Behavioral Finance

Course facts

Code:
BE1766
Credits:
7.5
Study period:
2027-01-19 - 2027-03-25
Organization:
Department of Finance
Information:
Elective Course (BSc BE)
CIVICA Course (BSc Programs)

Description

Course Director: Marieke Bos

Behavioral Finance is a field of study within economics and finance that examines how insights from psychology influence individuals’ financial decision-making and how these influences aggregate to affect financial markets, asset prices, and institutional outcomes.

The course studies systematic and predictable deviations from traditional economic models that assume fully rational decision-making. By combining theoretical frameworks with empirical evidence, the course seeks to explain why individuals and markets sometimes behave in ways that appear “irrational,” yet follow consistent and economically meaningful patterns. We explore the implications of these behaviors for investment, borrowing and consumption decisions, risk management, and the design of financial institutions and public policy.

While much of the course focuses on households and investors, the course also examines decision-making inside firms. In particular, we study behavioral corporate finance, emphasizing that managers are individuals subject to the same cognitive biases, beliefs, emotions, and experience effects as other decision-makers. Corporate policies—such as investment, financing, and merger decisions—are therefore shaped not only by incentives and constraints, but also by human psychology.

Course administrator: Anneli.Sandbladh@hhs.se

Intended learning outcomes

After passing the course, students should be able to:

  1. Summarize and explain the main theories in Behavioral Finance and relate them to limitations of traditional economic and financial models.
  2. Describe and evaluate the empirical research methods used in Behavioral Finance.
  3. Analyze how psychological factors influence both individual and managerial decision-making.
  4. Critically assess empirical evidence, with particular attention to identification strategies and statistical inference.

Prerequisites

Attendance is mandatory for Guest lectures (two confirmed, one possible), the student will have 15 points deducted from their final exam if they failed to attend all mandatory guest lectures. Attendance at all other lectures is strongly recommended.

Lecture slides will be posted on Canvas with a one-week delay and do not cover all material discussed in class. All material discussed in lectures may appear on the exam.

Prerequisites Students are expected to have completed:

  • BSc-level Microeconomics (Economics BE0101 or equivalent)
  • BSc-level Econometrics / Statistics

Students who are not enrolled in an SSE program must submit documentation proving completion of the prerequisites to anneli.sandbladh@hhs.se and marieke.bos@hhs.se. Final registration is granted only after approval.

Literature

General Reading Guidance (applies to all lectures)

For all required readings, students are expected to read:

  • the abstract,
  • the introduction, and
  • the specific sections indicated below or announced in the lecture slides.

Unless explicitly stated, students are not required to read:

  • mathematical proofs,
  • technical appendices,
  • online appendices, or
  • supplementary materials.

Lecture 1: Introduction to Behavioral Finance

Theme: Why standard models fail; psychology and economics; motivation and scope

Required

  • Rabin, Matthew. 2002. “A Perspective on Psychology and Economics.” European Economic Review 46 (4–5): 657–685. Read: Sections I–II.

Recommended

  • Thaler, Richard H. 2016. “Behavioral Economics: Past, Present, and Future.” American Economic Review 106 (7): 1577–1600. Read: Entire article.
  • Mullainathan, Sendhil, and Richard H. Thaler. 2000. “Behavioral Economics.” NBER Working Paper No. 7948. Read: Abstract and introduction.
  • Gabaix, Xavier, and David Laibson. 2008. “The Seven Properties of Good Models.” In Foundations of Positive and Normative Economics. Read: Conceptual discussion only.

Lecture 2: Benchmark Model, Evidence, and Identification

Theme: Rational benchmark, modeling assumptions, deviations, interpretation of evidence

Required

  • Rabin, Matthew. 2013. “Incorporating Limited Rationality into Economics.” Journal of Economic Literature 51 (2): 528–543. Read: Entire article (no technical appendix).

Lecture 3: Time Preferences I: Measurement and Motivation

Theme: Discounting, heterogeneity, empirical relevance of behavioral biases

Required

  • Frederick, Shane, George Loewenstein, and Ted O’Donoghue. 2002. “Time Discounting and Time Preference: A Critical Review.” Journal of Economic Literature 40 (2): 351–401. Read: Sections 1–4.1 and 5.1.

Recommended

  • Stango, Victor, and Jonathan Zinman. 2023. “We Are All Behavioral, More or Less.” Review of Economic Studies. Read: Introduction and motivation.

Lecture 4: Time Preferences II: Present Bias

Theme: Quasi-hyperbolic discounting; naïveté vs. sophistication

Required

  • O’Donoghue, Ted, and Matthew Rabin. 1999. “Doing It Now or Later.” American Economic Review 89 (1): 103–124. Read: Introduction, Sections I and III.

Recommended

  • Laibson, David. 1997. “Golden Eggs and Hyperbolic Discounting.” Quarterly Journal of Economics 112 (2): 443–477. Read: Abstract and intuition sections.

Lecture 5: Applications of Present Bias and Consumer Myopia

Theme: Commitment, self-control, exploitation, and firm responses

Required

  • DellaVigna, Stefano, and Ulrike Malmendier. 2006. “Paying Not to Go to the Gym.” American Economic Review 96 (3): 694–719. Read: Abstract, introduction, empirical design, and main results.

