Probabilistic Forecast Libraries
Decision modelers and forecasters increasingly realize the advantage of probabilistic forecasts that explicitly represent the inevitable uncertainties in the form of probability distributions. Many important quantities, such as GDP and the price of oil, are correlated or dependent. Lumina offers libraries, ready to incorporate in your models, of probabilistic forecasts for groups of such quantities.
These uncertain forecasts are represented as random samples using the DIST™ standard, a compact XML-based representation. Each individual random sample is a Stochastic Information Packet (SIP). A set of SIPs are bundled into a SLURP (Stochastic Library Unit with Relationship Preserved). Inidividual SIPs can be downloaded and read into Analytica or any spreadsheet application that supports the DIST representation, including Frontline Systems' Risk Solver and XLSim for use with Crystal Ball or @Risk. An entire SLURP can be downloaded and read into Analytica, which converts it into an array of samples, ready for use in your model.
Watch a brief recording (5:14 mins) of Max Henrion, CEO of Lumina, talking about how Analytica supports the DIST standard
AEO 2010 25-year Energy Forecasts
This SLURP includes projections for 21 quantities over 25 years, from 2010 to 2035. These include US GDP, US production, imports, consumption, and price of oil, gas, coal, and electricity, along with energy consumption by sector, energy intensity and CO2 emissions. The median values are based on US Department of Energy's Annual Energy Outlook (AEO) 2010. Lumina estimated the uncertainty about these forecasts from the actual percent error distributions by comparing the past 25 years of AEO forecasts against actual values. These distributions reproduce the historical serial correlation over time and cross-correlation among the 21 quantities.
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