Buying Fear Outperformed Nearly 2-to-1: VIX Dataset (1990

Q: Why does the VIX trade higher than realized volatility?

The VIX measures implied volatility from option prices. Investors systematically overestimate the probability of extreme losses, overpaying for put options, which inflates implied volatility above subsequently realized levels. This gap, the Volatility Risk Premium, is documented by Carr and Wu (2009) as one of the most robust anomalies in derivatives markets.

A daily dataset of 9,123 observations mapping VIX volatility regimes to subsequent S&P 500 returns (part of our broader work on market regimes between liquidity, real rates and financial dynamics) revealing that the market’s price for discomfort is systematically too high, and the periods investors fear most have delivered the strongest forward returns.

Eco3min Research · Last updated: March 2026 · Frequency: Daily · Coverage: Jan 1990 – Mar 2026

The VIX (the CBOE Volatility Index, widely known as the “fear gauge”) is the most recognized measure of expected stock market volatility. Yet its deepest analytical value lies not in what it says about risk, but in what it reveals about compensation. This page provides a complete daily dataset combining VIX levels with forward S&P 500 returns across five volatility regimes, demonstrating that buying equities during periods of elevated fear has produced systematically superior returns since 1990. Related dataset: the VIX implied-volatility series.

TL;DR

Buying the S&P 500 when the VIX exceeds 30 has produced a median 12-month forward return of +22.4% since 1990, compared to +11.8% when the VIX is below 15. At VIX levels above 45, the median 12-month return rises to +26.5% with a 99.1% hit rate. Volatility is not risk — it is the market’s compensation for absorbing discomfort, and that compensation has been systematically excessive. This mechanism is detailed in financial-market stress signals.

Latest Observation: March 27, 2026

31.05
VIX Level

93rd
Percentile (Since 1990)

Fear
Current Regime

−4.0%
S&P 500 vs Peak (Monthly Avg.)

Key Research Findings

Buying the S&P 500 on days when the VIX closed at or above 30, the Fear threshold, has produced a median 12-month forward return of +22.4% across 722 observations since 1990, compared to +11.8% when the VIX was below 15. The difference is not a statistical artifact: the Fear regime delivered nearly double the median return of the Complacency regime.
At the most extreme VIX levels — above 45 (the Panic threshold) — the median 12-month forward return rises to +26.5% with a hit rate of 99.1%. Only 1 of 112 Panic-regime observations produced a negative 12-month return. These readings have historically occurred during genuine crises (2008 GFC, COVID 2020, 2025 tariff shock) when investor sentiment was at its most negative.
The VIX exhibits a systematic premium over realized volatility, documented in the academic literature (Carr and Wu, 2009). This gap (the price investors pay for downside insurance above and beyond actual experienced volatility) has historically represented a transfer of wealth from hedgers to those willing to absorb equity risk during stress.
VIX mean reversion is a structural feature, not a coincidence. Following every episode where the VIX crossed above 30, it has returned to its long-run median (17.6) within a median of 139 trading days — approximately 6.6 months. No VIX spike above 30 in the 36-year dataset has failed to revert.
Monthly changes in the VIX are negatively correlated with monthly S&P 500 changes at −0.71 (monthly averages, 1990–2026), confirming the well-documented asymmetry: volatility rises faster on market declines than it falls on market advances. This asymmetry is what creates the behavioral mispricing — investors overweight the pain of losses relative to the probability of recovery.

9,123 daily observations · Study file not offered for download · Updated daily · Methodology · Cite this dataset

9,123
Daily Obs.

−0.71
VIX–SP500 Corr. (Monthly)

82.69
VIX All-Time High

9.14
VIX All-Time Low

17.61
VIX Median

+22.4%
Med. 12M Ret. (VIX≥30)

VIX Volatility Index, Daily, January 1990 to March 2026

Cboe Volatility Index (VIX): Daily Close, January 1990 to March 2026

VIX closing level on 9,123 NYSE trading days, with the study’s regime thresholds: Complacency (<15), Normal (15–20), Elevated (20–30), Fear (30–45), Panic (45 and above). Grey bands: NBER recessions.

Sources: Cboe, VIX daily close (FRED, VIXCLS); NBER recession dates (FRED, USREC). Chart: Eco3min Research.
NYSE trading days, January 2, 1990 to March 27, 2026.

