Computational Economics

, Volume 41, Issue 3, pp 359–386 | Cite as

The Forecasting Performance of Corridor Implied Volatility in the Italian Market



Corridor implied volatility introduced in Carr and Madan (Volatility: new estimation techniques for pricing derivatives, 1998) and recently implemented in Andersen and Bondarenko (Volatility as an asset class, 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 barrier levels, which are likely to 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 to 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 (CEFIN working paper no 23, 2010b). Moreover, we 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 realized and model-free variance measures accounting for both falls and increases in the underlying asset price. The forecasting performance of volatility measures is evaluated both in a statistical and an economic setting. The economic significance is assessed by employing trading strategies based on delta-neutral straddles. The comparison is pursued by using intra-day synchronous prices between the options and the underlying asset.


Corridor implied volatility Model-free implied volatility Variance swap Corridor variance swap 

JEL Classification

G13 G14 


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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Department of Economics and CEFINUniversity of Modena and Reggio EmiliaModenaItaly

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