Price Forecasting and Market Analysis
A game theoretic framework which analyzes strategic bidding behavior; natural gas prices and pipeline access; and Monte Carlo scenario analysis, we are able to develop a range of plausible wholesale electricity market outcomes, which we then employ to forecast revenues to generation stations
Risk registry, with attention to role of new entrants, changing fuel prices, and regulatory uncertainty
Assessment of impact of market design rules on EBITDA and Free Cash Flow
Measuring Value at Risk (VaR) and Gross Margin at Risk (GMaR) with attention to a range of plausible electricity and gas market outcomes
Methodology and Features
Contango Energy Consulting uses advanced Monte Carlo simulation techniques. Important characteristics are e.g. co-integrated commodity prices, and a mean-reverting multi-factor model with long-term, short-term and seasonal dynamics. Furthermore, users can also import their own price simulations for comparison.
The model applies dynamic programming and least squares Monte Carlo techniques for optimal dispatch and exercise decisions. The accompanying calibration tool uses historical data to easily derive the volatility term structure and other simulation inputs. Similarly, you may use implied option volatilities as well, by overwriting the historical volatility estimates.
The Value-at-Risk model computes the VaR on a portfolio of contracts and asset exposures in commodity markets. The VaR provides direct insight in potential portfolio losses. We offer different methodologies: variance-covariance, Monte Carlo simulation and historical simulation.
The AtRisk model calculates both the Cashflow-at-Risk and Earnings-at-Risk. Both risk metrics show the distribution of future results over longer horizons, particularly with the idea to reveal the impact of adverse market movements. The model also shows which trades (hedges) should be executed to minimize the risk.