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TT-Autotune · data 2026-10-11

XLMXLM trading bot: TT-Autotune tuned results by timeframe and regime

Tuned vs default Lorentzian Classification results for XLM across 5 timeframes and six market regimes, and how to automate XLM from TradingView paper first.

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XLM with TT-Autotune

TT-Autotune tunes the Lorentzian Classification strategy separately for every token, chart timeframe and market regime, then switches to that regime's champion settings live inside one TradingView strategy alert. This page summarizes what the optimizer found for XLM: 5 trained timeframes (15m, 30m, 1h, 4h, 1d) and 30 regime cells, of which 28 beat the stock default settings.

On tuned ROI averaged across regimes, the strongest XLM timeframe is 1d (+74.1% mean), and its best single regime is Bull+ at +120.7%. ROI here is the sum of per-trade ROI over each cell's walk-forward window, scored with fees and slippage, not a live result.

XLM on the 15m chart

On 15m, 6 of 6 regimes beat the default settings, led by Bull+, which is a strong uptrend: ADX of 25 or more with a strong positive slope, where buyers are in control and pullbacks stay shallow.

Bull+
tuned +19.0% vs default -3.2% (beats default by 22.2 pts)
Bull-
tuned +9.0% vs default -0.6% (beats default by 9.5 pts)
Bear+
tuned +9.5% vs default -1.2% (beats default by 10.6 pts)
Bear-
tuned +16.4% vs default +0.7% (beats default by 15.8 pts)
Chop
tuned +9.8% vs default -0.0% (beats default by 9.8 pts)
Quiet
tuned +12.1% vs default -0.3% (beats default by 12.3 pts)

XLM on the 30m chart

On 30m, 5 of 6 regimes beat the default settings, led by Bull-, which is a weak uptrend: ADX of 18 or more with a gentler positive slope, grinding higher with frequent pullbacks.

Bull+
tuned +13.3% vs default +2.8% (beats default by 10.4 pts)
Bull-
tuned +24.7% vs default -1.4% (beats default by 26.1 pts)
Bear+
tuned +4.5% vs default +0.0% (beats default by 4.5 pts)
Bear-
tuned +19.5% vs default -0.3% (beats default by 19.8 pts)
Chop
tuned +0.0% vs default +0.0% (trails default by 0.0 pts)
Quiet
tuned +11.0% vs default -15.8% (beats default by 26.8 pts)

XLM on the 1h chart

On 1h, 6 of 6 regimes beat the default settings, led by Bull-, which is a weak uptrend: ADX of 18 or more with a gentler positive slope, grinding higher with frequent pullbacks.

Bull+
tuned +28.5% vs default -3.9% (beats default by 32.4 pts)
Bull-
tuned +29.3% vs default +0.2% (beats default by 29.1 pts)
Bear+
tuned +21.5% vs default -1.8% (beats default by 23.3 pts)
Bear-
tuned +27.3% vs default +6.6% (beats default by 20.7 pts)
Chop
tuned +22.8% vs default -12.8% (beats default by 35.6 pts)
Quiet
tuned +20.3% vs default +2.9% (beats default by 17.4 pts)

XLM on the 4h chart

On 4h, 6 of 6 regimes beat the default settings, led by Bull+, which is a strong uptrend: ADX of 25 or more with a strong positive slope, where buyers are in control and pullbacks stay shallow.

Bull+
tuned +99.7% vs default -13.8% (beats default by 113.5 pts)
Bull-
tuned +42.7% vs default +15.2% (beats default by 27.5 pts)
Bear+
tuned +70.7% vs default -2.8% (beats default by 73.5 pts)
Bear-
tuned +87.7% vs default +10.2% (beats default by 77.5 pts)
Chop
tuned +60.6% vs default -9.9% (beats default by 70.5 pts)
Quiet
tuned +45.3% vs default -1.8% (beats default by 47.1 pts)

XLM on the 1d chart

On 1d, 5 of 6 regimes beat the default settings, led by Bull+, which is a strong uptrend: ADX of 25 or more with a strong positive slope, where buyers are in control and pullbacks stay shallow.

Bull+
tuned +120.7% vs default +4.0% (beats default by 116.6 pts)
Bull-
tuned +108.2% vs default -9.0% (beats default by 117.2 pts)
Bear+
tuned +77.7% vs default +17.2% (beats default by 60.5 pts)
Bear-
tuned +42.5% vs default -11.7% (beats default by 54.2 pts)
Chop
tuned +95.4% vs default -15.8% (beats default by 111.2 pts)
Quiet
tuned +0.0% vs default +0.0% (trails default by 0.0 pts)

How to read these XLM numbers

These are optimizer results on historical data, and every champion had to pass gates before publication: positive Sortino and ROI in its regime, beating the default on both, enough trades spread across walk-forward windows, and a plateau rather than a spike. Longer timeframes cover longer calendar windows, so compare timeframes with care. TensorTrader's forward testnet books have not yet shown an edge after fees, so treat any XLM cell as a hypothesis to paper trade, not a forecast.

Trade XLM from TradingView

  1. 1Connect a trade-only key on a live-ready venue that lists XLM perpetuals, on testnet first.
  2. 2Open the TensorTrader extension's TT-Autotune tab, select that key and browse the XLM cells.
  3. 3Enroll the XLM timeframes you want; each becomes one strategy alert with its regime champions injected.
  4. 4Watch fills and closed-trade accounting on paper before any live opt-in.

Not financial advice. Figures are TensorTrader optimizer or backtest results with the method stated; past results do not predict future returns.

Guides · Start on paper