Curve Fitting Job Automation
After validating and fine tuning a given forward curve model you can save it as an analytics job for re-use. Analytics jobs are each sandboxed and their parameters, inputs, and outputs saved. The parallel processor analytics engine can simultaneously execute multiple instances of such jobs. These can further be scheduled to launch automatically, providing automation of forward curve building or forecasting for trading support, risk management or asset optimization.
Advanced Curve Models
You can create and customize multiple forward curve models. The models are Fourier polynomials with multiple frequencies to capture multiple seasonal shapes and exponential or linear trend. For example, in energy and commodity markets, use a 6 month cycle to model summer/winter blocks, and a 12 month cycle for the shape to reproduce itself yearly. In FX and interest rate markets use a 2 to 4 year cycle, etc.
Forward Curve via Proxy Curves
Commodity and energy pricing points can have at most one liquid forward curve quoted in a future exchange. They lack forward market quotes at specific financial or physical locations or hubs. A friendly interface allows users to type in formulas (e.g., some weighted averages) involving other curves for which forward curve data is available, and point the forward curve of that pricing point to the formula. For example, the formula can involve some locational or broker curves as it's the case in many fuel, natural gas and food commodity markets. Consider this example in natural gas markets in North America. The forward curve of a local physical or financial gas hub can point to a weighted average: 35% on the very liquid futures contract HH, 45% on a much less liquid City Gate hub, and 20% on sparsely published Daily Rate, with the first two hubs having some base points attached to them: Average (0.35 * (HH + 0.25), 0.45*(City Gate + 0.15) + 0.20* Day Rate). The averaging function is sophisticated enough to handle the case of missing data points in some curves.