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Статті в журналах з теми "Credit risk measure"
Hilscher, Jens, and Mungo Wilson. "Credit Ratings and Credit Risk: Is One Measure Enough?" Management Science 63, no. 10 (September 2017): 3414–37. http://dx.doi.org/10.1287/mnsc.2016.2514.
Повний текст джерелаAlam, Pervaiz, Barry Hettler, and Han Gao. "Accounting downside risk measures and credit spreads." Review of Accounting and Finance 20, no. 1 (July 16, 2021): 103–20. http://dx.doi.org/10.1108/raf-08-2020-0244.
Повний текст джерелаTunay, K. Batu, Hasan F. Yuceyılmaz, and Ahmet Çilesiz. "An International Comparison on Excessive Credit Expansion, Credit Guarantee Programs and The Risks Arising." Khazar Journal of Humanities and Social Sciences 23, no. 1 (2020): 83–102. http://dx.doi.org/10.5782/2223-2621.2020.23.1.83.
Повний текст джерелаByström, Hans, and Oh Kang Kwon. "A simple continuous measure of credit risk." International Review of Financial Analysis 16, no. 5 (January 2007): 508–23. http://dx.doi.org/10.1016/j.irfa.2007.03.002.
Повний текст джерелаKiesel, Florian, and Jonathan Spohnholtz. "CDS spreads as an independent measure of credit risk." Journal of Risk Finance 18, no. 2 (March 20, 2017): 122–44. http://dx.doi.org/10.1108/jrf-09-2016-0119.
Повний текст джерелаFischer, Matthias, Thorsten Moser, and Marius Pfeuffer. "A Discussion on Recent Risk Measures with Application to Credit Risk: Calculating Risk Contributions and Identifying Risk Concentrations." Risks 6, no. 4 (December 7, 2018): 142. http://dx.doi.org/10.3390/risks6040142.
Повний текст джерелаSondakh, Jullie Jeanette, Joy Elly Tulung, and Herman Karamoy. "The effect of third-party funds, credit risk, market risk, and operational risk on profitability in banking." Journal of Governance and Regulation 10, no. 2 (2021): 179–85. http://dx.doi.org/10.22495/jgrv10i2art15.
Повний текст джерелаSTEIN, HARVEY J. "FIXING RISK NEUTRAL RISK MEASURES." International Journal of Theoretical and Applied Finance 19, no. 03 (April 21, 2016): 1650021. http://dx.doi.org/10.1142/s0219024916500217.
Повний текст джерелаWei, Lu, Chen Han, and Yinhong Yao. "The Bias Analysis of Oil and Gas Companies’ Credit Ratings Based on Textual Risk Disclosures." Energies 15, no. 7 (March 24, 2022): 2390. http://dx.doi.org/10.3390/en15072390.
Повний текст джерелаUberti, Pierpaolo, and Silvia Figini. "How to measure single-name credit risk concentrations." European Journal of Operational Research 202, no. 1 (April 2010): 232–38. http://dx.doi.org/10.1016/j.ejor.2009.05.001.
Повний текст джерелаДисертації з теми "Credit risk measure"
Klacar, Dorde. "Estimating Expected Exposure for the Credit Value Adjustment risk measure." Thesis, Umeå universitet, Nationalekonomi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-73104.
Повний текст джерелаGLANS, GUSTAV, and JESPER ROSENBERG. "Improving Measurement of SectorConcentration Risk in Credit Portfolios : Evaluation of sector classification and approaches to concentration measure characteristics." Thesis, KTH, Entreprenörskap och Innovation, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189498.
