Every forecast you've ever bought is wrong

Every forecast is wrong, ours included. The difference is that we tell you the range we are wrong within, rather than a single number that pretends otherwise.

TLDR

• VarialView is our own price view for the NEM out to 2040, our assumptions, not the ISP's.
• It is a fan of five scenarios, a P5 to P95 funnel, not a single number.
• The percentile labels set the shape of the fan, not the odds. You put your own probability on each scenario, in VAR.
• Every scenario runs on one consistent base, so the price gaps you see come from the assumptions we changed, not from a different starting point.
• Buy it and the whole fan becomes a basis you can build on in Spot and value across in VAR, weighted to your own view.

Why we built this, and who it's for

If you are carrying price risk in the NEM, whether you are financing a project, running a retail book, or trading a position, you need a price curve to value against. The usual options are a consultant's set of scenarios, or a single in-house number. Neither one tells you how much your book could move if the world comes in hotter or slower than the middle case.

VarialView is our answer to that. It is a standing house view of NEM prices, updated as needed and at least once a year, built to be used rather than filed. Central is the P50, the middle of the fan; the fan around it is the range your position has to account for. It is aimed at the people who live with that risk day to day: developers and financiers, large buyers and retailers, and traders who want a fundamentals-based view they can argue with.

Modelling principles

Re-weight, don't re-forecast

We think a fan is more useful than a fresh point forecast recreated every quarter. Most forecasters throw out last quarter's number and hand you a new one, and you are left guessing what actually changed and re-basing everything you built on the old one. You also get it late: a quarterly forecast reaches you already a quarter old, with its assumptions locked well before it was even published, so you are acting on a view of the world that has already moved on. We do not work that way. The fan is the durable object: unless the market moves materially, the five scenarios stay put quarter to quarter. What moves is not our curve, it is your conviction.

So instead of chasing a moving target, you slide your own weighting along a fan that holds still. Bullish news, a hotter demand print, a project slipping, a gas squeeze, and you shift weight up the fan toward High and Highest. Bearish news, and you shift it back down toward Low and Lowest. You move the moment the news breaks, not a quarter behind it. Your weights always sum to one; all you are doing is moving conviction between scenarios that are already on the table. Your expected value, the probability-weighted blend, walks up and down inside the fan as you re-weight, while the fan itself stays where it is.

We do re-cut the fan itself, but only when it should actually move: when the market shifts materially, and at least once a year regardless, so it never goes stale. What we will not do is bill you for a fresh forecast every quarter that does not move the dial. Short of a real change, a refresh is a nudge, not a new number, so you build once on a stable fan and manage your view by re-weighting rather than rebuilding every three months. When the fan does move, you will know exactly what changed and why.

Why a fan, not a point forecast

The only thing we know for certain about a point forecast is that it is wrong. That is not a dig at anyone who publishes one, it is just arithmetic: every input that drives price, demand, build pace, delivery, fuel, carbon, is itself uncertain, and multiplying a dozen uncertain inputs together does not hand you one clean answer, it hands you a range. And it is not only the inputs: any model that runs fifteen years out has to abstract a great deal of the real market to stay tractable, so even with perfect assumptions it would still carry error of its own. So we publish the range rather than hide it behind a confident-looking line. In all seriousness, we cannot reliably predict what we are having for dinner tonight, so a precise NEM price fifteen years out is a taller order again. Hence the fan.

Forecasting the NEM this far out is as much art as science, and the art is in how wide you draw the fan. We could tell you with total confidence that prices will land somewhere between minus $1,000 and the market price cap, we would be right every single time, and it would be completely useless. The skill is drawing a fan wide enough to be realistic, so the outcome that actually turns up sits somewhere inside it, but narrow enough to be commercially useful, so it still tells you something you can price a deal against. Getting that width right is most of the job.

The fan is not the same width everywhere. Uncertainty compounds the further out you look, so the scenarios sit close together in the near term and spread wider every year. That is deliberate: a project committed and nearly built barely moves between scenarios, while one that is years from delivery carries a much bigger delay fan, because early-stage things slip far more than near-complete ones. Read the funnel as narrow and firm up close, wide and open further out.

One consistent base across the fan

Every scenario runs on one consistent base, and that base starts from the Step Change pathway, the ISP scenario we and much of the market think is the most believable of the set. We lay our own assumptions over that skeleton and present the result as a new base in its own right, not as tweaks bolted onto someone else's number, so the only thing separating the five scenarios is the set of assumptions we deliberately changed.

A full model methodology document is being written up separately. Until it lands, the short version: the engine is ISP-like, with REZ and subregional flow modelling, wrapped around a bespoke bidding model built to be future-proof. There are no hardcoded elements, so it moves as the technology stack changes and as new forms of scarcity emerge, rather than needing a rebuild every time the market does something it has not done before.

