Role of Risk Management

The role of risk management function is to enable the company to maximize return on capital and help it grow profitably.

A risk control function is created whose objective is to preserve capital in trading and to also contribute to the decision making process. The various risks are identified and measured through an independent risk function.

Various risk measures such as VaR, Stress, Drawdown and Capital Consumed are used.

  • VaR – How much can you lose, over a given time period, with a given level of confidence, under normal market conditions?
  • Stress – How much can you lose under the worst circumstances?
  • Drawdown—How much have I lost from my peak cumulative gain?

These measures are calculated periodically (such as daily) and monitored relative to authorized limits.

The way risk measures are reported is consistent with how profit is reported and how positions are managed. Traders use these risk measures and utilize their risk limits accordingly. Everyone in the middle-office and back-office are required to have atleast a basic understanding of these risk measures.

Risk measures are also regularly back-tested with actual P/L results. This helps in verifying accuracy of risk measures and to make improvements.

Apart from the above dollar value risk measures other information related to key market and credit exposures is also monitored daily. Such information is used to analyse the biggest risks, risk concentrations, etc.

All the exposure related information must be presented in a format that is easy to understand and communicate to the people at various levels.

Risk management is very important as it ensures compliance, and reduces surprise gains and losses.

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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.