Market Volatility — VIX

Dedicated “Market Volatility Signal” capturing option-implied risk sentiment from the S&P 500 (CBOE VIX). Complements Liquidity, Credit, and USD signals.

Why: Captures risk sentiment in S&P 500 options. Source: CBOE / FRED (VIXCLS). Interpretation: <20 = calm; ≥30 = stress.

Abstract

We build a daily-to-weekly/monthly Market Volatility Signal (MVS) using the closing VIX index (VIXCLS). Components include level, short/medium-term momentum, a trailing percentile rank vs. history, and optional complements (realised volatility and options skew) to reduce false positives. A composite score maps to regimes—CALM, NORMAL, ELEVATED, STRESSED, CRISIS—anchored to intuitive thresholds (<20 calm; ≥30 stress) and robust z-scores.

1) Data

VIXCLS — CBOE Volatility Index (VIX close; annualised %; S&P 500 option‑implied 30‑day variance).
Derived snapshots — weekly (last business day) and monthly (month‑end), plus optional intraday/weekly stress capture (e.g., max VIX over week; or average of daily closes).
Realised volatility (optional complement) — computed from S&P 500 returns (e.g., 21‑trading‑day realised volatility; annualised). This is a model-free, ex‑post volatility estimator used to benchmark implied volatility.
Options skew (optional complement) — a tail‑risk / skew proxy (e.g., CBOE SKEW index, or a put‑call risk‑reversal if available) to distinguish “high vol with heavy downside tail” from “high vol without skew”.

Frequency & snapshot policy. VIXCLS is business‑daily. Month‑end snapshots support reporting consistency, but can miss intramonth stress bursts. For signal construction we prefer (i) weekly snapshots and/or (ii) a “stress capture” statistic over the month (e.g., max or 95th‑percentile VIX), with month‑end used only as a reporting anchor. Forward‑fill is allowed only for calendar alignment (≤3 business days).

2) Data Quality & Validation

Staleness: flag if last obs > 3 business days old.
Bounds & outliers: winsorise at 0.5–99.5th pct for stability; VIX is strictly non-negative.
Minimum history: ≥ 5 years preferred for percentile/z-scores; adaptive window ≥ 2 years allowed.
Trading holidays / stale prints: treat gaps as non-trading days; no interpolation beyond limit=3. Flag if the latest close is missing due to holidays or data delays.
Intraday spikes: month-end reporting can miss short-lived stress; optionally store weekly maxima (or 95th pct) and/or use weekly snapshots to capture episodic risk-off events.

data_quality_flag records staleness, winsorisation, and window adaptations.

3) Component Transforms

For daily series v_t (index points):

Level_t = v_t

Δ5d_t = v_t - v_{t-5}

Δ20d_t = v_t - v_{t-20}

PctRank_{2y}(t) = \text{percentile rank of } v_t \text{ in last 504 trading days}

EMA_{20}(t) = \text{exponential moving average over 20d}

We form gaps to intuitive thresholds: gap20 = v_t - 20, gap30 = v_t - 30.

4) Standardisation (Rolling z-scores)

Z-scores computed over rolling windows with robust median/MAD; fallback to mean/std if needed.

z_t = \dfrac{x_t - \text{median}_{W}(x)}{1.4826\,\text{MAD}_{W}(x)}

Suggested windows: W=504d (~2y) for level-based components; W=252d (~1y) for momentum.

5) Weighting & Composite Construction

We emphasise the level and percentile rank, with secondary weight to short-term momentum:

{
  "level_z": 0.40, "pct_rank": 0.25,
  "gap20_z": 0.10, "gap30_z": 0.10,
  "d5_z": 0.10, "d20_z": 0.05
}

MVS_t = \sum_k w_k\, z^k_t,\quad \sum_k w_k = 1

Missing components are renormalised out; contributions are stored for audit.

