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ORCL

Oracle CorporationClose $116.10EOD only
Max Pain
$128.00
Next expiry Nov 13, 2026
Expected Move
±$9.25
8.0% from close
Price Gap
+11.90
Distance to max pain
IV Rank
39
Middle-high premium
P/C OI
0.88
Slightly call-heavy
Consensus
5.5/10
Bullish tilt
Published snapshot: Nov 6, 2026 close
End-of-day snapshot

This page reflects ORCL options positioning from the latest published market-close snapshot. Intraday price and contract changes are not displayed.

Published Snapshot
Nov 6, 2026 close
ORCL AI Consensus Report
Analysis based on market close June 26, 2026
DirectionalTheta GangFlowEarningsConsensus

Historical consensus-supported lens with full content, report chain context, and metric rail.

Conviction
5.5

out of 10

5.5 not 7 because while all personas agree on high volatility and gamma risk, the strong bearish-bullish conflict reduces directional conviction.

Where Perspectives Agree

Bearish drift likely given negative gamma and spot below max pain $160, but bullish call flow introduces upside risk, making defined-risk strategies appropriate.

Where They Diverge

Directional and flow personas have opposing directional views (bearish vs bullish), creating low conviction in direction.

Top Trade
via directional

Buy 2026-07-17 $145/$130 put spread for net debit $1.20

Key Risk

Break below $130 flips dealer gamma long and triggers stop-loss cascade, accelerating to $120 support.

How to Use These Reports
This ai consensus reflects the market close on June 26, 2026.
What the reports do

Each report translates the same market-close options snapshot into a specific lens such as directional bias, premium-selling posture, flow quality, or earnings setup.

How traders use them

Reports are most useful for narrowing the playbook, surfacing entry and risk context, and deciding which raw data page to inspect next.

What to remember

These are interpretation layers, not execution guarantees. Validate the setup against chain liquidity, expected move, and exposure before sizing risk.

If the report conviction and the raw data disagree, slow down and resolve the mismatch before sizing risk.