Повний текст джерелаOn a technical level, the measurement of sector concentration risk poses a particularlychallenging problem. Existing literature lacks direct suggestions both regarding how sectors are to be divided and the risk-level measured. The purpose of the study is to evaluate and analyse different measures of - and approaches to sector concentration risk in credit portfolios. This has been addressed both by analysing sectorial division and which aspects that are of interest for determining the concentration imposed risk- level. The sectorial division has been addressed by comparing the correlation structures of two especially interesting sector classification methods; the standardised Morgan Stanley Capital Investment industry classification (MSCI) and the proposed sector classification of the Swedish Financial Supervisory Authority (SFSA). The sector concentration risk measurement has been analysed through employing different risk-measures on portfolios with varying concentration levels. The results show that in order to capture the risk-level from concentration, the main approach for sectorial division should seek to minimise inter-sector correlations and maximise intra-sector correlations. I.e. sectors should be distinct from each other and internally homogeneous. Moreover, an unambiguous sorting of individual exposures towards one sector should be possible and the considered sectors should not be of a diversified nature. It is also found that MSCI outperforms SFSA for assessing sector concentration risk on all fronts. When it comes to the risk measure, it is found that apart from exposure distribution; credit qualities and correlation structures are of great interest. The risk induced from a concentrated exposure is greater if credit qualities are low or if the exposure is high towards highly correlated sectors. But above all, the results imply that a uniform distribution is not to be seen as unconcentrated. In order for concentration measurement to incorporate natural concentrations it is thereby greatly important that concentration instead is considered as relative towards the aggregate credit market.
ANSELMI, GIULIO. "ESSAYS ON OPTION IMPLIED VOLATILITY RISK MEASURES FOR BANKS." Doctoral thesis, Università Cattolica del Sacro Cuore, 2016. http://hdl.handle.net/10280/10402.
Повний текст джерелаThe thesis comprehends three essays on option implied volatility risk measures for banks. The thesis is organized in three chapters. Chapter I - studies the informational content for banks' stock returns in option's implied volatilities skews and spread. Chapter II - analyzes the effect of volatility risk measures (volatility skew and realized volatility) on banks' leverage. Chapter III - studies the relationship between banks' liquidity ratio and volatility risk measures.
Weber, Stefan. "Measures and models of financial risk." Doctoral thesis, [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=973223421.
Повний текст джерелаRacheva-Iotova, Borjana. "An Integrated System for Market Risk, Credit Risk and Portfolio Optimization Based on Heavy-Tailed Medols and Downside Risk Measures." Diss., lmu, 2010. http://nbn-resolving.de/urn:nbn:de:bvb:19-123750.
Повний текст джерелаZhiyong, Li. "Predicting financial distress using corporate efficiency and corporate governance measures." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9934.
Повний текст джерелаClaußen, Arndt [Verfasser]. "Essays on risk management of financial institutions : systematic risk, cross-sectional pricing of risk factors, parameter errors affecting risk measures, and credit decisions under parameter uncertainty / Arndt Claußen." Hannover : Technische Informationsbibliothek und Universitätsbibliothek Hannover (TIB), 2015. http://d-nb.info/1078747318/34.
Повний текст джерелаBourgey, Florian. "Stochastic approximations for financial risk computations." Thesis, Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAX052.
Повний текст джерелаIn this thesis, we investigate several stochastic approximation methods for both the computation of financial risk measures and the pricing of derivatives.As closed-form expressions are scarcely available for such quantities, %and because they have to be evaluated daily, the need for fast, efficient, and reliable analytic approximation formulas is of primal importance to financial institutions.We aim at giving a broad overview of such approximation methods and we focus on three distinct approaches.In the first part, we study some Multilevel Monte Carlo approximation methods and apply them for two practical problems: the estimation of quantities involving nested expectations (such as the initial margin) along with the discretization of integrals arising in rough forward variance models for the pricing of VIX derivatives.For both cases, we analyze the properties of the corresponding asymptotically-optimal multilevel estimatorsand numerically demonstrate the superiority of multilevel methods compare to a standard Monte Carlo.In the second part, motivated by the numerous examples arising in credit risk modeling, we propose a general framework for meta-modeling large sums of weighted Bernoullirandom variables which are conditional independent of a common factor X.Our generic approach is based on a Polynomial Chaos Expansion on the common factor together withsome Gaussian approximation. L2 error estimates are given when the factor X is associated withclassical orthogonal polynomials.Finally, in the last part of this dissertation, we deal withsmall-time asymptotics and provide asymptoticexpansions for both American implied volatility and American option prices in local volatility models.We also investigate aweak approximations for the VIX index inrough forward variance models expressed in termsof lognormal proxiesand derive expansions results for VIX derivatives with explicit coefficients
Bedini, Matteo. "Information on a default time : Brownian bridges on a stochastic intervals and enlargement of filtrations." Thesis, Brest, 2012. http://www.theses.fr/2012BRES0032.
