An Overview Of cQuant.io Models
cQuant’s industry-leading models can be used individually or combined in Analytic Chains to create multi-faceted analytical workflows. For example, generate a standalone set of stochastic price simulations for use in downstream business processes. Or feed these simulations into cQuant’s Plant Dispatch Optimization and Cash Flow at Risk models for a complete portfolio-wide cash flow analysis. With new models added every 90 days, the possibilities for new Analytic Chains are growing rapidly, so check back often for new and updated models.
Battery Storage Optimization
Optimize stand-alone and renewable + storage assets relative to energy and ancillary services prices.
Supports co-optimization of bitcoin (or other cryptocurrency) mining operations relative to prices for Bitcoin, electricity, and ancillary services (regulation up/down, spinning/non-spinning reserves).
Cash-Flow-at-Risk (CFaR)/Gross-Margin-at-Risk (GMaR)
Report cash flow, generation, and fuel burn uncertainty for hybrid physical/financial energy portfolios.
Value contracts ranging from vanilla swaps and options to bespoke HRCOs, RPOs, VFAs, and other structured transactions.
Novel simulation engine that includes Market Price Simulation, Basis Simulation, Weather Simulation, Demand Simulation, Renewable Generation, and Ancillary Services Prices.
Counterparty Credit Exposure / PFE
Manage and report counterparty credit risk exposure and Potential Future Exposure for any custom selected time horizons.
Custom Reporting Models
While cQuant delivers standard output reports, users can leverage R and Python to create custom reports within the platform and make them easy to share across team members and business units.
Forward Curve Simulation
Simulates any market forward prices out to custom tenor horizon while ensuring coherent simulation paths across markets and commodities.
Gas Storage Optimization
Optimize injection and withdrawal of gas storage contracts to understand intrinsic and extrinsic (option) value.
Hedge Optimization / Portfolio Optimization
Allow users to specify a pool of tradable instruments to pick from, and a set of objective function criterions. The model will optimize the portfolio and pick the proper combination of tradable instruments from the pool to meet the objective function requirements.
Simulates hydro generation and reports the distribution of MWh generation and associated cash flows.
Monte Carlo VaR / MtM
Simulation based Value at Risk model with ability to account for non-linear portfolio items (ex. Options) and offer pricing using market volatility surface.
Report net position and risk for cash flows, power (MWh), renewable attributes (REC, GHG-Free), and more.
Nodal Forward Curve Generation
Generate forward curves for pricing nodes or other illiquid delivery points based on historical basis relationships.
Parametric VaR / MtM
Standard Parametric Value at Risk model with advanced features to drill down into any sub portfolio items, including assets and reporting MtM and financial greeks as extra outputs.
Plant Dispatch Optimization
Optimize hourly thermal plant dispatch relative to a full range of operational parameters and constraints.
Simulates power plant outages to value asset down times by eliminating these unplanned outage periods from the normal dispatch of the plant.
Renewable Asset /
Value and assess risk for existing or prospective wind, solar, and battery storage projects and PPAs.
Value retail portfolios while ensuring capture of hourly load profiles and exposures.
Upstream Production Analysis
Compute mark-to-market and cash flow at risk (CFaR) for portfolios of upstream production assets, gathering/take-in-kind contracts, and associated hedges.