Realized vs Implied Volatility
Both are quoted in the same annualized-percentage units and both describe how much an asset moves, but they look in opposite directions in time. Realized volatility is computed from observed returns over a window; it is a fact about the past. Implied volatility is backed out of option prices through a pricing model; it is a forecast the market is pricing, contaminated by the premium investors pay for protection. The gap between them, the variance risk premium, is itself a tradable and informative quantity. This matrix compares what each measures and where each belongs.
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The standard deviation of actual past returns over a chosen window, annualized. A backward-looking measurement of how much the asset actually moved.
Pros
- Directly measured from real returns, with no model or pricing assumption required
- Unambiguous: it is exactly the variation the asset experienced over the window
- The natural benchmark for evaluating whether a volatility forecast was any good
- Available for any asset with a price history, not just those with traded options
Cons
- Backward-looking, so it can lag a regime change and understate risk just before a shock
- Sensitive to the window length and to the sampling frequency used
- Says nothing about the market's expectation of the future
- Equal-weighting old and recent observations unless an exponential weighting is applied
Risk measurement, position sizing from observed risk, and evaluating the accuracy of volatility forecasts after the fact
The volatility that, plugged into an option pricing model, reproduces the option's market price. A forward-looking expectation embedded in option prices.
Pros
- Forward-looking: it reflects the market's expectation of volatility over the option's life
- Reacts immediately to news and changing sentiment, often before realized volatility moves
- Encodes a term structure and a skew that reveal how the market prices tail and time risk
- The required input for pricing and hedging options consistently with the market
Cons
- Contaminated by the variance risk premium, so it sits above realized volatility on average
- Model-dependent: the number depends on the pricing model and its assumptions
- Available only for assets with liquid options and reliable quotes
- Reflects expectation plus risk appetite, so it is not a clean forecast of future realized volatility
Forward-looking signals, options pricing and hedging, and gauging market expectations and fear via the term structure and skew
Decision Table
See the tradeoffs side by side
| Criterion | Realized (Historical) Volatility | Implied Volatility |
|---|---|---|
| Direction in time | Backward, measured | Forward, expected |
| Source | Actual returns | Option prices |
| Model dependence | None | Pricing model required |
| Contains a risk premium | No | Yes, sits above realized on average |
| Reacts to news | Slowly, after the fact | Quickly, often ahead |
| Availability | Any priced asset | Assets with liquid options |
Verdict
They are complements, not substitutes, and the relationship between them is where the insight lives. Use realized volatility when you need to measure risk that actually occurred, size positions to observed variation, or judge after the fact whether a forecast was right, because it is model-free and unambiguous. Use implied volatility when you need a forward-looking read, an options-pricing input, or a gauge of market fear, because it captures expectations and reacts before realized volatility moves. The catch is that implied is not a clean forecast: it consistently exceeds subsequent realized volatility on average, and that gap is the variance risk premium, the compensation option sellers earn for bearing volatility risk. Watching implied relative to realized, and the implied term structure and skew, is more informative than either number alone.
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FAQ
Questions people ask next
The short answers readers usually want after the first pass.
Sources & References
- The Variance Risk Premium — Carr and Wu, Review of Financial Studies (2009)
- Expected Stock Returns and Variance Risk Premia — Bollerslev, Tauchen, Zhou, Review of Financial Studies (2009)
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