Повний текст джерелаIn this PhD thesis the information process concerning a default time τ in a credit risk model is described by a Brownian bridge over the random time interval [0, τ]. Such a bridge process is characterised as to be a more adapted model than the classical one considering the indicator function I[0,τ]. After the study of related Bayes formulas, this approach of modelling information concerning the default time is related with other financial information. This is done with the help of the theory of enlargement of filtration, where the filtration generated by the information process is enlarged with a reference filtration modelling other information not directly associated with the default. A particular attention is paid to the classification of the default time with respect to the minimal filtration but also with respect to the enlarged filtration. Sufficient conditions under which τ is totally inaccessible are discussed, but also an example is given of a τ avoiding the stopping times of the reference filtration, which is totally inaccessible with respect to its own filtration and predictable with respect to the enlarged filtration. Finally, common financial contracts like defaultable bonds and credit default swaps are considered in the above described settings
Chao, Ling-pin, and 趙令斌. "Measure Credit Risk by Using Option Pricicng Model." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/02149588138400552548.
Повний текст джерела東吳大學
會計學系
88
Accompanied with the bullish economy in the eighties, there was a narrow gap in the credit risk spread. In order to compete, banks had to unconsciously face a significantly high credit risk. The production of derived instrument have also widened and make credit risk more complicate. Investors were not able to easily profit through interest rates and in the exchange market, thus turned into expanding or trading credit risk to gain. Moreover, the fast growth of new-rising markets caused investors and banks to face higher credit risk in making decision. These factors have caused the setting of monitoring controls for credit risk, and increased the importance of credit risk guidelines. This study uses option model to measure credit risk of Taiwan companies in the market with a view to provide more information regarding credit risk. This study defines credit risk as the company can''t pay their liability when assets value less than debt. Thus, a company''s credit risk can be estimated by knowledge of the distribution of its asset value. Inasmuch as company to borrow money is like buying call, a company''s asset value may be measure by option pricing. This study emulates the credit risk computation model of KMV Company by the computation of company default probability in three steps: a. computation of company asset value b. computation of distant from default c. computation of expected default probable In the first step this study uses semi-standard deviation and standard deviation of unusual return in stead of standard deviation of stock return. Moreover, TCRI score is used in place of assets return standard deviation as well. In conclusion, this study finds out that prediction for default risk is more accurate if TCRI score is used in place of standard deviation of assets return.
Книги з теми "Credit risk measure"
Tarashev, Nikola A. Modelling and calibration errors in measures of portfolio credit risk. Basel, Switzerland: Bank for International Settlements, 2007.
Знайти повний текст джерелаNavigating through the risks of credit card processing. Royal Oak, Michigan: MPCT Publishing Company, 2010.
Знайти повний текст джерелаRozhdestvenskaya, Tat'yana, and Aleksey Guznov. Banking supervision in the Russian Federation. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1693531.
Повний текст джерелаBarkley, Thomas. Energy Risk Management. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190656010.003.0024.
Повний текст джерелаFiordelisi, Franco, Corrado Meglio, Carlo Palego, Annalissa Richetto, Artem Danko, Maurizio Vallino, Pasqualina Porretta, Lorenzo Bocchi, Carlo Toffano, and Andrea Favretti. Pricing and risk adjusted measures. AIFIRM, 2021. http://dx.doi.org/10.47473/2016ppa00027.
Повний текст джерелаSimon, Gleeson. Part III Investment Banking, 17 Derivatives, Clearing, and Exposures to CCPs. Oxford University Press, 2018. http://dx.doi.org/10.1093/law/9780198793410.003.0017.
