OPEN-SOURCE SCRIPT
AetherEdge - Volatility Forecast
🖊️ Overview
ATR shows yesterday's volatility; AE-VOL forecasts the next move and states the uncertainty honestly. An adaptive EWMA variance model estimates forward volatility, drawn on price as a conformal-calibrated expected-range envelope, alongside a volatility regime and a vol-targeted position-size readout.
🔶 Key Features
Adaptive vol forecast — the EWMA decay λ is learned online and reacts to volatility clustering
Calibrated range envelope — the N-bar range is statistically calibrated to hit a target coverage
Forward cone — projects the forecast range into the future
Volatility regime — low/normal/high with expanding ↑ / contracting ↓
Expected move — next-bar ±% and N-bar ±%
Vol-targeted sizing — a multiple that shrinks when forecast vol is high, grows when low
Alerts on regime change; bar-close updates — no repaint
🧠 Technical Architecture
Vol model (adaptive EWMA): h_t = λ·h_{t-1} + (1-λ)·r² (RiskMetrics — a GARCH(1,1) special case with ω≈0; reactivity = 1-λ, persistence = λ). The single decay λ is learned online by quasi-likelihood (QLIKE) with a recursive derivative. A full 3-parameter GARCH has a flat, ill-conditioned likelihood that single-pass SGD won't recover, so AE-VOL adapts one well-conditioned parameter — robust and honest. Returns are in % for numerical stability.
Calibration (split-conformal): the forecast is wrapped in a distribution-free band — the (1-α) quantile of realized standardized moves rescales the envelope so coverage matches the target empirically (fat tails included). No lookahead: the standardizer is the forecast made N bars ago.
Sizing: multiple = clamp(target vol / forecast vol, min, max).
Honest scope: an EWMA variance recursion + one online-adapted parameter + nonparametric conformal calibration (this tool uses no RL). Not deep learning, not a guarantee.
⚙️ Recommended Settings & Tuning Guide (crypto 15m–4H)
Key parameters: decay learning rate, initial λ, horizon N, band significance (1-α), calibration window, target per-bar vol %.
Initial λ ≈ 0.94 is standard; it auto-adjusts (higher-vol assets converge to lower λ = more reactive)
N is how far ahead you care about; 5–20 bars for 15m–1H
Calibration window ≈ 200; longer is steadier, shorter tracks the recent regime
Target vol % is the per-bar vol you want per position; 0.5–1.5% for crypto 15m–1H
Band significance defaults to 0.90 (10% expected outside); the HUD shows realized coverage
💡 How to Use in Practice
Use the range envelope for take-profit/stop or range judgment (outside the band = statistically unusual)
Regime HIGH favors breakout/trend; LOW (squeeze) flags reversal/range setups
Use the size multiple for vol-targeted money management (auto-smaller in high vol)
The closer coverage is to target, the more trustworthy the band; if it drifts, adjust N or the window
Combine with AE-BPE (breakout probability) or AE-AVP (volume profile) to layer regime × level
⚠️ Important Notes
Needs a learning period (warmup); λ re-learns on timeframe/parameter change
The envelope is a probabilistic range, not a guarantee that price stays inside
The vol forecast gives magnitude, not direction
Probability, not a guarantee — always do your own due diligence and use risk management
🚨 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 decisions are your own — use proper validation and disciplined risk management.
ATR shows yesterday's volatility; AE-VOL forecasts the next move and states the uncertainty honestly. An adaptive EWMA variance model estimates forward volatility, drawn on price as a conformal-calibrated expected-range envelope, alongside a volatility regime and a vol-targeted position-size readout.
🔶 Key Features
Adaptive vol forecast — the EWMA decay λ is learned online and reacts to volatility clustering
Calibrated range envelope — the N-bar range is statistically calibrated to hit a target coverage
Forward cone — projects the forecast range into the future
Volatility regime — low/normal/high with expanding ↑ / contracting ↓
Expected move — next-bar ±% and N-bar ±%
Vol-targeted sizing — a multiple that shrinks when forecast vol is high, grows when low
Alerts on regime change; bar-close updates — no repaint
🧠 Technical Architecture
Vol model (adaptive EWMA): h_t = λ·h_{t-1} + (1-λ)·r² (RiskMetrics — a GARCH(1,1) special case with ω≈0; reactivity = 1-λ, persistence = λ). The single decay λ is learned online by quasi-likelihood (QLIKE) with a recursive derivative. A full 3-parameter GARCH has a flat, ill-conditioned likelihood that single-pass SGD won't recover, so AE-VOL adapts one well-conditioned parameter — robust and honest. Returns are in % for numerical stability.