One deliberate choice worth calling out up front: new build adjusts for demand but not for price. We size each scenario's renewable build to its demand: more solar and wind where the load is higher, so the fleet grows with demand. That sizing is an input we set, not something the model works out on its own. What build does not do is respond to price. In the real world, if prices sat up in the High or Highest range, more projects would stack up as viable and that extra build would eventually pull prices back down. We are not modelling that price feedback this quarter. It is real, and we will add it in a later version, but for now we have left it out on purpose, because we want to see the impact of under-forecasting demand while the price response of build stays switched off. So read the upper scenarios as what happens if the load turns up and build does not chase the resulting prices, not as a settled long-run equilibrium.

If you can't see it, don't trust it

Here is a rule we hold ourselves to, and one we would push any forecaster on: if you cannot see the model reproduce the recent past, do not trust what it says about the future. Before we read a single output price, we line the near-term forecast up against the last few years of actual outcomes on the same chart. If the model cannot get the recent history roughly right, the demand shape, the price level, the shoulder-season softness, then it has no business telling you what 2035 looks like. That is why you will see observed history sitting right next to the forecast on our charts: so you can run that check yourself rather than take our word for it. A model you cannot eyeball is a model you cannot trust.

There is a subtler check underneath that, and it is the one we most want your help with right now. We already know this quarter's assumptions will turn out wrong in the detail, that is a given, but if we have drawn the fan well they should still land somewhere inside it. So the thing to validate at this stage is not whether we nailed the exact 2035 gas price. It is whether the output prices genuinely reflect the input assumptions: push demand up and delivery out, and the prices should respond the way the physics says they must. Getting that causal chain right, so the numbers move for the right reasons, is the step that matters, and in our honest opinion not every forecaster gets it right. That is exactly what we are inviting you to pressure-test.

What we simulate, and what we don't

This is a fundamental, average-price view, but that does not mean it is weather-blind. We run real weather variability across five reference years, 2021 to 2025: demand, wind and solar generation, and coal availability all move with the weather year, so the funnel already carries the year-to-year swing that weather drives. What we hold back is the random-shock layer, we are not running Monte Carlo draws on fuel prices or simulating network outages, so those move smoothly rather than gapping. The five scenarios are five coherent worlds, each run across the weather years, not thousands of noisy draws scattered around one.

We hold the random-shock layer back on purpose, because random market shocks make asset valuations unfair. An asset built the quarter before a modelled spike looks better than an identical one built the quarter after, purely on the luck of the draw, and valuing on a consistent weather-driven baseline keeps that comparison honest.

Caveats, and what could move the curve

A house view is a set of judgements, and we would rather be upfront about ours than dress them up. A few things worth keeping in mind.

• Every scenario runs on one consistent base of our own assumptions. If the ground shifts underneath it, a big policy change, or the ISP we sanity-check against gets substantially revised, the base moves, and we re-cut it on the next refresh.
• The assumption magnitudes are our calibrated judgement, not laws of physics. We size them against the ISP's own scenarios and the real traces, but reasonable people could push them harder or softer, which is part of why we ship the whole fan rather than a point.
• New build is sized to demand but not to price, so supply does not respond to the price signal yet. If the upper scenarios are right about demand, real-world build would likely lift further to chase those prices and temper them, so treat the top of the fan as a what-if on under-supply, not a settled equilibrium. Capacity-expansion modelling is next on our list.
• The things most likely to move the curve are the ones the levers target: how fast new build and transmission actually land, when coal really retires, how hard demand and data centres pull, and how spiky fuel gets. Watch those, and watch where next quarter's view moves.

It is a house view, not a promise. We refresh it when the market moves and at least once a year, and if you think we have got a lever wrong, we genuinely want to hear it.

Our assumptions

The levers at a glance

Here is how we turn our view into numbers. In short, the levers lean on the things that most move price: how much firm energy turns up, when, and what it costs. Every scenario sets the same set of levers, wider in the tails and near the middle in Central; the headline settings, low to high, are below, and each lever is walked through underneath with its input chart. These are inputs, not outputs: the resulting price funnel is in the Prices tab.

Demand

We calibrate on operational demand, the load that actually sets price, and move it with the electrification bundle (EVs and the electrification of transport, industry and buildings) plus an additive data-centre block. The electrification components are tiny today and large by 2040, so the funnel auto-widens over the horizon: the scenarios sit close together in the near term and fan out as the decade runs on. Data centres are a clear upside: the ISP includes some, and we add more in the High and Highest cases, ramping to +1.5 GW and +4.5 GW by 2040. The native (underlying) demand shape gets a near-term correction across all scenarios, because the ISP steps the midday trough down faster than the actuals support, with a two-sided spread in the out-years. Landing points for operational demand at 2040, relative to the Central case: roughly -16%, -8%, flat, +17% and +34%.

