Gold’s pullback: thinking beyond buy or sell

Key takeaways

• A sharp pullback in gold does not automatically invalidate a long-term view, but it does raise an important question: how much downside are you willing to tolerate while staying invested.
• LEAPS (long-term equity anticipation securities) are simply listed options with more than one year to expiry. For long-term investors, a LEAPS call on GLD can be a way to keep exposure while defining the maximum loss to the premium paid.
• The example used below is a real contract from the GLD options chain, included to explain mechanics and trade-offs, not as a recommendation.

Why this article exists

After a strong multi-month rally, gold experienced a sudden and violent pullback. Episodes like this often leave investors in an uncomfortable middle ground: selling everything can feel premature, but adding or holding shares with open-ended downside can feel equally unsatisfying.

This article introduces one practical tool long-term investors sometimes use in such situations. It is not about predicting the next move in gold. It is about understanding how long-dated options can help structure exposure when risk control becomes more important than precision.

Setting the scene: trend versus turbulence

Despite the sharp sell-off, GLD remains above its longer-term trend measures on both daily and weekly charts. That does not guarantee anything about the next move, but it helps explain why many investors still view the broader trend as constructive rather than broken.

What LEAPS are, in plain English

LEAPS (long-term equity anticipation securities) are listed options with more than one year to expiry. They work like standard options, just over a longer timeframe.

A LEAPS call gives you the right, but not the obligation, to buy 100 shares of GLD at a fixed price (the strike) up to expiration. You pay a premium upfront. If the option finishes out of the money at expiry (for a call: GLD is below the strike), it expires worthless and the loss is limited to the premium paid.

This article focuses on calls, as they are commonly used by investors to express a constructive long-term view with defined downside.

Why investors sometimes use long-dated calls

Long-dated calls are typically considered for three investor-oriented reasons.

• First, they reduce upfront capital compared with buying 100 shares, while still maintaining exposure to potential upside.
• Second, they make risk explicit. With shares, losses depend on how far the price falls. With a long call, the worst-case outcome is known from day one.
• Third, they encourage discipline. Options force you to think in scenarios: what needs to happen, by when, and what would cause you to reassess.

The trade-off is that options introduce time and volatility sensitivity that shares do not have.

Important note: The strategies and examples provided in this article are purely for educational purposes. They are intended to assist in shaping your thought process and should not be replicated or implemented without careful consideration. Every investor or trader must conduct their own due diligence and take into account their unique financial situation, risk tolerance, and investment objectives before making any decisions. Remember, investing in the stock market carries risk, and it's crucial to make informed decisions.

To make this concrete, the screenshots below show one long-dated GLD call. This is a worked example used to explain mechanics, not a suggestion.

• Underlying: GLD last traded around 427 at the time of the snapshot.
• Expiry: 15 January 2027.
• Strike: 400.
• Call price shown: about 66.
• Indicative delta: roughly 0.70.
• Open interest at this strike: over 10,000 contracts.

Because one contract represents 100 shares, a price of 66 corresponds to about 6,600 USD premium paid. That amount is the maximum loss if the option is held to expiry and finishes out of the money.

At expiry, the breakeven level is the strike plus the premium paid. Using the numbers above, that is around 466.

Three mechanics that matter for investors

You do not need to master option theory to follow the logic, but three concepts are worth understanding.

• Delta. Delta describes how sensitive the option is to moves in GLD. A delta around 0.70 means the option may behave somewhat like holding roughly 70 shares, though this will change over time.
• Time decay. Options lose value as time passes. LEAPS decay more slowly than short-dated options, but they still lose value if GLD moves sideways for long periods.
• Implied volatility. Option prices reflect expected future variability. If volatility falls after a sharp pullback, an option can lose value even if GLD rises modestly.

The part investors often underestimate

Outcomes at expiry are clean and intuitive. The path before expiry is not.

Even if GLD eventually rises, a long-dated call can be uncomfortable to hold during extended sideways periods or renewed volatility. That does not make the idea wrong, but it means position size matters.

A useful self-check is simple: if the premium were marked down materially for several months, would you still be comfortable holding it as the cost of staying exposed.

Strike and expiry choices, briefly

There is no single “best” LEAPS contract.

Longer expiries give the thesis more time to work, but cost more. Lower strikes behave more like shares, but require higher premiums. Higher strikes are cheaper, but more dependent on a strong move.

These are trade-offs, not optimisations.

Key risks to keep in mind

Long-dated calls are conservative relative to many option strategies, but they are still options.

• Time risk: the option expires.
• Volatility risk: implied volatility can fall.
• Liquidity risk: spreads can widen.
• Sizing risk: a defined maximum loss is only helpful if the premium is proportionate to the portfolio.

A simple decision checklist

• What is your long-term reason for owning gold exposure.
• What would change that view.
• How large is the premium relative to your portfolio.
• What would make you reassess the position before expiry.

Closing thought

LEAPS on GLD are best viewed as a risk budgeting tool, not a forecasting tool. They can help investors stay exposed after a sharp pullback while keeping downside explicit.

As with any option, the discipline lies less in choosing the “right” contract and more in sizing it appropriately and understanding what you are paying for.

• Disruption fears stay loud, but customer commitments stay real, which is the first sign the model still works.

• Snowflake benefits from the “AI needs data” flywheel, yet guidance tone still drives near-term sentiment.

