# Suchergebnis: Katalogdaten im Frühjahrssemester 2021

Mathematik (Allgemeines Angebot) | ||||||

Aktuar SAV Ausbildung an der ETH Zürich Weitere Auskünfte über die Vertiefung in Versicherungsmathematik erteilt das Sekretariat von Prof. M. Wüthrich, HG F 42. | ||||||

Nummer | Titel | Typ | ECTS | Umfang | Dozierende | |
---|---|---|---|---|---|---|

401-3629-00L | Quantitative Risk Management | W | 4 KP | 2V + 1U | P. Cheridito | |

Kurzbeschreibung | This course introduces methods from probability theory and statistics that can be used to model financial risks. Topics addressed include loss distributions, risk measures, extreme value theory, multivariate models, copulas, dependence structures and operational risk. | |||||

Lernziel | The goal is to learn the most important methods from probability theory and statistics used in financial risk modeling. | |||||

Inhalt | 1. Introduction 2. Basic Concepts in Risk Management 3. Empirical Properties of Financial Data 4. Financial Time Series 5. Extreme Value Theory 6. Multivariate Models 7. Copulas and Dependence 8. Operational Risk | |||||

Skript | Course material is available on Link | |||||

Literatur | Quantitative Risk Management: Concepts, Techniques and Tools AJ McNeil, R Frey and P Embrechts Princeton University Press, Princeton, 2015 (Revised Edition) Link | |||||

Voraussetzungen / Besonderes | The course corresponds to the Risk Management requirement for the SAA ("Aktuar SAV Ausbildung") as well as for the Master of Science UZH-ETH in Quantitative Finance. | |||||

401-4920-00L | Market-Consistent Actuarial ValuationFindet dieses Semester nicht statt. | W | 4 KP | 2V | M. V. Wüthrich | |

Kurzbeschreibung | Introduction to market-consistent actuarial valuation. Topics: Stochastic discounting, full balance sheet approach, valuation portfolio in life and non-life insurance, technical and financial risks, risk management for insurance companies. | |||||

Lernziel | Goal is to give the basic mathematical tools for describing insurance products within a financial market and economic environment and provide the basics of solvency considerations. | |||||

Inhalt | In this lecture we give a full balance sheet approach to the task of actuarial valuation of an insurance company. Therefore we introduce a multidimensional valuation portfolio (VaPo) on the liability side of the balance sheet. The basis of this multidimensional VaPo is a set of financial instruments. This approach makes the liability side of the balance sheet directly comparable to its asset side. The lecture is based on four sections: 1) Stochastic discounting 2) Construction of a multidimensional Valuation Portfolio for life insurance products (with guarantees) 3) Construction of a multidimensional Valuation Portfolio for a run-off portfolio of a non-life insurance company 4) Measuring financial risks in a full balance sheet approach (ALM risks) | |||||

Literatur | Market-Consistent Actuarial Valuation, 3rd edition. Wüthrich, M.V. EAA Series, Springer 2016. ISBN: 978-3-319-46635-4 Wüthrich, M.V., Merz, M. Claims run-off uncertainty: the full picture. SSRN Manuscript ID 2524352 (2015). England, P.D, Verrall, R.J., Wüthrich, M.V. On the lifetime and one-year views of reserve risk, with application to IFRS 17 and Solvency II risk margins. Insurance: Mathematics and Economics 85 (2019), 74-88. Wüthrich, M.V., Embrechts, P., Tsanakas, A. Risk margin for a non-life insurance run-off. Statistics & Risk Modeling 28 (2011), no. 4, 299--317. Financial Modeling, Actuarial Valuation and Solvency in Insurance. Wüthrich, M.V., Merz, M. Springer Finance 2013. ISBN: 978-3-642-31391-2 Cheridito, P., Ery, J., Wüthrich, M.V. Assessing asset-liability risk with neural networks. Risks 8/1 (2020), article 16. | |||||

Voraussetzungen / Besonderes | The exams ONLY take place during the official ETH examination period. This course will be held in English and counts towards the diploma of "Aktuar SAV". For the latter, see details under Link. Knowledge in probability theory, stochastic processes and statistics is assumed. | |||||

401-3917-00L | Stochastic Loss Reserving Methods | W | 4 KP | 2V | R. Dahms | |

Kurzbeschreibung | Loss Reserving is one of the central topics in non-life insurance. Mathematicians and actuaries need to estimate adequate reserves for liabilities caused by claims. These claims reserves have influence all financial statements, future premiums and solvency margins. We present the stochastics behind various methods that are used in practice to calculate those loss reserves. | |||||

Lernziel | Our goal is to present the stochastics behind various methods that are used in prctice to estimate claim reserves. These methods enable us to set adequate reserves for liabilities caused by claims and to determine prediction errors of these predictions. | |||||

Inhalt | We will present the following stochastic claims reserving methods/models: - Stochastic Chain-Ladder Method - Bayesian Methods, Bornhuetter-Ferguson Method, Credibility Methods - Distributional Models - Linear Stochastic Reserving Models, with and without inflation - Bootstrap Methods - Claims Development Result (solvency view) - Coupling of portfolios | |||||

Literatur | M. V. Wüthrich, M. Merz, Stochastic Claims Reserving Methods in Insurance, Wiley 2008. | |||||