Commissioning

The ISP needs an unprecedented pace of new build held for more than a decade, and we do not assume it all arrives on time. Each scenario carries an annual build-rate ceiling, the most new capacity the industry can commission in a year, and anything over the ceiling carries forward to the next year, subject to that year's cap and the network's hosting limits. Tighter worlds build slower per year: the ceilings run from uncapped in Lowest down to about 8 GW a year in Highest, with Central near 13 GW. Because commissioning is heavy in 2027 to 2030, the ceiling binds hardest in exactly those years, delaying the VRE and storage roll-out that would otherwise cap prices. On top of the annual ceiling, every committed or anticipated project carries its own delivery delay that grows the further out its commissioning sits, because early-stage projects slip more than near-complete ones, and the chronic over-runners, Snowy 2.0 and Borumba, get a larger delay fan of their own. Build does adjust for demand, because we set it that way: we size each scenario's solar and wind build to its demand, and because that build follows the renewable zones it mostly lands outside NSW, so NSW keeps a similar fleet while its demand rises. What we do not do is let price pull extra build on top of serving demand: that capacity-expansion feedback is deferred (more on that choice in the section above).

Retirements

Coal retirements past 2030 shift earlier in the tighter scenarios and later in the looser ones, from +2 years later in Lowest to 2 years earlier in Highest. The near-term closures, Yallourn, Eraring and Gladstone, are locked to their announced dates, so the fan only opens up past 2030. When a unit leaves earlier, its output has to be replaced by the rest of the fleet.

Network

Transmission is the hardest part of the transition to deliver, and the part that slips most quietly. We leave the committed links on their dates and push the uncommitted flow-path and REZ (renewable energy zone) projects later in the tighter scenarios, Central a year, High two, Highest three. When a line slips, the zone behind it is stranded and the generation that depended on it slips too, so congestion and curtailment compound rather than cancel.

Fuel and carbon

Coal and gas still set the marginal price often enough that the fuel path does much of the work, and we reject the smooth, ever-declining fuel curves. The funnel carries firmer, spikier gas and coal in the upper scenarios, with Highest NSW gas reaching roughly $20/GJ by 2040.

Carbon is a clean add on top of a base that prices it at zero everywhere to start: Lowest and Low stay at zero, while Central, High and Highest fan up to roughly $50, $130 and $243 a tonne by 2040, switching on at different dates. The carbon path references the AER's Valuing Emissions Reduction guidance (May 2024). The market price cap is known through 2028 (the $26,485 cap), then escalates on each scenario's own inflation rate, 1.0% in Lowest up to 3.0% in Highest.

Results

Where prices land

The output is a fan of five price paths for the NEM, region by region, out to 2040. The regions move together but not in lockstep. The fan is tight in the near term, where the next few years are largely locked in, and spreads wider every year out as the uncertainty compounds. The headline chart is below; the Prices tab carries it region by region, quarterly and by time of day.

The generation mix that clears those prices follows from the assumptions above: a different build and retirement path, slower delivery, and our own fuel and demand settings. You can see the resulting stack in the Supply tab and the load in the Demand tab, scenario by scenario.

Dig into the full results

Everything behind the funnel is in the tabs above, one scenario and reference year at a time: quarterly and time-of-day prices, demand, the generation stack and new build, network flows and commodities. The deeper cuts unlock with the forecast: VWAPs and capture prices by region, MLFs, and curtailment. From there you can trace any scenario from an assumption right through to a captured price.

What's next

Unlock it in Spot and VAR

The report and the headline charts are open to everyone. The forecast itself, the full basis and the prices behind the funnel, is what you buy, and it is what turns a view into a working tool. Two things come with it, and they are the two that matter.

Unlock it in Spot to build on it. You get the complete input assumptions behind every scenario, wired in as a selectable basis, so you can take our fan and customise it: push a lever we did not, run your own sensitivity, or build a bespoke scenario straight on top of ours in the wizard. Our view becomes your starting point, not your ceiling.

Unlock it in VAR to value against it. The five price paths become a basis you can value your book or asset across, weighted your way, so you get a probability-weighted expected value and the full distribution around it, the value-at-risk read, in minutes rather than a spreadsheet marathon.

What we're hoping to learn

This is our first house view out in the open, and we are genuinely trying to learn from how you read it. Three things we would love your honest take on.

• The fan, or points? Does a five-scenario funnel actually help you, or would you rather we published a smaller set of named point scenarios? We lean towards the fan, but we want to know if it lands.
• One basis, or many? We put every scenario on the one Step Change basis, so the price differences you see come from the levers we moved, not from a different starting point. Is that the most useful way to see it, or would you rather each scenario carried its own basis?
• Do the prices ring true? Before we layer in capacity-expansion modelling, letting build respond to price, we want to know whether the price outlooks themselves feel right to the people who trade and build in this market. If a scenario looks off, tell us where and why.

None of these are rhetorical. The next version will move based on what we hear back, so if you have a view, get in touch through our contact page.