thetaOwl

MSTR

Strategy IncClose $179.36EOD only
Max Pain
$149.00
Next expiry Apr 24, 2026
Expected Move
±$9.75
5.4% from close
Price Gap
-30.36
Distance to max pain
IV Rank
34
Middle-high premium
P/C OI
0.82
Slightly call-heavy
Consensus
6.5/10
Range bias
Published snapshot: Apr 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
Apr 22, 2026 close
MSTR AI Consensus Report
Analysis based on market close April 23, 2026

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

Conviction
5.5

out of 10

5.5 because dealer gamma pinning and rich premium align sellers today, but mixed institutional flow plus an impending binary (earnings/news) meaningfully raise one-way tail risk that prevents higher conviction.

Where Perspectives Agree

Short-term pinning between roughly $150–$180 creates a neutral-to-mildly-bearish backdrop where selling defined-risk premium is the dominant, consensus response.

Where They Diverge

Earnings/event view flags a near-term binary that could produce a gap up and invalidate sell bias, while flow shows some institutional accumulation that suggests a rally could be sustained—those two directly contradict the premium-selling-as-safe thesis.

Top Trade
via theta

Sell May 08 $182.50/$200.00 call spread for a net credit (defined-risk, short call spread, expires pre-next monthly cycle).

Key Risk

A clean break and close above $200 on strong volume (news-driven or institutional flow) would flip dealer gamma short, remove the pin, and accelerate upside toward $220, invalidating the premium-selling thesis.

How to Use These Reports
This ai consensus reflects the market close on April 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.