Key Takeaway

The VIX spends the vast majority of its time below 25. Readings above 30, the Fear threshold, have occurred on only 8.1% of all trading days since 1990. Taken from the Cboe daily VIX history. Readings above 45, the Panic threshold, are rarer still, comprising just 1.3% of observations. Yet these brief, terrifying episodes have historically offered the most attractive entry points for equity investors. The series’ rhythm, long calm plateaus punctuated by violent spikes that rapidly revert, is the structural signature of a mean-reverting process with a behavioral premium. A companion piece: our study of contrarian VIX thresholds and subsequent equity recoveries.

How to Read the VIX

From January 1990 to March 2026, each daily close of the CBOE Volatility Index is classified into one of five regime bands, from Complacency (VIX below 15) through Elevated (20–30) to Panic (above 45).

The VIX measures the market’s expectation of 30-day forward volatility, derived from S&P 500 index option prices. It is not a direct measure of realized volatility — it reflects the price investors are willing to pay for downside protection. This distinction is critical: the VIX consistently trades at a premium to subsequently realized volatility, and that premium widens during stress. For context on how this interacts with the real rate–valuation relationship, elevated VIX regimes have historically coincided with the rate-driven valuation compression phases identified in that study.

The pattern in the daily series is clear: VIX spikes are sharp, vertical, and short-lived. The index rises rapidly during market stress and reverts (sometimes over weeks, sometimes over months) to the 15–20 range that has constituted its long-term equilibrium. This mean-reverting behavior is the structural foundation of the contrarian return premium documented in this dataset.

The Behavioral Mispricing: Why the Market Overpays for Protection

The dominant narrative treats the VIX as a risk indicator: when it rises, risk is high, and prudent investors should reduce exposure. This framing is intuitive, widely taught, and empirically backwards. The data shows that VIX readings above 30, the moments when financial commentary is most alarming, have preceded the strongest, not the weakest, forward equity returns.

This pattern is not a statistical anomaly. It reflects a well-documented behavioral mechanism. Prospect theory, developed by Daniel Kahneman and Amos Tversky (1979), demonstrates that individuals overweight the probability of losses relative to gains. In financial markets, this asymmetry manifests as an excessive demand for downside protection during periods of stress — demand that drives the VIX to levels that overshoot the actual risk of subsequent losses.

The mechanism operates through the options market. When investors panic, they bid up the price of put options. These elevated option premiums are what the VIX measures. The premium embedded in option prices — the gap between implied (VIX) and subsequently realized volatility — represents a systematic transfer of wealth from hedgers (who overpay for protection) to sellers of protection (who absorb the discomfort of holding equities during turbulence).

Critically, the VIX does not forecast equity returns by identifying “undervalued” markets. It identifies over-compensated markets — moments where the price of bearing equity risk is so inflated by behavioral bias that subsequent returns are mechanically elevated relative to calm periods. For a complementary perspective on how credit markets signal similar dislocations, see our research on credit spreads and recession risk.

Five Volatility Regimes: Classification and Historical Distribution

This dataset classifies each trading day into one of five volatility regimes based on the VIX closing level. The thresholds are not arbitrary — they correspond to well-established behavioral and structural transitions in the options market: the shift from complacent positioning below 15, through the normal fluctuation band of 15–20, into the elevated anxiety of 20–30, the acute fear phase above 30, and the rare panic readings above 45 that have historically coincided with systemic crises.

Regime	VIX Range	Trading Days	% of Sample	Character
Complacency	< 15	2,948	32.3%	Low hedging demand; extended calm
Normal	15 – 20	2,760	30.3%	Long-run equilibrium; median VIX = 17.6
Elevated	20 – 30	2,680	29.4%	Active hedging; uncertainty above baseline
Fear	30 – 45	620	6.8%	Crisis-level anxiety; sharp put demand
Panic	> 45	115	1.3%	Systemic dislocation; capitulation pricing

The distribution is telling: the VIX has spent 62.6% of all trading days since 1990 in the Complacency or Normal regimes, below 20. The Fear and Panic regimes combined account for just 8.1% of observations. The Elevated regime (20–30), where the market is uneasy but not panicked, represents the remaining 29.4%. This asymmetry, long periods of calm punctuated by brief spikes, is the structural reason why the contrarian premium exists. The spikes feel disproportionate because they are disproportionate: they compress the emotional and financial pain of correction into a compressed time window. For background on how the yield curve interacts with this pattern, curve inversions have historically preceded the transition from Complacency to Elevated/Fear regimes by 6–18 months.

