Is the volatility risk premium always positive?

No. An estimated expected premium can change sign, and a realized spread can be negative when realized risk exceeds the initial implied level. Its sign also depends on the stated subtraction convention. A positive historical average does not prevent large losses in individual periods.

Can I compare VIX with the past 20 trading days of SPX volatility?

That is a comparison with a trailing proxy, not a matched subsequent outcome. VIX targets 30-day SPX volatility. For an outcome study, retain the VIX observation time, measure SPX over the corresponding later calendar interval, and reconcile annualization and sampling. A trailing forecast must be labeled and tested as a forecast.

Does a 4.4-point volatility spread mean a 4.4% trading return?

No. The spread is measured in volatility percentage points. Currency P&L depends on the instrument and position, while account return also needs a capital denominator and costs. The worked contract example defines a separate variance payoff to make that distinction explicit.

TradingView Backtesting

Volatility Risk Premium: Match Horizons Before Comparing IV and RV

To study the volatility risk premium, compare option-implied risk with expected realized risk for the same underlying and future interval. State whether the difference uses volatility or variance units. IV minus subsequently realized volatility is an after-the-event spread: it contains an unexpected outcome as well as any premium. Future realized volatility cannot be an entry signal, and a positive spread does not establish a profitable option trade.

See the decision guide

Separate an expected premium from a realized spread

Bali and Zhou define the variance risk premium as risk-neutral expected variance minus physical, or real-world, expected variance over the same future interval. Both expectations are conditional on information at time t. This page uses that implied-minus-physical sign convention; papers using the reverse convention report the opposite sign. A single option IV squared is only a proxy for model-free implied variance, since its strike and pricing model matter.

The last bracket is a forecast error. One quiet month can produce a large realized spread even when the expected premium was modest.
Square root of expected variance is not generally expected volatility. The volatility spread above is a reporting transformation, not the variance premium in another unit.
IV minus trailing historical volatility can be an observable proxy if trailing volatility is your declared forecast. It is not a measurement of what subsequently happened, and that forecast needs its own evaluation.

All variance quantities use the same horizon and annualizationtext

q(t,T) = option-implied expected variance
m(t,T) = physical expected variance estimated at t
R(t,T) = variance realized later, between t and T

Expected variance premium = q(t,T) - m(t,T)
Realized variance spread  = q(t,T) - R(t,T)
                         = [q(t,T) - m(t,T)] + [m(t,T) - R(t,T)]
Realized volatility spread = sqrt(q(t,T)) - sqrt(R(t,T))

Join observations by their future interval

Store one research row per observation time t and horizon end T. The row needs the exact underlying, IV quote time, option expiry or constant-maturity definition, IV construction, year fraction and price sampling rule. Join the realized series to (t, T], not to a trailing window ending at t. Keep the price at t to calculate the first return.

Cboe VIX targets 30-day S&P 500 volatility using SPX option inputs. SPY realized returns introduce ETF basis and distribution differences; label that comparison as a proxy rather than an exact underlying match.
Record whether IV is from an at-the-money option, a delta bucket or a strip across strikes. Do not splice these constructions into one history without a documented change.
When constructing a constant maturity from two expiries, use the provider methodology. Linear interpolation of total implied variance, q × year fraction, differs from averaging the two volatility quotes.
For daily close sampling, retain overnight changes through consecutive close returns. Intraday-only returns omit those gaps. A daily estimate also misses intraday variation that reverses before the close.

Field	Required match	Failure to avoid
Underlying	Option underlying and realized price series identify the same asset.	VIX-based SPX risk compared with QQQ or an individual stock.
Horizon	Same start, end, timezone and settlement boundary.	A 30-calendar-day IV quote compared with the next 30 trading days.
Scale	Same year fraction and decimal or percentage convention.	Annual IV compared directly with an unannualized daily standard deviation.
Observation	Executable quote or documented index timestamp precedes the assumed trade.	Using a closing IV value for a trade entered earlier that day.

Recompute a hypothetical 30-day observation

Assume a hypothetical option-implied variance quote for asset A, observed at t, has square root 20% annualized on an ACT/365 basis. T is exactly 30 calendar days later. There are 21 complete close-to-close intervals within these boundaries: ten log returns of +0.01, ten of -0.01, then one of 0. The first 20 alternate signs. These are synthetic returns, not market observations; +0.01 is a log return, not exactly a 1% simple return.

The sum of squared log returns is a discretely sampled realized-variance measure. A centered sample variance with an n - 1 denominator is a different statistic. Contract settlement rules may require a different calculation.
The horizon implied variance is 0.04 × 30/365 = 0.0032876712. Subtract the horizon realized variance 0.002 to get 0.0012876712; dividing by the same year fraction recovers the annualized variance spread.
If the forecast saved at t was m = 0.03 annualized variance, the estimated expected premium was 0.04 - 0.03 = 0.01. The later forecast error was 0.03 - 0.0243333333 = 0.0056666667. Together they explain the realized spread.
Using 252/21 instead of 365/30 would give R = 0.024 and realized volatility of 15.4919%. That is a changed annualization convention. Convert the IV basis as well before comparing; the number 252 does not fix a calendar mismatch.
20 squared minus 15.5991 squared is approximately 156.6667. Squaring their difference gives about 19.3675 instead. A difference of squares is not a squared difference.

Decimal log returns; no sample-mean subtractiontext

tau = 30 / 365
q = 0.20^2 = 0.04
Sum of squared log returns = 20 * 0.01^2 + 0^2 = 0.002
R = 0.002 / tau = 0.0243333333 annualized decimal variance
Realized volatility = sqrt(R) = 0.1559914528

Volatility spread = 100 * (0.20 - sqrt(R)) = 4.4008547 percentage points
Variance spread = 0.04 - R = 0.0156666667 decimal variance
                = 10,000 * 0.0156666667 = 156.6666667 points squared

Keep future outcomes out of entry rules

A research table may place the later realized variance on the row dated t for evaluation. Its availability time is still T. A backtest that sells volatility when this completed-row spread is positive has already used the answer. Keep separate columns for observation_time, horizon_end and outcome_available_time.

