thetaOwl

MSTR

Strategy IncClose $109.46EOD only
Max Pain
$116.00
Next expiry Jun 26, 2026
Expected Move
±$8.25
7.5% from close
Price Gap
+6.54
Distance to max pain
IV Rank
6
Low premium
P/C OI
0.98
Balanced positioning
Consensus
5.0/10
Bearish tilt
Published snapshot: Jun 22, 2026 close
End-of-day snapshot

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

Published Snapshot
Jun 22, 2026 close
MSTR AI Consensus Report
Analysis based on market close June 23, 2026

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

Conviction
6.5

out of 10

6.5 not 7 because the bearish consensus is tempered by conflicting call flow and the proximity to earnings, which introduces binary risk.

Where Perspectives Agree

All personas favor bearish or neutral positioning with downside risk below $100, supported by negative GEX, high IV, and bearish flow.

Where They Diverge

Flow shows heavy call buying into weakness, which could indicate hedging rather than a bullish shift, while earnings expects post-event IV crush that may offset directional gains.

Top Trade
via directional

Buy 2026-07-31 $107/$95 bear put spread for $1.20 debit

Key Risk

Break below $100 flips dealer gamma long (from negative) and triggers stop-loss cascade, accelerating decline to $95 or lower.

How to Use These Reports
This ai consensus reflects the market close on June 23, 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.