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Lack of liquidity means a comeback for vol swaps

04 Jan 2011

Article by: Matt Cameron
Published by: Risk magazine
Date: 28 Jul 2009

“Dynamic replication of the payoff of volatility swaps on single stocks in illiquid markets is cheaper and easier than replicating variance swaps payoffs, dealers say.

“Activity in variance swaps has died down after volatility spiked in late 2008, causing many dealers to experience hefty losses, particularly in single stocks. The resulting pull-back has spurred dealers to search for other ways to offer volatility trades where clients are not required to delta-hedge options. Dealers such as BNP Paribas are actively pushing volatility swaps as a viable alternative.”

Full article: Link

 
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Posted in Implied volatility, Trading ideas

 

A hands on approach to volatility trading

26 Dec 2010

Article by: Matt Larsen
Published by: Futures Magazine
Date: Sep 2004

“Volatility can make or break a trader. Learning how to read this important market statistic can give you a real edge. Here’s how to incorporate the Volatility Index, or Vix, into your trading approach.

“The Volatility Index (Vix) is a useful tool in accurately reflecting upcoming changes in the intermediate trend. Unfortunately, most traders do not understand how to implement this tool successfully. This article takes a common sense approach toward successfully using the Vix to add to your bottom line.

“The Vix measures market volatility and is often referred to as the “investor fear gauge.” It works because it is inversely correlated, meaning as the S&P 500 moves down in price, the Vix (generally) moves higher. Without spending time on the academics of it, the equation for the Vix calculates volatility by averaging weighted prices of out-of-the-money put and call options.”

Full article: Link

 
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Posted in Implied volatility, Trading ideas

 

The predictive power of implied volatility: Evidence from 35 futures markets

21 Dec 2010

Article by: Andrew Szakmary, Evren Ors, Jin Kyoung Kim, Wallace N. Davidson III
Published by: Elsevier, Journal of Banking and Finance
Date: 19 Apr 2002

“Using data from 35 futures options markets from eight separate exchanges, we test how well the implied volatilities (IVs) embedded in option prices predict subsequently realized volatility (RV) in the underlying futures. We find that for this broad array of futures options, IV performs well in a relative sense. For a large majority of the commodities studied, the implieds outperform historical volatility (HV) as a predictor of the subsequently RV in the underlying futures prices over the remaining life of the option. Indeed, in most markets examined, regardless of whether it is modeled as a simple moving average or in a GARCH framework, HV contains no economically significant predictive information beyond what is already incorporated in IV. These findings add to previous research that has focused on currency and crude oil futures by extending the analysis into a very broad array of contracts and exchanges. Our results are consistent with the hypothesis that futures options markets in general, with their minimal trading frictions, are efficient.”

Full article (PDF): Link

 
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Posted in Implied volatility, Realized volatility

 

Range-based Volatility Estimators

19 Dec 2010

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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Posted in Implied volatility

 
 
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