B2217 - Macrofinance

Academic Year 2026/2027

  • Teaching Mode: In-person learning (entirely or partially)
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Applied Economics and Markets (cod. 6756)

Learning outcomes

At the end of the course, the student will have learned the main techniques needed for the analysis of the price movements in financial markets and their decomposition in terms of factor premia and market expectations, being able to evaluate financial products both under the “physical” measure P and the “risk neutral” measure Q. The student will also master the main issues of the impact of the macroeconomy on financial markets and vice versa. In particular he will be required to have adequate knowledge of the main techniques of risk measurement at the macroeconomic level, articulated in terms of systemic risk and contagion, in the relationship among sovereign entities, the financial sector and the real economy. Based on a sound knowledge of theoretical and technical aspects, the student will attain a personal and critical view of the unfolding of financial crises and the future long term risk drivers of the macroeconomy, including climate change and other secular topics.

Course contents

  • Since the aim of the course is to provide both theoretical background and knowledge of the markets, each three hour lesson will be partitioned in at least two parts. Very often, depending on current topics suggested by the Financial Times and other specialized sources, a third part will be carved out in the lesson, in which active participation of the students is expected. So, in general, the lesson will consist of three parts:

    1. Theory
    2. Markets
    3. Current topics

    Here below we report the program of Theory and Markets

    Theory

    1. Asset pricing: no arbitrage under measure P

    • Measure P and the risk-premium
    • Estimation of market prices of risk
    • AI and factor models: “factor zoo” and “virtue of complexity”

    2. Stochastic discount factor (SDF)

    • SDF: general definition
    • Hansen and Jagannathan bounds
    • SDF and the efficient frontier: the Sharpe ratio
    • SDF in the CAPM model
    • SDF in the consumption/investment model
    • SDF, risk free rate and equity premium

    3. Asset Pricing: no arbitrage under measure Q

    • Asset pricing (option pricing) in a binomial model
    • No arbitrage and the replicating porttolio
    • From the replicating portfolio to the probability measure Q
    • No arbitrage pricing under measure P and Q: comparison

    4. Equity premium puzzle and habit formation models

    • Equity premium puzzle
    • Habit formation: the Campbell-Cochrane model
    • Habit formation with skewness

    5. Recursive utility models

    • SDF with recursive utility
    • Long run risk and preference for early resolution
    • Bansal and Yaron modelClimate change application

    6. Long term investment and Growth Optimal Portfolio (GOP)

    • The information theory view: Kelly rule
    • The expected utility view: the Kelly-Samuelson controversy
    • Log-wealth maximization and Growth Optimal Portfolio (GOP)
    • Long term interest rate: the unit root hypothesis vs the DIR theorem
    • Long term return decomposition:Alvarez-Jermann and Hansen-Scheinkman

    7. Dynamic Term Structure Models (DSTM)

    • Taylor rule and the "balanced approach"
    • Dynamic Term Structure Models (VAR)
    • VAR and the factor spanning problem
    • Event studies of monetary policy decisions

    8. Monetary policy announcements

    • Event studies of monetary policy decisions
    • Target rates, forward guidance and quantitative easing
    • Monetary policy and communication: Delphi vs Odysseus

    9. Rare disasters

    • “Rare disasters” theory: Dietz-Barro model
    • “Dismal theorem”
    • Emerging risk: climate, geopolitical, cyber

    10 Systemic risk and contagion

    • Systemic risk: definition and measures
    • Contagion models: networks vs copula functions
    • Copula functions: structural vs intensity based approach
    • Frailty models
    • Common factor models: Marshall-Olkin

    Markets

    1.Linear products

    • Bonds, equities, derivatives
    • Futures, forwards and swaps
    • Term structures: taxonomy

    2. Fixed income

    • Risk free term structure: spot, forward, par
    • Treasury and swap markets
    • Dash for cash phenomena

