Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
  • Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model
Originally published: 30/04/2018 14:47
Last version published: 16/10/2018 09:19
Publication number: ELQ-38904-2
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Commodity Price Risk and Monte Carlo Simulation - Project Finance Excel Model

A commodity price risk model with Monte Carlo simulation within a project finance excel model.

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Description
A Monte Carlo simulation is a calculation, or method, combining multiple algorithms to work out a numberical value from preceding values that have a random quality. This is known as repeated random sampling. Randomness is used in order to solve problems that could be deterministic in principle - deterministic means that no randomness is involved at all.

Monte Carlo simulations allow you to make great frequency distributions, show sophisticated time series equations, and associate directly risks with mathematical statistics (i.e. mean reversion and volatility). It is a helpful tool if you're evaluating how much a cash flow sweep would reduce default probability.

You can measure the default probability without and with a sweep if you use a Monte Carlo simulation. It can also be useful when proving statistical concepts.The Monte Carlo simulation could be used for example to demonstrate that the Mean Square Error can be used to add up to standard deviation. Finally, if you'd like to demonstrate the risks that are associated with holding different portfolios of long and short term debt, you can effectively display the potential risks with the Monte Carlo simulation.

A video is included to show you how to set up a spreadsheet to create a Monte Carlo simulation.

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1 Commodity Price Risk and Monte Carlo Simulation: Project Finance Excel Model

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