Palo Alto Networks Inc (PANW) FY2026Q2 Earning Prediction
Palo Alto Networks Inc (PANW) is set to release its FY2026Q2 earnings performance on 02/17 16:10:00 ET in After Hours trading. Consensus forecasts predict a revenue of 2.58B and an earnings per share (EPS) of 0.94 for the FY2026Q2. With Intellectia's exclusive AI algorithms, users can predict whether the earnings will beat or miss expectations before the report drops. Leverage this powerful tool to strategize and position your trades ahead of the earnings release!
AI Earnings Prediction
Palo Alto Networks is expected to exceed revenue expectations due to strategic partnerships and acquisitions, though EPS might remain neutral influenced by M&A costs.
Scenario Analysis
Key Indicators Forecast
No data
Prediction Logic & Rational
The Fact Data highlights strategic initiatives and market positioning that align with Palo Alto Networks' core metrics, outweighing geopolitical and integration risks. Key drivers include:
- Expanded Google Cloud Partnership: Enhances AI-driven security solutions (Prisma AIRS) and cloud infrastructure, likely boosting RPO and NGS/SASE ARR growth.
- Acquisitions (Koi, CyberArk): Strengthen platform consolidation and cybersecurity capabilities, supporting long-term revenue visibility.
- Low Expectations: Stock underperformance (-16% vs. S&P) and minor estimate revisions create a low bar for upside.
Tactical Strategy Recommendations
- Stock: Accumulate shares pre-earnings; lowered expectations and strategic catalysts outweigh risks.
- Options: Buy $160 calls (Feb expiry) for leverage on Beat/Strong Beat scenarios. Hedge with $150 puts (5% allocation) for downside protection.
Rationale: PANW’s AI/cloud momentum and platform consolidation justify a Beat on revenue, though EPS may lag due to M&A costs. Market positioning favors upside surprise given depressed sentiment.
Earnings Surprise Analysis
PANW Transcript
The earnings call summary indicates strong financial performance with significant growth in SASE and NGS ARR, and positive market trends in AI and quantum security. The Q&A highlights management's strategic approach to AI and acquisitions, with positive analyst sentiment. Although some ambiguity exists in ARR contributions, the overall outlook is optimistic with growth in key areas and strategic acquisitions. The absence of major negative factors and the focus on innovation and integration suggest a likely positive stock price movement.
The earnings call indicates strong financial performance and strategic growth plans, including AI and quantum preparedness, SASE growth, and impactful acquisitions like Chronosphere and CyberArk. Despite some lack of detailed guidance, the optimistic outlook on revenue growth, next-gen security ARR, and strategic acquisitions suggest a positive sentiment. The Q&A section supports this with management addressing key growth drivers and strategic initiatives, aligning with the positive sentiment from the earnings summary.
PANW Slides
PANW Report
Frequently Asked Questions
What is the Palo Alto Networks Inc FY2026Q2 Earnings Release Date and Time?
Palo Alto Networks Inc (PANW) is scheduled to release its FY2026Q2 earnings report on Feb 17, 2026, After Hours (approximately 4:00 PM ET). This timing allows investors to react during after-hours trading, with a conference call typically following shortly after.
What Are the Consensus Forecasts for Palo Alto Networks Inc FY2026Q2 Revenue and EPS?
Analysts' consensus predicts 2.58B in revenue and an EPS of 0.94 for Palo Alto Networks Inc's FY2026Q2.
What Does Intellectia's AI Predict for Palo Alto Networks Inc FY2026Q2 Earnings?
Intellectia's exclusive AI algorithms forecast a Beat for Palo Alto Networks Inc's FY2026Q2 earnings, with a prediction date of Feb 17, 2026. Palo Alto Networks Inc Palo Alto Networks is expected to exceed revenue expectations due to strategic partnerships and acquisitions, though EPS might remain neutral influenced by M&A costs.
How Can I Use This Earnings Prediction to Trade PANW Stock?
Leverage Intellectia's AI forecast to position trades ahead of the Feb 17, 2026 release—consider calls for a beat scenario or protective puts for misses. Focus on pre-market volatility, and use the scenario probabilities to build strategies around revenue and guidance updates.
How Accurate Is Intellectia's AI for Earnings Predictions Like Palo Alto Networks Inc FY2026Q2?
Intellectia's predictions are backed by rigorous backtesting, showing a high hit rate for Beat and Miss calls compared to traditional analysis. While no forecast is 100% certain, we provide probability-based scenarios (e.g., 50% chance of a *Beat*) and detailed rationales to help you make informed decisions. Combine our insights with your strategy for the best results—it's like having a co-pilot for earnings season! Empowering users to strategize trades before reports drop.
How does AI Earnings Prediction generate its forecasts?
AI Earnings Prediction uses advanced Large Language Models (LLMs) to analyze a wealth of data, including past earnings transcripts, real-time market sentiment, analyst insights, and company news from the last three months. It focuses on key indicators like revenue, EPS, and margins to predict whether a company will *Beat*, *Miss*, or remain Neutral relative to market expectations. Think of it as a super-smart analyst crunching numbers and news 24/7 to give you a trading edge!
When are the predictions available, and how often are they updated?
Predictions are generated two days before a company's earnings release (e.g., 5:00 PM ET on Feb 13 for a Feb 15 report) to capture the latest market and company data. They're updated in real-time if significant news breaks, ensuring you get fresh insights.
Can I use AI Earnings Prediction for all types of stocks?
Currently, AI Earnings Prediction focuses on companies with market caps above $40 billion, covering major players like SPG, AAPL, MSFT, and NVDA for the 2025-2026 earnings seasons. We prioritize high-impact stocks with robust data to ensure reliable forecasts. Stay tuned as we expand coverage to more companies based on user demand!
