Tutorial TUT trading strategies
Live snapshot 05 Oct 2026, refreshes on load.
Net -40% over 30 days but a choppy path, a ranging read. The engine favours mean-reversion and waits for a real trend before committing.
Tutorial's short-term read (Bear) doesn't match its otherwise-consistent Choppy read elsewhere - exactly the kind of setup where the engine waits for confirmation across timeframes rather than committing to one story too early.
How zengtrade trades Tutorial
Tutorial doesn't yet have enough of a distinct behavioural profile in zengtrade's playbook to get a specialised angle, so the engine treats TUT with its standard regime-aware rules: confirm the trend, size conservatively, and stand down in choppy or high-vol conditions. Every strategy runs paper-first on live TUT data, so you prove an edge before a dollar is at risk, then run it on your own exchange (non-custodial, your keys).
Honest about the cost
zengtrade never hides friction. Fees, slippage and (for Indian users) the 1% TDS are subtracted from every TUT backtest and paper trade, so the edge you see is the edge net of cost, not a gross number that evaporates live. See exactly how these costs are calculated →
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Add real-time Tutorial (TUT) Binance spot pricing, 30-day trend chart, and quantitative regime detection to your crypto blog, Substack, Medium post, or research portal. Free, responsive, and updates live.
Tutorial FAQ
Can I paper-trade Tutorial strategies on zengtrade?
Yes. zengtrade runs regime-aware strategies on Tutorial (TUT) using live market data, 24/7, in paper first, so you prove an edge before any real capital is at risk.
Is Tutorial trading on zengtrade custodial?
No. zengtrade is non-custodial. Live execution runs on your own exchange with your own keys. It never holds your TUT or funds.
What market regime is Tutorial in right now?
As of 05 Oct 2026, Tutorial's 30-day tape reads Neutral/Choppy. Net -40% over 30 days but a choppy path, a ranging read. The engine favours mean-reversion and waits for a real trend before committing. Regimes change, so the engine re-reads every cycle.
Does Tutorial's short-term read agree with its longer-term trend?
Tutorial's short-term read (Bear) doesn't match its otherwise-consistent Choppy read elsewhere - exactly the kind of setup where the engine waits for confirmation across timeframes rather than committing to one story too early.
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Live data · educational software, not investment advice · paper-first, non-custodial