Volatility Library

Article by: Bradley Kay
Published by: Morningstar
Date: 11 Feb 2009

“Individuals can finally invest in volatility, but what is it?

“We cannot tell if the timing is superb or terrible, but individual investors can finally invest (almost) directly in volatility now that Barclays has released two iPath ETNs based on the widely tracked VIX index: iPath S&P 500 VIX Short-Term Futures ETN (VXX) and iPath S&P 500 VIX Mid-Term Futures ETN (VXZ). While the recent crash reminded us all why volatility is the ultimate diversifier, it has also made investors wary of ETNs and the credit risk they carry. Investors need only read our previous article on ETNs to see that we would suggest caution before running out to buy any of these debt instruments. However, these intriguing new exchange-traded products allow access to an exotic asset class that used to be the preserve of institutions that could trade complex options strategies or enormous futures contracts. Strategic stakes in volatility could help sophisticated investors protect their portfolio from the next big crash, which is why we called out for these funds a scant five months ago. Now that they have finally arrived, we wish to take the opportunity to elucidate how these new indexes work, why we were so excited about the prospect of a volatility investment in the first place, and why you shouldn’t rush to invest just yet.”

Full article: Link

Article by: Mark B. Garman, Michael J. Klass
Published by: University of California, Berkeley
Date: ?

“This paper examines the problem of estimating capital asset price volatility parameters from the most available forms of public data. While many varieties of such data are possible, we shall consider here only those which are truly universal in their accessibility to investors, that is, data appearing in the financial pages of the newspaper. In particular, we shall consider volatility estimators that are based upon the historical opening, closing, high, and low prices and transaction volume. Since high and low prices require continuous monitoring to obtain, they correspondingly contain superior information content, exploited herein.

Any parameter-estimation procedure must begin with a maintained hypothesis regarding the structural model within which estimation is to be made. Our structural model is described in Section II. Section III discusses the “classical” estimation approach. In Section IV we introduce some more efficient estimators based upon the high and low prices. “Best” analytic estimators, which simultaneously use the high, low, opening, and closing prices, are formulated in Section V. Section VI considers the complications raised by trading volume. Section VII provides a summary.”

Full article (PDF): Link

Article by: George J. Jiang, Yisong S. Tian
Published by: Oxford University Press
Date: 2005

“Britten-Jones and Neuberger (2000) derived a model-free implied volatility under the diffusion assumption. In this article, we extend their model-free implied volatility to asset price processes with jumps and develop a simple method for implementing it using observed option prices. In addition, we perform a direct test of the informational efficiency of the option market using the model-free implied volatility. Our results from the Standard & Poor’s 500 index (SPX) options suggest that the model-free implied volatility subsumes all information contained in the Black–Scholes (B–S) implied volatility and past realized volatility and is a more efficient forecast for future realized volatility.”

Full article: Link