Quantitative risk management exercises?

In summary, if you're looking for a resource to help you prepare for your upcoming written exam in quantitative risk management, I highly recommend checking out Applied Quantitative Risk Management.
  • #1
llstelle
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I have an upcoming written exam in a class on quantitative risk management (in the style of Quantitative Risk Management: Concepts, Techniques, and Tools by McNeil, Frey & Embrechts), covering concepts such as:

- risk factors and loss distributions (conditional and unconditional)
- mapping of risks, risk measurement (value-at-risk, expected shortfall, lower and upper partial moments, variance)
- Black-Scholes pricing and geometric Brownian motion
- time series
- linearized losses
- GARCH and ARMA processes...

The problem is... the homework has been strictly MATLAB programming so far and I don't know how I'll fare in a written test. Is there a good book with (let's say, more computational) exercises on any subset of the above that I can practise on before my written exam?

I'll appreciate any recommendation! Thanks!
 
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  • #2
I recommend looking at the book Applied Quantitative Risk Management: A Practical Guide to Financial Risk by Alexander J. McNeil, Rüdiger Frey, and Paul Embrechts for practical exercises related to the topics you've mentioned. The book focuses on the analysis of financial risk and provides a comprehensive guide to developing and applying quantitative risk management tools. It provides a thorough overview of the principles of quantitative risk management, complete with detailed examples and exercises that can be used to gain a better understanding of the topics. Additionally, the book includes MATLAB code that can be used to solve the problems presented in the exercises.
 

1. What is quantitative risk management?

Quantitative risk management is a process that involves using statistical and mathematical techniques to identify, analyze, and manage potential risks or uncertainties in a project or business. It involves using numerical data and calculations to assess the likelihood and impact of risks and make informed decisions to mitigate them.

2. Why is quantitative risk management important?

Quantitative risk management is important because it allows organizations to make data-driven decisions and prioritize risks based on their likelihood and impact. It also helps in identifying potential risks that may have been overlooked and provides a structured approach to managing them, reducing the chances of costly failures or losses.

3. What are the steps involved in a quantitative risk management exercise?

The steps involved in a quantitative risk management exercise include identifying the risks, collecting relevant data, analyzing the data using statistical and mathematical techniques, assessing the risks based on their likelihood and impact, and developing a risk management plan to mitigate or manage the identified risks.

4. How can quantitative risk management exercises benefit a business?

Quantitative risk management exercises can benefit a business in various ways. It helps in improving decision-making by providing a more objective and data-driven approach. It also helps in identifying potential risks and taking proactive measures to mitigate them, reducing the chances of costly failures or losses. Additionally, it can help in optimizing resources and improving overall business efficiency.

5. What are some common challenges faced in quantitative risk management exercises?

Some common challenges faced in quantitative risk management exercises include identifying and quantifying all potential risks, obtaining accurate and reliable data, using appropriate statistical and mathematical techniques, and interpreting and communicating the results effectively. Additionally, managing and updating the risk management plan as new risks emerge can also be a challenge.

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