FIN 3617 Behavioural Finance

APPLIES TO ACADEMIC YEAR 2015/2016

FIN 3617 Behavioural Finance


Responsible for the course
Costas Xiouros

Department
Department of Financial Economics

Term
According to study plan

ECTS Credits
7,5

Language of instruction
English

Introduction
The objective of this course is to provide bachelor students with a broad understanding of how human psychology affects financial decisions, with specific reference to the impact on financial markets, corporate finance, and personal financial decisions. As such, the course focuses on how the insights of behavioral finance complement the traditional paradigm in explaining various features of the finance world; namely corporate and individual financial decisions as well as the efficiency of the financial markets.

The course will shed light on the behavior of investors and managers (and hence corporate financial policies) as well as on explaining asset pricing anomalies. To this end, we will examine how people make predictable and repeatable mistakes in financial decision-making. We will describe the nature of these mistakes and their origin, using insights from psychology, neurosciences and experimental economics on how the human mind works. We will then discuss how incorporating these mistakes into our finance theories can markedly improve standard finance models studied in other courses. We will also consider how understanding the functioning of the human mind allows us to design a better world, e.g. better stock markets, retirement plans, etc. As such, this course is markedly multi-disciplinary, lying at the intersection of financial economics, a wide spectrum of disciplines outside finance (such as psychology, medicine, and sociology), and will include practical examples, experiments, and illustrations.

Learning outcome
Acquired Knowledge
Students will acquire a good understanding of behavioral biases among investors and how these biases affect the market outcomes. More specifically the students will develop their understanding with respect to the following topics:

  • Behavioral biases among individuals
  • How do behavioral biases affect financial decision-making?
  • Why do some people gamble? Why do the elderly take excessive risks? Why do people save too little?
  • How can “bubbles” be explained?
  • Which puzzles can be explained by insights from behavioral finance?
  • Which corporate policies could be explained by behavioral finance?
  • Can we overcome behavioral biases? If yes, how.

Acquired Skills
During the acquisition of the above mentioned knowledge the students will acquire the following skills:
  • Analyzing phenomena that cannot be explained by rational models
  • Combining rational models with insights from behavioral finance to understand investor behavior in actual world
  • Combining rational models with ideas from behavioral finance to understand corporate policies
  • Analyzing the impact of regulatory changes in consumer credit market
  • Analyze financial markets using behavioral finance concepts to identify problems and propose possible solutions.

Reflection
The acquired theoretical and practical knowledge provided by the course should enable the student to understand which behavioral biases are important in financial markets and households' financial decision making. It also provide students abilities to understand patterns and behaviors in markets that is not understood in the context of rational models.

Prerequisites
SØK 3520 Microeconomics or EXC 3520 Microeconomics and BØK 3423 Finance, or equivalent.