Recommended

  • Gabaix, Xavier, and David Laibson. 2006. “Shrouded Attributes, Consumer Myopia, and Information Suppression in Competitive Markets.” Quarterly Journal of Economics 121 (2): 505–540. Read: Abstract, introduction, and intuition sections (no proofs).
  • Bryan, Gharad, Dean Karlan, and Scott Nelson. 2010. “Commitment Devices.” Annual Review of Economics 2: 671–698. Read: Conceptual overview.

Lecture 6: Mandatory Guest Lecture

Required

  • Review company website and product.
  • Relate Plus1’s business model to behavioral concepts covered so far https://www.plus1.com/

Lecture 7: Risk Preferences I

Theme: Expected utility, calibration, small-stakes risk

Required

  • Rabin, Matthew. 2000. “Risk Aversion and Expected-Utility Theory: A Calibration Theorem.” Econometrica 68 (5): 1281–1292. Read: Abstract, intuition, and main argument (no proofs).

Recommended

  • Rabin, Matthew, and Richard H. Thaler. 2001. “Anomalies: Risk Aversion.” Journal of Economic Perspectives 15 (1): 219–232. Read: Entire article.

Lecture 8: Risk Preferences II: Prospect Theory and Insurance

Theme: Reference dependence, loss aversion, insurance choices

Required

  • Kahneman, Daniel, and Amos Tversky. 1979. “Prospect Theory: An Analysis of Decision under Risk.” Econometrica 47 (2): 263–291. Read: Sections I–IV (no proofs).
  • Thaler, Richard H. 1985. “Mental Accounting and Consumer Choice.” Marketing Science 4 (3): 199–214. Read: Entire article.

Recommended

  • Sydnor, Justin. 2010. “(Over)Insuring Modest Risks.” American Economic Journal: Applied Economics 2 (4): 177–199. Read: Abstract, introduction, and main results.

Lecture 9: Prospect Theory, Gambling, and Dynamic Inconsistency

Theme: Probability weighting, gambling behavior, risky choice over time

Required

  • Kahneman, Daniel, and Amos Tversky. 1992. “Advances in Prospect Theory: Cumulative Representation of Uncertainty.” Journal of Risk and Uncertainty 5: 297–323. Read: Conceptual sections.

Recommended

  • Barberis, Nicholas. 2012. “A Model of Casino Gambling.” Management Science 58 (1): 35–51. Read: Intuition and implications.

Lecture 10: Case Study: Behavioral Biases and Financial Decision Tools

Theme: Application and synthesis

Required

  • Case materials and guiding questions (distributed in advance).

Lecture 11: Asset Allocation and Myopic Loss Aversion

Theme: Evaluation frequency, investor behavior, equity premium puzzle

Required

  • Benartzi, Shlomo, and Richard H. Thaler. 1995. “Myopic Loss Aversion and the Equity Premium Puzzle.” Quarterly Journal of Economics 110 (1): 73–92. Read: Abstract and intuition.
  • Iqbal, Kamal, Asad Islam, John A. List, and Viet Nguyen. 2021. “Myopic Loss Aversion and Investment Decisions: From the Laboratory to the Field.” NBER Working Paper No. 28730. Read: Abstract, introduction, experimental design, and main results.

Lecture 12: Mandatory Guest Lecture

Required

  • Review company website and product.
  • Relate LYSA’s design choices to behavioral concepts. https://www.lysa.se/

Lecture 13: Behavioral Corporate Finance: Managers Are Humans Too

Theme: Overconfidence, experience effects, managerial decision-making

Required

  • Malmendier, Ulrike, and Geoffrey Tate. 2005. “CEO Overconfidence and Corporate Investment.” Journal of Finance 60 (6): 2661–2700. Read: Abstract, introduction, empirical design, and main results.
  • Malmendier, Ulrike, and Stefan Nagel. 2016. “Learning from Inflation Experiences.” Quarterly Journal of Economics 131 (1): 53–87. Read: Abstract, introduction, and selected empirical sections.

Lecture 14: Integration, Review, OR Mandatory Guest Lecture (if applicable)

  • No new readings

Examination

Teaching Format and Assessment
The course consists of lectures, one case study, unannounced pop-up quizzes, guest lectures, and in-class discussions. Participation is assessed during the case study session.

Pop-up Quizzes

  • Four unannounced in-class quizzes
  • No aids
  • Together worth up to 10 exam points

Case Study

  • Graded Pass/Fail
  • Students may earn up to 2 exam points for preparation and participation
  • Case study points cannot increase the total exam points beyond 10

Mandatory Guest Lectures

Failure to attend a mandatory guest lecture results in a 15-point deduction from the exam total. Meaning the student starts the exam with a max 85 points out of 100.

Grade Scale

Popup quizes total exam points available: 10 (popup quizes and case study)

  • Fail: 0
  • Pass: 1.0
  • Good: 1.5
  • Very good: 2.0
  • Excellent: 2.5

Final exam total exam points available: 100 minus (popup quizes points max 10) plus (guest lecture punishment max -15)

  • Fail: 0-50
  • Pass: 51-60
  • Good: 61-70
  • Very good: 71-80
  • Excellent: 81-90

Schedule

Find the course schedule in TimeEdit

Additional information

Have you been granted educational support because of a documented disability? If so, please contact the course director as soon as possible so that adequate accommodations can be made.

Contact specialneeds@hhs.se if you have questions about being granted educational support or need a copy of your educational support certificate.

For more information, visit the Specific Educational Needs page on the Student Hub (login required).