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Risk Analytics

  • Teacher(s):   V.Chavez  
  • Course given in: English
  • ECTS Credits: 3 credits
  • Schedule: Autumn Semester 2021-2022, 2.0h. course (weekly average)
  •  sessions
  • site web du cours course website
  • Related programmes:
    Maîtrise universitaire ès Sciences en management, Orientation Behaviour, Economics and Evolution

    Master of Science (MSc) in Management, Orientation Business Analytics

    Master of Science (MSc) in Management, Orientation Strategy, Organization and Leadership

    Master of Science (MSc) in Management, Orientation Marketing
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As human society becomes more complex and interconnected, it is more vulnerable

to rare but catastrophic events, such as the coronavirus pandemic, the extremes of

climate that regularly affect all regions of the world or the continuing turbulence

in the financial markets. For risk managers at major companies, banks and public

bodies, an accurate quantitative assessment of the risks linked to such events plays an

increasingly crucial role in decision making processes. Risk assessment involves using

past observations to forecast the future as well as possible, often extrapolating beyond

existing data, and assessing the uncertainties surrounding these forecasts. A critical

awareness of the statistical/stochastic ideas behind such calculations is essential in

understanding both their limitations and their sensitivity to failure of the underlying

assumptions, and, thus, in appreciating when and why such extrapolation may be

particularly dangerous.

Upon completion of that course the students will be able to:

• Apply techniques from a general methodological toolkit for measuring risk in

most fields of risk management

• Use risk management tools available in the statistical language R

• Analyse and estimate risk measures and their uncertainty assessment through

concrete datasets from fields of operations, insurance, finance and environment.


This course on methodologies for risk assessing includes the following topics:

• Why risk analytics matters?

• Extreme value theory (EVT)

• Monitoring and reporting risk

• Multivariate risk

• Dependence and Copulas


No mandatory document.

McNeil, A. J., Rüdiger, F and Embrechts, P., 2015, Quantitative Risk Management:

Concepts, Techniques and Tools - Revised Edition, Princeton Series in Finance.


Basic statistics and knowledge of statistical software R.


First attempt

Without exam (cf. terms)  

One final report: 60% of the grade

One final presentation: 40% of the grade


Without exam (cf. terms)  

A complement to the report will be asked.

The final report is 100% of the grade

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