Why IV Spikes Before Fed Days (And Why It Crushes After)

Summary. Implied volatility rises into scheduled announcements and falls once they are released because options price the extra variance the event is expected to add. This article derives the term-structure effect from variance additivity, shows how to back out the market's implied event move from two expiries, corrects a common arithmetic error, and reviews the evidence on event pricing and post-event behavior.

1. Variance adds, standard deviations do not

Treat an announcement as a single jump in the log price with standard deviation ${\sigma }_e$, independent of ordinary diffusion with annualized volatility ${\sigma }_b$. Variances of independent components add, so the total variance to an expiry $T$ (in years) that includes the event is

This decomposition goes back to Patell and Wolfson's study of options around earnings announcements and is the basis of modern event-risk pricing models such as Dubinsky, Johannes, Kaeck and Seeger [1, 2]. The event term ${\sigma }_e^2/T$ is largest for the shortest expiry that contains the event and fades for longer expiries, which produces the characteristic kink in the term structure.

2. A worked example

Suppose ordinary SPX volatility is 12%, which corresponds to a daily standard deviation of $0.12/\sqrt{252}\approx 0.76\%$, and the market expects the announcement to add a move with a standard deviation of 0.5%. For an option expiring at the end of announcement day ($T=1/252$),

A common shortcut adds the standard deviations instead (0.76% + 0.5% = 1.26% per day) and concludes that implied volatility must be about 20%. That overstates the effect, because independent risks combine through their variances. The correct daily standard deviation is $\sqrt{0.76^2+0.5^2}\approx 0.91\%$.

Figure 1 shows the full term structure. The announcement adds 2.4 points to the one-day expiry but only about 0.5 points to a five-day expiry (12.5%) and about 0.1 points to a 21-day expiry (12.1%).

3. The crush after the event

Once the announcement is out, the event variance is no longer in any option's future, so implied volatility for every expiry that contained it falls. For the five-day at-the-money straddle on SPX 6,000 in the example above, the value is about 84 points before the event and about 72 points one day later if spot is unchanged. Part of that drop is one day of ordinary time decay; the rest is the event variance leaving the price. Holders of event-spanning options need the realized event move to exceed what was priced to profit from the position.

Figure 2 separates the two parts. Without the event, the same straddle would be worth about 80.9 points, so the event adds about 3.5 points to its price. One day later the straddle is worth about 72.4 points: about 8.5 points of the drop is ordinary decay of a five-day option and 3.5 points is the event premium leaving the price.

The empirical literature confirms both parts of the pattern. Option-implied uncertainty rises ahead of scheduled releases and falls after them; Beber and Brandt document this for macroeconomic announcements in the Treasury options market [3], and Dubinsky and coauthors document it for earnings announcements in equity options [2]. Kelly, Pástor and Veronesi show that options spanning major political events are priced with a premium for the associated uncertainty [4].

3.1 What the 30-day VIX shows

The term-structure arithmetic predicts that a one-day event barely moves a 30-day volatility measure: in the example above the announcement adds about 0.1 points to a 21-day expiry. The data agree. Across the 79 scheduled FOMC statements from November 2016 to September 2026 [5, 6], the VIX changed by +0.01 points on average on statement day (95% confidence interval ±0.54), which is indistinguishable from its average change on other days (Figure 3). The VIX fell on 51% of statement days, compared with 55% of other days. The S&P 500's absolute return averaged 0.79% on statement days against 0.73% on other days [7].

The event premium and its removal therefore sit in short-dated options, the expiries that contain the announcement and little else, rather than in the 30-day index. Measures built from those expiries, such as same-day implied volatility, are the right place to look for the crush.

4. Backing out the implied event move

With two expiries, one ending before the event ($T_1$) and one after it ($T_2$), and assuming the base volatility is the same in both windows, the implied event variance is

The square root, ${\sigma }_e$, is the market's implied standard deviation of the announcement move. Comparing it with the distribution of past moves on similar announcements tells you whether the event is priced richly or cheaply. Daily SPX expirations make this calculation available for almost every scheduled release.

