Volatility Library

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.”

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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.”

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