Strategy

Wolf: the quantum hunter

A set of quantitative bots, one per trading pair, for long and short trading. Each bot looks for statistical price deviations and trades the return towards the expected range.

Trading pairs
46
Active bots
178
Avg. risk per trade
L0.5% S0.5%
Total returnfor 181 days
+19.47%
Timeframes6h · 8h · 12h · 1d
Closed trades3,689
Win rate77.7%
Max drawdown-2.5%

Best pairs over the whole history: NEARUSDT +1.82%BATUSDT +1.52%RSRUSDT +1.09%SUSDT +0.98%XLMUSDT +0.82%CHZUSDT +0.81%

Statistics updated daily · 07.11.2026. Results of the strategies on historical data; not the result of your account and no guarantee of future returns.

How Wolf trades

What Wolf trades

Wolf runs one bot per pair on 40+ USDT perpetual pairs. Each bot measures how far the price has deviated from its expected range on 6h to 1d candles and enters against the deviation, long after an excessive fall and short after an excessive rise.

Virtual losses and market memory

Wolf keeps a record of the trades it would have made. A series of virtual losses is a signal that the market phase is about to turn, and the bot enters only after it. Read more in the blog: Wolf and market memory.

AI entry filter

When enabled, a machine-learning model checks the entry conditions and skips entries with a weak forecast. Order levels, exits and risk are defined by the strategy rules and are the same for every pair.

Who it suits

Who Wolf suits

Traders who want wide diversification across altcoins with the same logic on every pair and both market directions. Wolf's history in the catalog starts in May 2026, when the current model was trained, so its statistics are fully out-of-sample.

What to keep in mind

Many pairs mean many simultaneous positions. The risk per entry of each bot is small, but check the total: 40 pairs with the x1 multiplier use a visible share of the deposit in a volatile week.

Questions about Wolf

How many pairs can I select?

Any subset of the strategy's pairs; the dashboard shows which are available on your exchange. You can also set a different risk multiplier for every pair.

Why does the history start in May 2026?

The AI entry filter was trained on data before that date. The catalog shows only the period the model did not see during training, so the statistics are not inflated by in-sample results.

Can I combine Wolf with Mole?

Yes. Both strategies are built from one-pair bots, so you can pick bots of both in My assembly and run them on one account.

Where do the statistics come from?

From the daily tests of every bot on historical Binance candles, net of exchange fees, on a fixed deposit with multiplier x1. Not a client result and no guarantee of future returns.

Ready to let the strategies trade?

Register, connect an exchange and pay only from the profit.

Start trading