Table of Contents

Academic Term (Anno Accademico) 2017/2018: financial economics

  • Teaching load: 63 hours (ECTS credits 9)
  • Lecturers: BOTTAZZI Giulio
  • Teaching Assistant: GIACHINI Daniele
  • Semester: Fall
  • Outline: This course aims to provide a modern theoretical foundation to the most widespread notions and tools in financial economics, including present value theory, real interest rate, arbitrage pricing, portfolio management 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 basic 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 in): 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 fake 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 future 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.
  3. Two date model. Spot and forward markets. Financial equilibrium. The role of arbitrage in setting prices.
  4. Present value prices and economic equilibrium. Redundant contracts.
  5. Real and nominal interest rates; 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 in setting real interest rates. Structure of security markets with uncertainty; complete markets and redundant assets (Textbook sections: [LRW] 1.6)
  7. Exercises and solutions of Assignment 1
  8. Left and right matrix inverse. Payoff pricing correspondence; the Law of One Price; state claims and state prices (Textbook sections: [LRW] 2.1, 2.3, 2.4, 2.5)
  9. Arbitrage and valuation: strong and weak arbitrage; positive pricing; the payoffs convex cone; (Textbook sections: [LRW] 3.2, 3.3, 3.4, 3.5, 5.1)
  10. Farkas' Lemma; the valuation functional and strong arbitrage; 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]
  11. 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; Concave transformation; comparison of utility functions; first and second order stochastic dominance (Textbook sections: [LRW] 9.2, 9.3, 9.4, 9.5, 9.6, 9.8; 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)
  12. Exercises and solutions of Assignment 2
  13. Valuation of derivatives in a two date model: forward and future (see the discussion of forward and future contracts in [Hu] Ch.1-3) [Assignment 3]
  14. 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)
  15. Portfolio optimization with one risky security: impact of wealth on optimal investment; exercises (Textbook sections: [LRW] 12.2).
  16. Exercises and solutions of Assignment 3.
  17. Put and call options. The role of options in completing the market. Exercise: an useful picture and the Octave/Matlab file; (Textbook sections: [LRW] 15.4).
  18. 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)
  19. Portfolio optimization with several risky securities: Linear Risk tolerance, recap on Euclidean spaces, Orthogonal projection and scalar product. [Assignment 4]
  20. Expectations kernel and pricing kernel (Textbook sections: [LRW] from 17.1 to 17.10, 18.5)
  21. Exercises and solutions of Assignment 4.
  22. Again on expectations kernel and pricing kernel (Textbook sections: [LRW] from 17.1 to 17.10, 18.5)
  23. Mean-variance frontier payoffs and mean-variance frontier returns with complete markets.
  24. Mean-variance frontier payoffs and mean-variance frontier returns with complete and incomplete markets. 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). [Assignment 5 see below for data]
  25. Economic equilibrium; representative agent model; equilibrium sufficient conditions; equilibrium and arbitrage. (Textbook sections: [LRW] 1.7, 1.8, 1.9, 2.4, 3.7)
  26. 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)
  27. Exercises and solutions of Assignment 4.
  28. Simulated exam
  29. 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) 2017/2018: advanced calculus

The aim of the course is to provide a deepest introduction to the basic tools and theorems of mathematical calculus. Undergraduate courses in the first and second year 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, BATTISTON Pietro
  • Semester: Fall
  • 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 some knowledge of linear algebra (linear space, linear map, basis, determinant, inversion, eigenvectors) and basic calculus.

List of topics covered by the lectures.

Functions of several real variables:

  • Continuity in Euclidean spaces
  • Derivative and differential
  • Concavity and convexity
  • Local and global maxima and minima
  • Implicit function theorem
  • Constrained maximization
  • Khun-Tucker conditions

Riemann integral:

  • Finite sum and limits
  • Summability conditions
  • Properties of the integral

Measure theory:

  • Sigma algebra, measurable space, measure
  • Measurable function
  • Borel sigma algrebra, outer measure, Lebesgue measure
  • Lebesgue integral
  • Multiple integral

Academic Term (Anno Accademico) 2017/2018: industrial dynamics

  • Teaching load: 10 hours
  • Lecturers: BOTTAZZI Giulio
  • Outline: The course introduces some theoretical aspects of the study of the growth dynamics of business firms. Basic stochastic processes and the classical models are reviewed.
  • References and Optional readings:

    On the Gibrat Distribution, M. Kalecki, Econometrica, 1945.
    A model of Income Distribution, D.G. Champernowne, The Economic Journal, 1953.
    On a class od skew distribution functions, H.A. Simon, Biometrika, 1955.
    A Brief History of Generative Models for Power Law and Lognormal Distributions, Michael Mitzenmacher, Internet Math, 2003.
    Power laws, Pareto distributions and Zipf's law, M. E. J. Newman, Contemporary Physics, 2004.
    Explaining the distribution of firms gwoth rates, G. Bottazzi and A. Secchi, RAND journal of economics, 2006.
    Gibrat's Law and Diversification, G. Bottazzi and A. Secchi, Industrial and Corporate Change, 2006.

    Note that these references do not contain a complete coverage of all the topics reviewed in the course.

List of lectures.

  1. Uncertain in the definition of measured quantities. The Pareto distribution and its properties: scale-free and fat tails. The central limit theorem for the sum of independent random variables. Characteristic function and cumulant generating functions. ([New] and [Mitz]).
  2. The asymptotic of Gibrat process: the case of auto-regressive growth rates and the dependence on size ([Kal]).
  3. From the Simon model to the Yule distribution. The Champernowne model. ([Simon] and [Cham]).
  4. Laplace distribution and firm growth rates. ([Bot1])
  5. Poisson process, Yule process and firm diversification. ([Bot2])

Author: Giulio Bottazzi

Created: 2018-05-16 Wed 17:04