Enterprise Risk Management: Theory and Practice

This reading is a part of the syllabus for FRM Part 2 Exam in the section ‘Operational and Integrated Risk Management'

A corporation can manage risks in one of two fundamentally different ways: (1) one risk at a time, on a largely compartmentalized and decentralized basis; or (2) all risks viewed together within a coordinated and strategic framework. The latter approach is often called “enterprise risk management,” or “ERM” for short.

In this article, the authors suggest that companies that succeed in creating an effective ERM have a long-run competitive advantage over those that manage and monitor risks individually. Our argument in brief is that, by measuring and managing its risks consistently and systematically, and by giving its business managers the information and incentives to optimize the tradeoff between risk and return, a company strengthens its ability to carry out its strategic plan.

[gview file="http://www.cob.ohio-state.edu/fin/faculty/stulz/publishedpapers/184\_nocco.pdf" save=1]

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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.