Course Title Course Level Domain Language Nb. Face to Face Hours E-learning Support ECTS

Risk, investment and insurance analysis Graduate Economics English 36 (3hrs. sessions) Mycourse yes 6

Course Title Risk, investment and insurance analysis

Professor Maria Luisa Ratto Contact Information Email : [email protected]

Language English

Overview (min 5 lines) This course is an advanced microeconomics course that focuses on insurance and financial investment decisions. The decision of full insurance is compared to the decision of partial insurance and the conditions for the optimality of the two are considered, under both symmetric and asymmetric information. After reviewing the types of financial markets and the types of assets traded, the course considers the measurement of return and risk of single assets and of a portfolio. The Markowitz model is presented to illustrate how single investors choose their optimal portfolio. The analysis is extended to all investors (CAPM model) to gain some understanding of how equilibrium prices are determined in financial markets.

Prerequisites Fundamentals of microeconomic theory: 1) Consumer choice theory. The analysis of optimal consumer choice under certainty (types of consumers’ preferences, indifference curves, budget constraint, relative prices, optimal consumption choice). 2) The utility framework: assumptions on the properties of individual preferences. 1

Fundamentals of Maths : derivatives, rules of differentiation, constrained optimization problems. Fundamentals of Stats: The moments of a distribution: mean, median and standard deviation.

Course Objectives The aim of this course is to learn the key tools and concepts to analyse how decision makers choose from a set of feasible alternatives when the consequences or outcomes are uncertain. These analytical tools are then applied to real-life economic and financial decisions, like the purchase of insurance and the trading of financial assets in financial markets, to gain some insights on how those markets work

Learning Outcomes Students will be provided with the key insights of theoretical models to understand why decisions such as full versus partial insurance are taken. The overview of the basic models of investors’ behaviour shall also provide students with a fundamental knowledge of investment theory. At the end of the course students should be able to compare investments in different assets by evaluating the expected return to maturity and to calculate the return and variance of a portfolio. This knowledge should help the reading of the financial press and should make students aware that the ability of a successful financial advisor stems from understanding the underlying theoretical concepts of investment decisions.

Mode of Assessment 50%(midterm test result+participation evaluation)+50% final exam result. Participation evaluation: overall attendance and participation in class and effort to solve exercises on a weekly basis. The mark for participation can vary from -2/20 to +2/20.

Course Schedule (11 weeks) 1 2

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Decision making under conditions of certainty and under conditions of risk: basic features The expected utility hypothesis: the von Neumann Morgenstern axioms. Expected utility and indifference curves over state-contingent commodities Risk attitudes: risk aversion, risk loving and risk neutrality The purchase of insurance. Optimal choice of insurance: full and partial insurance in competitive insurance markets under symmetric information Asymmetric information: adverse selection in competitive insurance markets Asymmetric information: moral hazard in competitive insurance markets The measurement of financial returns of single assets and of portfolios The measurement of risk of single assets and of portfolios Definition of Efficient portfolios Definition of Optimal portfolios. The Markowitz model The CAPM model: how equilibrium asset prices are set.

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Bibiography Main textbooks: Ø Eeckhoudt, L., Gollier C., Schlesinger, H. (2005), Economic and Financial Decisions under Risk, Princeton University Press. Chapters 1, 2, 3, 6, 12. Ø Elton, E., Gruber, M., Brown, S., and Goetzmann, W. (2003), Modern Portfolio Theory and Investment Analysis, John Wiley & Son, 6th edition. Chapters 1, 2, 3, 4, 5, 7, 13. Ø Timothy Van Zandt (2006) Introduction to the Economics of Uncertainty and Information. Chapters 1, 2, 5, 6, 11. Other recommended readings: o Besanko, D, Braeutigam, R, (2008), Microeconomics, John Wiley & Son, 3rd edition Chapters 3 and 4 . o Copeland, T., Weston, F. (1946) Financial Theory and Corporate Policy, AddisonWesley, Chapter 6. o Hargreaves Heap, S et al (1992), The Theory of Choice: A Critical Guide, Blackwell, Part I. o Hirshleifer, J and JG Riley (1979), The Analytics of Uncertainty and Information – An Expository Survey, Journal of Economic Literature, vol. 17 (4), pp. 1375-1421 o Lintner, J. , Security Prices, Risk and Maximal gains from diversification, Journal of Finance, 1965, 587-616. o Markowitz, H, Portfolio selection, Journal of Finance, 1952, 77-91. o Markowitz, H, Foundations of Portfolio Theory, Journal of Finance, 1991, 469-477 o Sharpe, W., Capital Asset Prices: a theory of market equilibrium under conditions of risk, Journal of Finance, 1969, 425-442.

MyCourse This course is on MyCourse : Yes

Grading The numerical grade distribution will dictate the final grade. Class participation: Active class participation – this is what makes classes lively and instructive. Come on time and prepared. Class participation is based on quality of comments, not quantity. Exam policy: In the exam, students will not be allowed to bring any document (except if allowed by the lecturer). Unexcused absences from exams or failure to submit cases will result in zero grades in the calculation of numerical averages. Exams are collected at the end of examination periods.

Academic integrity Be aware of the rules in Université Paris Dauphine about plagiarism and cheating during exams. All work turned in for this course must be your own work, or that of your own group. Working as part of a group implies that you are an active participant and fully contributed to the output produced by that group.

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