Complacency · VIX < 15 · Median 12M Return: +11.8%

The market’s “all clear” signal. Extended Complacency regimes occurred in 1993–1996, 2004–2007, 2013–2017, and 2024. While 12-month returns are positive (87.5% hit rate), the median is lower than in Fear/Panic regimes. The Complacency regime is not dangerous per se, but the absence of fear means the market is not compensating investors for bearing risk.

Normal · VIX 15–20 · Median 12M Return: +10.5%

The long-run equilibrium state. The VIX’s median since 1990 is 17.6, placing it squarely in this regime. Returns are consistent and positive. This is the default market condition from which departures, in either direction, create analytical signals.

Fear · VIX 30–45 · Median 12M Return: +21.5%

The contrarian sweet spot. Fear-regime readings have historically produced 12-month returns nearly double those of calm markets, with an 85.4% hit rate. This is where the behavioral premium is largest: investors are selling equities (or demanding expensive protection) at precisely the moment when subsequent returns are most favorable.

Panic · VIX > 45 · Median 12M Return: +26.5%

The rarest and most rewarding regime. Only 115 trading days (1.3% of the sample) have registered Panic-level VIX readings. Of the 112 observations with 12-month forward return data, 99.1% delivered positive returns. The median return of +26.5% reflects the extreme degree of investor capitulation embedded in Panic pricing, and the equally extreme recovery that typically follows.

The Return Map: Forward S&P 500 Performance by VIX Level at Entry

The central claim of this study, that buying fear outperforms buying calm, rests on the empirical relationship between VIX level at entry and subsequent S&P 500 returns. The table below breaks this relationship into granular VIX buckets, using all available observations with 12-month forward return data (8,874 of 9,123 daily observations; trading days from April 2025 onward lack a completed 12-month window, which would end after March 2026).

Median Forward 12-Month S&P 500 Return by VIX Level at Entry

VIX Bucket	Median 12M Return	Mean 12M Return	% Positive	Observations
< 12	+11.4%	+10.4%	84.9%	802
12 – 15	+11.8%	+11.7%	88.5%	2,121
15 – 18	+10.5%	+10.8%	87.9%	1,707
18 – 20	+11.1%	+8.2%	78.0%	904
20 – 25	+9.7%	+4.9%	66.3%	1,772
25 – 30	+11.9%	+7.1%	69.6%	846
30 – 40	+19.1%	+16.8%	83.6%	518
> 40	+26.5%	+29.9%	97.5%	204

The VIX Regime Return Map: Median 12-Month S&P 500 Change by VIX Level at Entry

Median change of the S&P 500 from the monthly average of the entry month to the monthly average 12 months later, for each VIX bucket. 8,874 trading days with a complete 12-month window, January 1990 to March 2025.

Sources: Cboe (FRED, VIXCLS); S&P 500 monthly averages of daily closes, Robert J. Shiller (Online Data). Chart: Eco3min Research.
Each trading day takes its month: change from that month’s average to the average 12 months later (price change, no dividends). Latest VIX observation: March 27, 2026.

Key Takeaway

The return map reveals a step-function pattern, not a gradient. For VIX levels below 30, median 12-month returns are remarkably stable — between about +10% and +12%, regardless of whether the VIX is at 12 or 25. The relationship is essentially flat. But once the VIX crosses 30, median returns jump discontinuously — to +19.1% in the 30–40 range and +26.5% above 40. The contrarian premium is not a continuous function of fear. It activates at a threshold, and that threshold is approximately 30.

The data reveals a striking asymmetry between medians and means in the Elevated regime (VIX 20–25). The median 12-month return is +9.7%, but the mean drops to +4.9% — the lowest mean in the table. This divergence reflects the left tail: the Elevated regime captures the early stages of major bear markets (2001, 2008, 2022), where initial anxiety was justified by subsequent larger declines. The few observations that produce large negative returns drag the mean down while the median remains resilient. This pattern is analytically important: the Elevated regime is the transition zone, it can lead either to a return to calm (most of the time) or to an escalation into Fear/Panic (during genuine crises). The regime’s signal improves substantially when combined with S&P 500 drawdown depth.

