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Forecasting Stock Index Volatility: Comparing Implied Volatility And The Intraday High-Low Price Range

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  • Charles Corrado
  • Cameron Truong

Abstract

The intraday high-low price range offers volatility forecasts similarly efficient to high-quality implied volatility indexes published by the Chicago Board Options Exchange (CBOE) for four stock market indexes: S&P 500, S&P 100, NASDAQ 100, and Dow Jones Industrials. Examination of in-sample and out-of-sample volatility forecasts reveals that neither implied volatility nor intraday high-low range volatility consistently outperforms the other. 2007 The Southern Finance Association and the Southwestern Finance Association.

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Bibliographic Info

Article provided by Southern Finance Association & Southwestern Finance Association in its journal Journal of Financial Research.

Volume (Year): 30 (2007)
Issue (Month): 2 ()
Pages: 201-215

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Handle: RePEc:bla:jfnres:v:30:y:2007:i:2:p:201-215

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Web page: http://www.southwesternfinance.org/
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Cited by:
  1. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
  2. Stavros Degiannakis & George Filis & Renatas Kizys, 2013. "Oil price shocks and stock market volatility: evidence from European data," Working Papers 161, Bank of Greece.
  3. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
  4. Liu, Hung-Chun & Chiang, Shu-Mei & Cheng, Nick Ying-Pin, 2012. "Forecasting the volatility of S&P depositary receipts using GARCH-type models under intraday range-based and return-based proxy measures," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 78-91.
  5. Louzis, Dimitrios P. & Xanthopoulos-Sisinis, Spyros & Refenes, Apostolos P., 2011. "The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting," MPRA Paper 35252, University Library of Munich, Germany.
  6. Li, Yingzi & Fortenbery, T. Randall, 2013. "Do Speculators in Futures Markets Make Cash Markets More Volatile?," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151296, Agricultural and Applied Economics Association.
  7. Bertrand B. Maillet & Jean-Philippe R. Médecin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
  8. Brian M Lucey and Alexander Eastman, 2008. "Comparing Garman-Klass and DU Volatility and Symmetry Measures in Intraday Futures Returns and Volumes: A Vector Autoregression Analysis," The Institute for International Integration Studies Discussion Paper Series iiisdp260, IIIS.

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