Calibration (split-conformal): the forecast is wrapped in a distribution-free band — the (1-α) quantile of realized standardized moves rescales the envelope so coverage matches the target empirically (fat tails included). No lookahead: the standardizer is the forecast made N bars ago.
Sizing: multiple = clamp(target vol / forecast vol, min, max).
Honest scope: an EWMA variance recursion + one online-adapted parameter + nonparametric conformal calibration (this tool uses no RL). Not deep learning, not a guarantee.
⚙️ Recommended Settings & Tuning Guide (crypto 15m–4H)
Key parameters: decay learning rate, initial λ, horizon N, band significance (1-α), calibration window, target per-bar vol %.
Initial λ ≈ 0.94 is standard; it auto-adjusts (higher-vol assets converge to lower λ = more reactive)
N is how far ahead you care about; 5–20 bars for 15m–1H
Calibration window ≈ 200; longer is steadier, shorter tracks the recent regime
Target vol % is the per-bar vol you want per position; 0.5–1.5% for crypto 15m–1H
Band significance defaults to 0.90 (10% expected outside); the HUD shows realized coverage
💡 How to Use in Practice
Use the range envelope for take-profit/stop or range judgment (outside the band = statistically unusual)
Regime HIGH favors breakout/trend; LOW (squeeze) flags reversal/range setups
Use the size multiple for vol-targeted money management (auto-smaller in high vol)
The closer coverage is to target, the more trustworthy the band; if it drifts, adjust N or the window
Combine with AE-BPE (breakout probability) or AE-AVP (volume profile) to layer regime × level
⚠️ Important Notes
Needs a learning period (warmup); λ re-learns on timeframe/parameter change
The envelope is a probabilistic range, not a guarantee that price stays inside
The vol forecast gives magnitude, not direction
Probability, not a guarantee — always do your own due diligence and use risk management
🚨 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 decisions are your own — use proper validation and disciplined risk management.
สคริปต์โอเพนซอร์ซ
ด้วยเจตนารมณ์หลักของ TradingView ผู้สร้างสคริปต์นี้ได้ทำให้เป็นโอเพนซอร์ส เพื่อให้เทรดเดอร์สามารถตรวจสอบและยืนยันฟังก์ชันการทำงานของมันได้ ขอชื่นชมผู้เขียน! แม้ว่าคุณจะใช้งานได้ฟรี แต่โปรดจำไว้ว่าการเผยแพร่โค้ดซ้ำจะต้องเป็นไปตาม กฎระเบียบการใช้งาน ของเรา
คำจำกัดสิทธิ์ความรับผิดชอบ
ข้อมูลและบทความไม่ได้มีวัตถุประสงค์เพื่อก่อให้เกิดกิจกรรมทางการเงิน, การลงทุน, การซื้อขาย, ข้อเสนอแนะ หรือคำแนะนำประเภทอื่น ๆ ที่ให้หรือรับรองโดย TradingView อ่านเพิ่มเติมใน ข้อกำหนดการใช้งาน
สคริปต์โอเพนซอร์ซ
ด้วยเจตนารมณ์หลักของ TradingView ผู้สร้างสคริปต์นี้ได้ทำให้เป็นโอเพนซอร์ส เพื่อให้เทรดเดอร์สามารถตรวจสอบและยืนยันฟังก์ชันการทำงานของมันได้ ขอชื่นชมผู้เขียน! แม้ว่าคุณจะใช้งานได้ฟรี แต่โปรดจำไว้ว่าการเผยแพร่โค้ดซ้ำจะต้องเป็นไปตาม กฎระเบียบการใช้งาน ของเรา
คำจำกัดสิทธิ์ความรับผิดชอบ
ข้อมูลและบทความไม่ได้มีวัตถุประสงค์เพื่อก่อให้เกิดกิจกรรมทางการเงิน, การลงทุน, การซื้อขาย, ข้อเสนอแนะ หรือคำแนะนำประเภทอื่น ๆ ที่ให้หรือรับรองโดย TradingView อ่านเพิ่มเติมใน ข้อกำหนดการใช้งาน