Table of Contents

Academic Term (Anno Accademico) 2016/2017: financial economics

  • Teaching load: 63 hours (ECTS credits 9)
  • Lecturers: BOTTAZZI Giulio and GIACHINI Daniele
  • Teaching Assistant: SANTI Caterina
  • Semester: Fall
  • Outline: This course aim to provide a modern theoretical foundation to the most widespread notions and tools in modern finance, including present value theory, real interest rate, arbitrage pricing, portfolio allocation and mean-variance analysis.
  • Objectives: The students should become acquainted with the notion of arbitrage and equilibrium price in different market settings. They should be able to solve the problem of portfolio optimization and mean-variance analysis in rather general terms.
  • Description: General equilibrium, no arbitrage in riskless economies, real interest rate and the yield curve. Arbitrage in security markets, state prices, complete and incomplete markets, valuation functional and the fundamental theorem of finance. Choices under uncertainty, expected utility theory and risk aversion. Portfolio choices, optimal portfolio with multiple risky assets. General equilibrium under uncertainty. Pricing kernel and mean-variance analysis. OPTIONAL: behavioral finance, asset prices under ambiguity, evolutionary finance and the market selection hypothesis.
  • Textbooks:
    Principles of Financial Economics, S.F. LeRoy and J. Werner
    Foundations of Financial Markets and Institutions, Fabozzi, Modigliani and Jones
  • Further references and Optional readings:

    Microeconomic Theory, A. Mas-Colell, M. D. Whinston, and J. R. Green
    Quantitative Financial Economics, K. Cuthbertson and D. Nitzsche
    Financial Economics, T. Hens and M. O. Rieger
    Ambiguity and Asset Markets, L. G. Epstein and M. Schneider, NBER paper;
    Options, Futures and Other Derivatives, J. C. Hull (7th ed.)
    The Ascent of Money: A Financial History of the World, Niall Ferguson
    Guide to the Financial Markets, The Economist

    see the syllabus for references to specific parts of these books.

  • Prerequisites: The course requires a knowledge of linear algebra (linear space, linear map, basis, inversion, eigenvectors and eigensystems), calculus (differential analyses of function of many real variables and static optimization) and, to a lesser extent, probability theory. Some basic knowledge of the theory of choice under uncertainty (utility theory) and economic equilibrium are in general given for granted and only cursorily reviewed.
  • Prerequisites suggested reading (relevant chapters): C. P. Simon, L. E. Blume, Mathematics for Economists, H. R. Varian Microeconomic Analysis.
  • Keywords: financial economics, general equilibrium, arbitrage, asset pricing, optimization
  • Final exam: the get the final grading students are required to pass a final written exam. At least one trial exam will be organized to test your level of preparation. Students get extra points for completing their homework during the course.
  • Calendar: check "Financial Economics" entries for the lectures timetable and locations

List of lectures. To have a guess about actual lectures check the previous years but consider that your mileage may vary.

