thetaOwl

HYG

iShares iBoxx High Yield Corporate Bond ETFClose $79.83EOD only
Max Pain
$79.50
Next expiry Jun 5, 2026
Expected Move
±$0.19
0.2% from close
Price Gap
-0.33
Distance to max pain
IV Rank
2
Low premium
P/C OI
3.84
Slightly put-heavy
Consensus
9.0/10
Bearish tilt
Published snapshot: Jun 4, 2026 close
End-of-day snapshot

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

Published Snapshot
Jun 4, 2026 close
HYG 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
9.0

out of 10

9 not 10 because while all three align, a low IV environment and potential pin at $80 could slow downside, and a sudden risk-on reversal remains a tail risk.

Where Perspectives Agree

All three personas strongly bearish: aggressive put buying, negative dealer gamma, and extreme put/call ratio signal downside risk; break of $79 support expected.

Where They Diverge

No material conflicts — all recommend bearish structures (put spreads, call credit spreads, follow flow); high alignment across signals.

Top Trade
via directional

Buy HYG 2026-07-17 $79.00/$75.00 put spread

Key Risk

Close above $80 holds for two sessions — gamma flip is avoided, bearish flow unwinds, and the pin at $80 delays downside.

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.