Cybersecurity stocks are surging. One looks promising into earnings
by Michael Khouw · CNBCIn this article
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Zscaler reports after the close. I'm leaning long the stock, which appears to be in the midst of a bearish-to-bullish reversal, but not long premium (the options).
At a 12.2% implied move versus an 11.3% long-term average, options aren't cheap.
I want to be relatively net flat premium with a bullish tilt/sentiment (aka "delta"). A call spread risk reversal, selling an out-of-the-money put and using the proceeds to buy a call spread, gives me long exposure, little to no premium outlay, while taking slightly less risk than purchasing the stock outright in the event earnings aren't well-received. The selling of the downside put will tie up cash, but no more than if you simply bought the stock.
Revenue is growing 26% year-over-year, trailing 12-month revenues are expected to hit $3.32 billion, and free cash flow margins are running at roughly 27%. With ~$1 billion in NTM free cash flow and nearly 24% expected YoY FCF growth, this may well become a cash compounding machine, and the $1.7 billion in net cash means no lurking balance sheet land mines. The Zero Trust Exchange platform is the linchpin for AI security, and that's not marketing language — it's architecture. When every enterprise AI agent needs a secure, inspectable pathway to cloud resources, Zscaler's inline proxy model is structurally positioned in a way that legacy firewall vendors simply cannot replicate. Palo Alto and Fortinet are retrofitting on-premise mindsets onto a cloud-native problem. ZS was born in the cloud, which is one reason why this is a SaaS business that can succeed in an AI world.
The AI agent exposure is the under-appreciated catalyst. Every new AI workload — Copilots, autonomous agents, LLM API calls — is a new traffic stream that needs to be inspected, secured, and governed by policy. Zscaler's AI Guardrails for public and private apps, along with its expanding AI security portfolio, are being built specifically to address the emerging risks posed by AI models and applications.
None of this suggests there aren't any business risks. Net retention could decelerate if enterprise budget cycles tighten. Hyperscaler competition, macro headwinds, and unmonetized AI features. The GAAP losses, while narrowing, give ammunition to critics who argue the profitability story keeps getting pushed out. This is an important quarter because the street's expectation is for reported profits. The stock has already recovered meaningfully from its lows on this expectation, so some of the good news may already be priced in.
The bottom line: The fundamentals are compounding, the AI security thesis is real and accelerating, the balance sheet is clean, and the market has already told me the fear is fairly priced.
I'll take the other side of that fear all day.