An improved model-free implied variation index (AVIX) is proposed in this article. The AVIX is developed under a generalized semi-martingale process with stochastic interest rates. An adaptive option screening mechanism is proposed to accommodate different market conditions. The effect of dividend protection is also considered. An empirical study of the China 50 ETF option market suggests that the AVIX is a better barometer of aggregate implied variation and investor sentiment than the traditional VIX. It reacts to market changes more rapidly and more sensitively. The AVIX also contains more information about future volatility and provides a more efficient forecast of future realized volatility.

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Purpose -The purpose of this paper is to study how the market correlation changes in Chinese stock market and how the market correlation affects stock returns. Design/methodology/approach -The authors first examine the relationship between the market correlation and the market return. Then, the authors run formal multiple regressions to see whether correlation risk is priced in security returns. Findings -The authors find that market correlation increases when the market index falls down. Though market correlation risk is partly influenced by macroeconomic shocks, volatility risk, liquidity risk and higher moment risk, market correlation contains unique information that measures the benefit investors gain from diversification strategies. The market correlation risk is negatively priced. This conclusion remains valid even if the authors have considered the influence of other risk factors and the impact of conditional information. Research limitations/implications -Subjected to the limited history of the Chinese stock market, the authors cannot use more accurate and specific empirical methodology to fulfill the empirical research. And this renders further study. Originality/value -This research provides empirical evidence in a new data sample and it sheds lights on correlation strategies for institutional investors in China.