Повний текст джерелаBesedovsky, Natalia. Uncertain Meanings of Risk. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198820802.003.0011.
Повний текст джерелаSimon, Gleeson. Part III Investment Banking, 12 The Trading Book. Oxford University Press, 2018. http://dx.doi.org/10.1093/law/9780198793410.003.0012.
Повний текст джерелаTorluccio, Giuseppe, Paolo Palliola, Paola Brighi, Lorenzo Dal Maso, Antonio Ciccaglione, Francesca Pampurini, and Anna Grazia Quaranta. IFRS9 e le sfide di contesto. AIFIRM, 2021. http://dx.doi.org/10.47473/2016ppa00032.
Повний текст джерелаSimon, Grieser, and Mecklenburg Christian. 6 The Revision of the Credit Derivative Definitions in the Context of the Bank Recovery and Resolution Directive. Oxford University Press, 2016. http://dx.doi.org/10.1093/law/9780198754411.003.0006.
Повний текст джерелаЧастини книг з теми "Credit risk measure"
Karminsky, Alexander, and Andrey Polozov. "Credit Ratings as A Financial Risk Measure." In Handbook of Ratings, 27–61. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39261-5_2.
Повний текст джерелаSantana, Patricia Jimbo, Laura Lanzarini, and Aurelio F. Bariviera. "FRvarPSO as an Alternative to Measure Credit Risk in Financial Institutions." In Lecture Notes in Networks and Systems, 419–34. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82196-8_31.
Повний текст джерелаSánchez, Mónica, Francesc Prats, Núria Agell, and Xari Rovira. "Kernel Functions over Orders of Magnitude Spaces by Means of Usual Kernels. Application to Measure Financial Credit Risk." In Current Topics in Artificial Intelligence, 415–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25945-9_41.
Повний текст джерелаAnolli, Mario. "Risk-Adjusted Performance Measures." In Retail Credit Risk Management, 134–47. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137006769_7.
Повний текст джерелаCarlone, Giulio. "Generation of a Simulation of a Real-World Case for Generating Exposure Regulatory Measures." In Introduction to Credit Risk, 23–28. First edition | Boca Raton : C&H/CRC Press, 2020. |: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781003036944-5.
Повний текст джерелаCarlone, Giulio. "Real-World Case of the Practical Phase for Generating Exposure Regulatory Measures in a Specific Bank with an Internal Model Method." In Introduction to Credit Risk, 13–18. First edition | Boca Raton : C&H/CRC Press, 2020. |: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781003036944-3.
Повний текст джерелаCarlone, Giulio. "Theoretical Approach of the Real-World Case Phase Related to the Methodology of Scenario Simulation Used for Generating Exposure Regulatory Measures." In Introduction to Credit Risk, 19–21. First edition | Boca Raton : C&H/CRC Press, 2020. |: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781003036944-4.
Повний текст джерелаPapanastasiou, Thomas-Nektarios. "The Implications of Political Risk Insurance in the Governance of Energy Projects: Τhe Case of Japan’s Public Insurance Agencies." In Public Actors in International Investment Law, 155–78. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58916-5_9.
Повний текст джерелаBindseil, Ulrich, and Alessio Fotia. "Conventional Monetary Policy." In Introduction to Central Banking, 29–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70884-9_3.
Повний текст джерелаStoian, Mirela-Madalina, and Rares-Gabriel Stoian. "Financial Risk Management." In Managing Project Risks for Competitive Advantage in Changing Business Environments, 301–11. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0335-4.ch015.
Повний текст джерелаТези доповідей конференцій з теми "Credit risk measure"
Sotiropoulos, Dionisios N., Michael Papasimeon, and Gregory Koronakos. "A Genetically Evolved Measure of Credit-Risk." In 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai52525.2021.00219.
Повний текст джерелаChen, Honglin, and Neng Jiang. "Empirical Study on Logistic Model and KMV Model to Measure Credit Risk of China's Manufacturing Listed Companies." In Fifth Symposium of Risk Analysis and Risk Management in Western China (WRARM 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/wrarm-17.2017.26.
