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TT-Autotune · data 2026-10-11

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

Tuned vs default Lorentzian Classification results for SNX across 4 timeframes and six market regimes, and how to automate SNX from TradingView paper first.

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SNX 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 SNX: 4 trained timeframes (15m, 1h, 4h, 1d) and 24 regime cells, of which 23 beat the stock default settings.

On tuned ROI averaged across regimes, the strongest SNX timeframe is 4h (+88.5% mean), and its best single regime is Bear+ at +144.4%. 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.

SNX 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 +19.0% vs default +0.2% (beats default by 18.9 pts)
Bull-
tuned +20.1% vs default -0.3% (beats default by 20.4 pts)
Bear+
tuned +19.3% vs default -1.2% (beats default by 20.5 pts)
Bear-
tuned +11.6% vs default +2.3% (beats default by 9.3 pts)
Chop
tuned +15.3% vs default +1.3% (beats default by 14.0 pts)
Quiet
tuned +25.5% vs default -8.7% (beats default by 34.2 pts)

SNX on the 1h chart

On 1h, 6 of 6 regimes beat the default settings, led by Bear+, which is a strong downtrend: ADX of 25 or more with a strong negative slope, where sellers are in control and bounces fail.

Bull+
tuned +32.4% vs default +0.1% (beats default by 32.3 pts)
Bull-
tuned +23.4% vs default +5.3% (beats default by 18.1 pts)
Bear+
tuned +41.8% vs default +0.8% (beats default by 41.0 pts)
Bear-
tuned +34.7% vs default -9.2% (beats default by 43.9 pts)
Chop
tuned +30.1% vs default -14.4% (beats default by 44.4 pts)
Quiet
tuned +23.6% vs default -15.8% (beats default by 39.4 pts)

SNX on the 4h chart

On 4h, 6 of 6 regimes beat the default settings, led by Bear+, which is a strong downtrend: ADX of 25 or more with a strong negative slope, where sellers are in control and bounces fail.

Bull+
tuned +101.3% vs default -5.6% (beats default by 106.9 pts)
Bull-
tuned +98.8% vs default -6.5% (beats default by 105.4 pts)
Bear+
tuned +144.4% vs default +30.8% (beats default by 113.6 pts)
Bear-
tuned +93.0% vs default -3.2% (beats default by 96.1 pts)
Chop
tuned +78.2% vs default +10.0% (beats default by 68.2 pts)
Quiet
tuned +15.3% vs default +0.0% (beats default by 15.3 pts)

SNX on the 1d chart

On 1d, 5 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 +139.4% vs default -9.4% (beats default by 148.8 pts)
Bull-
tuned +53.1% vs default -27.2% (beats default by 80.3 pts)
Bear+
tuned +87.1% vs default +15.7% (beats default by 71.4 pts)
Bear-
tuned +140.6% vs default -26.4% (beats default by 167.0 pts)
Chop
tuned +93.7% vs default +5.5% (beats default by 88.2 pts)
Quiet
tuned +0.0% vs default +0.0% (trails default by 0.0 pts)

How to read these SNX 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 SNX cell as a hypothesis to paper trade, not a forecast.

Trade SNX from TradingView

  1. 1Connect a trade-only key on a live-ready venue that lists SNX perpetuals, on testnet first.
  2. 2Open the TensorTrader extension's TT-Autotune tab, select that key and browse the SNX cells.
  3. 3Enroll the SNX 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