MF006 Seminary on Financial Mathematics

Faculty of Science
Spring 2011
Extent and Intensity
0/2. 2 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: z (credit).
Teacher(s)
Mgr. Martin Řezáč, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Ivanka Horová, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Timetable of Seminar Groups
MF006/01: Thu 14:00–15:50 MP2,01014a, M. Řezáč
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
Topics for the seminar will be levied on the practical problems being solved in financial institutions. Among the topics are, for example: Methods for Exploratory data analysis, application of logistic regression models, Bayesian models, neural networks and other methods used in financial practise.
Syllabus
  • Methods for Exploratory data analysis,
  • Application of logistic regression models,
  • Bayesian models,
  • Neural networks,
  • Decision trees.
Literature
  • ANDERSON, Raymond. The credit scoring toolkit : theory and practice for retail credit risk management and decision automation. 1st pub. Oxford: Oxford University Press, 2007, lvi, 731. ISBN 9780199226405. info
  • SIDDIQI, Naeem. Credit risk scorecards : developing and implementing intelligent credit scoring. Hoboken, N.J.: Wiley, 2006, xi, 196. ISBN 047175451X. info
  • THOMAS, L. C., David B. EDELMAN and Jonathan N. CROOK. Credit scoring and its applications. Philadelphia, Pa.: Society for Industrial and Applied Mathematics, 2002, xiv, 248. ISBN 0898714834. URL info
  • WEST, Mike and Jeff HARRISON. Bayesian forecasting and dynamic models. 2nd ed. New York: Springer, 1997, xiv, 680. ISBN 0387947256. info
  • BISHOP, Christopher M. Neural networks for pattern recognition. 1st pub. Oxford: Oxford University Press, 1995, xvii, 482. ISBN 0198538499. info
Teaching methods
Exercises-application of methods on selected data, data processing in MS Excel, Matlab and Clementine/SAS.
Assessment methods
final project
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2008 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Spring 2010, Spring 2012, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2011, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2011/MF006