B2217 - MACROFINANCE

Academic Year 2025/2026

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Applied Economics and Markets (cod. 5969)

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

  • Asset pricing: no arbitrage under measure P and Q
    • Measure P and the risk-premium
    • Measure Q and martingale pricing
    • Estimation of market prices of risk
    • AI and risk premia
  • 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
  • Fixed income
    • Bonds, futures, swaps
    • Spot, forward and par yields
    • Treasury and swap markets
    • Dash for cash phenomena
  • 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
  • Credit risk
    • 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
  • Securitisation and multiname credit risk
    • Securitisation: description of the products and markets
    • CDO and ABS zoology
    • Correlation risk and correlation trading
    • The "subprime crisis"
    • Perspectives: the Draghi plan and ESBIES
  • Equity premium puzzle and habit formation models
    • Equity premium puzzle
    • Habit formation
    • Extensions
  • Monetary policy and the term structure
    • Taylor rule and the "balanced approach"
    • Dynamic Term Structure Models (VAR)
    • VAR and the factor spanning problem
    • Event studies of monetary policy decisions
    • Target rates, forward guidance and quantitative easing
  • 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)
  • Recursive utility models
    • SDF with recursive utility
    • Long run risk and preference for early resolution
    • Bansal and Yaron model
    • Climate change application
  • Long term returns
    • Long term interest rate: the unit root hypothesis
    • Long term interest rate: the DIR theorem
    • Long term return decomposition:Alvarez-Jermann and Hansen-Scheinkman
  • Rare disasters
    • “Rare disasters” theory: Dietz-Barro model
    • “Dismal theorem”
    • Emerging risk: climate, geopolitical, cyber
    • Text-based risk measures
  • 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

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

Assessment methods

The exam will be based on:

  1. a term paper (and a PPT or PDF presentation)
  2. an oral examination.

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

  1. 15 minute presentation of the term paper (with PPT or PDF)
  2. 10-15 minutes of questions on content of the course.

The term paper will account for up to 8 points in the final grade.

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.

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