The forward curve is the market's current consensus on future delivery prices — the term structure of energy. It is the foundation for valuation, hedging, and optimization: every structured contract, PPA, or storage dispatch decision references it. Yet energy forward curves behave fundamentally differently from financial curves because of non-storability (power) or costly storage (gas).
A forward curve maps delivery period → price for a given commodity and location at a given moment in time:
| Property | Power Forward | Gas Forward (TTF) | Financial Yield Curve |
|---|---|---|---|
| No-arbitrage link to spot | Weak — non-storable, no cash-and-carry | Moderate — storage links carry cost to spread | Strong — bonds replicate forwards exactly |
| Seasonality | Strong (temperature + solar/wind patterns) | Strong (heating demand, injection/withdrawal) | None (or minimal) |
| Mean reversion | Strong — marginal cost anchors long-run | Moderate — long-run supply/demand equilibrium | Weak — rates can trend persistently |
| Spikes | Extreme (scarcity pricing, 4000€ cap) | Moderate (storage depletion events) | Rare (crisis events only) |
| Granularity | Base/Peak/Off-peak × hourly shape | Monthly/quarterly/seasonal | Continuous term |
| Contango/Backwardation | Seasonal — winter contango in summer | Storage-driven (injection = contango) | Yield curve slope analogous |
The curve is constructed from observable market quotes — futures and forwards traded on exchanges (EEX, ICE) and OTC. The challenge: traded products have different delivery periods (months, quarters, years, base vs. peak), and you need a consistent hourly (or quarter-hourly) price for every delivery period.
| Product | Delivery | Type | Quote (example) |
|---|---|---|---|
| DE Base Month Aug-25 | All hours of August 2025 | Baseload | 62.50 €/MWh |
| DE Peak Month Aug-25 | Peak hours (08-20 weekdays) of Aug 2025 | Peakload | 78.30 €/MWh |
| DE Base Quarter Q4-25 | All hours Oct-Dec 2025 | Baseload | 71.80 €/MWh |
| DE Base Year Cal-26 | All hours 2026 | Baseload | 65.40 €/MWh |
Longer products are disaggregated into shorter ones, ensuring volume-weighted consistency:
A quarterly price must equal the weighted average of its constituent monthly prices. Similarly, a yearly price must cascade into quarters, and quarters into months. Where monthly prices are not directly traded, they must be inferred from the quarterly quote + seasonal shape assumptions.
With base and peak quotes, you can derive off-peak. The "peak" definition is typically Mon-Fri 08:00-20:00 CET (12 hours × ~22 weekdays per month). Off-peak = remaining hours (nights + weekends).
The final step transforms monthly base/peak prices into an hourly profile. This uses a shape factor — a normalized pattern derived from historical spot prices:
where Sh is the shape factor for hour h (average historical ratio of that hour's spot price to the monthly average). Σ Sh / N = 1 by construction. Shape factors capture the typical daily pattern: higher prices in morning/evening peaks, lower overnight.
Limitation: Shape factors are backward-looking. If the generation mix is changing (e.g., more solar depresses midday prices), historical shapes may not reflect future patterns. Advanced methods use fundamental models or recent shapes only.
For storable commodities like gas, the forward curve is linked to spot via the cost of carry:
where: F = forward price, S = spot price, r = interest rate, u = storage cost (injection/withdrawal + capacity), c = convenience yield (value of physical inventory). If F > S + carry cost → inject (buy spot, store, sell forward). If F < S + carry cost → withdraw (sell spot, buy forward to replace).
Power cannot be stored cheaply at scale. This breaks the cost-of-carry relationship:
| Feature | What It Signals | Optimization Implication |
|---|---|---|
| Contango (far > near) | Market expects higher future prices or values carry | Gas: inject now, sell forward. Power: sell forward if you disagree. |
| Backwardation (near > far) | Current scarcity or convenience yield premium | Gas: withdraw if physical. Power: near-term generation more valuable. |
| Steep seasonality | Large winter/summer spread | Storage value high; flexible assets should capture seasonal spread. |
| Flat back-end | Market reverts to long-run equilibrium view | Less hedging value in far-term; limited information content. |
| Peak/Off-peak spread | Intra-day flexibility value | Storage/flex assets capture daily cycle; wide spread = high flex value. |
Forward curves are the valuation backbone for energy portfolios:
For the theory of energy commodity forward curves and the storage model:
Eydeland, A. & Wolyniec, K. (2003). Energy and Power Risk Management. Wiley. Chapters 3-5 on forward curve modelling remain the standard reference for energy quants.
For empirical analysis of power forward premia:
Bessembinder, H. & Lemmon, M. (2002). "Equilibrium Pricing and Optimal Hedging in Electricity Forward Markets." Journal of Finance, 57(3), 1347–1382. — Landmark paper on why power risk premia are systematically positive and vary with demand variance.
Why can't the relationship F = S × e^(r+u-c)(T-t) be applied to electricity forward pricing?
In the cascading step of forward curve construction, what constraint must be satisfied?
A gas forward curve showing steep summer-winter contango (winter >> summer) signals that:
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