Perspectives on Liquidity Stress Testing (Iceland Example)

This reading is a part of the syllabus for FRM Part 2 Exam in the section ‘Current Issues in Financial Markets’.

The global financial crisis revealed weaknesses in the stress testing exercises performed on financial institutions and systems around the world. These failures were most evident in the area of liquidity risk, where now-obvious vulnerabilities were left largely undetected, with stress tests having largely focused on solvency risk. This paper uses publicly available data from a now-defunct bank in Iceland, where liquidity shocks were immense, to demonstrate how a combination of stress tests of the various risks would have provided a clearer picture of existing vulnerablities. We show that, ultimately, stress test models do not necessarily need to be complex or overly sophisticated. Basic stress tests, using appropriate assumptions and shocks, could reveal key areas of risk to inform contingency planning. The liquidity stress test templates used in this paper are included.

[gview file="http://www.imf.org/external/pubs/ft/wp/2010/wp10156.pdf" save=1]

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $29 (Regular $57)
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.