<p><i>IFRS 9 and CECL Credit Risk Modelling and Validation</i> covers a hot topic in risk management. Both IFRS 9 and CECL accounting standards require Banks to adopt a new perspective in assessing Expected Credit Losses. The book explores a wide range of models and corresponding validation procedures. The most traditional regression analyses pave the way to more innovative methods like machine learning, survival analysis, and competing risk modelling. Special attention is then devoted to scarce data and low default portfolios. A practical approach inspires the learning journey. In each section the theoretical dissertation is accompanied by Examples and Case Studies worked in R and SAS, the most widely used software packages used by practitioners in Credit Risk Management.</p><ul><li>Offers a broad survey that explains which models work best for mortgage, small business, cards, commercial real estate, commercial loans and other credit products</li><li>Concentrates on specific aspects o
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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...
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<p><b>An irreplaceable roadmap to modern risk management from the undisputed masters of the subject </b><p>Edited by a co-founder and the former Chief Risk Officer of BlackRock¿the world¿s largest asset manager¿<i>BlackRock¿s...
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Written by leading market risk academic, Professor Carol Alexander, Practical Financial Econometrics forms part two of the Market Risk Analysis four volume set. It introduces the econometric techniques that are commonly applied to finance with a critical...
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