Home

Understanding why prices change is the oldest problem in markets. “Supply and demand” is the standard answer, but it rarely tells you how imbalance gets converted into price. In practice, the mechanism lives in the tape: what prints, in what order, and with what persistence. This framing aligns with the APS Viewpoint Decoding the Dynamics of Su...

You know the feeling. You quote both sides. The spread is one tick. Fills arrive often enough to feel productive. Then the market corrects you, quietly. A sell hits your bid. Then another. Then a short burst. You’re long now, but it still looks fine: the bid queue is thick and the book looks “supported.” And then the bid disappears. Not as a...

A sentence keeps showing up in conversations about AI, usually with optimism: “When memorization becomes cheap, understanding becomes valuable.” Sometimes it shows up in technical clothing: “When code production becomes cheap, verification becomes valuable.” The claim sounds like simple economics: when one thing gets cheaper, the sca...

If you want to understand a machine, don’t start with the pitch deck. Put it on a lift. Trace the pipes. Find the parts that glow when you push them too hard. “Equity perpetuals” keep resurfacing in crypto as live markets: TSLA, NVDA, sometimes broad indices. The promise is simple to say out loud: trade equity price exposure like BTC-24/7, wit...

TL;DR: Who’s right about the ADL trilemma? A lot of people are tired already, so here’s the scoreboard up front. Dan is right that: The “ADL trilemma” in Tarun’s paper does not apply to all perp venues in all regimes. The trilemma only bites when the exchange is in a structural deficit regime: expected tail shortfalls...

Tarun Chitra’s ADL paper triggered a big argument around Hyperliquid’s October 10–11 event1234. Who’s right about what, and what actually needs fixing? The ADL debate around Hyperliquid’s October 10–11 event has three main characters: Hyperliquid, whose ADL is implemented in contracts and described only briefly in docs5. Tarun’s paper, w...

When a Transformer controls a $100M DeFi vault, can it be jailbroken into draining funds? When an AI oracle publishes “anonymized” embeddings on-chain, can adversaries recover the private data? These aren’t hypothetical questions, they’re architectural constraints imposed by two recent theorems about the functional properties of deep neural netw...

The Arbitrum post proposes replacing a single, exponential “backlog” pricer with a multi-constraint version and, further, a constraint ladder that inserts intermediate time scales between long-horizon and short-horizon resource constraints1. Short-horizon constraints (keeping executors from falling behind) should prompt fast fee responses, while...