Two important caveats apply to this analysis. First, the forward returns use overlapping observation windows (every trading day of a month shares that month’s forward return, and consecutive 12-month windows overlap by 11 of 12 months), which inflates the effective sample size and introduces autocorrelation. Second, the analysis captures the raw statistical relationship without accounting for transaction costs, timing precision, or the psychological difficulty of executing contrarian strategies during periods of genuine market distress.

Mean Reversion: The VIX Always Comes Home

The contrarian premium documented in this study rests on a structural feature of the VIX: it is a mean-reverting process. Unlike equity prices, which can sustain trends for years, the VIX is pulled back toward its long-run median by the mechanics of the options market itself. As time passes, options decay, hedging demand normalizes, and the volatility premium compresses back toward equilibrium.

In the dataset, every single episode where the VIX crossed above 30 was eventually followed by a reversion to the long-run median of 17.6. The median time to revert from a VIX reading above 30 to the long-run median is 139 trading days — approximately 6.6 months. The fastest reversion occurred in 7 trading days; the slowest took 362 trading days (approximately 17 months), during the protracted 2008–2009 financial crisis.

The VIX long-run median since 1990 is 17.61. The mean is 19.46 — the positive skew reflecting the occasional extreme spike.
Following a VIX spike above 30, the median time to revert to the 17.6 median is 139 trading days (~6.6 months). Every episode has reverted — zero exceptions in 36 years of data.
VIX readings above 40 have a half-life of about 2 trading days: 21 of the 33 streaks of consecutive closes above 40 since 1990 ended within 2 trading days, and 28 within 8. The longest lasted 62 sessions (October 2 to December 30, 2008).
The VIX’s 90th percentile is 28.6, meaning 90% of all trading days since 1990 have closed below this level. Its 95th percentile is 33.0, and its 99th percentile is 46.8.
Only one streak of VIX closes above 30 has lasted more than 60 consecutive trading days: 170 sessions, from September 15, 2008 to May 18, 2009, during the GFC. The next longest lasted 50 sessions each: August 4 to October 13, 2011 (US downgrade) and February 27 to May 7, 2020 (COVID). Twelve months after the month each of these three streaks ended, the S&P 500’s monthly average was 24.7%, 19.1% and 42.8% higher, respectively.

The economic logic is straightforward. The VIX is derived from option prices, and options are wasting assets. Every day that passes without the feared outcome materializing, the time value of those options decays, pulling implied volatility lower. The VIX can spike on sudden demand for protection, but it cannot remain elevated indefinitely because the cost of maintaining protection accumulates. Hedgers either reduce positions as anxiety fades, or new sellers enter to collect the elevated premium. Either way, the VIX reverts. This structural mean reversion is what transforms the behavioral mispricing, the tendency to overweight fear, into a repeatable return pattern. For how this relates to the broader monetary cycle, see our research on monetary regimes and market cycles.

The Volatility Risk Premium: The Market’s Systematic Overcharge for Insurance

The VIX consistently trades above subsequently realized volatility: a phenomenon known as the Volatility Risk Premium (VRP). This premium represents the compensation that option sellers receive for providing downside insurance to the market.

Measuring the premium requires realized volatility computed from daily index closes. This page uses monthly averages of the S&P 500, which cannot measure 20-day realized volatility, so it publishes no estimate of its own; the evidence on the premium comes from the academic research below.

Research by Carr and Wu (2009, Review of Financial Studies) demonstrated that the volatility risk premium is one of the most robust anomalies in derivatives markets. It exists because volatility is negatively correlated with equity returns — protection is most valuable precisely when markets are falling, which means insurance buyers are willing to pay a structural premium, and this premium is harvested by sellers willing to bear the tail risk. The contrarian return pattern documented in this study is, in essence, the equity-side expression of this same premium: holding equities during Fear/Panic regimes is the functional equivalent of selling volatility insurance, and it is compensated accordingly.

Key Takeaway

The VIX premium over realized volatility is the market’s “insurance markup.” On average, implied volatility has exceeded subsequently realized volatility (Carr and Wu, 2009); the gap turns negative mainly during rapidly accelerating sell-offs, when realized volatility temporarily overtakes implied volatility. An extreme markup signals that the market is paying an unusual price for protection.

