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论坛 数据科学与人工智能 数据分析与数据科学 MATLAB等数学软件专版
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2016-01-21








We introduce a new form of volatility index, the cross-sectional volatility index. Through
formal central limit arguments, we show that the cross-sectional dispersion of stock
returns can be regarded as an efficient estimator for the average idiosyncratic volatility of
stocks within the universe under consideration. Among the key advantages of the crosssectional
volatility index measure over currently available measures are its observability at
any frequency, its model-free nature, and its availability for every region, sector, and style
of the world equity markets, without the need to resort to any auxiliary option market.
We also provide some interpretation of the cross-sectional volatility index as a proxy for
aggregate economic uncertainty, which suggests that the cross-sectional volatility index should
be intimately related to option-based implied volatility measures. We confirm this intuition
by reporting high correlation between the VIX index and the corresponding cross-sectional
volatility index based on the S&P500 universe. We also find the high correlation between the
two volatility measures to be robust with respect to changes in sample period, changes in market
conditions, and changes in the region under consideration. Overall, these results suggest that the
cross-sectional volatility index is intimately related to other volatility measures where and when
such measures are available, and that it can be used as a reliable proxy for volatility when such
measures are not available.
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