The Volatility Weighting Function (VWF) is the mathematical engine that powers the Timeframe-Weighted Volatility Framework (TWVF). While the Universal Volatility Baseline (DS = 16 × ATR256) defines the structural protection boundary, and the Timeframe-Indexed Exposure Curve (1%–9%) allocates risk across time, it is the VWF that binds these components into a unified, volatility-coherent system.
In short:
VWF is the formula that adjusts risk, position size, and break-even behavior according to volatility structure, timeframe depth, and macro-regime stability.
1. Purpose of the Volatility Weighting Function
The purpose of VWF is to ensure that GATS respects the relative volatility landscape of the asset being traded. Each asset exhibits:
- a unique volatility signature,
- a volatility noise floor,
- a volatility expansion ceiling,
- a regime transition behavior.
A static volatility model cannot accommodate these differences. VWF solves this by dynamically weighting volatility according to:
- timeframe (1–9),
- asset volatility (ATR256 vs ATR50),
- regime environment (Nine Laws),
- DAATS adaptation cycles.
This ensures that GATS is universally stable across all markets and all time horizons.
2. Core Equation of the Volatility Weighting Function
The VWF formula is expressed as:
VWF = ( ATR₅₀ / ATR₂₅₆ ) × TFᵂ × R
Where:
- ATR₅₀ = local (adaptive) volatility,
- ATR₂₅₆ = structural (regime) volatility,
- TFᵂ = timeframe weight (1–9),
- R = regime adjustment coefficient from the Nine Laws.
This formula dynamically adjusts risk by aligning:
- short-term volatility movements,
- long-term volatility truth,
- timeframe strength,
- macro-regime filters.
This makes the system responsive without destabilizing its structural integrity.
3. Interpretation of ATR₅₀ / ATR₂₅₆
The ratio ATR₅₀ / ATR₂₅₆ is the core of volatility intelligence in GATS.
It expresses:
the current volatility regime relative to the long-horizon volatility baseline.
The ratio reveals three fundamental volatility states:
A. Compression State (ATR₅₀ < ATR₂₅₆)
- market is contracting,
- trends are forming or pausing,
- risk should be decreased,
- stops should tighten adaptively.
B. Equilibrium State (ATR₅₀ ≈ ATR₂₅₆)
- market is stable,
- trends behave normally,
- risk remains neutral.
C. Expansion State (ATR₅₀ > ATR₂₅₆)
- market is trending strongly,
- large moves are possible,
- risk may be increased,
- DAATS must widen adaptively.
This ratio is the most powerful volatility detector in the system.
4. Timeframe Weight TFᵂ (1–9)
TFᵂ maps directly to the Timeframe-Indexed Exposure Curve:
- M1 = 1
- M5 = 2
- M15 = 3
- M30 = 4
- M60 = 5
- M240 = 6
- M1440 = 7
- M10080 = 8
- M43200 = 9
It ensures that:
- higher timeframes have greater influence on volatility weighting,
- lower timeframes remain sensitive to microstructure changes,
- exposure increases with trend reliability.
This makes the system naturally fractal.
5. The Role of Regime Adjustment (R)
The Nine Laws Framework provides the regime coefficient R. It encodes behaviors such as:
- correlation spikes (CRTL),
- volatility dissipation (WDHDI),
- macro shock propagation (MSPL),
- break-even gating (ADBED),
- slippage and transaction cost buffers (TCSOL).
R scales volatility weighting according to regime intensity:
- R > 1 during instability,
- R = 1 in normal regimes,
- R < 1 during compression.
This turns VWF into a regime-aware volatility engine.
6. How VWF Integrates With Position Sizing
Position size under TWVF becomes:
Position Size = (Risk$ / DS) × (1 / VWF)
Meaning:
- Higher volatility → smaller position
- Lower volatility → larger position
- Higher timeframe → larger position
- Higher instability → smaller position
This ensures **universal stability** across all markets.
7. How VWF Integrates With Break-Even Logic
Break-even behavior under TWVF uses:
BE% = Risk% × VWF Post-BE% = Risk% × VWF
This ensures:
- BE events occur earlier during instability,
- BE events occur later during macro trends,
- BE logic adapts to volatility cycles.
This makes TWVF self-stabilizing.
8. The Philosophical Meaning of VWF
VWF represents Dr. Glen Brown’s view that:
Volatility is not something to avoid. It is something to understand, weight, and harmonize with.
Just as the Universal Volatility Baseline reveals macro truth, VWF reveals local truth and connects it with temporal truth.
Thus, VWF is both:
- a quantitative mechanism, and
- a philosophical principle of harmonization.
9. Transition to Chapter 7
With the VWF established, we now move into the heart of the operational framework: how TWVF governs all nine GATS strategies, from M1 to M43200.
Next: Chapter 7 — TWVF Across All Nine GATS Strategies.