VIX Level vs Forward 12-Month S&P 500 Return

VIX at Entry vs Subsequent 12-Month S&P 500 Change: 8,874 Trading Days (1990–2025)

Each dot is one trading day: VIX close (x-axis) against the S&P 500 change from the entry month’s average to the average 12 months later (y-axis); days of the same month share one outcome. Line: median by VIX bucket. Dashed line: median of all days (+11.6%).

Key Takeaway

Across the 8,874 daily observations with a 12-month outcome, forward returns fan upward at high VIX levels. Half of the observations above VIX 40 fall between +23% and +47%. The large negative outcomes (12-month returns below −10%) are concentrated in the Elevated regime (VIX 20–30): 645 of 985 such days, against 64 in the Fear/Panic zone. This is the paradox: the moment that feels most dangerous (VIX > 40) has historically been the safest entry point, while the moment of modest unease (VIX 20–30) contains the genuine risk of further deterioration.

Interactive Tool

VIX Regime Lookup Calculator

Enter a VIX level to see which historical regime it falls into, the median forward returns from that level, and the historical hit rate. Based on 9,123 daily observations (1990–2026).

Enter VIX Level
31.1

885

Forward Return Horizon
12 months

1M12M

Fear
VIX Regime

93rd
Historical Percentile

+21.5%
Median Fwd Return

85.4%
% Positive

Current scenario: A VIX level of 31.1 places the market in the Fear regime. In the 1990–2026 dataset, buying the S&P 500 at VIX levels between 30 and 45 has produced a median 12-month forward return of +21.5% with a positive outcome in 85.4% of observations.

Historical Episodes: When Fear Peaked and What Happened Next

March 16, 2020: COVID Crash: VIX 82.69

The VIX reached its all-time high of 82.69 on March 16, 2020, as the COVID-19 pandemic triggered a global market shutdown. In monthly averages, the S&P 500 stood 19.1% below its pre-crash high (January 2020) in March 2020. The Fear/Panic regime (VIX at 30 or above) lasted 50 consecutive trading days, from February 27 to May 7, 2020. Counting a second flare-up in June, the VIX closed at 30 or above on 69 of the 87 sessions from February 27 to June 30. From its March 2020 average, the S&P 500 gained 47.4% over the subsequent 12 months (March 2021 average). The episode confirmed the contrarian thesis at its most extreme: buying in the month of the single worst day of implied volatility in market history produced one of the strongest 12-month returns on record.

November 20, 2008: GFC Peak: VIX 80.86

The second-highest VIX reading in history, 80.86, occurred on November 20, 2008, as Citigroup’s stock collapsed and the banking system appeared on the verge of failure. In monthly averages, the S&P 500 was down 42.6% from its October 2007 peak. The VIX remained above 30 for 170 consecutive trading days (September 15, 2008 to May 18, 2009). Investors who bought the S&P 500 in November 2008 experienced further losses in the near term (the monthly average would not bottom until March 2009) but the 12-month forward return from the November 2008 average was approximately +23%. The extended duration of this Fear episode makes it the most important test case for the mean-reversion thesis. For how real interest rates interacted with this episode, the Fed’s emergency rate cuts drove real rates deeply negative by early 2009, creating the conditions for the subsequent decade-long equity rally.

October 8, 1998: LTCM Crisis: VIX 45.74

The collapse of Long-Term Capital Management pushed the VIX to 45.74, as the interconnected leverage of a single hedge fund threatened the stability of the global financial system. The S&P 500’s October 1998 average stood 10.7% below its July 1998 average. The Fear episode (VIX at 30 or above) lasted 49 consecutive trading days, from August 20 to October 28, 1998. The VIX fell back below 30 fifteen sessions after its October 8 peak. The subsequent 12-month return from the October 1998 average was approximately +26%. This episode is notable because the crisis was resolved rapidly (the Fed brokered a private-sector bailout), demonstrating how quickly the VIX can revert when the structural threat is contained.

