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Forecasting foreign exchange volatility: Why is implied volatility biased and inefficient? And does it matter?

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  • Neely, Christopher J.

Abstract

Research has consistently found that implied volatility is a conditionally biased predictor of realized volatility across asset markets. This paper evaluates explanations for this bias in the market for options on foreign exchange futures. Several recently proposed solutions - including a model of priced volatility risk - fail to explain a significant portion of the conditional bias found in implied volatility. Further, while implied volatility fails to subsume econometric forecasts in encompassing regressions, these forecasts do not significantly improve delta-hedging performance. Thus this paper argues that statistical metrics are inappropriate measures of the information content of implied volatility. Implied volatility appears much more useful when measured by a more relevant, economic metric.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of International Financial Markets, Institutions and Money.

Volume (Year): 19 (2009)
Issue (Month): 1 (February)
Pages: 188-205

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Handle: RePEc:eee:intfin:v:19:y:2009:i:1:p:188-205

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Web page: http://www.elsevier.com/locate/intfin

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Keywords: Exchange rate Option Implied volatility GARCH High-frequency;

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References

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Citations

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Cited by:
  1. Christoffersen, Peter & Mazzotta, Stefano, 2004. "The informational content of over-the-counter currency options," Working Paper Series 0366, European Central Bank.
  2. Hui Guo & Christopher J. Neely & Jason Higbee, 2008. "Foreign Exchange Volatility Is Priced in Equities," Financial Management, Financial Management Association International, vol. 37(4), pages 769-790, December.
  3. Ariful Hoque & Chandrasekhar Krishnamurti, 2012. "Modeling moneyness volatility in measuring exchange rate volatility," International Journal of Managerial Finance, Emerald Group Publishing, vol. 8(4), pages 365-380.
  4. Kellard, Neil & Dunis, Christian & Sarantis, Nicholas, 2010. "Foreign exchange, fractional cointegration and the implied-realized volatility relation," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 882-891, April.
  5. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
  6. Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.

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