What is the Volatility Risk Premium?

By EC Assets Research Team · Published 15 May 2026 · Updated 15 October 2026

Volatility Risk Premium: The volatility risk premium is the gap between option-implied volatility and the realized volatility that follows: sellers of options have historically collected it, hedgers pay it. In equity indices the spread has averaged several volatility points, which is the economic engine behind covered calls, put writing and most systematic short-volatility strategies.

What the Volatility Risk Premium Measures

The volatility risk premium is the persistent gap between the volatility implied by option prices and the volatility the underlying subsequently realises. For major equity indices, implied volatility has on average exceeded the volatility that followed, so investors who sold options have on average been paid for doing so.

In formal terms it is the difference between two expectations of future variance: the risk-neutral expectation embedded in option prices, which includes compensation for risk, and the physical expectation of what will actually be realised. The gap is what buyers of protection pay and sellers collect, and it is the main reason the VIX usually sits above the volatility the S&P 500 goes on to realise.

How It Works

Two definitions are common. In variance terms, following Bollerslev, Tauchen and Zhou (2009),

$$\text{VRP}t = E^Q_t!\left[\sigma^2{t,t+T}\right] - E^P_t!\left[\sigma^2_{t,t+T}\right]$$

In practice desks track the ex-post spread in volatility points,

$$\text{VRP}_t \approx \text{IV}t - \text{RV}{t,,t+T}$$

using the VIX or at-the-money implied volatility at the start and the volatility realised over the next T days. Carr and Wu (2009) use the opposite sign, realised minus implied, so their premium is negative for the buyer of variance; the economics are the same.

Research splits the index premium into parts. Bakshi and Kapadia (2003) show that delta-hedged option positions lose money on average, the signature of a negative price of volatility risk for the buyer. Bollerslev and Todorov (2011) attribute a large share to compensation for jump and tail risk, and Driessen, Maenhout and Vilkov (2009) show that much of the index premium is a price for correlation risk: correlations between stocks rise in selloffs, lifting index variance above the average single-stock variance.

The cleanest instrument for measuring and trading the premium is a variance swap, whose payoff is linear in realised variance.

Worked Example

A seller of a 30-day S&P 500 variance swap with a volatility strike of 18 and a vega notional of 100,000 has a variance notional of 100,000 / (2 × 18) ≈ 2,778 per variance point. The seller's profit is that notional times 324 minus realised variance:

The gain is bounded at 900,000, when nothing moves; the loss is not.

A realised volatility of 14, four points below the strike, earns the seller 355,556. Now suppose the seller writes this swap every month for a year, eleven months realise 14 and one realises 36. The year earns 11 × 355,556 - 2,700,000 ≈ 1,211,111: still positive, but the single bad month erases about 7.6 good ones. That is the shape of the premium, and the variance risk premium calculator runs other combinations.

When It Applies (and Limitations)

It depends on the regime. The premium is most reliably positive in calm and normal markets and compresses or reverses as a crisis begins. Implied volatility reprices with a lag, so the spread can stay negative for weeks while the market adjusts.

It differs by market. Equity indices carry the largest and most persistent premium. Single stocks carry less, and in commodities, currencies and rates its size and sign vary with the regime and with hedging demand.

Costs and sizing decide the outcome. Bid-ask spreads, roll costs and margin reduce the net premium, and because losses are many times the typical gain, a position sized on the average spread can be ruined by one month. Limits on vega and on stress loss matter more than the capital allocated.

The tenor changes the trade. Short-dated options typically carry more premium per unit of vega but more gamma and more frequent rolls; longer maturities are smoother but less rewarding.

Track records mislead. A record that does not include a full crisis cannot show the tail risk that defines the strategy, so a high historical Sharpe ratio is weak evidence on its own.

Why It Matters for Institutional Investors

It is a return source. Covered calls, put writing and variance selling all collect the premium, with different payoff shapes and operational burdens. Each adds income to an equity allocation at the cost of deeper losses in a selloff.

It is a cost line. Every option-based hedge pays the premium. A tail-hedge programme bought continuously loses money in calm periods by design; its value lies in what it pays in a crisis, so it is judged against the drawdowns it offsets rather than as a stand-alone investment.

It concentrates, not diversifies, equity risk. Short volatility loses when equities fall. Adding it to an equity portfolio raises income but also the correlation of losses in stress, which mean-variance optimisation based on calm-period data understates.

It is a due-diligence test. Comparing the implied volatility at entry with the volatility subsequently realised, as in realised versus implied volatility, separates managers who harvest the premium with explicit tail limits from those who simply collect option income and have not yet met a volatility spike.

References

1. Carr, P., & Wu, L. (2009). Variance Risk Premiums. Review of Financial Studies, 22(3), 1311-1341.
2. Bollerslev, T., Tauchen, G., & Zhou, H. (2009). Expected Stock Returns and Variance Risk Premia. Review of Financial Studies, 22(11), 4463-4492.
3. Bakshi, G., & Kapadia, N. (2003). Delta-Hedged Gains and the Negative Market Volatility Risk Premium. Review of Financial Studies, 16(2), 527-566.
4. Driessen, J., Maenhout, P. J., & Vilkov, G. (2009). The Price of Correlation Risk: Evidence from Equity Options. Journal of Finance, 64(3), 1377-1406.
5. Bollerslev, T., & Todorov, V. (2011). Tails, Fears, and Risk Premia. Journal of Finance, 66(6), 2165-2211.