August 2011: US Downgrade: VIX 48.00

Standard & Poor’s downgraded US sovereign debt from AAA to AA+ on August 5, 2011, triggering a VIX spike to 48.00 on August 8. The S&P 500’s August 2011 average stood 11.4% below its May 2011 average. The VIX remained above 30 for 50 consecutive trading days (August 4 to October 13, 2011). Despite the historically unprecedented nature of the event, the world’s benchmark risk-free asset was downgraded, the 12-month forward return from the August 2011 average was approximately +18%. The episode demonstrated that the VIX’s predictive power operates independently of the nature of the crisis: whether the trigger is a banking collapse, a pandemic, or a sovereign downgrade, extreme VIX readings have consistently preceded strong recoveries. For how the yield curve behaved during this episode, the 10Y–2Y spread was already positive, suggesting the market did not price a recession, and no recession followed.

April 8, 2025: Tariff Shock: VIX 52.33

The announcement of sweeping US tariffs in early April 2025 triggered the most severe VIX spike since COVID, reaching 52.33 on April 8, 2025. The S&P 500’s April 2025 average stood 11.1% below its February 2025 average. The Fear/Panic regime lasted about three weeks, from April 3 to April 22, 2025 (12 closes above 30 in 13 sessions), before the VIX reverted below 30. This recent episode provides a real-time test of the contrarian thesis in the current market environment.

March 27, 2026: Current Observation

The VIX closed at 31.05 on March 27, 2026 — in the Fear regime, at the 93rd percentile of its historical distribution. The S&P 500’s March 2026 average stood 4.0% below its highest monthly average (January 2026). The current reading places the market in the regime where the contrarian premium has historically been largest: VIX above 30 and investor sentiment shifting from complacency toward acute anxiety. Whether this configuration resolves through rapid reversion (as in 2011 and 2015) or extended stress (as in 2008) will depend on the macroeconomic catalyst, but the historical record is clear that this entry point has produced positive 12-month returns in 87.5% of prior observations.

Methodology

This dataset combines the CBOE Volatility Index (VIX) with monthly averages of the S&P 500 (Robert J. Shiller) to construct a forward-return analysis across five volatility regimes. The core innovation is the systematic pairing of VIX level at entry with subsequent equity returns across multiple time horizons — a dataset that does not exist in any single public source.

VIX data. The CBOE Volatility Index measures the market’s expectation of 30-day forward volatility, derived from the prices of S&P 500 index options (puts and calls across a range of strike prices). Data sourced from FRED (series VIXCLS, daily close), kept on NYSE trading days (values published on NYSE holidays are excluded). The VIX calculation methodology was revised in 2003 to use a wider range of options; the pre-2003 “VXO” methodology has been retroactively backcasted by the CBOE, and the FRED series reflects the current methodology throughout.

S&P 500 data. Monthly averages of daily closes, Robert J. Shiller (Online Data, shillerdata.com). Returns are computed as simple price returns (excluding dividends). Including reinvested dividends would typically add approximately 1.5 to 2.5 percentage points to annualized forward returns.

Forward returns. Each trading day takes its month m. The forward return over N months is the percentage change in the S&P 500 monthly average from month m to month m + N, where N is 1, 3, 6 or 12; the 1-month return therefore compares a month’s average with the following month’s. All trading days of the same month share the same forward return. Windows ending after March 2026 are recorded as missing values.

VIX regime classification. Five regimes based on VIX closing level: Complacency (<15), Normal (15–20), Elevated (20–30), Fear (30–45), Panic (>45). These thresholds align with established market conventions and correspond to behavioral transitions in option market dynamics.

Forward Return_m,N = (SP500_m+N / SP500_m) − 1 | SP500_m = monthly average of daily closes

Dataset Design

Variable	Description	Unit	Source
date	Trading day	YYYY-MM-DD	–
vix_close	CBOE Volatility Index, daily close	Index	CBOE / FRED (VIXCLS)
sp500_monthly	S&P 500, monthly average of daily closes (month of the trading day)	Index points	Robert J. Shiller, Online Data
vix_regime	Volatility regime classification	Categorical	Eco3min (computed)
fwd_1m	S&P 500 return from the month’s average to the average 1 month later	Percent	Computed
fwd_3m	S&P 500 return from the month’s average to the average 3 months later	Percent	Computed
fwd_6m	S&P 500 return from the month’s average to the average 6 months later	Percent	Computed
fwd_12m	S&P 500 return from the month’s average to the average 12 months later	Percent	Computed
vix_percentile	Expanding-window percentile rank of VIX	Percent	Computed
vix_20d_ma	20-day moving average of VIX	Index	Computed
sp500_peak	Highest monthly average of the S&P 500 to date	Index points	Computed
sp500_drawdown	Distance of the monthly average from that peak	Percent	Computed

