Risk Analysis and Simulation (RAS)

The aim of this course is to introduce statistical methods of risk analysis and simulation of rare events. Our method courses are designed independently of software and are­also suitable for users who do not work with statistics.

Target group:
This course is aimed at professionals in service or industrial companies who want to develop best-case or worst-case scenarios, forecast damage and fraud or assess risks such as product defects or incidents.

Course contents:
The course provides a practical overview of risk assessment and simulation methods. Special distribution models and simulation techniques based on pseudo-random numbers are used. The topics:

  • Stationary time series and block extrema
  • Risk as quantile of a frequency distribution
  • Value-at-Risk (VaR) und Expected Shortfall (ES)
  • General extreme value distribution Type I-III (GEV)
  • Threshold value method: Peak over Threshold (POT)
  • Generalized Pareto Distribution (GPD)
  • Mathematical generators for pseudo-random numbers
  • Simulation of univariate distribution models
  • Latin Hypercube Sampling vs Monte Carlo Method
  • Risk assessment with multivariate simulation

The course is designed to be software-independent and cross-industry. Participants receive a printed manual with all course slides.

In order to fully benefit from the training, the participants should have methodological knowledge in univariate statistics.

Supplementary courses:
For participants without sufficient previous knowledge, we offer our Methods Course "Introduction to Statistics - Part 1" (STA1), and for further consolidation the Methods Courses "Big Data Analytics" (BDA), "Methods for Statistical Data Mining" (MDM) and "Data Mining in Practice" (PDM).

Duration: 1 day Time: 9:30 - 17:00 hrs




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