End-of-Day market price forward curves
- Contains smart algorithm to calculate expected forward curves
- End-of-day curves based on settlement market data
- Applicable to power, gas and other commodity markets
- Available as a data service, and as software solution
End-of-day forward curves are widely used for marking-to-market all trading positions and are a fundamental piece of information for any company active in the energy and commodity market.
Benefits
1. Get a good price forward curve
A good forward curve includes seasonal patterns, deviates between weekdays and weekends, incorporates public holidays, and contains the right level of variation between the hours. KyCurve performs all these tasks automatically when new settlement data arrive. The KyCurve model can be used to construct detailed curves for power, gas and other commodity markets.
2. Integration with valuation and risk modules
The optimization and valuation models of the KYOS Analytical Platform can be triggered when a new end-of-day price forward curve is created by KyCurve. This give you always optimal pricing and hedging information that can be used for trading and reporting purposes.
3. Use advanced model or get price curves as a service
The KyCurve model can be delivered as a model in the KYOS Analytical Platform. This allows you to schedule calculations based on your own settings and data feeds. Alternatively, KYOS offers price forward curves for many European power and gas markets as a service via www.pricecurves.com. Depending on your preference, you can choose between both possibilities.
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Features
KyCurve uses advanced statistics to make an end-of-day forward curve based on available settlement data.
KyCurve is fully integrated in the KYOS Analytical Platform. Automated data feeds with exchanges and data providers ensure you always have the most recent end-of-day prices, ready to be used for contract pricing, power plant dispatch or MtM calculations.
Methodology
KyCurve applies an advanced statistical methodology to calculate detailed price curves. Seasonal shapes are found based on historical relationships in forward markets. Weekday patterns are filtered from historical time series, and an innovative statistical routine determines the optimal daily and hourly shaping. Of course, the impact of public holidays and bridge days is included in the optimization algorithm.
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