Based on the author's extensive work, research and presentationsin the area, the book fills a gap in quantitative risk managementby introducing a new and very intuitively appealing approach tostress testing based on expert judgement and Bayesian networks. Itconstitutes a radical departure from the traditional statisticalmethodologies based on Economic Capital or Extreme-Value-Theoryapproaches.
The book is split into four parts. Part I looks at stresstesting and at its role in modern risk management. It discusses thedistinctions between risk and uncertainty, the different types ofprobability that are used in risk management today and for whichtasks they are best used. Stress testing is positioned as a bridgebetween the statistical areas where VaR can be effective and thedomain of total Keynesian uncertainty. Part II lays down thequantitative foundations for the concepts described in the rest ofthe book. Part III takes readers through the application of thetools discussed in part II, and introduces two different systematicapproaches to obtaining a coherent stress testing output that cansatisfy the needs of industry users and regulators. In part IV theauthor addresses more practical questions such as embedding thesuggestions of the book into a viable governance structure.