Opinions
Analysis, tutorials, and essays on prediction markets, causal models, and agent-driven trading.
Building a prediction market monitoring system: heartbeat architecture for 24/7 edge tracking
Markets move at 3am and your edge decays while you sleep — here is the architecture for a system that never stops watching.
The complete guide to prediction market order types: market, limit, and thesis-informed
How I decide between market and limit orders on Kalshi, and why a causal model changes the math on both.
Prediction market liquidity: why depth matters more than volume for serious traders
Volume tells you how many people showed up; depth tells you whether you can actually trade.
Causal trees for prediction markets: turning macro intuition into tradeable structure
A practical walkthrough of building hierarchical probabilistic models that map directly to binary contracts on Kalshi and Polymarket.
Prediction market edge detection: a practical framework for finding mispriced contracts
Most prediction market traders have opinions but no framework for measuring whether those opinions are worth trading — here is a systematic approach to finding and sizing edge.
Adversarial search: how I try to kill my own thesis before trading on it
The single most valuable feature in my trading system is the one that actively tries to prove me wrong every 15 minutes.
Limit orders on Kalshi: why thesis-informed makers outperform blind spread collectors
The edge isn't in being a maker — it's in knowing where to place the bid before the book tells you.
How I track my macro thesis across 49 Kalshi contracts without checking the screen
A causal tree, 12 edges, and a heartbeat that runs every 15 minutes so I don't have to.
Your prediction market thesis is in your head. That's a problem.
Most prediction market traders carry their thesis as an unwritten feeling — and bleed money when that feeling quietly shifts without them noticing.
The case for agentic market making on Kalshi
Traditional market makers won't touch prediction markets — but thesis-informed agents with catalyst awareness can provide liquidity and profit from it.
Making vs taking in prediction markets: two completely different games
Most traders don't realize they're playing the wrong game — market making and market taking in prediction markets require opposite personalities, opposite edges, and opposite relationships with time.
I automated my Kalshi thesis with a causal tree. Here's what I learned in 3 months.
Externalizing your thesis into a trackable causal structure changes how you think — not just how you trade.
Why prediction markets break traditional quant models — and what works instead
Statistical models that crush equities fall apart on prediction markets — because there's no history, no continuity, and exactly one instance of every event.
Why Prediction Market Orderbooks Are Nothing Like Stock Orderbooks
Every price is a probability. Every order is a belief statement. Every spread is a disagreement about the future. Prediction market microstructure operates on fundamentally different logic than equities — and the traders who understand that difference are the ones extracting alpha.
Prediction Markets Are Underpriced Insurance
If you are long oil equities, buying "Recession YES" at 35 cents is a cheaper hedge than any options strategy your broker will show you.
Why Your Trading Bot Needs a Thesis, Not Just a Signal
Signal-chasing bots lose money in prediction markets because they confuse price movement with probability changes. Here is the fix.
The Case for Automated Market Making on Kalshi
Most Kalshi markets have wide spreads because nobody is making them. That is both a problem and an opportunity.
Prediction Markets vs Polls: Why Prices Beat Pundits
Polls measure what people say they believe. Markets measure what people will pay to be right. The difference is everything.
AI Agents Don't Need More Data. They Need Judgment.
The bottleneck for AI agents in financial markets isn't data access — it's the ability to structure beliefs, track causation, and know when they're wrong.
Prediction Markets Are Already Pricing the Post-Terminal-Value World
Chamath says terminal value is collapsing. Prediction markets never had terminal value to begin with — every contract has an expiry date. They're the native pricing instrument for a short-duration world.
Kalshi API: From Data to Decisions (Not Just Another Wrapper)
Every Kalshi API article stops at "here's how to call the endpoint." This one starts there.
How to Build a Thesis-Driven Prediction Market Strategy
Not how to build a bot. How to structure your thinking about a prediction market bet — from causal tree to executable edge.