DXF_OCAK Asset Pricing

Faculty of Economics and Administration
Spring 2021
Extent and Intensity
24/0/0. 12 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Martin Svoboda, Ph.D. (lecturer)
doc. Ing. Tomáš Výrost, PhD. (lecturer)
Oleg Deev, Ph.D. (assistant)
Guaranteed by
doc. Ing. Martin Svoboda, Ph.D.
Department of Finance - Faculty of Economics and Administration
Contact Person: Mgr. Lucie Přikrylová
Supplier department: Department of Finance - Faculty of Economics and Administration
Timetable
Fri 26. 3. 8:00–12:00 S307, Fri 9. 4. 8:00–12:00 S307, Fri 23. 4. 8:00–12:00 S307, Fri 7. 5. 8:00–12:00 S307, Fri 21. 5. 8:00–12:00 S307
Prerequisites
The use of own personal laptops with a spreadsheet program is strongly encouraged. The use of econometric software is strongly encouraged (for example, GRETL may be freely downloaded from http://gretl.sourceforge.net/, available for Windows/Linux/Mac). The course participants are expected to be familiar with the following topics: – Univariate and multivariate functions. – Unconstrained optimization, constrained optimization using Lagrange multipliers. – Matrix algebra – addition, multiplication, transpose, inversion. – Basic statistics – expected value, variance, covariance. – Basic econometrics – model specification, estimation via OLS, model assumptions.
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
there are 26 fields of study the course is directly associated with, display
Course objectives
The aim of this course is to provide the participants with information and practical experience with the most common asset pricing models. The participants should become familiar with the concepts of market efficiency, cross-section of stock returns, CAPM and factor models, as well as term structure modelling.
Learning outcomes
At the end of this course a student will be able to: - use some of the most common pricing models for modeling return; - use different performance measures in asset pricing; - understand equity premium and risk-free rate puzzles, stochastic discount factor models and consumption-CAPM; - model the term structure.
Syllabus
  • - Basic concepts in finance and statistics (discounted present value, utility, asset demand, significance tests, linear models, single/multivariate models). - Efficient market hypothesis, predictability of stock returns (definition of EMH, empirical tests of EMH, econometric models for stock return predictability). - CAPM and factor models, performance measures (Capital asset pricing model, systematic risk, performance measures, extensions, Fama-French three-factor model, empirical application and testing). - Stochastic discount factor models, consumption-CAPM (return predictability under C-CAPM, equity premium puzzle, extensions). - Term structure modelling (prices and yields, theories of the term structure, the expectation hypothesis, empirical evidence on the term structure).
Literature
    required literature
  • CUTHBERTSON, Keith and Dirk NITZSCHE. Quantitative financial economics : stocks, bonds and foreign exchange. Second edition. Chichester: John Wiley & Sons, 2005. xiv, 720. ISBN 0470091711. info
    recommended literature
  • BALI, Turan G.; ENGLE, Robert F.; MURRAY, Scott. Empirical asset pricing: the cross section of stock returns. John Wiley & Sons, 2016. ISBN 978-1-118-09504-1
  • COCHRANE, John H. Asset pricing. Rev. ed. Princeton: Princeton University Press, 2005. xvii, 533. ISBN 0691121370. info
  • Financial engineering and computationprinciples, mathematics, algorithms. Edited by Yuh-Dauh Lyuu. New York, NY: Cambridge University Press, 2002. xix, 627 p. ISBN 052178171X. info
Teaching methods
Lectures, online study materials.
Assessment methods
Online exam. Grades: 100 - 92 % = A, 91 - 84 % = B, 83 - 76 % = C, 75 - 68 % = D, 67 - 60 % = E, less than 60 % = F.
Language of instruction
English
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
The course is also listed under the following terms Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2018, Spring 2019, Spring 2020.
  • Enrolment Statistics (recent)
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