AI Power Grid & Infrastructure

VST
CEG
TLN
+1
11 assetslow risk1d

Bets on companies powering AI's explosive growth by supplying electricity and grid equipment.

byAmaltash Advisors LLC

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The idea

Bets on companies powering AI's explosive growth by supplying electricity and grid equipment.

Targets the critical bottleneck in the AI revolution — power. Every data center, every GPU cluster, every reshored factory needs massive electricity, and the US grid can't keep up. More than half of planned data centers face delays because transformers and switchgear are in critical shortage. This strategy holds 11 stocks across the power supply chain: independent power producers with 10-20 year contracted revenue from hyperscalers like Microsoft, Amazon, and Meta (Vistra, Constellation Energy, Talen Energy), grid equipment makers building the transmission and distribution infrastructure to deliver that power (Eaton, GE Vernova, Quanta Services, Hubbell), and specialist suppliers of data center switchgear, cooling, and connectivity (Powell Industries, Vertiv, Amphenol). XLU regime filter de-risks the speculative tiers when utility sentiment weakens, while Tier 1 power producers stay invested through downturns backed by locked-in purchase agreements. $1.4 trillion in committed utility capex through 2030 and $650B+ in hyperscaler AI spending in 2026 alone ensure the demand pipeline extends for years.

Design

How it works

  1. Invests in power plants contracted to major tech companies like Microsoft and Amazon

  2. Holds equipment makers building electrical infrastructure for data centers

  3. Uses market sentiment as a safety valve to reduce risk when conditions weaken

  4. Checks positions once per day, not constantly trading

Conditions

Where it works, and where it doesn't

Every strategy is built for a particular kind of market. These are the conditions this one is designed around — and the ones it is not.

Built for

  • When tech companies keep building data centers and signing long-term power deals
  • When electricity demand from AI keeps growing faster than supply
  • When the overall market trends upward and investor confidence is steady
  • When utility stocks and infrastructure investments are in favor with investors

Not built for

  • When the market crashes suddenly and investors panic-sell everything
  • When tech companies slow down data center expansion or delay projects
  • When interest rates spike sharply, making long-term contracts less attractive
  • When overall market sentiment turns negative toward infrastructure and utilities

The Simulation Lab

Ten bad markets, before your money is in one.

Almost anything looks good in a rising market. That is not a test. So we put the strategies listed here through the same ten bad markets, and this one has been through them. They are stretches of real market history, with names and dates: the 2022 slump, the COVID crash, a year that went nowhere. We picked them before this strategy existed.

Two of them are below. Each one shows our drawing of what that market looked like, and the rules this strategy follows when a market like it turns up. None of this is a score. What actually happened to the strategy is in your dashboard, not on this page.

10bad markets, picked before this strategy existed
8 of 10can run on the real trading days of the time they name
2 of 10we model ourselves, and we mark them as modelled
5 Sep 2026when we last ran this strategy through them

When markets fall

The 2022 Slump

A full year of falling prices as interest rates shot up.

our model of the S&P 500 around 2022ends about 20% below where it begana shape, not a scale · not this strategy

Index
S&P 500
The real dates
3 Jan – 30 Dec 2022
What the index did
fell 19.4%
How we run it
Real trading days

A full year of lower highs as the Federal Reserve raised rates from near zero to over 4%. The index was down 25% at its October low, having staged two rallies of more than 10% on the way down, and a third of 14% into the year end.

The rules this strategy follows here

  1. 1
    What it holds

    11 companies.

  2. 2
    When it sells

    One of them drops 15% to 18% below the price it was bought at.

  3. 3
    What it does

    It sells that one. The rest carry on.

No overnight drops in this market.

When markets go nowhere

When Tech Handed Over to Oil

Yesterday’s winners became 2022’s losers.

our model of the S&P 500 around 2021–22rises about 27% at its turn, then ends about 2% above where it begana shape, not a scale · not this strategy

Index
S&P 500
The real dates
4 Jan 2021 – 30 Dec 2022
What the index did
2.2% higher
How we run it
Real trading days

The index gained 27% in 2021 and gave almost all of it back in 2022, finishing the two years roughly where it began. Underneath that flat line the leadership inverted: technology, the index's largest sector, contributed most of the 2021 gain and was among the hardest hit in 2022, while energy was 2022's best-performing sector by a wide margin.

The rules this strategy follows here

  1. 1
    What it holds

    11 companies.

  2. 2
    When it sells

    One of them drops 15% to 18% below the price it was bought at.

  3. 3
    What it does

    It sells that one. The rest carry on.

No overnight drops in this market.

A market that ends where it started still charges you for every trade made inside it. This is where the cost of trading adds up fastest. That is why it sits in the set right next to the crash.

When markets fall

The COVID Crash

A third of the market’s value gone in a month — most of it overnight.

our model of the S&P 500 around Feb–Mar 2020falls about 34% at its worst, then ends about 14% below where it begana shape, not a scale · not this strategy

Index
S&P 500
The real dates
19 Feb – 23 Mar 2020
What the index did
fell 33.9%

When markets rise

The Bull Run of 2016–17

Two calm years when the market just kept climbing.

our model of the S&P 500 around 2016–17ends about 42% above where it begana shape, not a scale · not this strategy

Index
S&P 500
The real dates
4 Jan 2016 – 29 Dec 2017
What the index did
rose 30.8%

Sign in to see how this strategy did in each one.

The results open in your dashboard, where we can explain what they mean for you. They are simulated results, so we never show them here.

Open the stress tests

trade.amaltash.com/marketplace/ai-power-grid-infrastructure?tab=stress

All ten markets

  • The Bull Run of 2016–17When markets rise · modelled · shown above Tested
  • The 2020 ReboundWhen markets rise Tested
  • The 2022 SlumpWhen markets fall · shown above Tested
  • The COVID CrashWhen markets fall · shown above Tested
  • The Christmas 2018 ScareWhen markets fall Tested
  • The Year That Went NowhereWhen markets go nowhere · modelled Tested
  • The Wild Swings of Late 2022When markets go nowhere Tested
  • The Quiet YearWhen markets rise Tested
  • The Magnificent Seven YearWhen markets go nowhere Tested
  • When Tech Handed Over to OilWhen markets go nowhere · shown above Tested

These ten are the whole set. We picked them for the damage they did — the fastest crash on record, a year that went nowhere, a grind that punished every rally — not for how they make anything look.

8 of these 10 can run on the real trading days of the time they name. We model the other 2 — The Bull Run of 2016–17 and The Year That Went Nowhere. A strategy needs a stretch of history to warm up on before a test starts, and our price data does not go back far enough to give these that. So we built stand-ins that behave like those years, rather than replays of them. A modelled market is not a forecast, and it is not what would have happened. The shapes drawn above are our models of those markets — never this strategy — and they have no scale. The dates and index moves next to each one are the real figures for the period it is modelled on. Nothing on this page says how any strategy did in these tests.

Holdings

What it holds

A few of the 11 positions this strategy trades. Sign in to see the full basket and the weights behind it.

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+ 7 more assets in this strategy

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Risk Disclosure: Trading in financial instruments involves substantial risk, including the possible loss of your entire investment, and may not be suitable for all investors. Prices can be affected by external factors such as financial, regulatory, or political events. Trading on margin or with leverage increases potential losses. Past performance is not indicative of future results.

Not Financial Advice: The information provided on this platform is for informational purposes only and does not constitute investment, financial, or trading advice. We do not recommend any particular trading strategy or instrument. Please conduct your own research and consult with a qualified financial advisor before making investment decisions.

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