Actuarial Principles: Lifetables and Mortality Models explores the core of actuarial science: the study of mortality and other risks and applications. Including the CT4 and CT5 UK courses, but applicable to a global audience, this work lightly covers the mathematical and theoretical background of the subject to focus on real life practice. It offers a brief history of the field, why actuarial notation has become universal, and how theory can be applied to many situations. Uniquely covering both life contingency risks and survival models, the text provides numerous exercises (and their…mehr
Actuarial Principles: Lifetables and Mortality Models explores the core of actuarial science: the study of mortality and other risks and applications. Including the CT4 and CT5 UK courses, but applicable to a global audience, this work lightly covers the mathematical and theoretical background of the subject to focus on real life practice. It offers a brief history of the field, why actuarial notation has become universal, and how theory can be applied to many situations. Uniquely covering both life contingency risks and survival models, the text provides numerous exercises (and their solutions), along with complete self-contained real-world assignments.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr Andrew Leung is a fellow of the actuarial professions in both the UK and Australia. He also has post graduate qualifications in pure mathematics and mathematical economics. He has worked for international actuarial consulting firms, in banking, insurance and investment. For more than 10 years he led the professional investment courses for the Australian profession and was the editor of the Australian Actuarial Journal. More recently, he established the actuarial course at Monash University, Melbourne, on which his book is based.
Inhaltsangabe
1. Introduction to Deep Learning and Financial Modeling 2. Deep Learning and Addressing the Class Imbalance Problem 3. Predicting Interest Rates and Spreads Using Deep Learning 4. Predicting Stock Market prices using Deep Learning 5. Predicting Inflation Rates using Deep Learning 6. Analyzing the GDP using Deep Learning 7. Predicting Exchange Rates using Deep Learning 8. Asset Allocation Optimization Using Deep Learning 9. Deep Learning, Credit Scoring and Underwriting 10. Deep Learning and Fraud Detection 11. Deep Learning and Sentiment/News Analysis 12. Banking and Insurance Solvency Capital Calculation Using Deep Learning 13. Insurance Pricing Using Deep Learning 14. Conclusion
1. Introduction to Deep Learning and Financial Modeling 2. Deep Learning and Addressing the Class Imbalance Problem 3. Predicting Interest Rates and Spreads Using Deep Learning 4. Predicting Stock Market prices using Deep Learning 5. Predicting Inflation Rates using Deep Learning 6. Analyzing the GDP using Deep Learning 7. Predicting Exchange Rates using Deep Learning 8. Asset Allocation Optimization Using Deep Learning 9. Deep Learning, Credit Scoring and Underwriting 10. Deep Learning and Fraud Detection 11. Deep Learning and Sentiment/News Analysis 12. Banking and Insurance Solvency Capital Calculation Using Deep Learning 13. Insurance Pricing Using Deep Learning 14. Conclusion
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