It is colloquially referred to as the fear index or the fear gauge. The formulation of a volatility index, and financial instruments based on such an index, were developed by Menachem Brenner and Dan Galai in and described in academic papers. A volatility index would play the same role as the market index play for options and futures on the index.
In , Brenner and Galai proposed to the American Stock Exchange the creation of a series of volatility indices, beginning with an index on stock market volatility, and moving to interest rate and foreign exchange rate volatility.
In , Brenner and Galai met with Joseph Levine and Deborah Clayworth at the Chicago Board of Options Exchange to propose various structures for a tradeable index on volatility; those discussions continued until The current VIX concept formulates a theoretical expectation of stock market volatility in the near future.
The CBOE retained consultant Robert Whaley in to develop a tradable volatility instrument based on index option prices. Based on historical index option prices, Whaley has computed a data series of retrospective daily VIX levels from January onward. As of February 24, , it became possible to trade VIX options contracts. Several exchange-traded funds seek to track its performance. The formula uses a kernel -smoothed estimator that takes as inputs the current market prices for all out-of-the-money calls and puts for the front month and second month expirations.
The VIX is calculated as the square root of the par variance swap rate for a day term [ clarify ] initiated today. Note that the VIX is the volatility of a variance swap and not that of a volatility swap volatility being the square root of variance, or standard deviation.
A variance swap can be perfectly statically replicated through vanilla puts and calls whereas a volatility swap requires dynamic hedging. The VIX is quoted as an annualized standard deviation. The price of call and put options can be used to calculate implied volatility, because volatility is one of the factors used to calculate the value of these options. Higher or lower volatility of the underlying security makes an option more or less valuable, because there is a greater or smaller probability that the option will expire in the money i.
Thus, a higher option price implies greater volatility, other things being equal. In practical terms, when investors anticipate large upside volatility, they are unwilling to sell upside call stock options unless they receive a large premium. Option buyers will be willing to pay such high premiums only if similarly anticipating a large upside move. The resulting aggregate of increases in upside stock option call prices raises the VIX just as does the aggregate growth in downside stock put option premiums that occurs when option buyers and sellers anticipate a likely sharp move to the downside.
When the market is believed as likely to soar as to plummet, writing any option that will cost the writer in the event of a sudden large move in either direction may look equally risky. Hence high VIX readings mean investors see significant risk that the market will move sharply, whether downward or upward. The highest VIX readings occur when investors anticipate that huge moves in either direction are likely. Only when investors perceive neither significant downside risk nor significant upside potential will the VIX be low.
Chow, Jiang and Li  demonstrated that without imposing any structure on the underlying forcing process, the model-free CBOE volatility index VIX does not measure market expectation of volatility but that of a linear moment-combination. Particularly, VIX undervalues overvalues volatility when market return is expected to be negatively positively skewed.
Alternatively, they develop a model-free generalized volatility index GVIX. Empirically, VIX generally understates the true volatility, and the estimation errors considerably enlarge during volatile markets. VIX is sometimes criticized in terms of it being a prediction of future volatility. It is a measure of the current price of index options.
Despite their sophisticated composition, critics claim the predictive power of most volatility forecasting models is similar to that of plain-vanilla measures, such as simple past volatility. Some practitioners and portfolio managers seem to completely ignore or dismiss volatility forecasting models.
In a similar note, Emanuel Derman expressed his disillusion with the enormous supply of empirical models unsupported by theory. Michael Harris has argued that VIX just tracks the inverse of price and it has no predictive power as a result.
VIX should have predictive power as long as the prices computed by the Black-Scholes equation are valid assumptions about the volatility predicted for the future lead time the remaining time to maturity. Shiller argues that it would be circular reasoning to consider VIX to be proof of Black-Scholes, because they both express the same implied volatility. He also finds that calculating VIX retrospectively in does not predict the highest-ever volatility of the Great Depression , due to the anomalous conditions of the Great Depression itself, and we thus have no confidence in VIX to predict, even weakly, such severe events if they should occur in the future.
From Wikipedia, the free encyclopedia. For other uses, see Vix disambiguation. The neutrality of this article is disputed. Relevant discussion may be found on the talk page. Please do not remove this message until conditions to do so are met. August Learn how and when to remove this template message. Retrieved 7 March Whaley, , "Derivatives on market volatility: Hedging tools long overdue," Journal of Derivatives 1 Fall , See the definition volatility for a discussion of computing inter-period volatility.