• Salesforce proves paid AI is moving beyond demos, but investors still watch for seat compression and pricing pressure.

Snowflake and Salesforce just gave investors something rare in an AI-driven market: fresh evidence. The debate is loud, but the questions are simple. Does artificial intelligence (AI) make software easier to replace. Does it shrink pricing power. Or does it increase demand for the platforms that make AI useful.

This review uses the same lenses from our software as a service (SaaS) disruption shortlist.

Our disruption shortlist is not a “winners and losers” list. It is a way to ask better questions. Earnings are useful because they force management to answer those questions with numbers, customer language, and guidance.

Four lenses matter most for long-term investors:

First, pricing mechanics. Seat-based pricing depends on how many people log in. Task-based pricing depends on how much work gets done. AI agents can reduce seats, but they can also create new tasks.

Second, bundling pressure. When a large platform adds “good enough” features, point tools can lose pricing power even if the product is still good.

Third, proof of paid AI. Demos are easy. Paid add-ons and recurring revenue are harder, and more informative.

Fourth, forward demand. Bookings and backlog measures help you see what customers commit to, not just what they used last quarter.

With that in mind, Snowflake and Salesforce tell two different, but connected stories.

Snowflake: the “picks and shovels” case, with one catch

Snowflake sells cloud software that helps companies store, organise, and analyse data. If AI is a new engine, data is still the fuel. That puts Snowflake closer to “enabler” than “victim”.

The headline from the release is that demand looks healthy and customer commitments beat expectations, according to data compiled by Bloomberg. That matters because disruption fears often start with a scary assumption: “customers will pause spending until the dust settles”. Snowflake does not show that kind of freeze.

The softer part is guidance tone. Management guides next quarter product revenue roughly in line with Bloomberg consensus. In a calm market, “in line” is fine. In a nervous market, “in line” can feel like “not enough”, especially when investors want a bold statement that AI demand is accelerating right now.

Snowflake’s strategic message is also clear: it keeps expanding the product set, especially AI tools that sit on top of data already in the platform. AI revenue is still early, with the company previously pointing to about 100 million USD in annual revenue run rate for AI products. That is encouraging, but it also tells you why the stock reaction can be fussy. The promise is big, the proof is still building.

Snowflake’s main risk is not that AI replaces it. The risk is that large platforms bundle more data tooling into broader cloud contracts, turning “best of breed” into “nice to have”. Snowflake must keep earning the right to be the specialised layer.

Salesforce: strong AI traction, but the market wants a cleaner growth story

Salesforce is the leading customer relationship management (CRM) software company. It runs sales and service workflows for many large firms. That scale is an advantage, but the pricing model creates a classic disruption worry: if AI agents do more work, customers may need fewer human users, and therefore fewer seats.

This is why Salesforce sits in a tricky middle ground. It can benefit from AI adoption, yet it also has more to defend. The quarter itself reads well, but guidance lands as lukewarm, and that is what drives the narrative.

The key positive is that Salesforce puts real weight behind Agentforce, its AI agent product. Management says Agentforce annual recurring revenue (ARR) reaches 800 million USD, up 169% year on year, and it highlights a rising count of Agentforce deals. That is the kind of data point our shortlist lens looks for. It signals that AI is moving from “feature” to “paid product”.

The key question is what happens next. Salesforce talks about organic growth re-acceleration later in the year. Investors hear a different subtext: “show me that AI adds revenue, not just buzzwords”. This matters because AI can push pricing in two directions at once. It can expand value if customers pay for outcomes. It can compress value if customers cut seats and negotiate harder.

Salesforce also leans on customer commitments, pointing to remaining performance obligations (RPO), a future revenue indicator. In a market obsessed with disruption, those commitments are a quiet counterpoint: customers still sign multi-year deals when the platform is deeply embedded.

Risks: where the story can still turn

The first risk is budgeting, not technology. If enterprise spending tightens, consumption and new projects slow quickly, even if the product remains strategically important.

The second risk is bundling. AI makes it easier for bigger platforms to ship “good enough” features faster, which can pressure pricing across SaaS.

The third risk is measurement. If companies talk a lot about AI but show little paid adoption, the market’s patience can run out fast. Watch for vague language that replaces clear metrics.

Investor playbook

• Track customer commitments like RPO and renewals. They show real confidence, not only usage.

• Separate “AI trials” from “paid AI”. Look for recurring revenue, not just product announcements.

• Listen for pricing shifts from seats to tasks. It often signals where value is moving.

• Watch bundling signals. When platforms include features for “free”, standalone tools must prove differentiation.

The obituary is early, but the checklist stays

AI has turned software investing into a weekly debate club. These two earnings calls drag it back to something more useful: what customers commit to, and what they actually pay for. Snowflake looks like plumbing for the AI era, but investors still want guidance that feels bolder than “fine”. Salesforce shows that AI can be monetised, yet the market still asks whether agents add revenue faster than they compress seats.

The neat takeaway is not that SaaS is dead, or saved. It is that disruption is a process, not a headline. Earnings are the weather report. The long-term climate still depends on pricing power, product relevance, and execution. This material is marketing content and should not be regarded as investment advice. Trading financial instruments carries risks and historic performance is not a guarantee of future results. The instrument(s) referenced in this content may be issued by a partner, from whom Saxo receives promotional fees, payment or retrocessions. While Saxo may receive compensation from these partnerships, all content is created with the aim of providing clients with valuable information and options.