  1. Introduction: the structure of the course and its textbooks; the role of financial institutions slides (Textbooks sections: [FBJ] Ch. 1, 2 and 3; [Ni] Ch. 1; [Eco] Ch. 1)
  2. The notion of economic equilibrium; Two agents, two goods, one date model. The role of prices.
  3. Two date model. Spot and forward markets. Financial equilibrium.
  4. Present value prices and economic equilibrium. Redundant contracts; the role of arbitrage in setting prices.
  5. Real and nominal interest rate; The role of inflation; Pricing of future contracts. (Textbooks sections: FBJ] Ch. 4 and 5 [Hu] Sections from 4.1 to 4.8 all Chapter 5 and section from 6.1 to 6.3 [Ni] Ch. 2) [Assignment 1]
  6. Inter-temporal allocation in a one good two date model: the role of preferences and endowments.
  7. Structure of security markets with uncertainty; complete market and redundant assets; Left and right matrix inverse; (Textbook sections: [LRW] 1.6)
  8. Exercises and solutions of Assignment 1.
  9. Payoff pricing correspondence; the Law of One Price; state claims and state prices (Textbook sections: [LRW] 2.1, 2.3, 2.4, 2.5)
  10. Arbitrage and valuation: strong and weak arbitrage; positive pricing; the payoffs convex cone; Farkas' Lemma; the valuation functional and strong arbitrage; (Textbook sections: [LRW] 3.2, 3.3, 3.4, 3.5, 5.1)
  11. Stiemke's Lemma; the valuation functional and arbitrage; Arbitrage and valuation: the fundamental theorem of finance; multiplicity of valuation functionals; risk neutral probabilities; (Textbook sections: [LRW] 5.2, 5.3, 5.5, 6.3, 6.4, 6.5, 6.6, 6.7;) [Assignment 2]
  12. Valuation of derivatives in a two date model: forward and future
  13. Put and call options. the role of options in completing the market (see the discussion of forward and future contracts in [Hu] Ch.1-3)
  14. Exercises and solutions of Assignment 2
  15. Choices under uncertainty: consumption and portfolio choices, Expected Utility Theory, separable and time invariant utilities; risk aversion; absolute and relative risk aversion coefficients; certainty equivalent; (Textbook sections: [LRW] 9.2, 9.3, 9.4, 9.5, 9.6, 9.8)
  16. Concave transformation; comparison of utility functions; first and second order stochastic dominance; (Textbook sections: the proves of the theorems can also be found in [MWG] Ch.6 Sec.B; further examples are discussed in [CN] Ch.1 Sec.3-5)
  17. Portfolio optimization: first order conditions; arbitrage and optimal portfolio, optimal consumption, prices and returns. (Textbook sections: [LRW] 1.4, 1.5, 2.6, 3.6, 11.1, 11.2; see [CN] Ch.15 for an introductory discussion of the problem)
  18. Portfolio optimization with one risky security: impact of wealth on optimal investment; exercises (Textbook sections: [LRW ]12.2)
  19. Portfolio optimization with several risky securities: from consumption to investment optimization; risk-return trade off; optimal portfolio under fair pricing; (Textbook sections: [LRW] 13.2, 13.3, 13.4, 9.9, 13.6)
  20. Portfolio optimization with several risky securities: Linear Risk tolerance [Assignment 4]
  21. Constrained utility maximization. [Assignment 3]
  22. Orthogonal projection and scalar product, expectations kernel, pricing kernel (Textbook sections: from 17.1 to 17.10, 18.5)
  23. Mean-variance frontier payoffs and mean-variance frontier returns with complete and incomplete markets.
  24. Zero-Covariance Frontier Returns, Sharpe Ratio of mean-variance frontier returns (Textbook sections: 18.1, 18.2 and Th. 18.2.1 with proof 18.4, 18.6; see also the discussion in [CN] Ch.15 Sec.1-2)
  25. Exercises and solutions of Assignment 4
  26. Economic equilibrium; Example with heterogeneous agents, log-utilities and Arrow securities.
  27. Economic equilibrium; representative agent model; equilibrium sufficient conditions; equilibrium and arbitrage. (Textbook sections: [LRW] 1.7, 1.8, 1.9, 2.4, 3.7)
  28. Consumption based security pricing; a first derivation of CAPM;, the social planner problem; equilibrium and Pareto optimality, first and second welfare theorems; (Textbook sections: [LRW] 14.2, 14.3, 14.5, 15.2, 15.3, 15.4, 15.5, without theorem 15.5.1)
  29. Introduction to otimal betting and Kelly rule
  30. Exercises and solutions of Assignment 5
  31. Simulated exam
  32. Correction and discussion of the exercises of the simulated exam

Data for Assignment 5: weekly closing prices of America Corporation (BAC), General Electric Company (GE), Ford Motor Co. (F), Citigroup, Inc. (C), Pfizer Inc. (PFE), Hewlett-Packard Company (HPQ), JPMorgan Chase & Co. (JPM), AT&T, Inc. (T), Wells Fargo & Company (WFC) and J. C. Penney Company, Inc. (JCP)

Academic Term (Anno Accademico) 2016/2017: advanced calculus

The aim of the course is to provide a deepest introduction to the basic tools and theorems of mathematical calculus. It is taught as a companion courses for second and third year students. Undergraduate courses in the first and second years are oriented to provide a specific set of computational procedures to be applied to the solution of specific problems. The present course might constitute a good complement as it is more concerned with the definition and study of general notions and it is characterized by a theorem-proving approach.

