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Corridor implied volatility and the variance risk premium in the Italian market

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  • Silvia Muzzioli

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Abstract

Corridor implied volatility introduced in Carr and Madan (1998) and recently implemented in Andersen and Bondarenko (2007) is obtained from model-free implied volatility by truncating the integration domain between two barriers. Corridor implied volatility is implicitly linked with the concept that the tails of the risk-neutral distribution are estimated with less precision than central values, due to the lack of liquid options for very high and very low strikes. However, there is no golden choice for the barriers levels’, which will probably change depending on the underlying asset risk neutral distribution. The latter feature renders its forecasting performance mainly an empirical question. The aim of the paper is twofold. First we investigate the forecasting performance of corridor implied volatility by choosing different corridors with symmetric and asymmetric cuts, and compare the results with the preliminary findings in Muzzioli (2010b). Second, we examine the nature of the variance risk premium and shed light on the information content of different parts of the risk neutral distribution of the stock price, by using a model-independent approach based on corridor measures. To this end we compute both realised and model-free variance measures which accounts for drops versus increases in the underlying asset price. The comparison is pursued by using intra-daily synchronous prices between the options and the underlying asset.

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Bibliographic Info

Paper provided by Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi" in its series Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) with number 11112.

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Length: pages 36
Date of creation: Nov 2011
Date of revision:
Handle: RePEc:mod:wcefin:11112

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Keywords: corridor implied volatility; variance swap; corridor variance swap; variance risk;

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  1. Tim Bollerslev & Hao Zhou, 2007. "Expected Stock Returns and Variance Risk Premia," CREATES Research Papers 2007-17, School of Economics and Management, University of Aarhus.
  2. S. Muzzioli, 2010. "Option-based forecasts of volatility: an empirical study in the DAX-index options market," The European Journal of Finance, Taylor & Francis Journals, vol. 16(6), pages 561-586.
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  4. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
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Cited by:
  1. Chiara Pederzoli & Costanza Torricelli, 2013. "Efficiency and unbiasedness of corn futures markets: New evidence across the financial crisis," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 13091, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".
  2. Stefano Cosma & Elisabetta Gualandri, 2013. "The sovereign debt crisis: the impact on the intermediation model of Italian banks," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 13102, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".
  3. Elisabetta Gualandri & Valeria Venturelli, 2013. "The financing of Italian firms and the credit crunch: findings and exit strategies," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 13101, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".

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