The Global Derivatives Study: Group of Thirty Best Practices

Introduction

Derivatives have fundamentally changed financial management by providing new tools to manage risk. As the use of derivatives has grown rapidly in the past 15 years, they have moved into the mainstream of finance.

Yet many, both inside and outside of the financial industry, remain uncomfortable with derivatives activity. They see it as complex and obscure, potentially subject to abuse that might lead to the failure of individual firms or even to a crisis in the financial system. This Study recognizes and addresses these concerns by explaining derivatives and their uses and by formulating and disseminating recommendations about their management.

The Global Derivatives Study

This Study consists of the Recommendations, an Overview of Derivatives Activity, and three Appendices:

The Recommendations

The Study offers 20 recommendations to help dealers and end-users manage derivatives activity and continue to benefit from its use. The Study also recommends four ways that supervisors and regulators, for their part, can help the financial infrastructure keep up with derivatives activity.

The 20 recommendations for a dealer and end-user of derivatives cover:

  1. The Role of Senior Management
  2. Marking to Market
  3. Market Valuation Methods
  4. Identifying Revenue Sources
  5. Measuring Market Risk
  6. Stress Simulations
  7. Investing and Funding Forecasts
  8. Independent Market Risk Management
  9. Practices by End-Users
  10. Independent Credit Risk Management
  11. Measuring Credit Exposure
  12. Aggregating Credit Exposures
  13. Master Agreements
  14. Credit Enhancement
  15. Promoting Enforceability
  16. Professional Expertise
  17. Systems
  18. Authority
  19. Accounting Practices
  20. Disclosures

In addition, there are four recommendations for legislators, regulators, and supervisors:

  1. Recognizing Netting
  2. Legal and Regulatory Uncertainties
  3. Tax Treatment
  4. Accounting Standards

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What's Included:

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  • Data Visualization with R
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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.