The Analytics Of Risk Model Validation
DOWNLOAD eBooks
Download The Analytics Of Risk Model Validation PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get The Analytics Of Risk Model Validation book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
The Analytics Of Risk Model Validation
DOWNLOAD eBooks
Author : George A. Christodoulakis
language : en
Publisher: Elsevier
Release Date : 2007-11-14
The Analytics Of Risk Model Validation written by George A. Christodoulakis and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-14 with Business & Economics categories.
Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk. *Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk
The Validation Of Risk Models
DOWNLOAD eBooks
Author : S. Scandizzo
language : en
Publisher: Springer
Release Date : 2016-07-01
The Validation Of Risk Models written by S. Scandizzo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-01 with Business & Economics categories.
This book is a one-stop-shop reference for risk management practitioners involved in the validation of risk models. It is a comprehensive manual about the tools, techniques and processes to be followed, focused on all the models that are relevant in the capital requirements and supervisory review of large international banks.
Credit Risk Analytics
DOWNLOAD eBooks
Author : Bart Baesens
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-19
Credit Risk Analytics written by Bart Baesens and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-19 with Business & Economics categories.
The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.
Risk Model Validation
DOWNLOAD eBooks
Author : Christian Meyer
language : en
Publisher:
Release Date : 2011
Risk Model Validation written by Christian Meyer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Risk management categories.
An essential part of a decision-maker's armoury, Risk Model Validation provides an intensive guide to asking the key questions when integrating the outputs of quantitative modeling into everyday business decisions.
Credit Risk Analytics
DOWNLOAD eBooks
Author : Harald Scheule
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-11-23
Credit Risk Analytics written by Harald Scheule and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-23 with Bank loans categories.
Credit risk analytics in R will enable you to build credit risk models from start to finish. Accessing real credit data via the accompanying website www.creditriskanalytics.net, you will master a wide range of applications, including building your own PD, LGD and EAD models as well as mastering industry challenges such as reject inference, low default portfolio risk modeling, model validation and stress testing. This book has been written as a companion to Baesens, B., Roesch, D. and Scheule, H., 2016. Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS. John Wiley & Sons.
Risk Model Validation
DOWNLOAD eBooks
Author : Peter Quell
language : en
Publisher:
Release Date : 2016
Risk Model Validation written by Peter Quell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Risk management categories.
Validation Of Risk Management Models For Financial Institutions
DOWNLOAD eBooks
Author : David Lynch
language : en
Publisher: Cambridge University Press
Release Date : 2023-01-31
Validation Of Risk Management Models For Financial Institutions written by David Lynch and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-31 with Business & Economics categories.
A comprehensive book on validation with coverage of all the risk management models.
Managing Model Risk
DOWNLOAD eBooks
Author : Bart Baesens
language : en
Publisher:
Release Date : 2021-06-30
Managing Model Risk written by Bart Baesens and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-30 with categories.
Get up to speed on identifying and tackling model risk! Managing Model Risk provides data science practitioners, business professionals and analytics managers with a comprehensive guide to understand and tackle the fundamental concept of analytical model risk in terms of data, model specification, model development, model validation, model operationalization, model security and model management. Providing state of the art industry and research insights based on the author''s extensive experience, this illustrated textbook has a well-balanced theory-practice focus and covers all essential topics. Key Features: Extensive coverage of important trending topics and their risk impact on analytical models, starting from the raw data up until the operationalization, security and management. Various examples and case studies to highlight the topics discussed. Key references to background literature for further clarification. An online website with various add-ons and recent developments: www.managingmodelriskbook.com. What Makes this Book Different? This book is based on both authors having worked in analytics for more than 30 years combined, both in industry and academia. Both authors have co-authored more than 300 scientific publications on analytics and machine learning and have worked with firms in different industries, including (online) retailers, financial institutions, manufacturing firms, insurance providers, governments, etc. all over the globe estimating, deploying and validating analytical models. Throughout this time, we have read many books about analytical modeling and data science, which are typically written from the perspective of a theorist, providing lots of details with regards to different model algorithms and related mathematics, but with limited attention being given to how such models are used in practice. If such concerns are tackled, it is mainly from an implementation, use case or data engineering perspective. From our own experience, however, we have encountered many cases where analytics, AI, machine learning etc. fail in organizations, even with skilled people working on them, due to a myriad of reasons: bad data quality, difficulties in terms of model deployment, lack of model buy-in, incorrect definitions of underlying goals, wrong evaluation metrics, unrealistic expectations and many other issues can arise which cause models to fail in practice. Most of these issues have nothing to do with the actual algorithm being used to construct the model, but rather with everything else surrounding it: data, governance, maintenance, business, management, the economy, budgeting, culture etc. As such, we wanted to offer a new perspective with this book: it aims to provide a unique mix of both practical and research-based insights and report on do''s and don''ts for model risk management. Model risk issues are not only highlighted but also recommendations are given on how to deal with them, where possible. Target Audience This book is targeted towards everyone who has previously been exposed to both predictive and descriptive analytics. The reader should hence have some basic understanding of the analytics process model, the key activities of data preprocessing, the steps involved in developing a predictive analytics model (using e.g. linear or logistic regression, decision trees, etc.) and a descriptive analytics model (using e.g. association or sequence rules or clustering techniques). It is also important to be aware of how an analytical model can be properly evaluated, both in terms of accuracy and interpretation. This book aims to offer a comprehensive guide for both data scientists as well as (C-level) executives and data science or engineering leads, decision-makers and managers who want to know the key underlying concepts of analytical model risk.
Credit Risk Model Validation And Monitoring Methods
DOWNLOAD eBooks
Author : Sunil Verma
language : en
Publisher:
Release Date : 2008-02-28
Credit Risk Model Validation And Monitoring Methods written by Sunil Verma and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-28 with categories.
* Credit Risk Model Validation and Monitoring Methods provides a one-stop guide to the latest validation and monitoring techniques.
Analytical Techniques In The Assessment Of Credit Risk
DOWNLOAD eBooks
Author : Michalis Doumpos
language : en
Publisher: Springer
Release Date : 2018-09-29
Analytical Techniques In The Assessment Of Credit Risk written by Michalis Doumpos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-29 with Business & Economics categories.
This book provides a unique, focused introduction to the analytical skills, methods and techniques in the assessment of credit risk that are necessary to tackle and analyze complex credit problems. It employs models and techniques from operations research and management science to investigate more closely risk models for applications within the banking industry and in financial markets. Furthermore, the book presents the advances and trends in model development and validation for credit scoring/rating, the recent regulatory requirements and the current best practices. Using examples and fully worked case applications, the book is a valuable resource for advanced courses in financial risk management, but also helpful to researchers and professionals working in financial and business analytics, financial modeling, credit risk analysis, and decision science.