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ORCL

Oracle CorporationClose $192.64EOD only
Max Pain
$185.00
Next expiry Jun 18, 2026
Expected Move
±$8.78
4.6% from close
Price Gap
-7.64
Distance to max pain
IV Rank
41
Middle-high premium
P/C OI
0.89
Slightly call-heavy
Consensus
8.0/10
Bullish tilt
Published snapshot: Jun 15, 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
Jun 15, 2026 close
ORCL AI Consensus Report
Analysis based on market close June 16, 2026
DirectionalTheta GangFlowEarningsConsensus

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

Conviction
6.5

out of 10

6.5 not 7.5 because mixed net premium and call flow cap upside, but positive GEX and pinning consensus prevent lower score.

Where Perspectives Agree

All personas see a pinning range between $185 and $200 with dealer gamma support, despite bearish net premium and high IV.

Where They Diverge

Flow's aggressive call buying suggests upside, but earnings note negative net premium and call wall cap upside, creating directional ambiguity.

Top Trade
via earnings

Sell 2026-07-02 $177.50/$172.50 put spread and $205.00/$210.00 call spread for $0.85 credit

Key Risk

Break below $185 support flips dealer gamma long, accelerating downside to $175; break above $200 caps upside.

How to Use These Reports
This ai consensus reflects the market close on June 16, 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.