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AetherEdge - VECTOR | Conformal Forecast
🖊️ Overview
AE-VECTOR forecasts the move over the next H bars and attaches a calibrated prediction interval to the target. A point estimate alone cannot be trusted or sized. AE-VECTOR learns the expected move with online regression and uses conformal prediction to draw a band around the target within which the realized value lands roughly 1 − α of the time. Its essence is quantifying the uncertainty of the forecast, not just its center.
🔶 Key Features
Online linear regression that learns the H-bar move (in ATR units) — m̂
A calibrated target band via conformal regression (target ± q·ATR, coverage ≈ 1 − α)
The band is volatility-normalized, so it widens in high vol and tightens in low vol automatically
A target cone at the right edge (projection line + band box + target/coverage label)
A highly selective signal that fires only when decisive (even the pessimistic band end is beyond price)
A gold HUD showing direction, predicted move, target, band width, coverage, and decisiveness
No repaint — signals gate on bar close; labels use the H-bar-lagged realized move
🧠 Technical Architecture
Regression: trend slope, RSI momentum, short momentum, range position, and volatility regime are standardized (EWMA), and a linear model m̂ = w·x + b is trained by SGD (squared loss, L2). The label is the realized H-bar move (ATR units); the current forecast uses no future data.
Conformal target band: the realized absolute residuals of past forecasts (in ATR units, i.e. volatility-normalized) are stored in a rolling calibration set. For a new forecast, the (1 − α) empirical quantile q gives the band target ± q·ATR. By the split (inductive) conformal guarantee, the realized value falls inside this band with coverage calibrated to about 1 − α.
Honest scope: a linear regressor plus inductive conformal prediction — not a neural network, and not a guarantee of the point estimate. What is guaranteed is the band's coverage.
⚙️ Recommended Settings & Tuning Guide
Key parameters: H (horizon), α (band coverage = 1 − α), moveThr (minimum predicted move), lr (learning rate), warmup.
Lower α → wider, higher-coverage band (conservative); higher → tighter band
H: small (5–8) for scalping, large (20–40) for swing
Crypto starting points (tune on your chart):
BTC / ETH (1H–4H): defaults are the baseline (H = 10, α = 0.10)
SOL / XRP and high-vol alts: moveThr ≈ 0.8 to filter small noisy forecasts; α = 0.08 for a slightly wider band
Scalping (5–15m): H = 5–8, lr = 0.02 for fast adaptation
Swing (daily): H = 20–40, raise calibN to stabilize the quantile estimate
Requiring "decisive" narrows to confident targets where even the pessimistic band end favors the trade
💡 How to Use in Practice
As a target: the cone's center line is the target, the band its uncertainty — an objective basis for take-profit levels and R:R
Reading band width: narrow = stable forecast (model confident), wide = uncertain (stand aside or downsize)
Decisive signals: a calibrated, strong condition that the target sits beyond price even pessimistically — useful at the start of a move
What coverage means: a 90% band has historically contained ~90% of realized values — a calibrated expectation
Multi-timeframe: target direction from a higher-timeframe VECTOR, timing on a lower one
Combinations: pair with AE-QUORUM's directional probability or AE-HELM's trade management, and design exits with VECTOR's band
⚠️ Important Notes
Learning period: until both the regression and the calibration spin up (warmup + minCalib bars), the target shows "warming" and no signals fire
Learning reset: changing inputs, symbol, or timeframe re-learns the internal state
The band is guaranteed, not the center: the point estimate can be wrong, and during shocks the band can briefly under-cover
Linear extrapolation has limits: it is weak to sharp regime changes and unforeseen news — treat it as a projection of the current state
🚨 Disclaimer
This indicator is for educational and informational purposes only and is not financial advice or a recommendation to buy or sell. No method guarantees future profits; past performance does not indicate future results, and trading carries the risk of loss. All trading decisions are your own — use proper backtesting and disciplined risk management.
AE-VECTOR forecasts the move over the next H bars and attaches a calibrated prediction interval to the target. A point estimate alone cannot be trusted or sized. AE-VECTOR learns the expected move with online regression and uses conformal prediction to draw a band around the target within which the realized value lands roughly 1 − α of the time. Its essence is quantifying the uncertainty of the forecast, not just its center.
