A First Course in Model Validation and Model Risk Management offers robust coverage for current and future financial engineers. Useful as part of a masters program, for self-study, or as a valuable reference, the textbook explains in step-by-step, practical terms how mathematical models owned by financial institutions are essential to their public activities, including sales, trading, risk management, and internal audits. Like a diverse fleet of cars maintained by a rental car location, a bank must make sure customers can "drive" any of its models for a specific financial product. The book covers both pricing and risk models. Chapters consider modeling basics, marked-to-market and marked-to-model asset classes, market risk, credit risk, portfolio risk, operational risk, capital model risk, and financial crime, along with machine learning/AI.
To support course use and practical applications, the text provides examples in Python throughout, as well as an appendix containing homework problems for all chapters, further supported by an ftp site for data and sample code. Additional appendices cover global model risk management, and a refresher in statistics.
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Jonathan Schachter holds a PhD from University of California, Berkeley, and has over 23 years of experience as a model risk professional, with a practical background in market risk, portfolio risk, operational risk, capital model risk, and AI risk. Currently Jonathan is CEO and Founder of Delta Vega Inc, and has previously held positions at Jefferies Financial and Citibank, among other firms.
Martin Goldberg holds a PhD from City University of New York, and is Vice President in Model Validation at Mizuho Americas. He has held past positions at Citigroup, Bloomberg, AIG, and Chase Manhattan Bank. He is also on the Board of Directors for Rutgers University (Newark), for their Master of Quantitative Finance (MQF) Program, and has presented widely at conferences and universities on topics related to model risk assessment.
Chandrakant Maheshwari is a seasoned expert in model validation with over 20 years of experience in financial risk analytics. An alum of the Indian Institute of Technology, Delhi, he is also an avid blogger and regularly publishes articles on model validation, sharing his extensive knowledge and insights in the field, and works in the financial sector.
A First Course in Model Validation and Model Risk Management offers robust coverage for current and future financial engineers. Useful as part of a masters program, for self-study, or as a valuable reference, the textbook explains in step-by-step, practical terms how mathematical models owned by financial institutions are essential to their public activities, including sales, trading, risk management, and internal audits. Like a diverse fleet of cars maintained by a rental car location, a bank must make sure customers can "drive" any of its models for a specific financial product. The book covers both pricing and risk models. Chapters consider modeling basics, marked-to-market and marked-to-model asset classes, market risk, credit risk, portfolio risk, operational risk, capital model risk, and financial crime, along with machine learning/AI.
To support course use and practical applications, the text provides examples in Python throughout, as well as an appendix containing homework problems for all chapters, further supported by an ftp site for data and sample code. Additional appendices cover global model risk management, and a refresher in statistics.
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Taschenbuch. Zustand: Neu. Neuware -A First Course in Model Validation and Model Risk Management offers robust coverage for current and future financial engineers. Useful as part of a masters program, for self-study, or as a valuable reference, the textbook explains in step-by-step, practical terms how mathematical models owned by financial institutions are essential to their public activities, including sales, trading, risk management, and internal audits. Like a diverse fleet of cars maintained by a rental car location, a bank must make sure customers can 'drive' any of its models for a specific financial product. The book covers both pricing and risk models. Chapters consider modeling basics, marked-to-market and marked-to-model asset classes, market risk, credit risk, portfolio risk, operational risk, capital model risk, and financial crime, along with machine learning/AI.To support course use and practical applications, the text provides examples in Python throughout, as well as an appendix containing homework problems for all chapters, further supported by an ftp site for data and sample code. Additional appendices cover global model risk management, and a refresher in statistics. 582 pp. Englisch. Bestandsnummer des Verkäufers 9780443337468
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Taschenbuch. Zustand: Neu. Neuware -A First Course in Model Validation and Model Risk Management offers robust coverage for current and future financial engineers. Useful as part of a masters program, for self-study, or as a valuable reference, the textbook explains in step-by-step, practical terms how mathematical models owned by financial institutions are essential to their public activities, including sales, trading, risk management, and internal audits. Like a diverse fleet of cars maintained by a rental car location, a bank must make sure customers can 'drive' any of its models for a specific financial product. The book covers both pricing and risk models. Chapters consider modeling basics, marked-to-market and marked-to-model asset classes, market risk, credit risk, portfolio risk, operational risk, capital model risk, and financial crime, along with machine learning/AI.To support course use and practical applications, the text provides examples in Python throughout, as well as an appendix containing homework problems for all chapters, further supported by an ftp site for data and sample code. Additional appendices cover global model risk management, and a refresher in statistics. 582 pp. Englisch. Bestandsnummer des Verkäufers 9780443337468
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Taschenbuch. Zustand: Neu. Neuware -A First Course in Model Validation and Model Risk Management offers robust coverage for current and future financial engineers. Useful as part of a masters program, for self-study, or as a valuable reference, the textbook explains in step-by-step, practical terms how mathematical models owned by financial institutions are essential to their public activities, including sales, trading, risk management, and internal audits. Like a diverse fleet of cars maintained by a rental car location, a bank must make sure customers can 'drive' any of its models for a specific financial product. The book covers both pricing and risk models. Chapters consider modeling basics, marked-to-market and marked-to-model asset classes, market risk, credit risk, portfolio risk, operational risk, capital model risk, and financial crime, along with machine learning/AI.To support course use and practical applications, the text provides examples in Python throughout, as well as an appendix containing homework problems for all chapters, further supported by an ftp site for data and sample code. Additional appendices cover global model risk management, and a refresher in statistics. Bestandsnummer des Verkäufers 9780443337468
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Zustand: New. Offers practical concepts for learning model validation and model risk managementExplains how to use Python-based models to assess and manage model riskCovers the US gold standard of model risk, Federal Reserve Board SR 11-7 , inc. Bestandsnummer des Verkäufers 2666003638
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Taschenbuch. Zustand: Neu. Neuware - A First Course in Model Validation and Model Risk Management offers robust coverage for current and future financial engineers. Useful as part of a masters program, for self-study, or as a valuable reference, the textbook explains in step-by-step, practical terms how mathematical models owned by financial institutions are essential to their public activities, including sales, trading, risk management, and internal audits. Like a diverse fleet of cars maintained by a rental car location, a bank must make sure customers can 'drive' any of its models for a specific financial product. The book covers both pricing and risk models. Chapters consider modeling basics, marked-to-market and marked-to-model asset classes, market risk, credit risk, portfolio risk, operational risk, capital model risk, and financial crime, along with machine learning/AI.To support course use and practical applications, the text provides examples in Python throughout, as well as an appendix containing homework problems for all chapters, further supported by an ftp site for data and sample code. Additional appendices cover global model risk management, and a refresher in statistics. Bestandsnummer des Verkäufers 9780443337468
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