Voraussetzungen / Besonderes | The exams ONLY take place during the official ETH examination periods. This course will be held in English and counts towards the diploma "Aktuar SAV". For the latter, see details under Link. Basic knowledge in probability theory is assumed, in particular conditional expectations. | |||||

401-3936-00L | Data Analytics for Non-Life Insurance Pricing | W | 4 KP | 2V | C. M. Buser, M. V. Wüthrich | |

Kurzbeschreibung | We study statistical methods in supervised learning for non-life insurance pricing such as generalized linear models, generalized additive models, Bayesian models, neural networks, classification and regression trees, random forests and gradient boosting machines. | |||||

Lernziel | The student is familiar with classical actuarial pricing methods as well as with modern machine learning methods for insurance pricing and prediction. | |||||

Inhalt | We present the following chapters: - generalized linear models (GLMs) - generalized additive models (GAMs) - neural networks - credibility theory - classification and regression trees (CARTs) - bagging, random forests and boosting | |||||

Skript | The lecture notes are available from: Link | |||||

Voraussetzungen / Besonderes | This course will be held in English and counts towards the diploma of "Aktuar SAV". For the latter, see details under Link Good knowledge in probability theory, stochastic processes and statistics is assumed. | |||||

401-3923-00L | Selected Topics in Life Insurance Mathematics | W | 4 KP | 2V | M. Koller | |

Kurzbeschreibung | Stochastic Models for Life insurance 1) Markov chains 2) Stochastic Processes for demography and interest rates 3) Cash flow streams and reserves 4) Mathematical Reserves and Thiele's differential equation 5) Theorem of Hattendorff 6) Unit linked policies | |||||

Lernziel | ||||||

401-3956-00L | Economic Theory of Financial Markets | W | 4 KP | 2V | M. V. Wüthrich | |

Kurzbeschreibung | This lecture provides an introduction to the economic theory of financial markets. It presents the basic financial and economic concepts to insurance mathematicians and actuaries. | |||||

Lernziel | This lecture aims at providing the fundamental financial and economic concepts to insurance mathematicians and actuaries. It focuses on portfolio theory, cash flow valuation and deflator techniques. | |||||

Inhalt | We treat the following topics: - Fundamental concepts in economics - Portfolio theory - Mean variance analysis, capital asset pricing model - Arbitrage pricing theory - Cash flow theory - Valuation principles - Stochastic discounting, deflator techniques - Interest rate modeling - Utility theory | |||||

Voraussetzungen / Besonderes | The exams ONLY take place during the official ETH examination period. This course will be held in English and counts towards the diploma of "Aktuar SAV". For the latter, see details under Link. Knowledge in probability theory, stochastic processes and statistics is assumed. | |||||

363-1017-00L | Risk and Insurance Economics | W | 3 KP | 2G | I. Gemmo | |

Kurzbeschreibung | The course covers the economics of risk and insurance, in particular the following topics will be discussed: 2) individual decision making under risk 3) fundamentals of insurance 4) information asymmetries in insurance markets 5) the macroeconomic role of insurers | |||||

Lernziel | The goal is to introduce students to basic concepts of risk, risk management and economics of insurance. | |||||

Inhalt | “The ability to define what may happen in the future and to choose among alternatives lies at the heart of contemporary societies. Risk management guides us over a vast range of decision-making from allocation of wealth to safeguarding public health, from waging war to planning a family, from paying insurance premiums to wearing a seatbelt, from planting corn to marketing cornflakes.” (Peter L. Bernstein) Every member of society faces various decisions under uncertainty on a daily basis. Many individuals apply measures to manage these risks without even thinking about it; many are subject to behavioral biases when making these decisions. In the first part of this lecture, we discuss normative decision concepts, such as Expected Utility Theory, and contrast them with empirically observed behavior. Students learn about the rationale for individuals to purchase insurance as part of a risk management strategy. In a theoretical framework, we then derive the optimal level of insurance demand and discuss how this result depends on the underlying assumptions. After learning the basics for understanding the specifications, particularities, and mechanisms of insurance markets, we discuss the consequences of information asymmetries in these markets. Insurance companies do not only provide individuals with a way to decrease uncertainty of wealth, they also play a vital role for businesses that want to manage business risk, for the real economy by providing funds and pooling risks, and for the financial market by being important counterparties in numerous financial transactions. In the last part of this lecture, we shed light on these different roles of insurance companies. We compare the implications for different stakeholders and (insurance) markets in general. Finally, course participants familiarize themselves with selected research papers that analyze individuals’ decision-making under risk or examine specific details about the different roles of insurance companies. | |||||

Literatur | Main literature: - Eeckhoudt, L., Gollier, C., & Schlesinger, H. (2005). Economic and Financial Decisions under Risk. Princeton University Press. - Zweifel, P., & Eisen, R. (2012). Insurance Economics. Springer. Further readings: - Dionne, G. (Ed.). (2013). Handbook of Insurance (2nd ed.). Springer. - Hufeld, F., Koijen, R. S., & Thimann, C. (Eds.). (2017). The Economics, Regulation, and Systemic Risk of Insurance Markets. Oxford University Press. - Niehaus, H., & Harrington, S. (2003). Risk Management and Insurance (2nd ed.). McGraw Hill. - Rees, R., & Wambach, A. (2008). The Microeconomics of Insurance, Foundations and Trends® in Microeconomics, 4(1–2), 1-163. |

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