Our Models


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.

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Battery Storage Optimization

Optimize stand-alone and renewable + storage assets relative to energy and ancillary services prices.

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Bitcoin Optimization

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).

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Cash-Flow-at-Risk (CFaR)/Gross-Margin-at-Risk (GMaR)

Report cash flow, generation, and fuel burn uncertainty for hybrid physical/financial energy portfolios.

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Contract Valuation

Value contracts ranging from vanilla swaps and options to bespoke HRCOs, RPOs, VFAs, and other structured transactions.

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CORE

Novel simulation engine that includes Market Price Simulation, Basis Simulation, Weather Simulation, Demand Simulation, Renewable Generation, and Ancillary Services Prices.

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Counterparty Credit Exposure / PFE

Manage and report counterparty credit risk exposure and Potential Future Exposure for any custom selected time horizons.

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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.

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Forward Curve Simulation

Simulates any market forward prices out to custom tenor horizon while ensuring coherent simulation paths across markets and commodities.

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Gas Storage Optimization

Optimize injection and withdrawal of gas storage contracts to understand intrinsic and extrinsic (option) value.

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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.

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Hydro

Simulates hydro generation and reports the distribution of MWh generation and associated cash flows.

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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.

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Net-Position-at-Risk

Report net position and risk for cash flows, power (MWh), renewable attributes (REC, GHG-Free), and more.

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Nodal Forward Curve Generation

Generate forward curves for pricing nodes or other illiquid delivery points based on historical basis relationships.

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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.

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Plant Dispatch Optimization

Optimize hourly thermal plant dispatch relative to a full range of operational parameters and constraints.

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Plant Outage

Simulates power plant outages to value asset down times by eliminating these unplanned outage periods from the normal dispatch of the plant.

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Renewable Asset /
PPA Valuation

Value and assess risk for existing or prospective wind, solar, and battery storage projects and PPAs.

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Retail Valuation

Value retail portfolios while ensuring capture of hourly load profiles and exposures.

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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.