Quantitative methods in risk management

Data is displayed for academic year: 2023./2024.

Course Description

Quantitative risk evaluation in credit granting and account management. Using credit scoring concepts in other fields, e.g. insurance or Internet, analysing and predicting visitors interactions. Neural networks applied for detecting fraud in card transactions. Technical analysis of data in equity and commodity markets and its usage in making future trading decisions. An introduction to modern view of the power of analytics in decision making and the recent "Big Data" concept.

Study Programmes

Postgraduate doctoral study programme

Literature

Edward M. Lewis (1994.), An Introduction to Credit Scoring,
Robert J. Schalkoff (1997.), Artificial Neural Networks, McGraw-Hill
Steven Achelis (2000.), Technical Analysis from A to Z, 2nd Edition, McGraw Hill Professional
Larry E. Rosenberger, John Nash (2009.), The Deciding Factor, John Wiley & Sons
Viktor Mayer-Schönberger, Kenneth Cukier (2013.), Big Data, Houghton Mifflin Harcourt

For students

General

ID 154889
  Summer semester
6 ECTS
L0 English Level
L1 e-Learning