6) Scaling & Regime Mapping

Regimes reflect absolute thresholds and relative elevation:

CALM: VIX < 16 and MVS z < 0
NORMAL: 16 ≤ VIX < 20 or MVS z in [0, +0.5)
ELEVATED: 20 ≤ VIX < 30 or MVS z in [+0.5, +1.0)
STRESSED: VIX ≥ 30 or MVS z ≥ +1.0
CRISIS: VIX ≥ 45 or MVS z ≥ +2.0 sustained ≥ 5d

We also report a 0–100 score using rolling min–max scaling over 2–5 years.

Percentile-first guardrail (recommended). To avoid strict level thresholds (and structural shifts in volatility), also classify regimes by trailing percentile rank over a rolling window (e.g., 2–5y): CALM (<30th), NORMAL (30–60th), ELEVATED (60–80th), STRESSED (80–95th), CRISIS (>95th), with the absolute VIX levels (<20, ≥30, ≥45) acting as backstops.

7) Comparison Hooks

Liquidity Composite: Rising VIX with tight liquidity reinforces risk-off.
Credit Spreads: High-yield OAS widening with ELEVATED/ STRESSED VIX strengthens stress signal.
USD / Real Yields: Risk-off often coincides with stronger USD and higher real yields; note divergences.

Only the other signals’ latest regime/score are required; no structural dependency assumed.

8) Implementation Notes (Python)

# FRED series (daily closes)
vix = fred.get_series("VIXCLS")

# Align to business daily; bounded ffill (<=3)
vix_d = vix.asfreq("B").ffill(limit=3)

# Components
import pandas as pd
d5  = vix_d - vix_d.shift(5)
d20 = vix_d - vix_d.shift(20)
gap20 = vix_d - 20.0
gap30 = vix_d - 30.0
ema20 = vix_d.ewm(span=20, adjust=False).mean()

# Robust z-scores on rolling windows (252-504d), then weighted sum -> MVS, map regimes as specified.

9) Reproducibility & Monitoring

Persist source ID (VIXCLS), retrieval timestamps, resampling policy, and windows.
Log winsorisation bounds, staleness flags, and window adaptations.
Store panels: raw, transforms, z-scores, contributions, composite, regimes.

10) Interpretation & Applications

VIX is a short-horizon risk gauge. Values below 20 are generally consistent with calm conditions; 30 and above indicate market stress. Use alongside Liquidity and Credit to calibrate risk-on/off stance and to set expectations for drawdown risk.

11) Model interpretation (how to read the signal)

The signal is designed to separate risk sentiment (implied volatility) from realised turbulence (ex‑post volatility) and tail risk (skew). In practice, interpret it as a probabilistic risk‑off thermometer, not a timing tool.

VIX level vs. percentile rank: use level for intuitive communication (e.g., ≥30 = stress), but use percentile rank for robustness across regimes and decades.
Implied vs. realised volatility: when implied vol rises faster than realised vol, markets are pricing a higher volatility risk premium (often consistent with tighter risk appetite).
Skew / tail risk: elevated VIX with worsening skew implies downside‑tail hedging demand, which historically aligns with higher crash‑risk compensation.
Event-driven spikes: if the weekly max VIX is high but the month‑end close is benign, treat the regime as “latent stress” and look for confirmation from credit/liquidity signals.

Academic anchors (why these complements help): high‑frequency realised volatility is a statistically efficient estimator of return variation (Andersen, Bollerslev, Diebold & Labys, 2003), variance risk premia (implied minus realised) have predictive content for equity returns (Bollerslev, Tauchen & Zhou, 2009), and option‑implied higher moments (including skew) are linked to differential option pricing and tail‑risk compensation (Bakshi, Kapadia & Madan, 2003). The original VIX concept as a benchmark for expected market volatility traces to Whaley’s work on volatility indices and their market interpretation.

Practical rule: treat STRESSED/CRISIS as a regime where risk control dominates (position sizing, hedging), while CALM/NORMAL regimes support carry/risk premia harvesting—subject to confirmation from liquidity and credit.

12) Governance & Change Control

Quarterly review of components, thresholds, weights, and backtests.
Document rationale for changes; maintain semantic versioning.