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Titlebook: Credit-Risk Modelling; Theoretical Foundati David Jamieson Bolder Book 2018 Springer International Publishing AG, part of Springer Nature 2

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書(shū)目名稱Credit-Risk Modelling
副標(biāo)題Theoretical Foundati
編輯David Jamieson Bolder
視頻videohttp://file.papertrans.cn/240/239650/239650.mp4
概述Demonstrates a broad range of state-of-the-art credit-risk models and underscores their interlinkages.Includes extensive Python code to bring the models, diagnostic tools, and estimation of key inputs
圖書(shū)封面Titlebook: Credit-Risk Modelling; Theoretical Foundati David Jamieson Bolder Book 2018 Springer International Publishing AG, part of Springer Nature 2
描述The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios is an area of ongoing and increasing importance for finance practitioners. It is, unfortunately, a topic with a high degree of technical complexity. Addressing this challenge, this book provides a comprehensive and attainable mathematical and statistical discussion of a broad range of existing default-risk models. Model description and derivation, however, is only part of the story. Through use of exhaustive practical examples and extensive code illustrations in the Python programming language, this work also explicitly shows the reader how these models are implemented. Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study. The entire work is also liberally supplemented with model-diagnostic, calibration, and parameter-estimation techniques to assist the quantitative analyst in day-to-day implementation as well as in mitigating model risk. Written by an active and experienced practitioner, it is an invaluable learning r
出版日期Book 2018
關(guān)鍵詞python code; monte carlo; financial engineering; model risk; risk modeling; default risk; binomial models;
版次1
doihttps://doi.org/10.1007/978-3-319-94688-7
isbn_softcover978-3-030-06900-1
isbn_ebook978-3-319-94688-7
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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The Genesis of Credit-Risk Modellingo the genesis of the field of credit-risk modelling. This chapter focuses exclusively on this approach. Not only would it be an injustice to ignore this still-pertinent model, but it offers a range of useful insights into the class of threshold models. The Merton (1974, ., 449–470) framework was con
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A Regulatory Perspectivesions. Regulators, in a slightly alternative context, perform a similar task. They face, however, a rather different set of constraints and objectives. Regulators, in fact, use standardized models to promote fairness, a level playing field, monitor the solvency of individual entities, and enhance ov
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Monte Carlo Methodsnveterately in previous chapters. Care and caution are always advisable when employing a complex numerical technique. Prudence is particularly appropriate, in this context, because default is a rare event. Unlike the asset-pricing setting, where we typically simulate expectations in the central part
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Default and Asset Correlationn of default probabilities, addressed in the previous chapter, the characterization of default dependence is model dependent rendering this task more difficult. Since different models incorporate the relationship between obligor defaults in alternative ways, dependence is governed by some subset of
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Bestehende und potenzielle Wettbewerber, default, the following discussion thus walks through its implementation—both numerically and analytically—in the context of our concrete portfolio example. It also explores its asymptotic properties and provides an alternative entry point, which will aid in expanding this foundation in the followin
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