What sentiment actually measures
Sentiment is the distance between what participants believe and what they own. When that distance widens, price becomes reflexive; when it closes, price becomes structural.
Sentiment is not what people say. It is what they have done with capital. Reading Bitcoin sentiment means reading positioning across on-chain data, derivatives, and social behavior — and knowing which layer is leading at any given moment.
Sentiment is the distance between what participants believe and what they own. When that distance widens, price becomes reflexive; when it closes, price becomes structural.
On-chain shows conviction. Derivatives show speculation. Social shows narrative. Each lies without the other two — read them together.
IM7 runs sentiment as a stack, not a score: liquidity → positioning → participation → narrative. Each layer explains the next.
Sentiment is contrarian at extremes and trend-following at averages. Most misreadings come from applying one rule to the wrong regime.
The Daily Loop is IM7's operational answer: four touchpoints a day rather than forty refreshes. See the Daily pillar for the schedule.
Every supporting essay under this pillar. Cluster essays are grouped by topic and linked back to strengthen the pillar's authority.
The cost of holding leverage — and what it says about crowds.
How much conviction is currently at risk.
Forced selling as a behavioral signal.
The dry powder of the crypto system.
What is on the shelf, and what has gone home.
What the crowd is saying versus what it owns.
How large holders move — and how often they matter.
Institutional demand as a slow-moving tide.
Participation as confirmation.
The behavioral geometry of the book.
Sentiment is the aggregate emotional and positional state of market participants. It is measured through on-chain data, derivatives, and social behavior.
For Bitcoin, funding rates, open interest, and stablecoin flows carry the most signal. Social indicators confirm — they rarely lead.
Persistently positive funding shows crowded longs; persistently negative funding shows crowded shorts. Both extremes historically precede short-term reversals.
At extremes. Average readings are usually trend-following; extreme readings are usually contrarian.