154-0353/03 – Financial Econometrics (FE)

Gurantor departmentDepartment of FinanceCredits3
Subject guarantordoc. Ing. Aleš Kresta, Ph.D.Subject version guarantordoc. Ing. Aleš Kresta, Ph.D.
Study levelundergraduate or graduateRequirementChoice-compulsory type B
Study languageCzech
Year of introduction2019/2020Year of cancellation2021/2022
Intended for the facultiesEKFIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
KRE330 doc. Ing. Aleš Kresta, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit 1+2

Subject aims expressed by acquired skills and competences

The aim of the course is to provide a general knowledge of econometrics with application to the practical finance and financial modelling. It is placed the great emphasis on the general principles and methods in order students to be able to solve the real problems. It is possible in the course to work on real problem of diploma thesis. Students will be able after the course: - to apply estimation methods correctly and suitably, - to create empirical models not only for financial time series, - to make predictions of future trends, - to work with mathematical software.

Teaching methods

Individual consultations
Project work


The course is focused on application of econometrical methods to the finance. It aims at creating empirical models applicable both in corporate finance as well as in financial modelling. Within the seminars, selected problems of proposing empirical models are solved and the emphasis is placed on their practical application. The course is a good complement to the course Econometrics. Problems are solved mainly in Microsoft Excel.

Compulsory literature:

ALEXANDER, Carol. Market risk analysis. Volume II, Practical financial econometrics. Chichester: Wiley, 2008. 396 p. ISBN 978-0-470-99801-4. BRANDIMARTE, Paolo. Numerical methods in finance and economics: a MATLAB-based introduction. 2nd ed. Hoboken: Wiley, 2006. 696 p. ISBN 0-471-74503-0. GREENE, William H. Econometric Analysis. Upper Saddle River: Pearson Prentice Hall, 2008. 1178 p. ISBN 978-0-13-513245-6. LEWIS, Nigel Da Costa. Market Risk Modeling. London: Risk Books, 2003. 238 p. ISBN 1-904339-07-7. ZMEŠKAL, Z., D. DLUHOŠOVÁ and T. TICHÝ. Finanční modely: koncepty, metody, aplikace. 3., přeprac. a rozšíř. vyd. Praha: Ekopress, 2013. 267 s. ISBN 978-80-86929-91-0.

Recommended literature:

COLES, Stuart. An introduction to statistical modeling of extreme values. London: Springer, c2001, xiv, 208 p. ISBN 1-85233-459-2. COOPER, W. W., L. M. SEIFORD a K. TONE. Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software. 2nd ed. New York: Springer, c2007, xxxviii, 489 p. ISBN 978-0-387-45281-4. HARDIN, James W and Joseph HILBE. Generalized linear models and extensions. 3rd ed. College Station: Stata Press, 2012, xxiv, 455 p. ISBN 978-1-59718-105-1. KENNEDY, Peter. A guide to econometrics. Malden: Blackwell, 2008. 600 p. ISBN 978-1-4051-8258-4. KING, Alan J and Stein W WALLACE. Modeling with stochastic programming. New York: Springer, c2012, xvi, 173 p. ISBN 978-0-387-87816-4. LEFEBVRE, Mario. Applied stochastic processes. New York: Springer, c2007, x, 382 p. ISBN 978-0-387-34171-2. RACHEV, Svetlozar T. et al. Financial econometrics: from basics to advanced modeling techniques. Hoboken: Wiley, 2007. 553 p. ISBN 978-0-471-78450-0.

Way of continuous check of knowledge in the course of semester

Credit - defence of seminar work


Other requirements

There are no other requirements on student.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1. Basic problems in financial econometrics. 2. Simulation Monte-Carlo – random numbers generators. 3. Estimation methods – capabilities and restrictions. 4. Regression analysis – estimation of empirical arbitrage model. 5. Regression analysis – generalized linear models and applications. 6. Introduction to stochastic optimization – applications and solution techniques. 7. Application of principal component analysis. 8. Controlling of extremal losses – estimation of risk with low probabilities. 9. Introduction to Visual Basic for Application. 10. Application of given mixture probability distributions. 11. Application of stochastic processes. 12. Modelling volatility with asymmetric effect. 13. Modelling dependences, covariance matrices. 14. Introduction to data envelopment analysis (DEA).

Conditions for subject completion

Full-time form (validity from: 2019/2020 Winter semester, validity until: 2021/2022 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit Credit 85 (85) 85 2
        Zápočtová písemka Written test 85  85 2
Mandatory attendence participation:

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2021/2022 (N0488A050004) Finance and Accounting (S01) Finance P Czech Ostrava 2 Choice-compulsory type B study plan
2020/2021 (N0488A050004) Finance and Accounting (S01) Finance P Czech Ostrava 2 Choice-compulsory type B study plan
2019/2020 (N0488A050004) Finance and Accounting (S01) Finance P Czech Ostrava 2 Choice-compulsory type B study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

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