Long/Short Ratio. Which way the crowd is leaning.
Most major derivatives exchanges publish how their users are positioned: what proportion of accounts are net long versus net short, often split between all accounts and the largest traders.
It is the most direct positioning data available, and it is routinely misread because the headline number is account-weighted rather than size-weighted.
Counting accounts and counting money give different answers
If ninety small accounts are long and ten large ones are short, an account-based ratio reports overwhelming bullishness while the actual money is positioned the other way. This is why exchanges publish a separate top-trader ratio, and why the gap between the two is often more informative than either alone: it shows retail and larger participants disagreeing.
Long/Short Ratio in a strategy
An extreme ratio shows one side is heavily populated and therefore vulnerable to a squeeze.
A wide gap between all-account and top-trader ratios is a genuine disagreement worth noting.
A rapid change in the ratio says more than its absolute value, which varies by venue.
Extreme positioning alongside high funding and rising open interest is the classic squeeze precondition.
Only short when the crowd is already long
Rather than a standalone contrarian trade, this uses positioning as permission for a short your strategy already wanted to take.
- IFThe all-account long/short ratio is above 2.0, meaning twice as many accounts are long
- ANDThe top-trader ratio is below 1.0, so larger accounts are net short
- ANDFunding is positive, confirming longs are paying to hold
- ANDYour strategy has independently produced a short entry signal
The second condition is doing the heavy lifting. Retail being long on its own is a weak signal that persists for weeks in a bull market. Retail long while the largest accounts are short is a much narrower and more interesting condition. Requiring an independent entry signal keeps positioning as a filter rather than a trigger, because crowded markets routinely stay crowded far longer than a naive contrarian position can survive.
Binance, Bybit and OKX publish long/short account ratios per contract at fixed intervals.
Several venues publish a separate ratio for their largest accounts by position or margin.
Third-party dashboards combine venues, though the underlying definitions differ enough that comparison is rough.
It only describes one exchange's users
Each venue reports its own population, and those populations differ enormously in size and sophistication. A ratio from one exchange is not a market-wide measurement, and definitions of what counts as a top trader are not standardised between venues.
Build a bot around Long/Short Ratio tonight.
No screens to babysit: define the conditions and the bot does the rest.
- Crowding
- Retail versus top traders
- Shifts, not levels