Every strategy we've killed.
Each one was judged on a bar we wrote down before we looked, and published with the real numbers. Tap any row for the full autopsy — and a calculator that compounds exactly what it would have done to your money.
Why these numbers can't be faked →The 27 we have published, backed by 2,248 automated tests. The strategies that survive stay private, that is the edge.
Copying the “smart-money” wallets only looked profitable because one lucky wallet carried the whole group, drop that single wallet and the strategy loses money.
We bet prices would bounce off the day’s high and low; they didn’t. The setup is rare, the move was tiny, and it went the opposite way to the bet.
Our automated HYPE bot lost almost three times as much as you’d have lost by simply buying HYPE and holding it over the same week.
We assumed a price gap would close within half an hour; across 5,800 cases it usually didn’t, the gap tends to stick around, not snap back.
An upgraded copy-trading bot made only two trades in the test window, far too few to prove anything, so we can’t call it a win.
Copying the single best-performing trader made money on paper, but 92% of it came from one trade; over three months he’d have lost to just holding.
We built a filter to improve the copy-trading bot, but the bot was shut down before the filter ever saw enough trades to be judged.
The “free” price gap between exchanges was never once wide enough to cover trading costs, not in a single hour out of 4,216.
A Bitcoin-linked stock doesn’t predict Bitcoin; it just moves alongside it after the fact, so there’s nothing to trade ahead of.
We wanted an AI to read price charts like a human, but the only trader it could have learned from traded coins we don’t touch, so we stopped before spending on it.
Yesterday’s funding rate tells you nothing useful about tomorrow’s price direction, and even if it did, the edge is too small to cover costs.
The volatility around the 8-hour funding reset is real, but it’s spread evenly through the cycle, there’s no special moment to time a trade to.
Trading the speed-up in volatility, rather than its level, added nothing, once you account for the level, the acceleration actually hurts.
Bitcoin and Solana volatility move together at the exact same moment, so there’s no head-start to trade on.
The bot’s own “good day” filter actually picked worse days than the ones it skipped, the filter points the wrong way.
Betting that forced sell-offs keep falling worked in old data but fell apart on fresh data, the effect shrank tenfold and flipped direction.
The trade needed HYPE funding data from Binance and Bybit, but HYPE doesn’t trade there, so there was literally nothing to measure.
Liquidation cascades bounce back rather than keep running, so riding them as they speed up loses money.
Our cascade detector fired perfectly, but prices bounce back instead of continuing, so it pointed us to bet in exactly the wrong direction.
HYPE’s buy/sell gap is too thin to earn the rebate for posting both orders, the spread disappears before both can fill.
When several exchanges agreed on funding direction, that agreement still didn’t predict anything you could trade.
Betting against “overstretched” moves looked great on a chart but lost money on every single coin we tested it on.
This pattern made a tiny profit, but over only eight trades, far too few to tell skill from luck.
There’s no reliable reversal at the Asian market open; the result was indistinguishable from random noise.
We tested about ninety chart patterns at once; after correcting for the fact that a few always look good by chance, not one held up.
A score meant to flag a fragile order book worked on old data but couldn’t tell fragile from stable when shown fresh data.
We checked other exchanges for an edge Hyperliquid didn’t already have; none offered one, so we stayed put.