Python Reproduction Code

import pandas as pd
import pandas_market_calendars as mcal

# VIX: Cboe Volatility Index, daily close (FRED series VIXCLS), NYSE trading days only
vix = pd.read_csv("https://fred.stlouisfed.org/graph/fredgraph.csv?id=VIXCLS",
                  index_col=0, parse_dates=True, na_values=".").iloc[:, 0].dropna()
nyse = mcal.get_calendar("NYSE").valid_days("1990-01-02", "2026-03-27").tz_localize(None)
vix = vix[vix.index.isin(nyse)]

# S&P 500: monthly averages of daily closes, Robert J. Shiller, Online Data (ie_data.xls, needs xlrd)
sh = pd.read_excel("ie_data.xls", sheet_name="Data", header=7)
sh = sh[pd.to_numeric(sh["Date"], errors="coerce").notna()]
dates = sh["Date"].astype(float)
months = [pd.Period(year=int(x), month=round((x - int(x)) * 100), freq="M") for x in dates]
sp = pd.Series(sh["P"].astype(float).values, index=pd.PeriodIndex(months))

# Regime classification
def classify(v):
    if v return 'Complacency'
    elif v return 'Normal'
    elif v return 'Elevated'
    elif v return 'Fear'
    else: return 'Panic'

df = pd.DataFrame({'vix_close': vix})
df['vix_regime'] = df['vix_close'].apply(classify)

# Forward returns (months): each trading day takes its month
m = df.index.to_period('M')
last = pd.Period('2026-03', freq='M')
for label, n in [('fwd_1m',1),('fwd_3m',3),('fwd_6m',6),('fwd_12m',12)]:
    r = sp.reindex(m + n).values / sp.reindex(m).values - 1
    df[label] = pd.Series(r, index=df.index).where(m + n to_csv("vix-contrarian-almanac-1990-2026.csv")

Explore more macroeconomic datasets:
Eco3min Macro Data Hub
, inflation, yield curves, equity returns, credit spreads and global indicators.

Study File & Reproducibility

The study file is not offered for download: it contains data whose owner restricts redistribution (S&P 500 index levels, Cboe VIX data). The methodology lists every source.

Data Sources & Academic References

Primary
Chicago Board Options Exchange (CBOE): VIX Volatility Index, daily close (FRED series VIXCLS).
Primary
Robert J. Shiller, Online Data (shillerdata.com): S&P 500, monthly averages of daily closes.
Primary
National Bureau of Economic Research (NBER): US Business Cycle Dating Committee, recession dates.
Research
Kahneman & Tversky (1979): “Prospect Theory: An Analysis of Decision under Risk,” Econometrica. Foundation of the behavioral mispricing framework.
Research
Carr & Wu (2009): “Variance Risk Premiums,” Review of Financial Studies. Systematic documentation of the volatility risk premium.
Research
Whaley (2009): “Understanding the VIX,” Journal of Portfolio Management. Comprehensive methodology overview by the VIX creator.
Reference
CBOE: VIX White Paper: methodology for calculating the VIX from S&P 500 option prices.
Research
Bollerslev, Tauchen & Zhou (2009): “Expected Stock Returns and Variance Risk Premia,” Review of Financial Studies. Links VIX premium to equity return predictability.

