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Archive for the ‘Implied volatility’ Category

Range-based Volatility Estimators

19 Dec

Article by: Michael Stastny
Published by: Michael Stastny Weblog
Date: 23 Dec 2006

“Recently, Teresa asked for my opinion regarding range-based volatility estimators because, for years, traders have incorporated Wells Wilders’ Average True Range into many facets of their analysis and systems.

“While I know nothing whatsoever about ATR, I had to figure out something to keep her happy…: The most simple range-based volatility estimator is based on the difference between the maximum and minimum prices observed during a certain period. Parkinson [1980] showed that the daily high-low range, properly scaled, is also an unbiased estimator of daily volatility — but five times more efficient than the squared daily close-to-close return when the underlying process is a random walk.

“Many other estimators that include high, low, open, and close values have been developed Garman and Klass[1980], Rogers and Satchell [1991], Alizahdeh, Brandt and Diebold [2001] and Yang and Zhang [2002]). I think one has to play around with all these estimators to see how they perform in the wilderness. What I liked about Parkinson’s paper was that it was a clear and easy-to-follow exposition, so I reprinted (slightly edited) the most interesting part for those of you who have never heard of range-based volatility estimators before and do not have acess to JSTOR:”

Full article: Link

 
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On the informational content of implied volatility

10 Dec

Article by: Juan Carlos Sosa
Published by: Boston College
Date: 1 Jan 2000

“Previous literature examines whether the volatility estimates implicit in option prices constitute accurate forecasts of future volatility for the underlying asset. Most studies address two questions. Do Black-Scholes implied volatilities predict future volatilities? Do they incorporate all past time series information? The empirical answers to both questions are conflicting. However, previous studies typically find that implied volatilities overestimate future volatilities. Christensen & Prabhala (98) provide evidence of a structural shift in the pricing mechanism of OEX options around the Crash of ’87. In contrast with the pre-Crash results of Canina & Figlewski (93), CP show that after the Crash implied volatilities predict future volatilities and dominate moving average forecasts. They also show that implied volatilities are unbiased, and that errors-in-variables is responsible for previous bias findings. The objective of this dissertation is fourfold. First, we implement encompassing regressions on a recent sample of OEX options. Our full-sample findings are consistent with other studies that support the informational efficiency of implied volatilities in recent years. However, the regressions are very sensitive to the degree of moneyness of implied volatility. Furthermore, we find that the degree of predictive power of implied volatility is strongly time-frame dependent. Second, we show that implied volatilities do overestimate realized volatilities and that CP’s unbiasedness finding is due to an ill choice of instrument, in addition to a low test power. Third, we attempt to correct for potential misspecification in the encompassing regressions and find that lagged implied volatility is important. Yet, we show that the significance of lagged implied volatility is not a symptom of market inefficiency, but of skewness-related model error in implied volatility estimates. Finally, we assess the economic value of informational efficiency via a trading analysis, and find it to be quite limited. In summary, we find that at-the-money implied volatilities are biased estimators of realized volatility, that they suffer from substantial model error, that their predictive power is time-frame dependent, and that moving average estimators perform just as well from an economic point of view.”

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Posted in Implied volatility, Realized volatility

 

The VIX, CIV, and MFIV — Measuring up the accuracy of option-based predictors of volatility

06 Dec

Article based on the Research of Torben Andersen And Oleg Bondarenko
Published by: Kellog Institute
Date: Sep 2080

“Beyond growth and leverage, a key factor in the value of a given stock, and the broader market, is volatility, or the magnitude of variation in prices over time. Especially in today’s uncertainty-ridden market including a major credit crisis and declining dollar, investors pay sizeable premiums to be hedged against increases in volatility, which typically represent bad market conditions. So it is no surprise that there has been growing market and academic interest in equity-index volatility measures. The best-known volatility measure is the volatility index, or VIX, established by the Chicago Board of Options Exchange (CBOE) in 1993. Practitioners and business scholars have established that the VIX, which is based on real-time option market prices for the S&P 500 stock index, correlates significantly with future equity market volatility as well as global risk factors embedded in credit and sovereign debt spreads. Thus the VIX has also become known as the “global fear index”—the higher the VIX, the greater the concern about global markets. In response, multiple public and over-the-counter markets have emerged to enable direct trading of volatility for different assets—using the methodology behind the VIX—rather than more traditional volatility measures based on the Black-Scholes options pricing model.

“The great practical interest in forecasting volatility raises two key questions: How accurate is the VIX as a predictor of actual future return volatility? And, are there more accurate alternative predictors based on option market prices?

“To answer these questions, Torben G. Andersen, professor of finance at Northwestern’s Kellogg School of Management, and co-author Oleg Bondarenko conducted a study of the construction, interpretation, and predictive value of the VIX and several other option-based volatility measures….”

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Posted in Implied volatility

 

It's Hard to Be Right on the VIX

09 Nov

Article by: Howard Simmons
Published by: TheStreet
Date: 13 Jun 2006

“I love volatility in all its manifestations, yes I do. In practice, it reminds traders that this is a risky business, and it has a way of transferring positions from the tourists and various weak hands in the market to those long-term investors we are supposed to admire. In theory, I use it in all sorts of analytic and modeling applications. If loving the VIX is wrong, I don’t want to be right.

“But having a well-designed and useful instrument is one thing; having a good trading tool is something else indeed. The significant problems associated with futures on the VIX were apparent months before their actual launch in March 2004; these were discussed in September 2003. Now that the Chicago Board Options Exchange has launched options on the VIX — options on futures on an index of the two-month strike-weighted volatility of an index of common stocks, each of which represents the discounted stream of future dividends; who needs reality? — and the VIX futures have gained some real trading traction, let’s see how they operate in practice.”

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Posted in Implied volatility

 
 
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