How Effectively Does the Market Predict Volatility?


The CBOE Volatility Index (VIX) got here on the scene within the Nineteen Nineties as a means for traders to trace anticipated danger available in the market going ahead. The Chicago Board Choices Alternate’s VIX does one thing distinctive in that it makes use of 30-day choices on the S&P 500 Index to gage merchants’ expectations for volatility. In essence, it provides us a ahead estimate of what the market thinks volatility in equities goes to be.

However how correct is that this measure on a realized foundation and when does it diverge from the market? We tackled this query by evaluating the complete spectrum of VIX knowledge going again to 1990 to realized volatility of the S&P 500 Index. We discovered that, on common, the market overestimated volatility by about 4 share factors. However there have been distinctive occasions when there have been vital misestimations by the market. We inform this story in a sequence of reveals.

Exhibit 1 is a picture of the complete time sequence of information. It reveals that, on common, the VIX overshot realized volatility constantly over time. And the unfold was constant as nicely, apart from throughout spike intervals (occasions when markets go haywire).

Exhibit 1.

Vix Vs. Volatility

In Exhibit 2, we summarize the information. The typical S&P 500 Index realized volatility on a 30-day ahead foundation was 15.50% over the 35-year interval. The typical VIX (30-day ahead estimate) was 19.59% over the identical interval. There’s a 4.09% unfold between the 2 measures. This means that there’s an insurance coverage premium of 4.09 share factors on anticipated volatility to be insulated from it, on common.

Exhibit 2.

Common (%) Median (%)
S&P Volatility (ahead 30 days) 15.50427047 13.12150282
VIX (30-day Estimate) 19.59102883 17.77
Distinction (Precise Vs Estimate) -4.086758363 -4.648497179

Subsequent, we flip towards a time when no main disaster occurred: from 1990 to 1996. Exhibit 3 highlights how markets labored throughout these regular occasions. The VIX constantly overshot realized volatility by roughly 5 to seven share factors.

Exhibit 3.

Vix vs. Volatility

Exhibit 4 depicts a really completely different interval: the 2008 international monetary disaster (GFC), and we are able to see a really completely different story. In July 2008, realized volatility on a 30-day, forward-looking foundation started to spike over the VIX. This continued till November 2008 when the VIX lastly caught up and matched realized volatility. However then realized volatility fell again down and the VIX continued to climb, overshooting realized volatility in early 2009.

Exhibit 4.

Vix vs. Volatility

This seems to be a normal sample in panics. VIX is sluggish to react to the oncoming volatility after which overreacts as soon as it realizes the volatility that’s coming. This additionally says one thing about our markets: The Federal Reserve and different entities step in to quell the VIX as soon as issues look too dangerous going ahead, thereby lowering realized volatility. In Exhibit 5, we noticed this dynamic once more throughout the COVID interval.

Exhibit 5.

Vix vs. Volatility

The Displays yield two attention-grabbing takeaways. One, traders, on common, are paying a 4% premium to be protected against volatility (i.e. the distinction between the VIX and realized volatility). Two, the market is constant on this premium; is sluggish to initially react to massive, surprising occasions just like the GFC and COVID; after which overreacts.

For these which can be utilizing VIX futures or different derivatives to guard in opposition to catastrophic occasions, these outcomes spotlight how a lot of a premium you’ll be able to count on to pay for tail danger insurance coverage in addition to the danger you soak up overpaying throughout occasions of market panic.

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All posts are the opinion of the writer. As such, they shouldn’t be construed as funding recommendation, nor do the opinions expressed essentially replicate the views of CFA Institute or the writer’s employer.

Picture credit score: ©Getty Photographs / Ascent / PKS Media Inc.


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