be analyzed before fully implementing a risk management plan for dairy operations.
Books on the topic "Risk analysis"
Aven, Terje. Risk Analysis. Chichester, UK: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781119057819.
Full textZervos, Constantine, Kathleen Knox, Lee Abramson, and Rob Coppock, eds. Risk Analysis. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-0730-1.
Full textFlaus, Jean-Marie. Risk Analysis. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118790021.
Full textManagement, Institute of Risk, ed. Risk analysis. London: Witherby & Co., 2003.
Find full textDickson, G. C. A. Risk analysis. London: Institute of Risk Management, 1987.
Find full textChartered Institute of Public Finance and Accountancy., ed. Risk analysis. London: Chartered Institute of Public Finance and Accountancy, 1986.
Find full textL, Rubio J., Brebbia C. A, Usō J-L, and International Conference on Computer Simulation in Risk Analysis and Hazard Mitigation (1st : 1998 : Valencia, Spain), eds. Risk analysis. Boston: WIT Press, 1998.
Find full textAven, Terje. Risk analysis. Chichester, West Sussex, United Kingdom: John Wiley & Sons, 2015.
Find full textCox, Louis A. Improving risk analysis. New York, NY: Springer, 2012.
Find full textGreenberg, Michael. Explaining Risk Analysis. Abingdon, Oxon ; New York, NY : Routledge, 2017.: Routledge, 2016. http://dx.doi.org/10.4324/9781315647579.
Full textBook chapters on the topic "Risk analysis"
Viscusi, W. Kip. "Risk-Risk Analysis." In The Mortality Costs of Regulatory Expenditures, 5–17. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1360-1_1.
Full textEdgerton, Sylvia A. "Risk Tracers: Surrogates for Assessing Health Risks." In Risk Analysis, 85–92. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-0730-1_10.
Full textLevinson, Alfred. "Risk Communication: Talking About Risk Reduction Instead of Acceptable Risk." In Risk Analysis, 387–92. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-0730-1_38.
Full textFlaus, Jean-Marie. "Modeling Risk." In Risk Analysis, 71–91. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118790021.ch5.
Full textAlleman, Glen B., and Jon M. Quigley. "Risk Analysis." In Risk Management, 58–109. Boca Raton: Auerbach Publications, 2024. http://dx.doi.org/10.1201/9781003425465-3.
Full textSheedy, Elizabeth. "Risk Analysis." In Risk Governance, 102–14. Abingdon, Oxon ; New York, NY : Routledge, 2021. | Series: Routledge contemporary corporate governance: Routledge, 2021. http://dx.doi.org/10.4324/9781003123736-10.
Full textBorghesi, Antonio, and Barbara Gaudenzi. "Risk Analysis." In Risk Management, 53–85. Milano: Springer Milan, 2012. http://dx.doi.org/10.1007/978-88-470-2531-8_6.
Full textHantschel, Thomas, and Armin I. Kauerauf. "Risk Analysis." In Fundamentals of Basin and Petroleum Systems Modeling, 341–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-72318-9_7.
Full textAven, Terje. "Risk Analysis." In Springer Series in Reliability Engineering, 125–49. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-470-8_5.
Full textBhattacharya, Keron. "Risk Analysis." In The New Frontiers for Business Analysis, 95–105. London: Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1007/978-1-349-08612-2_7.
Full textConference papers on the topic "Risk analysis"
Zahedi, S. "Risk typology." In RISK ANALYSIS 2008. Southampton, UK: WIT Press, 2008. http://dx.doi.org/10.2495/risk080221.
Full textFederici, A. "Trade openness and policy tools: a vulnerability approach for the Italian regions." In RISK ANALYSIS 2008. Southampton, UK: WIT Press, 2008. http://dx.doi.org/10.2495/risk080311.
Full textDeshpande, N. P., and R. Gupta. "Crowd management using fuzzy logic and G.I.S." In RISK ANALYSIS 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/risk100281.
Full textDragomir, C. S., and A. S. Tronac. "Seismic risk assessment of reinforced concrete buildings." In RISK ANALYSIS 2014. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/risk140071.
Full textAmicucci, G. L., and P. Gentile. "Reliability evaluation of metal oxide varistors for maintenance scheduling." In RISK ANALYSIS 2006. Southampton, UK: WIT Press, 2006. http://dx.doi.org/10.2495/risk060171.
Full textCharchalis, A. "Diagnosis as a fundamental element for the safe exploitation of marine power plants." In RISK ANALYSIS 2006. Southampton, UK: WIT Press, 2006. http://dx.doi.org/10.2495/risk060301.
Full textKawata, Y. "Recent development of tsunami disaster reduction management in Japan after the 2004 Indian Ocean Tsunami." In RISK ANALYSIS 2008. Southampton, UK: WIT Press, 2008. http://dx.doi.org/10.2495/risk080171.
Full textAntunes do Carmo, J. Simão. "Guidelines and tools to prevent risks in valleys downstream from large dam-reservoir systems: a review." In RISK ANALYSIS 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/risk100131.
Full textMajdara, A., and T. Wakabayashi. "Computerized fault tree construction for improved reliability analysis." In RISK ANALYSIS 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/risk100141.
Full textHamid, N. H., and S. A. Anuar. "Seismic risk assessment of three types of exterior beam-column joints using fragility curves." In RISK ANALYSIS 2014. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/risk140081.
Full textReports on the topic "Risk analysis"
Helms, J. Quantitative Risk Analysis. Office of Scientific and Technical Information (OSTI), February 2017. http://dx.doi.org/10.2172/1345342.
Full textStedinger, Jery, David C. Heath, and Kay Thompson. Risk Analysis for Dam Safety Evaluation: Hydrologic Risk. Fort Belvoir, VA: Defense Technical Information Center, March 1996. http://dx.doi.org/10.21236/ada316926.
Full textShedrow, C. B. DWPF risk analysis summary. Office of Scientific and Technical Information (OSTI), October 1990. http://dx.doi.org/10.2172/6215794.
Full textPrescott, Steven, Ramprasad Sampath, and John Biersdorf. Risk-Informed Systems Analysis (RISA) Dynamic Fire PRA Roadmap. Office of Scientific and Technical Information (OSTI), March 2018. http://dx.doi.org/10.2172/1467474.
Full textEngel, David W. Initial Decision and Risk Analysis. Office of Scientific and Technical Information (OSTI), February 2012. http://dx.doi.org/10.2172/1062507.
Full textHaimes, Yacov Y., Raja Petrakian, Per-Ola Karlsson, and James Mitsiopoulos. Multiobjective Risk Partitioning: An Application to Dam Safety Risk Analysis. Fort Belvoir, VA: Defense Technical Information Center, April 1988. http://dx.doi.org/10.21236/ada197011.
Full textRish, W. R. Approach to uncertainty in risk analysis. Office of Scientific and Technical Information (OSTI), August 1988. http://dx.doi.org/10.2172/7141098.
Full textStenner, R. D., D. L. Strenge, and J. W. Buck. RAMS (Risk Analysis - Modular System) methodology. Office of Scientific and Technical Information (OSTI), October 1996. http://dx.doi.org/10.2172/398559.
Full textBooth, Steven, and Ariel Lybarger. Application and Interpretation of Acumen Risk® Schedule and Cost Risk Analysis. Office of Scientific and Technical Information (OSTI), July 2020. http://dx.doi.org/10.2172/1893653.
Full textBasche, A. D. Single-shell tank interim stabilization risk analysis. Office of Scientific and Technical Information (OSTI), July 1998. http://dx.doi.org/10.2172/362432.
Full text