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Errors in Implied Volatility Estimation

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Author Info
Hentschel, Ludger
Abstract

Estimating implied volatility by inverting the Black-Scholes formula is subject to considerable error when option characteristics are observed with plausible errors. Especially for options away from the money, large changes in volatility produce small changes in option prices. Conversely, small errors in option prices and other option characteristics produce large errors in implied volatilities. In the presence of small measurement errors, unobserved truncation of option prices that violate lower bounds for absence of arbitrage can also lead to systematic volatility smiles. The paper proposes feasible GLS estimators that reduce the noise and bias in implied volatility estimates.

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Publisher Info
Article provided by Cambridge University Press in its journal Journal of Financial and Quantitative Analysis.

Volume (Year): 38 (2003)
Issue (Month): 04 (December)
Pages: 779-810
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:cup:jfinqa:v:38:y:2003:i:04:p:779-810_00

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  1. Günter Franke & Erik Lüders, 2005. "Return Predictability and Stock Market Crashes in a Simple Rational Expectations Model," CoFE Discussion Paper 05-05, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
  2. Marcelo Fernandes & Marcelo Cunha Medeiros & MArcelo Scharth, 2007. "Modeling and predicting the CBOE market volatility index," Textos para discussão 548, Department of Economics PUC-Rio (Brazil). [Downloadable!]
  3. Patrick Dennis & Stewart Mayhew, 2009. "Microstructural biases in empirical tests of option pricing models," Review of Derivatives Research, Springer, vol. 12(3), pages 169-191, October. [Downloadable!] (restricted)
  4. Bernd Engelmann & Matthias Fengler & Morten Nalholm & Peter Schwendner, 2006. "Static versus dynamic hedges: an empirical comparison for barrier options," Review of Derivatives Research, Springer, vol. 9(3), pages 239-264, November. [Downloadable!] (restricted)
  5. V. Moriggia, S. Muzzioli, C. Torricelli, 2007. "Call an Put Implied Volatilities and the Derivation of Option Implied Trees," Frontiers in Finance and Economics, Lille Graduate School of Management, vol. 4(1), pages 35-64, June. [Downloadable!]
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  6. Ahoniemi, Katja & Lanne, Markku, 2007. "Joint Modeling of Call and Put Implied Volatility," MPRA Paper 6318, University Library of Munich, Germany. [Downloadable!]
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  7. Matthias R. Fengler, 2005. "Arbitrage-Free Smoothing of the Implied Volatility Surface," SFB 649 Discussion Papers SFB649DP2005-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  8. Günter Franke & Erik Lüders, 2004. "Why Do Asset Prices Not Follow Random Walks?," CoFE Discussion Paper 04-05, Center of Finance and Econometrics, University of Konstanz. [Downloadable!]
  9. Francesco Audrino & Dominik Colagelo, 2007. "Forecasting Implied Volatility Surfaces," University of St. Gallen Department of Economics working paper series 2007 2007-42, Department of Economics, University of St. Gallen. [Downloadable!]
  10. Li, Minqiang, 2008. "Price Deviations of S&P 500 Index Options from the Black-Scholes Formula Follow a Simple Pattern," MPRA Paper 11530, University Library of Munich, Germany. [Downloadable!]
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