🔶 Key Features
Online linear regression that learns the H-bar move (in ATR units) — m̂
A calibrated target band via conformal regression (target ± q·ATR, coverage ≈ 1 − α)
The band is volatility-normalized, so it widens in high vol and tightens in low vol automatically
A target cone at the right edge (projection line + band box + target/coverage label)
A highly selective signal that fires only when decisive (even the pessimistic band end is beyond price)
A gold HUD showing direction, predicted move, target, band width, coverage, and decisiveness
No repaint — signals gate on bar close; labels use the H-bar-lagged realized move
🧠 Technical Architecture
Regression: trend slope, RSI momentum, short momentum, range position, and volatility regime are standardized (EWMA), and a linear model m̂ = w·x + b is trained by SGD (squared loss, L2). The label is the realized H-bar move (ATR units); the current forecast uses no future data.
Conformal target band: the realized absolute residuals of past forecasts (in ATR units, i.e. volatility-normalized) are stored in a rolling calibration set. For a new forecast, the (1 − α) empirical quantile q gives the band target ± q·ATR. By the split (inductive) conformal guarantee, the realized value falls inside this band with coverage calibrated to about 1 − α.
Honest scope: a linear regressor plus inductive conformal prediction — not a neural network, and not a guarantee of the point estimate. What is guaranteed is the band's coverage.
⚙️ Recommended Settings & Tuning Guide
Key parameters: H (horizon), α (band coverage = 1 − α), moveThr (minimum predicted move), lr (learning rate), warmup.
Lower α → wider, higher-coverage band (conservative); higher → tighter band
H: small (5–8) for scalping, large (20–40) for swing
Crypto starting points (tune on your chart):
BTC / ETH (1H–4H): defaults are the baseline (H = 10, α = 0.10)
SOL / XRP and high-vol alts: moveThr ≈ 0.8 to filter small noisy forecasts; α = 0.08 for a slightly wider band
Scalping (5–15m): H = 5–8, lr = 0.02 for fast adaptation
Swing (daily): H = 20–40, raise calibN to stabilize the quantile estimate
Requiring "decisive" narrows to confident targets where even the pessimistic band end favors the trade
💡 How to Use in Practice
As a target: the cone's center line is the target, the band its uncertainty — an objective basis for take-profit levels and R:R
Reading band width: narrow = stable forecast (model confident), wide = uncertain (stand aside or downsize)
Decisive signals: a calibrated, strong condition that the target sits beyond price even pessimistically — useful at the start of a move
What coverage means: a 90% band has historically contained ~90% of realized values — a calibrated expectation
Multi-timeframe: target direction from a higher-timeframe VECTOR, timing on a lower one
Combinations: pair with AE-QUORUM's directional probability or AE-HELM's trade management, and design exits with VECTOR's band
⚠️ Important Notes
Learning period: until both the regression and the calibration spin up (warmup + minCalib bars), the target shows "warming" and no signals fire
Learning reset: changing inputs, symbol, or timeframe re-learns the internal state
The band is guaranteed, not the center: the point estimate can be wrong, and during shocks the band can briefly under-cover
Linear extrapolation has limits: it is weak to sharp regime changes and unforeseen news — treat it as a projection of the current state
🚨 Disclaimer
This indicator is for educational and informational purposes only and is not financial advice or a recommendation to buy or sell. No method guarantees future profits; past performance does not indicate future results, and trading carries the risk of loss. All trading decisions are your own — use proper backtesting and disciplined risk management.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.
오픈 소스 스크립트
트레이딩뷰의 진정한 정신에 따라, 이 스크립트의 작성자는 이를 오픈소스로 공개하여 트레이더들이 기능을 검토하고 검증할 수 있도록 했습니다. 작성자에게 찬사를 보냅니다! 이 코드는 무료로 사용할 수 있지만, 코드를 재게시하는 경우 하우스 룰이 적용된다는 점을 기억하세요.
면책사항
해당 정보와 게시물은 금융, 투자, 트레이딩 또는 기타 유형의 조언이나 권장 사항으로 간주되지 않으며, 트레이딩뷰에서 제공하거나 보증하는 것이 아닙니다. 자세한 내용은 이용 약관을 참조하세요.