SKEW: The Market's Own Admission of Tail Risk

Описание и применение

SKEW показывает, как рынок ценит риск краша, даже когда волатильность низкая. Интеграция индекса в симулятор позволяет выявлять скрытые угрозы и улучшать модели риска.

Задача

Risk models that rely solely on realized history miss the market’s continuous pricing of tail risk, leading to underestimation of crash probability during calm periods.

Результат

By integrating SKEW, the crash simulator identifies steep skew during rallies, signaling heavy tail pricing that historical data alone would miss, thus improving risk model accuracy.

Рабочий процесс

• 1. Download VIX and SKEW CSV data from Cboe public endpoints.
• 2. Compute 5‑year percentile ranks and 5‑day/21‑day changes.
• 3. Classify market regime as calm, stressed, or panic based on VIX and SKEW thresholds.
• 4. Output a hazard multiplier reflecting tail risk intensity.
• 5. Feed multiplier into downstream risk model (V9 P2) for endogenous hazard calibration.

Доказательства

SKEW is a Cboe index that quantifies the volatility skew: the difference between what the options market charges for out‑of‑the‑money puts versus what it charges for upside calls.

Источник

The simulator now ingests both Cboe indices through a small free‑data pipeline (src/market_state.py).

Источник

Running it today: VIX 15.3 (25th percentile, calm), SKEW 151.58 (83rd percentile, high). The pipeline classified the regime as calm — while flagging the unusually heavy tail pricing that history alone would never show you.

Источник