Methodological Limitations

Overlapping observation windows. Forward returns are computed for each trading day from monthly averages: all trading days of a month share the same forward return, and consecutive 12-month windows overlap by 11 of 12 months. This inflates the apparent sample size and introduces strong autocorrelation. The 9,123 daily observations do not represent 9,123 independent return experiments; the effective sample size for 12-month returns is closer to 36 (the number of non-overlapping annual windows). Weighting also matters: counting each month once instead of each trading day, the median 12-month return after a month with at least one VIX close at or above 30 is +17.5% (81 months), against +11.8% after a month with at least one close below 15 (199 months).
Price returns vs total returns. The S&P 500 returns in this dataset are price-only, excluding dividends. Including reinvested dividends would add approximately 1.5–2.5 percentage points to annualized forward returns across all regimes. The relative comparison between regimes is not materially affected.
Survivorship and selection bias. The analysis covers only the US equity market (S&P 500), which has experienced a secular upward trend over the sample period. The contrarian premium may be partially attributable to this positive structural drift. Whether the pattern holds for markets with weaker long-term performance (e.g., Japan’s Nikkei 225 since 1990) is an open question.
VIX methodology change (2003). The VIX calculation was revised in September 2003 from a narrow (VXO-style, 8 options) to a broad methodology (current VIX, wider option range). Pre-2003 data uses the retroactively backcasted series, which may introduce subtle measurement differences.
Implementation gap. The analysis treats each VIX closing level as an actionable entry signal. In practice, executing a contrarian strategy during periods of extreme VIX requires buying equities when news flow, commentary, and emotional pressure are at their most negative. The behavioral difficulty of implementation, which is the very mechanism that creates the premium, cannot be captured in a backtest.
Tail risk and drawdown path. The 12-month forward return data masks the drawdown path. An entry at VIX 35 may produce a +25% 12-month return but may first experience a further −20% drawdown before recovering. The magnitude of interim losses is not captured in the median forward return statistics.

Frequently Asked Questions

Is a high VIX a buy signal for stocks?

The historical record shows a strong statistical association between high VIX readings and above-average subsequent equity returns. Since 1990, buying the S&P 500 when the VIX exceeds 30 has produced a median 12-month forward return of +22.4% — nearly double the +11.8% from buying when the VIX is below 15. However, this is a statistical relationship observed over 36 years of data, not a timing signal. The VIX can remain elevated for weeks or months during genuine bear markets (e.g., 2008–2009), and intermediate drawdowns can be severe even when the eventual 12-month outcome is positive.

What is the highest VIX level ever recorded?

The VIX reached its all-time closing high of 82.69 on March 16, 2020, during the COVID-19 pandemic market crash. The second-highest closing level was 80.86 on November 20, 2008, during the Global Financial Crisis. The all-time low was 9.14 on November 3, 2017, during a period of extended market complacency.

How long does it take for the VIX to return to normal after a spike?

The VIX is a mean-reverting index. Following every episode where the VIX crossed above 30, it has returned to its long-run median (17.6) within a median of 139 trading days — approximately 6.6 months. The fastest reversion took 7 trading days; the slowest took approximately 362 trading days during the 2008–2009 financial crisis. No VIX spike above 30 in the 36-year dataset has failed to revert.

Why does the VIX trade higher than realized volatility?

The VIX measures implied volatility: the level of volatility embedded in option prices. Because investors systematically overestimate the probability and magnitude of extreme losses (a behavioral bias documented by Kahneman and Tversky), they overpay for put options, which inflates implied volatility above the level of volatility that subsequently materializes. This gap, the Volatility Risk Premium, represents the compensation received by those willing to sell protection. Carr and Wu (2009) document it as one of the most robust anomalies in derivatives markets.

What is the current VIX level and what does it mean?

As of March 27, 2026, the VIX closed at 31.05 — in the Fear regime (VIX 30–45), at the 93rd percentile of its historical distribution. This level is consistent with elevated investor anxiety but below crisis-level Panic readings above 45. Historically, buying the S&P 500 at VIX levels between 30 and 45 has produced a median 12-month forward return of +21.5% with a positive outcome in 85.4% of observations.

Can I use this dataset for academic research or backtesting?

The file is not offered for download (S&P 500 index levels, Cboe VIX data); the methodology lists every source, so the series can be rebuilt from them. Eco3min text and analysis: CC BY 4.0, with attribution. The study file includes all variables needed for volatility regime analysis, contrarian strategy backtesting, and forward return studies across four time horizons. Python reproduction code is provided on this page. Please cite as: Eco3min Research (2026), “The Contrarian’s Almanac: VIX Volatility Regimes and Forward S&P 500 Returns (1990–Present).”

Source

Eco3min Research (2026)
The Contrarian’s Almanac: VIX Volatility Regimes and Forward S&P 500 Returns, Dataset (1990–Present).
Eco3min Macro Data Hub: Research Indicators.
Eco3min.fr/en/vix-contrarian-almanac-dataset/

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Last updated — 15 October 2026

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