Frequently Asked Questions

Who is VolX?

VolX is a company that has designed novel RealVol Instruments and RealVol Indices based on the RealVol Formulas.

What problem do the RealVol Indices solve?

Looking at risk in one dimension or with only one number is fraught with problems.  VolX has settled on 40 vital risk measures in order to give the market participant the most complete picture of risk ever assembled.  Providing traders with all those measures on key global assets allows them to compare risk levels between or among assets in a standardized manner.

Are the calculations difficult?

It is not hard to calculate realized volatility.  It can be accomplished using two columns in a spreadsheet.  However, realized volatility is just one piece of the puzzle — some of the other formulas and models are more complex, the data often needs adjusting, the data must be cleaned, and the process of rolling between futures contracts must be handled properly.

Who are your competitors?

Many index companies create only baskets of stocks.  The few that calculate risk do so on just their proprietary indices and provide only one dimension of risk — realized volatility — leaving out the other important measures.  There is no other service today that provides this level of depth and breadth of risk analysis on all of the key global assets.

Who is your target market?

Individual investors, academics, brokers, investment banks, hedge funds, options traders, pension funds, mutual funds, and insurance companies.

Why use realized volatility?

Realized volatility attempts to measure the actual price risk in the market.  While implied-volatility instruments have enjoyed success, the true measure of a market’s risk is the actual price movements of the underlying.  The magnitude of implied volatility often does not reflect market movement regardless of direction; rather, it evaluates the cost of insurance and the relative expensiveness of options, as reflected through their premiums.

How does realized volatility differ from implied volatility?

Realized volatility measures actual price risk that the underlying asset displays.  Implied volatility uses an options model to infer or imply a volatility level based on the premiums traded in the marketplace.  For example, if one looks at the actual dollar loss incurred from a house fire versus the cost of homeowners insurance, one might get a good idea of the difference between realized and implied volatility.

Is the standard statistical method of measuring realized volatility sufficient?

Using interday, close-to-close, realized volatility is the standard method of measuring longer-term (a month or more) price risk in the market.  Statistically speaking, at least 20 observations are required for the calculation of realized volatility to be valid.  This corresponds to the time frame of the 1-month VOL index (symbol VOLm).

Why have an overnight/intraday risk measure?

Our overnight/intraday risk measure is approximately five times more efficient at providing the “true” risk in the market.  Also, different hedging strategies rely on different frequencies of trading.  While a reference to close-to-close volatility (VOL) might be relevant when trading just once a day, DVOL would be a more appropriate benchmark for the trader whose style is to execute one or more intraday hedges.

Why are there six time frames?

Investors and traders have different trading styles.  VolX has settled on six standardized time frames that correspond to most traders’ investment horizons (from one day to one year).

Why calculate vol of vol?

When an instrument on realized volatility becomes available for trading, one is compelled to determine the risk of that instrument.  This risk is expressed as the realized volatility of realized volatility, or “vol of vol.”

Why calculate variance?

Variance is just the square of volatility.  However, it has an interesting property — variance is linear.  Therefore, for mathematical purposes, it is much easier to manipulate expressions of variance than those of volatility.  In addition, one can replicate a variance payoff, theoretically, with a static array of options.  Volatility is much harder to replicate and can be accomplished only through a dynamic process, which is considerably more costly to execute.

Why calculate correlation?

Correlation between the underlying asset’s price and its realized volatility is the key to knowing if the underlying has a volatility bias.  For instance, many have observed that, upon occasion, the stock market can drop rather quickly but often rises more slowly.  When this phenomenon occurs, it might show up as negative correlation (market down, volatility up, and vice versa).  Some commodities typically demonstrate just the opposite correlation.  However, as with any measure related to volatility, correlations change, and sometimes dramatically.

Why are there so many adjustments to the underlying data?

We call all instances of contrived or artificial price movements “phantom volatility.”  Phantom volatility is introduced not by economic conditions, but by structural ones such as:  futures that expire, deliverable commodities in the delivery month, stocks that pay a dividend, prices of some interest-rate instruments when rates go to zero, market disruption events, etc.  In these instances, phantom volatility is removed prior to calculating realized volatility.

How is the roll between expiring futures actually accomplished?

As far as we know, no service that calculates realized volatility rolls properly.  Often, they just avoid the issue by not allowing the calculation on futures contracts (because they expire).  When the calculation is available, there are two methods the services choose, and both are incorrect:  either they ignore the typical jump in price between an expiring contract and the next available one (which causes an artificial jump in volatility levels), or they normalize the whole price series of the expiring contract (a better method but still not the correct way to accomplish the task).  VolX first calculates returns using same-contract expirations only, then calculates the ensuing volatility.  This process eliminates phantom volatility typically introduced by the other services.

Why not use the customary standard deviation formula?

The traditional standard deviation formula found in statistics textbooks subtracts the mean from all observations.  This works well, as an example, for finding the distribution of the heights of all children in the fifth grade, but it is not appropriate for measuring the volatility of markets.  In essence, subtracting the mean is like assuming that the recent trend will continue forever.  We have never seen a market that moves in only one direction.

Which model is better at forecasting?

Forecasting market volatility is difficult.  However, the HARK and Rough Vol models have shown to be excellent predictors of realized volatility levels.  One should be aware that the models approach their forecasts from very different vantage points.  While the predictions often are very close to each other, they can and do diverge.  Traders should look at the two models to decide which suits their trading style, investment horizon, and the underlying asset being considered — all of which can affect the accuracy of the model.  Please remember that past results are not a guarantee of future performance.

Why hasn’t anyone done this before?

Someone has to be first!  While there are software “solutions” that calculate realized volatility, these services often do not use the correct formula or clean data, nor do they adjust for phantom volatility.  If you are using another service, please make certain that their exact process is known and is proper.

 


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