    3. Options markets and implied information

    • Option pricing, implied volatility and smiles
    • Put-Call Parity and implied dividends
    • Implied probability: Breeden-Litzenberger
    • Contingent claims and Arrow-Debreu prices

    4. Default risk and the CDS markets

    • Defaultable bonds: bonds vs CDS credit spreads
    • Credit risk and equity as options: structural models and distance to default
    • CDS and implied default intensity
    • Sovereign risk and redenomination risk

    5. Securitisation and multiname credit risk

    • Securitisation: description of the products and markets
    • CDO and ABS zoologyCorrelation risk and correlation trading

    6. The EU bond market

    • Perspectives: the Draghi plan
    • Background: Eurobonds and ESBies
    • The new EU bond market: problems and perspectives

    7. The Great Financial Crisis

    • Subprime mortgages and the OTD (Originate to Distribute) model
    • SIV, accounting system and crisis propagation
    • Toxic assets and the legacy of the crisis

    8. The European sovereign crisis

    • The discovery of Greek crisis
    • The theme of the crisis: the “doom loop”
    • Greece vs Argentina: the CAC (Collective Act Clauses)

    9. Emerging risks

    • Emerging risks: climate, geopolitical, cyber
    • Text based analysis of new risks
    • The new EU bond market: problems and perspectives

    10. AI frontiers

    • The perspectives of AI in the financial markets
    • The efficient market hypothesis (EMH) revisited
    • AI and the other emerging risks.



Readings/Bibliography

Selected Chapters in Books

John H. Cochrane: Asset Pricing, 2009 Princeton University Press

John Y. Campbell, Andrew W. Lo and A. Craig MacKinlay, The Econometrics of Financial Markets, 1999 Princeton University Press,

Main topic articles

John L. Kelly: A new interpretation of information rate, 1956, Bell System Technical Journal, 35, 917-26

Stephen A. Ross: Adding risks: Samuelson's fallacy of large numbers revisited, 1999, Journal of Financial and Quantitative Analysis, 34(3), 323-339

Larry G. Epstein, Stanley E. Zin: Substitution, risk aversion and the temporal behavior of consumption and asset returns: an empirical analysis, 1991, Journal of Political Economy, 99(2), 263-286

John Y. Campbell, John H. Cochrane: By force of habit: a consumption-based explanation of aggregate stock market behavior, 1999, Journal of Political Economy,107(2), 205-251

Ravi Bansal, Amir Yaron: Risks for the long run: a potential resolution for asset pricing puzzles, 2004, Journal of Finance, 59(4), 1481-1509

Robert J. Barro: Rare disasters and asset markets in the twentieth century, 2006, The Quartely Journal of Economics, 823-866

F. Alvarez, Urban J. Jermann, Using asset prices to measure the persistence of marginal utility of wealth, Econometrica, 73(6), 1977-2016

R.S. Gürkaynak, B. Sack, E. Swanson: Do actions speak louder than words? The response of asset prices to monetary policy actions and statements, 2005, International Journal of Central Banking, 1(1), 55-93

Teaching methods

Lectures, class discussion

Assessment methods

The exam will be based on:

  1. a term paper (and a PPT or PDF presentation)
  2. a written multiple choice exam (10 questions)

The term paper will be sent 5 days before the exam, which will be individual and consist of

  1. 30 minute multiple choice exam
  2. 15 minute presentation of the term paper (with PPT or PDF)

The multiple choice test will grant up to 5 points, and the term paper up to 8 points.

The term paper (about 10 pages) should consist of

  1. an introduction to the problem or topic chosen
  2. a review of the literature on the subject
  3. a mathematical treatment of the problem
  4. an illustrative example with data, either real or simulated

The maximum possible score is 30 cum laude. Laude will be awarded at discretion of the instructor for special originality and results in the term paper.

The grades are described as follows

< 18 failed

18-23 sufficient

24-27 good

28-30 very good

30 cum laude Excellent

Teaching tools

Slides.

Office hours

See the website of Umberto Cherubini