VIX (CBOE Volatility Index)


The VIX (the CBOE Volatility Index) is the most widespread benchmark for stock market volatility. This “investor fear gauge”, quoted as a percentage, gives a reliable snapshot of the expected near-term stock volatility based on the S&P500 option prices.

The VIX proved to be a consistent and useful flag in the past crisis: each time the VIX rose brutally, it corresponded to a significant regime change in the stock market conditions (see charts below as an example).


Investors have been using the VIX for a while to get the real-time market temperature: but how can they use this instantaneous market information in a more systematic way to better apprehend their risk?

Why use the VIX?
Historic-based risk models, as advanced as they might be, are not able to detect short-term regime changes on the financial markets. Indeed, time-series have a smoothing effects on recent perturbations, which could lead to a dangerous under-estimation of the risk taken.

Limits of the VIX
So why use historical data in the quantitative risk modeling approach? Historical information remains fundamental for a fine risk modeling and a dynamic estimation of the interdependences. Using the sole Volatility Index as an input for the risk estimation might give too much importance to localized picks of volatility, hence ignore the global trend.

How to use the VIX
Finding the right trade-off between instantaneous and historical information is the key: as simple as it may sound, this mixed approach requires adaptative modeling tools to be able to aggregate the information in a consistent yet systematic way.

How about other asset classes?
Stock volatility indices are available for a wide range of geographical zones and different time-horizons, inspired by the CBOE VIX methodology. But there is still no widespread benchmark to measure the short-term volatility for asset classes such as the commodities, foreign exchange,… Still, there exist some modeling approaches to rebuild such indices “in-house”.