Compulsory reading

Collection of articles:
Collection of articles. Will be available in Library Databases.
1. Gur Huberman and Tomer Regev (2001). Contagious Speculation and a Cure for Cancer: A Non-event that Made Stock Prices Soar. Journal of Finance 56, 387-396.
2. Barber, B. M., Lee, Y. T., Liu, Y. J., & Odean, T. (2009). Just how much do individual investors lose by trading?. Review of Financial Studies 22, 609-632.
3. Choi J, Laibson D, Madrian B., (2010), Why Does the Law of One Price Fail? An Experiment on Index Mutual Funds. Review of Financial Studies 23, 1405-1432.
4. Benartzi, Shlomo, and Thaler, Richard H. (2007). Heuristics and Biases in Retirement Savings Behavior, Journal of Economic Perspectives 21, 81-104.
5. Barber, Brad and Terrance Odean (1999). The courage of misguided convictions: The trading behavior of individual investors. Financial Analyst Journal November/December, 41-55.
6. Ulrike Malmendier and Geoffrey Tate (2008). Who makes acquisitions? CEO overconfidence and the market’s reaction. Journal of Financial Economics 89, 20-43.
7. Nicholas Barberis (2013), Psychology and the Financial Crisis of 2007-2008, in Financial Innovation: Too Much or Too Little?, Michael Haliassos ed., MIT Press.
8. Frazzini, Andrea (2006). The disposition effect and under-reaction to news. Journal of Finance 61, 2017-2046
9. Cohen, Lauren, Andrea Frazzini (2008). Economic links and predictable returns, Journal of Finance 63, 1977-2011.
10. Cooper, Michael, Huseyin Gulen, and Michael Schill (2008). Asset growth and the cross‐section of stock returns, Journal of Finance 63, 1609-1651.
11. Cohen, Lauren, Dong Lou (2012). Complicated firms, Journal of Financial Economics 104, 383-400.
12. Bali, Turan, Nusret Cakici, and Robert Whitelaw (2011). Maxing out: Stocks as lotteries and the cross-section of expected returns, Journal of Financial Economics 99, 427-446.
13. Lamont, Owen and Richard Thaler (2003). Anomalies: The law of one price in financial markets. Journal of Economic Perspectives 17, 191-202.
14. Markus K. Brunnermeier, and Stefan Nagel (2004). Hedge funds and the technology bubble. Journal of Finance 59, 2013-2040.
15. Lamont, Owen (2012). Go down fighting: Short sellers vs. firms. Review of Asset Pricing Studies 2, 1-30.
16. Eli Ofek and Matthew Richardson, (2003). DotCom mania: The rise and fall of internet stock prices. Journal of Finance 58: 1113-1137
17. Karl B. Diether, Christopher J. Malloy and Anna Scherbina (2002). Differences of opinion and the cross-section of stock returns. Journal of Finance 57, 2113-2141
18. P. Raghavendra Rau, Michael J. Cooper and Orlin Dimitrov (2001). A rose.com by any other name. Journal of Finance 56, 2371-2388
19. Malcolm Baker and Jeffrey Wurgler (2000). The equity share in new issues and aggregate stock returns. Journal of Finance 55, 2219-2258
20. Malcolm Baker and Jeffrey Wurgler (2002). A catering theory of dividends. Journal of Finance 59, 1125-1165.

Recommended reading

Course outline
  1. Conventional Finance and Market Efficiency
  2. Behavioral Science Foundations
  3. Behavioral Finance and Investor Behavior
  4. Behavioral Finance and Market Outcomes
  5. Behavioral Finance and Corporate Finance
  6. Behavioral Finance and Household Financial Decision-Making

Computer-based tools
Spreadsheets (Excel) will be used for certain practical applications and examples. It is recommended that students become familiar with their use.

Learning process and workload
The course will include a combination of lectures, experiments, and group presentations by students.

Specific information regarding any aspect of the course or student evaluation will be provided in class. It is the student's responsibility to obtain this information. Class participation is highly important in this course. Students will be expected to actively participate in all in-class discussions (related to case studies, experimental results, course concepts, applications of behavioural finance in the industry, etc.). Also, students will regularly have the opportunity to answer questions I’ll be asking during the lectures about topics of the “mandatory article”, which has to be read each week as part of class preparation. It is the students’ responsibility to obtain any information provided in class that is not included on the course homepage/itslearning or in the text book.

The following is an indication of the time required:
Activity
Workload
Lectures
36
Plenary sessions where experiments and student presentations will take place
6
Preparation for lectures
78
Preparation of class-work assignments
40
Preparation for the final exam
40
Total recommended workload
200



    Examination
    This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information below in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course.

    The final grade in the course will be based on the following components and weightings:
    - 40% class-work (15% students' presentations of articles, 15% class participation, 10% two problem sets)
    - 60% 3-hour written final exam.

    You will find detailed information about the point system and the cut off points with reference to the letter grades on the course site on itslearning. Specific information regarding student evaluation beyond the information given in the course description will be provided in class. This information may be relevant for requirements for term papers or other hand-ins, and/or where class participation can be one for several elements of the overall evaluation.
    Examination code(s)
    FIN 36171 – Process evaluation, counts 100% towards the final grade in the course FIN 3617 Behavioural Finance, 7,5 ECTS.

    Examination support materials
    Interest tables and BI approved exam calculator. Examination support materials at written examinations are explained under examination information in the student portal @bi. Please note use of calculator and dictionary in the section on support materials (https://at.bi.no/EN/Pages/Exa_Hjelpemidler-til-eksamen.aspx).

    Re-sit examination
    Re-sit examination is offered at the next scheduled course.
    At re-sit it will be required that the entire evaluation process is conducted again, and that students who do not achieve points in one or more exam components will get a lower grade or fail the course. Previously conducted examination components will not be part of the assessment for a new character.

    Additional information

    Semester

    Oversettelser