5. Why the premium persists

• Hedging demand. Institutions buy protection over known event windows regardless of price, and end-user demand pressure raises option prices [8].
• Residual tail risk. The event distribution has fat tails. A surprise far larger than the priced standard deviation produces large losses for sellers.
• General volatility premium. Event options also carry the ordinary variance risk premium discussed in realized versus implied volatility.

Whether selling event volatility is profitable on average depends on the period and the event type. A positive average does not protect against the occasional large surprise, so sizing should assume that one will occur.

6. What happens to price after the event

When implied volatility falls after an announcement, dealer hedging through vanna can add buying pressure under the usual positioning convention (see vanna and charm). Separately, Lucca and Moench documented large average equity returns in the 24 hours before scheduled FOMC announcements [9]; later work finds that this pre-announcement drift largely disappeared after 2015 [10]. Neither effect is reliable enough to trade as a calendar rule without positioning and pricing information.

7. Practical checklist

1. Identify the shortest expiry that contains the event and the expiry immediately before it.
2. Back out the implied event move with the two-expiry formula and compare it with historical moves for the same event type.
3. Express the comparison in dollars: what the event-spanning straddle costs versus what the event typically delivers.
4. For directional views, prefer expiries that do not contain the event or use structures whose event exposure is offset.

DataFirst's volatility term-structure view shows implied volatility by expiry so that event kinks are visible at a glance.

For educational and informational purposes only. Not financial advice. Options trading involves substantial risk of loss. Example values are illustrative.

References

1. Patell, J. M., & Wolfson, M. A. (1979). Anticipated information releases reflected in call option prices. Journal of Accounting and Economics, 1(2), 117–140. doi.org/10.1016/0165-4101(79)90003-X
2. Dubinsky, A., Johannes, M., Kaeck, A., & Seeger, N. J. (2019). Option pricing of earnings announcement risks. Review of Financial Studies, 32(2), 646–687. doi.org/10.1093/rfs/hhy060
3. Beber, A., & Brandt, M. W. (2006). The effect of macroeconomic news on beliefs and preferences: Evidence from the options market. Journal of Monetary Economics, 53(8), 1997–2039. doi.org/10.1016/j.jmoneco.2005.09.004
4. Kelly, B., Pástor, Ľ., & Veronesi, P. (2016). The price of political uncertainty: Theory and evidence from the option market. Journal of Finance, 71(5), 2417–2480. doi.org/10.1111/jofi.12406
5. Board of Governors of the Federal Reserve System. FOMC meeting calendars, statements and minutes (2016 to 2026). www.federalreserve.gov/monetarypolicy/fomccalendars.htm
6. Cboe Global Markets. Cboe Volatility Index: VIX [VIXCLS]. Retrieved from FRED, Federal Reserve Bank of St. Louis, 9 October 2026. fred.stlouisfed.org/series/VIXCLS
7. S&P Dow Jones Indices LLC. S&P 500 [SP500]. Retrieved from FRED, Federal Reserve Bank of St. Louis, 9 October 2026. fred.stlouisfed.org/series/SP500
8. Gârleanu, N., Pedersen, L. H., & Poteshman, A. M. (2009). Demand-based option pricing. Review of Financial Studies, 22(10), 4259–4299. doi.org/10.1093/rfs/hhp005
9. Lucca, D. O., & Moench, E. (2015). The pre-FOMC announcement drift. Journal of Finance, 70(1), 329–371. doi.org/10.1111/jofi.12196
10. Kurov, A., Wolfe, M. H., & Gilbert, T. (2021). The disappearing pre-FOMC announcement drift. Finance Research Letters, 40. ideas.repec.org/a/eee/finlet/v40y2021ics1544612320315956.html
11. Lucca, D. O., & Moench, E. (2011, revised 2013). The pre-FOMC announcement drift. Federal Reserve Bank of New York Staff Report No. 512. www.newyorkfed.org/medialibrary/media/research/staff_reports/sr512.pdf