OVERVIEW
OVERVIEW
The Strategic Optimization solution helps companies protect margins and stabilize earnings by finding the best balance between hedging, inventory, and supply chain decisions using advanced mathematical optimization. It calculates optimal hedge ratios with methods like mean-variance optimization and CVaR minimization, adjusting positions dynamically based on price forecasts and changing market volatility to provide effective cash flow protection aligned with the company’s risk tolerance.
The solution also improves supply chain and procurement decisions: for example, selecting the most cost-effective coal deliveries or the right mix of forward and spot purchases to lower costs and manage risks. In processing industries, it supports blending and production choices, such as refining crude oil to maximise crack spread margins. It also recommends suitable financial instruments, favoring options for nonlinear risks and proxy hedges when direct hedges are not available.
Overall, this solution offers a data-driven, flexible roadmap that aligns risk management with market conditions and business goals, helping companies unlock value in volatile markets.
The solution also improves supply chain and procurement decisions: for example, selecting the most cost-effective coal deliveries or the right mix of forward and spot purchases to lower costs and manage risks. In processing industries, it supports blending and production choices, such as refining crude oil to maximise crack spread margins. It also recommends suitable financial instruments, favoring options for nonlinear risks and proxy hedges when direct hedges are not available.
Overall, this solution offers a data-driven, flexible roadmap that aligns risk management with market conditions and business goals, helping companies unlock value in volatile markets.
METHODOLOGY AND OPTIMIZATION LOGIC
METHODOLOGY AND OPTIMIZATION LOGIC
Our solution combines mean-variance optimization and CVaR-based risk controls to identify portfolio configurations that balance return targets with downside constraints. The model updates hedge ratios and allocation weights as volatility, correlation structures, and market expectations change.
INPUTS, CONSTRAINTS, AND OUTPUTS
INPUTS, CONSTRAINTS, AND OUTPUTS
- Inputs
- price curves and volatility assumptions
- exposure profile by asset/tenor
- liquidity and covenant constraints
- procurement and inventory requirements
- Constraints
- risk limits and policy thresholds
- instrument availability and hedgeability
- accounting and reporting boundaries
- Outputs
- optimized hedge ratios
- recommended allocation mix
- scenario-based downside profile
- execution priorities by time horizon
INDUSTRY APPLICATIONS
INDUSTRY APPLICATIONS
- Power and utilitiesOptimize fuel procurement and hedge structure under volatile power and commodity prices.
- Oil and refiningImprove crude sourcing, blending, and hedge calibration to protect crack spreads.
- Metals and miningAlign production-linked exposure with hedge tenors and working capital limits.
- AgribusinessBalance seasonal procurement, inventory, and price-risk transfer decisions.
IMPLEMENTATION ROADMAP
IMPLEMENTATION ROADMAP
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Phase 1
Data onboarding and exposure mapping - Phase 2Model calibration and scenario design
- Phase 3Optimization run and decision pack generation
- Phase 4Execution support and monitoring loop
Apply optimization methods to real portfolio decisions
Model-driven approach • Practical implementation • Ongoing refinement