The Mission

Since the 2022 energy crisis, energy prices have become one of the biggest financial risks for European companies. Gas and electricity prices multiplied within months, and many mid-sized manufacturers, food processors and other energy-intensive businesses saw their margins wiped out. This risk is here to stay: as more wind and solar power enters the grid, electricity prices are becoming more volatile from hour to hour and season to season, while rising CO2 prices add a further cost that is hard to predict. Large corporations manage these risks with professional trading desks, risk analysts and sophisticated models. Mid-sized companies, the backbone of regions like Limburg, usually have none of this. They decide when to fix their energy contracts based on gut feeling, broker advice or habit, and often lock in prices at the worst possible moment. HedgeWise closes this gap. We apply the quantitative methods used by professional traders and risk managers (volatility modelling, scenario simulation and risk measurement) to each company's own energy consumption, and translate the results into clear, practical decisions. Beyond contracts, HedgeWise also shows how investments in solar panels, batteries or long-term green power contracts reduce a company's exposure to price shocks, which turns sustainability into a risk management tool. Our mission is to make energy costs predictable for mid-sized companies, so they can plan with confidence, invest in the energy transition, and stay resilient when the next price shock comes.

The Challenge

Mid-sized companies are highly exposed to volatile energy and CO2 prices, but lack the tools and expertise to manage this risk. This creates four problems: 1. Poor timing: companies must decide when to fix their energy prices and for how long. Without price risk models, they often lock in at expensive moments or stay fully exposed during price spikes. 2. Hidden risk: most companies know last year's energy bill, but not how bad next year's could realistically get. This makes budgeting, pricing their own products and planning investments unreliable. 3. No independent advice: energy brokers are paid to sell contracts, so their advice is not independent. Professional risk management consultancies exist, but they are built and priced for large corporations. 4. Undervalued green investments: companies evaluate solar panels, batteries or green power contracts only on their expected savings, and miss their second benefit, protection against price shocks. As a result, sustainable investments look less attractive than they really are, and the energy transition slows down. The result is that mid-sized companies, which often have the thinnest margins, carry the largest unmanaged energy risk. A single price shock can turn a profitable year into a loss, delay investments, or in the worst case threaten the survival of the business.

The solution

HedgeWise is an independent decision-support platform for energy procurement and energy investments. It works in four steps: 1. Consumption profile: we analyse the company's historical energy use, including seasonality, production patterns and expected growth, to understand exactly how much energy it needs and when. 2. Price risk modelling: we model gas, electricity and CO2 prices using time-series and volatility models (such as GARCH) on historical spot and forward market data. With Monte Carlo simulation, we generate thousands of realistic price scenarios and measure the company's risk with standard financial risk measures such as Value-at-Risk and Expected Shortfall. 3. Hedging strategy: the platform compares procurement strategies, such as fixing a share of next year's energy now, buying in tranches over several months, or staying on variable prices, and shows the expected cost and worst-case cost of each. 4. Green investment as a hedge: the platform also evaluates solar panels, batteries and long-term green power contracts (PPAs) as risk reduction tools, showing not only how much they save on average but also how much they protect the company in a crisis scenario. The output is clear advice that a CFO or business owner can act on, for example: "Fixing 60% of next year's gas now reduces your worst-case energy bill by €180,000, at an expected extra cost of €15,000. Adding a 500 kW solar installation reduces your worst-case exposure by a further €70,000." How we build it: our team focuses on what we do best, which is the econometric modelling, risk analysis and business validation. To build the software quickly, we use Claude, an AI coding assistant, to help us write, test and document our Python code, from data collection and the GARCH and Monte Carlo models to the interactive dashboard. This allows a small, quantitative student team to build a working prototype within the challenge period, without a large development budget. Every model is designed, checked and validated by our team, and AI speeds up the implementation. What makes us different: HedgeWise is independent. We do not sell energy contracts, so our only goal is the best decision for the client. We bring quantitative methods from financial markets to a segment that has never had access to them, at a price that fits a mid-sized company. Proof of concept: we will backtest our models and strategies on European energy prices from 2021–2023, showing how much a company using HedgeWise could have saved during the energy crisis compared with typical procurement behaviour. Business model: an annual subscription for mid-sized companies, priced by energy consumption, with optional advisory sessions. In a later phase, we will partner with banks, accountancy firms and sustainability consultants, who can offer HedgeWise to their business clients, for example when assessing loans for green investments. Milestones during the challenge: 1. Build and backtest the first version of the price risk model in Python, developed with the help of Claude as our AI coding assistant. 2. Interview at least 10 finance managers of mid-sized and energy-intensive companies in Limburg about how they buy energy today and what it has cost them. 3. Run a pilot analysis on real consumption data from one or two companies. 4. Present a working prototype dashboard at the Grand Finale.