Магистратура
2024/2025
Поведенческие финансы
Статус:
Курс по выбору (Стратегическое управление финансами фирмы)
Направление:
38.04.08. Финансы и кредит
Кто читает:
Школа финансов
Где читается:
Факультет экономических наук
Когда читается:
1-й курс, 1, 2 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Преподаватели:
Бесстремянная Галина Евгеньевна,
Гусева Ольга Александровна,
Подухович Дмитрий Сергеевич,
Степанова Анастасия Николаевна
Прогр. обучения:
Стратегическое управление финансами фирмы
Язык:
английский
Кредиты:
6
Контактные часы:
48
Course Syllabus
Abstract
During several decades financial theories have been guided by efficient markets theory. The key assumption of the major financial models is the rational behaviour of investors and other agents. But in reality this assumption is regularly being broken. Markets are often inefficient. Information disclosure is expensive. Sunny weather or upcoming vacations may change the investors’ behaviour and bias their decisions.Each investment decision depends on our previous investment decisions: we are anchored. We do not live in vacuum. Behavioural biases attracted the attention of the academia and investors’ world in late 1990s. The key question was whether these biases from the rational behaviour might have significant impact over market estimations and investment decisions.Empirical tests demonstrate that behavioural biases may significantlychange even classicalasset pricing models. Several bestsellers were written on the behavioural finance issues during 2000s. CFA curriculum part devoted to behavioural finance becomes larger and larger every year. Behavioural biases do matter. So, if you want to be successful as a portfolio manager or individual investor, as a CFO or independent director and of course as a consulter, you should take into account different behavioural biases. Based on key concepts of cognitive psychology decision theory, behavioural finance studieshow real-life investorsinterpret and act on available information.This course is a finance course of advanced level.
Learning Objectives
- Provide the student with sufficient knowledge to understand difference between the classical financial theory and behavioural finance
Expected Learning Outcomes
- - Be able to compare expected utility theory with the prospect theory
- - Be able to describe how behavioral biases of managers affect the decision-making process in a corporation
- - Be able to describe the process of behavioral biases contribution to the asset prices models
- - Be able to explain and demonstrate using empirical data the challenges to the efficient market hypothesis
- - Be able to explain the nature and forecast the consequences of key behavioral biases of investors
- - Know bounded rationality concept
- - Know key anomalies in the markets proving the behavioral biases
- - Know key behavioral biases of individual and professional investors
- - Know key behavioral biases of top managers
- - Know main assumptions and ideas of prospect theory
- - Know theoretical and empirical foundations and challenges to the efficient market hypothesis
Course Contents
- Class 1. Behavioral finance: introduction
- Class 2-3. Efficient market hypothesis (by Fama).
- Class 4. Failing EMH. Evidence of motivating phenomena.
- Class 5. Behavioral economics and finance: prospect theory and asset pricing.
- Class 6-7. Heuristics and behavioral biases of investors.
- Class 8-9. Behavioral corporate finance.
- Class 10. Demonstrating behavioral biases in action: Empirical evidence from emerging markets.
Bibliography
Recommended Core Bibliography
- FAMA, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance (Wiley-Blackwell), 25(2), 383–417. https://doi.org/10.2307/2325486
- Regression analysis of count data, Cameron, A. C., 2013
Recommended Additional Bibliography
- Eugene F. Fama. (1998). Market Efficiency, Long-Term Returns, and Behavioral Finance. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.A07A16D6