Commodities – Learning Roadmap

Price volatility in crude oil, gold, silver, cotton, sugarcane, wheat and cereals has created an unprecedented opportunity for corporate relationship managers to cross sell treasury products to their institutional, trading, manufacturing and high net worth customers.

 

What are the prerequisites?

We recommend the following basic courses that will help you become familiar with the terminology and methods used in our models:

  • Correlation
  • Market Risk Metrics
  • Calculating Value at Risk (VaR)
  • Computational Finance: Building Monte Carlo (MC) Simulators in Excel

 

What topics are covered?

1) A framework for empowering client-facing treasury teams to go out and cross sell high value, high margin trading concepts to clients by educating customers about their exposures and informing them of some of the solutions available to reduce the risk associated with these exposures.

  • Cross Selling Treasury products

This covers:

  • Core concepts such as volatilities, trailing volatilities, interconnections & relationships and trends
  • Specific products and trades such as futures, forwards and options, exotic contracts etc.
  • Trading tools such as analyzing the fundamentals of oil and gold
  • Treasury limits such as stop loss limits, PFE, PSE or counterparty limits
  • Calculating Value at Risk, Pre Settlement Risk (PSR) and Potential Future Exposure (PFE)
  • Linking PFE and PSE to counterparty limits

2) Modeling of commodity prices using various methods.

  • Understanding Crude Oil. A model for dissecting crude oil
  • Crude Oil Mispricing model
  • Relative Gold Price model
  • Understanding Gold! Short Gold or add to your positions? A look at gold silver ratio and relative value argument
  • Monte Carlo Simulator with Historical Returns

This covers:

  • Estimation of the possible direction prices will move in response to certain market drivers.
  • Impact of interrelationships between commodity pairs and between the commodity and other risk classes, and the impact of a break-down in these relationships under times of stress.
  • Market fundamentals, demand for and supply of the commodities, reducing/ increasing spreads between different blends in the case of crude oil, growth of commodity stockpiles, market growth trends in the developed and developing world, etc and how these factors could impact the results of our models.

3) Case studies

  • Real world examples
  • A crude oil specific case study that covers a risk management framework for managing inventory and margin losses of a petrochemical firm. A Value at Risk based approach is utilized to determine acceptable levels of risk for the firm which is then used in devising a plan for the implementation and management of an appropriate control structure.

 

Related Video Courses

  • Quant Crash Course
  • Calculating VaR (Value at Risk) using VCV and Historical Simulation
  • Setting Value at Risk (VaR), Stop Loss, Pre Settlement (PSR) and Counterparty Limits

 

Related Book/PDF Files

 

Related EXCEL Fles

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