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Course, academic year 2023/2024
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Selected Software Tools for Finance and Insurance - NMFM404
Title: Vybraný software pro finance a pojišťovnictví
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: summer
E-Credits: 3
Hours per week, examination: summer s.:2/0, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: not taught
Language: English, Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: doc. RNDr. Michal Pešta, Ph.D.
Class: M Mgr. FPM
M Mgr. FPM > Povinné
Classification: Mathematics > Financial and Insurance Math.
Incompatibility : NMFP406
Pre-requisite : NMSA407
Interchangeability : NMFP406
Is incompatible with: NMFP406
Is interchangeable with: NMFP406, NFAP007
Annotation -
Last update: T_KPMS (14.05.2013)
Software (mostly R, but Mathematica as well) in finance and insurance. Modeling financial, economic, and insurance processes. Practical exercises and problems from finance and insurance, model testing, parameter estimation, prediction in stochastic models and their diagnostics. Computational intensive methods, copulae, and their application in finance and insurance. Practice with databases. Requirements: Basics of statistical modeling.
Aim of the course -
Last update: T_KPMS (14.05.2013)

Solving real problems from finance and insurance by using stochastic models and statistical software.

Course completion requirements -
Last update: doc. RNDr. Michal Pešta, Ph.D. (02.02.2018)


Literature -
Last update: doc. RNDr. Michal Pešta, Ph.D. (28.10.2019)

[1] Peter Dalgaard: Introductory statistics with R. Birkhäuser, 2002.

[2] David W. Hosmer and Stanley Lemeshow: Applied Logistic Regression (Second edition). Wiley, 2000.

[3] John H. Maindonald, John Braun: Data analysis and graphics using R: an example-based approach (Third edition). Cambridge University Press, 2010.

[4] David Ruppert: Statistics and finance: an introduction. Springer, 2004.

[5] William N. Venables, Brian D. Ripley: Modern applied statistics with S. Birkhäuser, 2002.

Teaching methods -
Last update: T_KPMS (14.05.2013)


Requirements to the exam -
Last update: doc. RNDr. Michal Pešta, Ph.D. (30.01.2018)

Written solution of two home projects (1st one - the first half of semester, 2nd one - the end of semester).

Oral part (in the examination period) is composed of the projects' defence and additional questions.

Syllabus -
Last update: T_KPMS (14.05.2013)

Software usage for the following applied methods in finance and insurance: generalized linear models, categorical data analysis, random effects models, panel/longitudinal data analysis, generalized estimating equations, bayes methods, bootstrap, Markov chain Monte Carlo, copulae, extreme observations and large claims analysis (GEV and POT methods).

Entry requirements -
Last update: doc. RNDr. Michal Pešta, Ph.D. (26.04.2018)

Basic knowledge of mathematical statistics and linear regression.

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