TT-Autotune · data 2026-09-26
VET trading bot: TT-Autotune tuned results by timeframe and regime
Tuned vs default Lorentzian Classification results for VET across 4 timeframes and six market regimes, and how to automate VET from TradingView paper first.
VET 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 VET: 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 VET timeframe is 4h (+78.4% mean), and its best single regime is Chop at +111.7%. 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.
VET 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 +23.5% vs default -12.1% (beats default by 35.5 pts)
- Bull-
- tuned +19.5% vs default -3.0% (beats default by 22.5 pts)
- Bear+
- tuned +9.8% vs default -1.6% (beats default by 11.4 pts)
- Bear-
- tuned +17.7% vs default -1.9% (beats default by 19.6 pts)
- Chop
- tuned +21.7% vs default +1.0% (beats default by 20.8 pts)
- Quiet
- tuned +24.2% vs default +0.2% (beats default by 24.1 pts)
VET on the 1h chart
On 1h, 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 +38.0% vs default -0.5% (beats default by 38.5 pts)
- Bull-
- tuned +29.1% vs default -9.8% (beats default by 38.9 pts)
- Bear+
- tuned +25.5% vs default -2.1% (beats default by 27.6 pts)
- Bear-
- tuned +29.9% vs default -12.9% (beats default by 42.8 pts)
- Chop
- tuned +31.2% vs default -7.3% (beats default by 38.6 pts)
- Quiet
- tuned +41.8% vs default +2.9% (beats default by 39.0 pts)
VET on the 4h chart
On 4h, 6 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 +79.8% vs default -4.1% (beats default by 83.9 pts)
- Bull-
- tuned +108.5% vs default +4.3% (beats default by 104.3 pts)
- Bear+
- tuned +70.1% vs default -2.1% (beats default by 72.2 pts)
- Bear-
- tuned +49.8% vs default -11.5% (beats default by 61.2 pts)
- Chop
- tuned +111.7% vs default -5.1% (beats default by 116.8 pts)
- Quiet
- tuned +50.5% vs default +4.1% (beats default by 46.4 pts)
VET 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 +20.5% vs default -6.8% (beats default by 27.3 pts)
- Bull-
- tuned +82.4% vs default +11.3% (beats default by 71.1 pts)
- Bear+
- tuned +70.3% vs default +26.9% (beats default by 43.4 pts)
- Bear-
- tuned +95.1% vs default -8.3% (beats default by 103.4 pts)
- Chop
- tuned +101.4% vs default +14.6% (beats default by 86.8 pts)
- Quiet
- tuned +0.0% vs default +0.0% (trails default by 0.0 pts)
How to read these VET 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 VET cell as a hypothesis to paper trade, not a forecast.
Trade VET from TradingView
- 1Connect a trade-only key on a live-ready venue that lists VET perpetuals, on testnet first.
- 2Open the TensorTrader extension's TT-Autotune tab, select that key and browse the VET cells.
- 3Enroll the VET 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.