Sentiment-Cycle Convergence
I'm an independent crypto analyst operating from Austin, Texas — the epicentre of America's digital asset ecosystem. My work sits at the intersection of behavioural finance and blockchain data science, producing a unique analytical discipline I call 'sentiment-cycle convergence': the study of how crowd psychology, social media velocity, and narrative momentum map onto repeating market cycle structures.
Where most analysts fixate on price charts or isolated on-chain metrics, I build composite behavioural models that track the emotional architecture of market phases — accumulation apathy, early-cycle curiosity, mid-cycle euphoria, and distribution denial. My proprietary frameworks aggregate social sentiment scoring, funding rate psychology, exchange deposit behaviour, and Google Trends velocity to identify cycle inflection points before they materialise in price.
My editorial output is distinguished by its contrarian clarity. I consistently publish against prevailing market consensus when my sentiment models diverge from crowd positioning — a discipline that has earned me a reputation for identifying major tops and bottoms ahead of the curve.