February 2, 2017    6 minute read

Why the Volatility Index Can’t Be Trusted

Market Overreactions    February 2, 2017    6 minute read

Why the Volatility Index Can’t Be Trusted

The British parliament has passed the vote on Article 50 and backed Theresa May’s plea to start negotiating for EU withdrawal. There is no doubt Britain will face a year of uncertainty. There will be increasing socio-political conflicts in the wider world caused by the upcoming presidential races in France and Germany and the questionable leadership of Donald Trump, as well as Brexit’s negotiations.

Moreover, the speculation caused by the end of the ultra-low interest rate era and the temporary retreat of China’s currency internationalisation has flooded the financial markets with uncertainty.

Yet, the CBOE Volatility Index (VIX), which is designed to reflect uncertainty and fear in the market, has reached its lowest level since 2008 and suggests a calm future. Because of this contrast, people have started to question the reliability of the VIX in reflecting market volatility. Is the index ‘lying’?

The truth is that VIX can reflect market volatility, but there are a few issues with it which mean that it should not be completely trusted.

VIX_2008to17 chart

(Source: CBOE Volatility Index)

The ‘Fear Index’

The VIX, or the Sigma Index as it was originally called, was developed in 1987 by Professor Menachem Brenner and Professor Dan Galai, and introduced by Chicago Board Options Exchange in 1993. It is used to estimate the implied volatility from any given point over the following 30 days.

It is one of the world leading barometers for measuring investor sentiment. Often referred as the ‘Fear Index’ in the media, it measures the implied volatility of S&P 500 index options.

Yet, the term ‘Fear Index’ is something of an exaggeration, and is not a correct interpretation of what the VIX really is. The actual formula of the index took years to invent and would need a few academic essays to fully explain. Under the assumption that investors price in a premium of options to compensate for their expected risk, the CBOE uses the price premium to derive the VIX and the measures the expected volatility in the market.

The basic mechanism behind the VIX is that if market uncertainty goes up, investors pay more for the premium to make up for the increase in the risk they bear and the VIX goes up. The index is expressed in percentages and can be interpreted as the range of expected movement in the S&P 500.

For example, if the VIX stands at 17%, it means that 68% of the time, the S&P 500 is not expected to rise or drop by more than 17%.

The Bias of the VIX

Despite being widely used, the VIX does not reflect the actual volatility in returns. One of the key issues is its downward bias with increasing volatility. If one looks solely at the VIX, it is very likely that one will underestimate the volatility in the market, especially in times of unpredictable movements.

VIX_downward bias

(Source: Chow, Jiang and Li)

This diagram plots the downward bias of VIX. It shows that the higher VIX is, the larger the deviation from the actual return volatility.

In times of volatile movements, this underestimation can lead investors to miss the opportunity of capturing a huge rebound, or to suffer from devastating loss just by misplacing their portfolio on a slightly more aggressive algorithm. In this way, VIX fails to provide a comprehensive review of actual volatility and should always be used together with other barometers.

Its Questionable Powers of Prediction

Another question often raised by people is whether the VIX can really predict future movements. Some experienced practitioners suggest that the index only really tracks the inverse of price. They believe that VIX is ultimately nothing but a function of the price that reflects little more than the current performance of prices.

Fortunately for CBOE and VIX derivative investors, this statement is most likely wrong. Theoretically, it will have some predictive power as long as the Black-Scholes model holds. Nevertheless, the Black-Scholes model is based on various assumptions and one of them is the assumption of constant volatility.

This assumption is a major disadvantage for the model, especially when pricing currency and stock indices. Empirical data shows this assumption does not fully match real-life scenarios. Nevertheless, the constant volatility assumption does capture some of the features of the market and it is still quite useful in most scenarios.

Should the VIX Be Used?

Despite having its flaws, the VIX is still a commonly-used barometer for understanding market uncertainty. It may not be the ideal indicator of the market’s emotions or a good predictor of future movement, but it does undoubtedly reflect some degree of information in the market. Combined with other tools, information about the market can certainly be derived from the index.

Apart from VIX, there is a wide diversity of other indices measuring different sides of the market. For example, the VVIX, which is essentially a VIX for the VIX, measures the volatility of volatility. Or the percentage price oscillator, which is a momentum based parameter that also reflects the stock volatility.

CNN even combined a portfolio of seven different indicators, from Junk Bond Demands to the McClellan Volume Summation Index, to create The Fear and Greed index in an attempt to gauge market sentiments. If one carefully analyses these indices together, they can give a comprehensive view of the market.

The study of volatility is one of the most exciting fields in financial statistics. After rounds and rounds of heated debates, innovative models such as the Black-Scholes, SARB model, and the VIX itself were developed and all these make up baby steps towards uncovering the ‘truth’ of the market.

Despite concerted efforts and results from brilliant financial minds around the world, there is still a long road ahead before creating the perfect index for volatility. People can argue for decades just to settle on one simple definition or assumption. The future is not going to be easy, but where would be the fun in researching financial volatility if it were?

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