thetaOwl

MSTR

Strategy IncClose $129.37EOD only
Max Pain
$140.00
Next expiry Jun 5, 2026
Expected Move
±$5.17
4.0% from close
Price Gap
+10.63
Distance to max pain
IV Rank
70
High premium
P/C OI
1.02
Balanced positioning
Consensus
6.0/10
Bullish tilt
Published snapshot: Jun 4, 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 4, 2026 close
MSTR AI Consensus Report
Analysis based on market close June 5, 2026

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

Conviction
7.0

out of 10

7 not 8 because the short-vs-long premium conflict and lack of near-term catalyst reduce certainty; if spot breaks below $104, conviction increases to 8.

Where Perspectives Agree

All personas bearish — short gamma, heavy put flow, and negative net premium reinforce downside pressure toward $104 support.

Where They Diverge

Theta recommends short premium (strangle/credit spread) which profits from volatility crush, directly conflicting with directional and earnings long put strategies that benefit from downside expansion.

Top Trade
via directional

Buy 2026-06-26 $120/$105 bear put spread for $3.50 debit — defined risk, aligns with directional/flow/earnings consensus.

Key Risk

Spot rallies above $130 — flips dealer gamma positive, triggers short covering, and invalidates bearish thesis due to call wall absorption.

How to Use These Reports
This ai consensus reflects the market close on June 5, 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.