Generate entry signals only from IV and forecasts available at the decision time. If a close is needed, choose an execution rule after that close or document a valid closing-auction process.
Fit forecast coefficients and choose thresholds using training observations whose outcomes had finished by the training cutoff. A row beginning before the cutoff can still leak future information if its horizon ends after it.
For daily observations of a 30-day horizon, adjacent realized windows share most of their returns. More rows do not mean equally many independent observations. Report the number of rows and the number of non-overlapping windows.
Use a predeclared non-overlapping evaluation sample, or uncertainty estimates that account for dependence, such as a suitable HAC estimator or block bootstrap. State bandwidth or block length and show sensitivity. An ordinary independent-observation standard error can overstate precision.
A rolling historical average can mix calm and crisis regimes. Report the spread distribution, negative periods and stress episodes alongside the mean; do not select a window after seeing its profits.

Translate the spread into a specified trade before subtracting costs

For arithmetic only, define a hypothetical short variance contract that pays $10 per squared percentage point of annualized strike variance minus realized variance. Assume its strike is 400 points squared, it settles on exactly the estimator above, has no cap, and is held to settlement. This explicitly defined payoff is not a quote for an available product and is not a straddle backtest.

The $600 cost budget is a hypothetical all-in cash assumption, not an estimate of typical costs. Separate execution spread, commissions, financing and any hedge costs in an actual ledger. Do not deduct a cost twice if it is already embedded in fills or reported P&L.
For options, specify strikes, expiries, quantities, fills and delta-hedging rules. Changing gamma, gaps, discrete hedges, early exercise or assignment, and an exit before expiry can break a simple variance-spread interpretation. Mark-to-market losses and margin calls can occur before a favorable final settlement.
A VIX future has its own entry price and settlement mechanism. A positive spot-IV-minus-realized spread is not its payoff. Do not substitute a volatility index chart for historical option or futures execution data.
Report currency P&L separately from return on capital. A variance notional is not invested capital; percentage returns require an explicit collateral, margin and cash-flow policy.

Outcome	Gross settlement	Assumed total costs	Net P&L
Example: realized variance 243.3333 points squared	$10 × (400 - 243.3333) = $1,566.67	$600	$966.67
Same example, higher costs	$1,566.67	$1,800	-$233.33
Stress: realized volatility 45%, variance 2,025 points squared	$10 × (400 - 2,025) = -$16,250	$600	-$16,850

Reject incomplete or incompatible research rows

If T has not arrived, the realized outcome is pending. Leave it missing. If the price history, quote metadata or matched horizon is incomplete, mark the row invalid and report the exclusion. Neither zero filling nor silently changing the horizon produces the requested comparison.

Scheduled exchange closures are different from missing scheduled observations. Use an exchange calendar, and retain any close-to-close move across a weekend according to the estimator.
A zero realized variance from genuinely unchanged sampled prices is mathematically valid. It does not prove there was no intraday risk. Negative implied variance is invalid; a zero IV needs investigation of the quote source.

Failure	Consequence	Research action
Missing close inside the intended sample	A multi-day endpoint return cannot recover the omitted squared returns.	Recover the data or exclude the row under a stated rule.
Zero or negative price, nonfinite input, T at or before t	Log returns or annualization are undefined.	Reject the row; do not take absolute prices or invent a year fraction.
Stale IV or a revised historical series	The stored value may not represent information available at entry.	Keep quote timestamps and data vintages; flag unavailable evidence.
Split, dividend, futures roll or synthetic chart mismatch	An artificial price change can dominate realized variance.	Use a documented series consistent with the option underlying and payoff.

Use TradingView exports for the data they contain

TradingView chart exports include loaded chart data, while Strategy Report exports are specific to the selected tab. Export List of Trades for trade analysis; it does not replace the underlying price history and historical IV observations needed for this study. Save the symbol, session, interval, adjustment settings and timestamps with each dataset.

Backtest Deep Report parses trade IDs, entry and exit records, timestamps, prices, quantities, P&L and excursion fields from supported TradingView trade CSVs. Its existing metrics include net profit, profit factor and drawdown from a trade-derived equity curve.
The report does not provide the matched IV, subsequent realized variance, physical variance forecast or overlap-adjusted inference described here. Calculate those statistics separately and reconcile the results with the actual strategy ledger.
Pine Script AI Coding Agent can help draft a chart calculation or an observable entry rule once you provide the exact input series, horizon and availability rules. Verify the data feed and compare individual values with an independent calculation. Generating code cannot supply missing historical IV or option fills.

Where Pineify fits

Backtest Deep Report

Review supported profit and drawdown metrics from exported TradingView trades after calculating the matched volatility study separately.

Also useful: Pine Script AI Coding Agent. Draft a rule using data available at entry, with explicit timestamps and horizon definitions, then verify its output.

Review exported trades

Related resources

TradingView backtesting guides Audit backtest data and execution assumptions Check synthetic-price backtest limitations Export TradingView strategy trades

Frequently asked questions

Educational information, not investment advice. All numerical examples are hypothetical. The described spreads are research statistics, not observed strategy returns or a promise of future profits. Short volatility positions can incur large losses.

Sources and verification

Last verified: 2026-10-18

Published by Pineify. Pineify is an independent product and is not affiliated with TradingView. Sources support the technical explanations; examples do not establish trading performance.