Spot-Vol Beta — ^GSPC vs. ^VIX
Rolling regression between spot returns and implied volatility changes
What does this page show? —
Spot-Vol beta measures how strongly volatility (VIX) reacts to price moves in the index. A negative beta means: falling prices push vol up disproportionately (typical fear pattern). Here you see the OLS regression, rolling beta over time and automatically detected regime turning points. Sidebar: choose the index/VIX pair, period and rolling window.
Methodology
Data Basis
- Data source: Supabase (Yahoo Finance), updated daily
- 3 fixed pairs (only meaningful combinations):
- • VIX → ^GSPC or SPY (S&P 500)
- • VXN → ^NDX or QQQ (Nasdaq 100)
- • OVX → CL=F or USO (WTI Crude)
- Period: 3–20 years or Max (since 1990)
Calculation
- Returns: percentage or log (selectable)
- Daily Beta: Spot return × Vol change
- Total Beta: OLS regression y = α + βx, with y=Vol change, x=Spot return
- R²: Share of vol variance explained by spot returns
- Rolling Beta: OLS regression over window (20–252 trading days)
Interpretation
- β ≤ −0.8 — classic "Fear Gauge" (strongly inverse relationship)
- β between −0.3 and −0.8 — normal inverse relationship
- β near zero — weak relationship (regime change possible)
- β > 0 — very rare, Vol rises despite rising prices
Regime Turning Points
- VIX Spike: VIX ≥ threshold — how does the spot react afterwards?
- VIX Complacency: VIX ≤ threshold — warning signal for complacency?
- Beta Stress: Rolling Beta ≤ threshold — panic regime, turning point?
- Events are decoupled with a minimum gap of 10 days (to avoid counting the same phase twice)
Note
- The Spot-Vol relationship is not stationary — it can change abruptly during crisis periods
- Historical regressions are no guarantee for the future