GLP-1 Revolution

LLY
AMGN
TMO
+1
12 assetslow risk1d

Bets on obesity drug companies and their suppliers, automatically adjusting positions based on momentum and upcoming news.

byAmaltash Advisors LLC

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The idea

Bets on obesity drug companies and their suppliers, automatically adjusting positions based on momentum and upcoming news.

Obesity is no longer a lifestyle problem — it's the largest addressable drug market of the decade. Eli Lilly posted $12.9B from GLP-1 drugs in a single quarter. Novo Nordisk's oral Wegovy hit 50,000 weekly prescriptions within three weeks of launch. Amgen's MariTide promises monthly or even quarterly dosing that could reshape patient compliance entirely. The injectable era opened the market. The oral era — now live with two pills on the market — is about to blow the doors off it. But the real story isn't just the drugs. Every injection needs a prefillable syringe (West Pharmaceutical), sterile fill-finish manufacturing (Thermo Fisher just built a 1.5B-unit-per-year production line), and subcutaneous delivery technology (Halozyme's ENHANZE platform is licensed by both Lilly and Amgen — they collect royalties regardless of who sells more). Behind the supply chain, the next generation is already forming: Viking Therapeutics showed best-in-class Phase 2 data and is the most talked-about acquisition target in biotech. Structure Therapeutics is building an oral small-molecule GLP-1 that doesn't need peptide manufacturing at all. Healthcare ETFs like XLV and XBI give you exposure to this theme buried inside hundreds of holdings — hospital operators, generic drugmakers, insurance companies, dental suppliers — that have nothing to do with the GLP-1 revolution. This strategy strips away the noise and concentrates on 12 high-conviction names across three layers: the drug makers writing blockbuster prescriptions, the manufacturers scaling to meet demand, and the challengers that could be acquired at a 50% premium overnight. The strategy isn't passive. When biotech enters a sustained downtrend, it automatically moves speculative positions to cash and preserves capital in the revenue-backed core. Each month it ranks every holding by momentum and rotates the weakest names out for the strongest opportunities in. Before earnings and FDA catalyst dates — events that can move biotech stocks 20-30% overnight — it trims profitable positions to lock in gains. A healthcare ETF just sits there and absorbs the drawdown. This strategy was built to manage the volatility that comes with owning the future of metabolic medicine.

Design

How it works

  1. Focuses on 12 companies making or supplying GLP-1 weight-loss drugs

  2. Automatically sells weakest performers each month, buys strongest ones

  3. Reduces risk before major announcements that could swing stocks 20-30%

  4. Moves to cash when the whole biotech sector is falling

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 obesity drug demand is growing and stock prices trending upward
  • When the biotech sector is stable and not in panic mode
  • When new drug approvals or prescription data create positive momentum
  • When you own it for months, not days (strategy needs time to work)

Not built for

  • When the entire biotech sector crashes suddenly (like FDA rejection news)
  • When interest rates spike and investors flee growth stocks overnight
  • When a major drug faces safety concerns or competition emerges
  • When the market is choppy and sideways with no clear direction

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 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%
How we run it
Real trading days

The fastest fall of that size on record: 23 trading days from an all-time high to the bottom. Much of it happened overnight — big companies opened 8-12% below where they had closed the day before.

The rules this strategy follows here

  1. 1
    What it holds

    12 companies.

  2. 2
    When it sells

    One of them drops 15% to 22% below the price it was bought at.

  3. 3
    What it does

    It sells that one. The rest carry on.

On nine days here, the market opened far below where it closed the day before.

An order set to sell at 15% to 22% down can end up selling far below that. If the market opens below that price, there is no chance to sell at it. That is what this market is here to show, and why we keep it in the set.

When markets go nowhere

The Year That Went Nowhere

2015 swung up and down all year and finished where it started.

our model of the S&P 500 around 2015swings about 9% either way, and ends about 1% above where it begana shape, not a scale · not this strategy

Index
S&P 500
The real dates
2 Jan – 31 Dec 2015
What the index did
roughly flat
How we run it
Our model of it

A year that ended where it began, after swinging repeatedly in between — including a 12% drop in August when China devalued its currency, fully recovered by November.

The rules this strategy follows here

  1. 1
    What it holds

    12 companies.

  2. 2
    When it sells

    One of them drops 15% to 22% 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 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

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%

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/glp1-revolution?tab=stress

All ten markets

  • The Bull Run of 2016–17When markets rise · modelled 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 · shown above 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 12 positions this strategy trades. Sign in to see the full basket and the weights behind it.

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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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