Повний текст джерелаHyde, A., S. Park, J. McFadden, and A. Graettinger. "Examining Credit Score as a Surrogate Measure of Risk to Improve Traffic Crash Prediction—California Case Study." In International Conference on Transportation and Development 2021. Reston, VA: American Society of Civil Engineers, 2021. http://dx.doi.org/10.1061/9780784483534.012.
Повний текст джерелаDunkel, Jorn, and Stefan Weber. "Efficient Monte Carlo methods for convex risk measures in portfolio credit risk models." In 2007 Winter Simulation Conference. IEEE, 2007. http://dx.doi.org/10.1109/wsc.2007.4419692.
Повний текст джерелаSKAČKAUSKIENĖ, Ilona, and Anastasija BUSARĖVA. "RESEARCH OF THE EFFICIENCY OF LITHUANIAN BANKS CREDIT GRANTING PROCESS." In International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering". Vilnius Gediminas Technical University, 2021. http://dx.doi.org/10.3846/cibmee.2021.577.
Повний текст джерелаGo, Tanaka, Sato Takashi, Komori Yuji, and Matsumoto Keiji. "iB1350: Part 2 — Level1 PRA Considering Optimization of Safety Systems for the iB1350." In 2018 26th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icone26-82552.
Повний текст джерелаCrivellari, Anna, Alessandro Tugnoli, Costanza Martina, Sarah Bonvicini, and Valerio Cozzani. "Inherently Safer Choices in Early Design of Offshore Oil and Gas Installations: A Multi-Target KPI Approach." In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-77700.
Повний текст джерелаMa, Ying, and Minmin Zhang. "Notice of Retraction: The forming mechanism of e-business credit risk and precautionary measures." In 2011 International Conference on E-Business and E-Government (ICEE). IEEE, 2011. http://dx.doi.org/10.1109/icebeg.2011.5881415.
Повний текст джерелаZhang, Xiaoyan. "Research on the Risk Rating and Risk Control Measures on E-commerce Credit based on Nash Game Analysis." In 2016 International Conference on Economics, Social Science, Arts, Education and Management Engineering. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/essaeme-16.2016.110.
Повний текст джерелаGarud, Y. S., and David A. Steininger. "A Rational Basis for Deterministic Margins in CUF-Based Fatigue Evaluation With Uncertainty." In ASME 2015 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/pvp2015-45806.
Повний текст джерелаЗвіти організацій з теми "Credit risk measure"
Gamboa-Estrada, Fredy, and Jose Vicente Romero. Modelling CDS Volatility at Different Tenures: An Application for Latin-American Countries. Banco de la República de Colombia, May 2022. http://dx.doi.org/10.32468/be.1199.
Повний текст джерелаAna Kristel, Lapid, Rogelio Mercado Jr, and Peter Rosenkranz. Concentration in Asia’s Cross-Border Banking: Determinants and Impacts. Asian Development Bank, May 2021. http://dx.doi.org/10.22617/wps210170-2.
Повний текст джерелаVargas-Herrera, Hernando, Juan Jose Ospina-Tejeiro, Carlos Alfonso Huertas-Campos, Adolfo León Cobo-Serna, Edgar Caicedo-García, Juan Pablo Cote-Barón, Nicolás Martínez-Cortés, et al. Monetary Policy Report - April de 2021. Banco de la República de Colombia, July 2021. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr2-2021.
Повний текст джерелаFinancial Stability Report - First Semester of 2020. Banco de la República de Colombia, March 2021. http://dx.doi.org/10.32468/rept-estab-fin.1sem.eng-2020.
Повний текст джерелаFinancial Stability Report - Second Semester of 2020. Banco de la República de Colombia, March 2021. http://dx.doi.org/10.32468/rept-estab-fin.sem2.eng-2020.
Повний текст джерелаPayment Systems Report - June of 2021. Banco de la República, February 2022. http://dx.doi.org/10.32468/rept-sist-pag.eng.2021.
Повний текст джерелаMonetary Policy Report - July 2022. Banco de la República, October 2022. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr3-2022.
Повний текст джерела