  • Teaching load: 40 hours (ECTS credits 3)
  • Lecturer : BOTTAZZI Giulio
  • Semester: Spring
  • Textbook: Notes directly provided by the teacher
  • Further references and Optional readings: Principles of Mathematical Analysis, W.A. Rudin, chapters 3, 6 and 9
  • Prerequisites: The course requires a knowledge of linear algebra (linear space, linear map, basis, determinant, inversion, eigenvectors) and basic calculus.

List of topics covered by the lectures (not necessarily in this order)


  • Sets, equivalence relations and functions
  • Order relations, upper and lower bounds, supremum and infimum
  • Countable sets
  • Real numbers

Introduction to topology and metric spaces:

  • Topological spaces
  • Compact and connected sets
  • Basis of a topology
  • Countable spaces
  • Continuity
  • Notion of distance and induced topology

Sequences in Metric Spaces:

  • Cauchy sequences.
  • Limit of sequences and sub-sequences.
  • Comparison theroem for limit of sequences.
  • The number e as a limit of a sequence.


  • Series as limit of partial sums.
  • Root, ratio and comparison tests for series.

Functions and Limits on Metric Spaces:

  • Notion of limit of function in a metric space.
  • Properties of limit (sum, ratio and product of limits)

Limits of Real Functions:

  • Some important limits.
  • Properties of limits of functions (comparison test)
  • The number e as limit of a function.

Continuity of Real Functions:

  • Uniform continuity.
  • Weiestrass Theorem.

Real functions:

  • Properties of derivatives.
  • Continuity and differential.
  • Lagrange theorem.
  • de L'Hopital rule and application.
  • Derivatives of fundamental functions.

Functions of several real variables:

  • Continuity in Euclidean spaces
  • Derivative and differential
  • Concavity and convexity
  • Local and global maxima and minima

Academic Term (Anno Accademico) 2016/2017: Probability, Certainty and Security in Economics, Part I

  • Teaching load: 24 hours (ECTS credits 9)
  • Lecturer: BOTTAZZI Giulio
  • Semester: Spring
  • Prerequisites: Basic mathematical skills. A previous basic knowledge of economic notions is helpful.
  • References: S.O. Hansson, Decision Theory: a brief introduction, M.D. Resnik, Choices, P.L. Berstain, Against the Gods: The Remarkable Story of Risk,

This is the first part of a two part course taught in the MISS master programme in Political Science.

The course is aimed at familiarizing students with the concepts of risk, uncertainty and security in micro and macro economics and their present and historical role in economic reasoning. After the introduction of the basic mathematical tools, the course cover the basics of decision making under uncertainty, its normative and positive aspects and its role in modern economic institutions. Through discussion of notable examples the students will see the application of these concepts to practical issues

By the end of this part of the course students should:

  • Understand the problem of decision theory under uncertainty,
  • Be able to apply the notion of expected payoff and expected utility to practical example,
  • Be able to distinguish between the normative content of decision theory and the positive findings about human decision process in uncertain environment.

List of lectures:

  1. Short history of risk (1/2)
  2. Short history of risk (2/2)
  3. Expected payoff in games of chance (1/2)
  4. Expected payoff in games of chance (2/2)
  5. Utility theory: non satiating hypothesis, decreasing marginal utility
  6. Expected utility theory, certainty equivalent
  7. The role of wealth and preferences in decision making
  8. Paradoxes and behavioral approach (1/2)
  9. Paradoxes and behavioral approach (2/2)
  10. Individual probability and Bayesian updating (1/2)
  11. Individual probability and Bayesian updating (2/2)
  12. Trial exam (with solutions)

Author: Giulio Bottazzi

Created: 2017-07-18 Tue 10:35