Judgment and Decision Making

mlsmm2124  2024-2025  Mons

Judgment and Decision Making
5.00 credits
30.0 h
Q1
> Schedule
Teacher(s)
De Winne Rudy;
Language
French
Main themes
  • Economic foundations of modern finance
  • Foudations of behavioral economics and decision-making
  • Investor behavior and biases in financial decisions
  • Experimentation-based research methods
Learning outcomes

At the end of this learning unit, the student is able to :

1 With regard to the LSM Competency framework at the Master level, this learning unit contributes to the development of the following capabilities:
  • A scientific and systematic approach (3.1 + 3.2 + 3 .4)
  • Knowledge and reasoning (2.1 + 2.2 + 2.4 + 2.5)
  • Corporate citizenship (1.1)

At the end of this learning unit, students will be able to:
  • Formulate a hypothesis and test it using a scientific approach
  • Explain the complexity of decision-making, and distinguish the reality of a situation from the perception one may have
  • Explain and analyze the respective contributions of standard finance and behavioral finance in financial decision-making
  • Explain the behavioral biases that may affect financial decision-making and analyze their potential consequences
 
Content
This course is part of a major in finance and will therefore be more focussed on judgements and decisions in the context of financial decisions. Behavioral finance analyzes elements affecting decision-making, such as biases in perceptions or cognitive biases likely to change individual decisions, and proposes some models allowing for a better description of individual choices in finance. For the "Transition" aspect of the major, the link with sustainable development or climate challenges will be made through examples offered in the different parts of the course.
Chapter 1: Course content and goals
  • What is behavioral finance? BF versus Traditional Finance (TF)?
  • How do we make decisions? Are they rational? Rational preferences?
Chapter 2 : Méthodes de recherche
  • Expérimentations : Quoi ? Pourquoi ? Comment ?
  • Classification et design + analyse des données expérimentales
Chapter 3: Foundations of finance and limitations
  • Uncertainty, Risk, Expected Utility Theory and Risk attitude
  • Diversification, CAPM and Market Efficiency
  • Allais’ Paradox and Prospect Theory
Chapter 4: Judgement and decisions biases
  • Biases and heuristics
  • Biases in Decision-Making
Chapter 5: Well-known Biases and Mistakes in Finance
  • Disposition effect, Attention Bias and Excessive Trading
  • Diversification and Home Bias 
  • Market Sentiment and Limits to Arbitrage
Teaching methods
  • Usual and flipped classrooms (based on videos to be seen before coming in the classroom)
  • Simple computerized experiments will be organized in order to illustrate several concepts
Evaluation methods
  • Written exam (June) / Oral exam (August)
  • A part of the final grade may be based on individual / group assignments
Other information
If possible, students are requested to bring a device allowing an internet connection (tablet, smartphone or laptop). You will need this device to access the 'app' specifically developped to boost interaction in this course and to replicate several scientific experiments.
Bibliography
  • Daniel Kahneman, Thinking, Fast and Slow, Penguin Books, 2011.
  • Daniel Kahneman, Paul Slovic & Amos Tversky, Judgement under Uncertainty: Heuristics and Biases, Cambridge University Press, 1982
  • Richard Thaler & Cass Sunstein, Nudge: Improving Decisions About Health, Wealth, and Happiness, Penguin Books, 2009
  • Itzhak Venezia, Lecture Notes in Behavioral Finance, World Scientific Publishing, 2018
Faculty or entity
> CLSM


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Management
GESM2M
5
Master [60] in Management
GESM2M1
5
Master [120] in Business Management
GENT2M
5
Master [120] : Business Engineering
INGE2M
5
Master [120] in Management
GEST2M
5
Master [120] : Business Engineering
INGM2M
5
Master [120] in Management (with work-linked-training)
GESA2M
5