TT-Autotune · data 2026-09-26
XLM 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.
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 (+75.5% mean), and its best single regime is Chop at +129.4%. 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 Quiet, which is no trend and low volatility: tight ranges where fees can eat most edges.
- Bull+
- tuned +12.4% vs default -4.9% (beats default by 17.3 pts)
- Bull-
- tuned +16.3% vs default -3.6% (beats default by 20.0 pts)
- Bear+
- tuned +9.7% vs default +0.5% (beats default by 9.2 pts)
- Bear-
- tuned +12.0% vs default +0.4% (beats default by 11.6 pts)
- Chop
- tuned +5.3% vs default -0.3% (beats default by 5.6 pts)
- Quiet
- tuned +18.4% vs default +1.8% (beats default by 16.7 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 +15.0% vs default +0.0% (beats default by 15.0 pts)
- Bull-
- tuned +20.5% vs default -5.0% (beats default by 25.5 pts)
- Bear+
- tuned +8.2% vs default +0.0% (beats default by 8.2 pts)
- Bear-
- tuned +17.6% vs default +4.3% (beats default by 13.3 pts)
- Chop
- tuned +0.0% vs default +0.0% (trails default by 0.0 pts)
- Quiet
- tuned +10.2% vs default -12.3% (beats default by 22.6 pts)
XLM on the 1h chart
On 1h, 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 +58.7% vs default -5.0% (beats default by 63.7 pts)
- Bull-
- tuned +32.7% vs default -5.7% (beats default by 38.4 pts)
- Bear+
- tuned +24.4% vs default -12.5% (beats default by 36.9 pts)
- Bear-
- tuned +35.5% vs default -1.9% (beats default by 37.5 pts)
- Chop
- tuned +35.0% vs default -9.8% (beats default by 44.8 pts)
- Quiet
- tuned +34.8% vs default +5.6% (beats default by 29.2 pts)
XLM on the 4h chart
On 4h, 6 of 6 regimes beat the default settings, led by Bear-, which is a weak downtrend: a slow bleed with sharp bounces and frequent short squeezes.
- Bull+
- tuned +100.2% vs default -15.0% (beats default by 115.3 pts)
- Bull-
- tuned +30.8% vs default +15.7% (beats default by 15.1 pts)
- Bear+
- tuned +82.7% vs default -5.2% (beats default by 88.0 pts)
- Bear-
- tuned +119.3% vs default +14.3% (beats default by 105.0 pts)
- Chop
- tuned +66.4% vs default -13.4% (beats default by 79.8 pts)
- Quiet
- tuned +50.8% vs default -1.8% (beats default by 52.5 pts)
XLM on the 1d chart
On 1d, 5 of 6 regimes beat the default settings, led by Chop, which is no trend but high volatility: big swings in both directions where breakouts often fail.
- Bull+
- tuned +110.3% vs default +0.0% (beats default by 110.3 pts)
- Bull-
- tuned +97.5% vs default -9.0% (beats default by 106.5 pts)
- Bear+
- tuned +71.3% vs default +17.2% (beats default by 54.1 pts)
- Bear-
- tuned +44.2% vs default -11.7% (beats default by 55.9 pts)
- Chop
- tuned +129.4% vs default -15.8% (beats default by 145.2 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
- 1Connect a trade-only key on a live-ready venue that lists XLM perpetuals, on testnet first.
- 2Open the TensorTrader extension's TT-Autotune tab, select that key and browse the XLM cells.
- 3Enroll the XLM timeframes you want; each becomes one strategy alert with its regime champions injected.
- 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.