Trade Analysis


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Understand portfolio MtM and risk, identify optimal hedges, and perform trade- or portfolio-level sensitivity/scenario analysis.

cQuant.io offers a suite of trade analysis and reporting tools custom-tailored to the unique needs of the energy finance sector. From value at risk (VaR) and mark to market (MtM) reporting to structured transaction deal valuation and cash flow reporting, cQuant provides the data-driven insight traders need to transact with confidence.

Deal valuation, from vanilla products to complex structured transactions, including hybrid structures with physical and financial components.

Hedge effectiveness and risk reduction value (RRV) assessment.

MtM, VaR, and future cash flow distribution analysis at the individual trade and total portfolio levels.

Transacting in today’s highly volatile energy markets requires quick decision-making based on precise and robust analytics. cQuant.io’s cloud-based energy analytics platform puts powerful analytics in the hands of energy market participants, allowing them to examine deals from every angle. Correlated Monte Carlo price simulations provide a probabilistic view of future market conditions and facilitate sensitivity and scenario analysis on forward curves, trade volumes, contract terms, and portfolio make-up. These simulations provide a solid foundation on which to build valuations for complex deals, such as bespoke proxy unit heat rate call options, revenue put options, volume firming agreements for renewable PPAs, full or partial requirements load contracts, and other structured transactions.

Trade analysis can also be combined with cQuant’s asset valuation solution for a treatment of value and risk at the portfolio level. Asset valuation and risk assessment models for thermal generation, battery and gas storage, renewable assets and PPAs, and retail energy contracts help to provide a holistic analytical view that spans multiple asset classes and enables valuation of hybrid deals with both physical and financial components. The simulation-based approach provides insight into distributions of future cash flows, enabling rigorous evaluation of hedge effectiveness and risk reduction value in a portfolio context.

In today’s energy markets, not having access to the best data analytics is not only a competitive disadvantage, it’s a financial liability. cQuant.io’s trade analysis solution provides the analytical power your organization needs to stay ahead of the market.

Use cases

Market Forecasting

Simulate future market prices consistent with observed historical trends in price uncertainty down to the sub-hourly level.

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Use cases

Mark-to-Market (MtM) Reporting

Track current market value for a portfolio of physical and financial assets.

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