Deep dives into AI trading, market analysis, and the future of DeFi.
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Replace constant-bps slippage with size, volatility and liquidity-dependent cost curves: the square-root law, fitting curves from TCA fills or public data, regime stress multipliers, and why your strategy leaderboard reshuffles.
Why crypto SOR is harder than equities routing: no consolidated tape, phantom liquidity, prefunded capital. A convex routing optimization with math and Python, maker-aware tactics, and per-venue markout league tables from your own TCA.
Maker vs taker is an adverse-selection trade wearing a fee schedule. Break-even math via Glosten-Milgrom, real crypto fee tiers and token discounts, rebate mining history, queue-dependent rebate value, and modeling tiered fees in a backtest.
Perold's implementation shortfall turned into a working TCA pipeline for crypto bots: arrival-price decomposition, markout curves at t+1s/10s/60s, ~200 lines of Python over your own fills, and feeding the results back into your backtest cost model.
How Aave v3 and Compound liquidations actually work: health factor math, close factors, liquidation bonuses, Chainlink oracle triggers, and what it takes to run a flash-loan liquidation bot in 2026.
How Uniswap v3 really works under the hood: virtual reserves, liquidity L, sqrtPriceX96, tick math, feeGrowthInside, and why an LP position is a short-volatility payoff. With exact formulas and a worked numeric example.
Every swap you send to a public RPC is a visible limit order nobody has to honor. A technical breakdown of how MEV extraction works: mempool ordering, sandwich math on Uniswap v2, PGAs, Flashbots, and trader defenses.