We identify a strong presence of sentiment exposure in commodity futures returns. Sentiment is able to provide additional explanatory power for comovement among commodity futures beyond the macro-and equity-related sources. Commodity futures with low open interest growth, high volatilities, low momentum, or low futures basis are more sensitive to change in sentiment. Similar to Baker and Wurgler (2006), we construct a market sentiment index by Partial Least Squares regressions (PLS) with non-return based stock market proxies, in particular higher moments of the option implied return distribution. Moreover, our sentiment index can be built on a daily basis.

This paper proposes a new copula-based approach to test for asymmetries in the dependence structure of financial time series. Simply splitting observations into subsamples and comparing conditional correlations leads to spurious results due to the well-known conditioning bias. Our suggested framework is able to circumvent these problems. Applying our test to market data, we statistically confirm the widespread notion of significant asymmetric dependence structures between daily changes of the VIX, VXN, VDAXnew, and VSTOXX volatility indices and their corresponding equity index returns. A maximum likelihood method is used to perform a likelihood ratio test between the ordinary t-copula and its asymmetric extension. To the best of our knowledge, our study is the first empirical implementation of the skewed t-copula to generate meta skewed student t-distributions. Its asymmetry leads to significant improvements in the description of the dependence structure between equity returns and implied volatility changes.

Using a complete sample of US equity options, we find a positive, highly significant relation between stock returns and lagged implied volatilities. The results are robust after controlling for a number of factors such as firm size, market value, analyst recommendations and different levels of implied volatility. Lagged historical volatility is-in contrast to the corresponding implied volatility-not relevant for stock returns. We find considerable time variation in the relation between lagged implied volatility and stock returns.

This article proposes a new copula-based approach to test for asymmetries in the dependence structure of financial time series. Simply splitting observations into subsamples and comparing conditional correlations lead to spurious results due to the well-known conditioning bias. Our suggested framework is able to circumvent these problems. Applying our test to market data, we statistically confirm the widespread notion of significant asymmetric dependence structures between daily changes of the VIX, VXN, VDAXnew, and VSTOXX volatility indices and their corresponding equity index returns. A maximum likelihood method is used to perform a likelihood ratio test between the ordinary t-copula and its asymmetric extension. To the best of our knowledge, our study is the first empirical implementation of the skewed t-copula to generate meta-skewed Student's t-distributions. Its asymmetry leads to significant improvements in the description of the dependence structure between equity returns and implied volatility changes.copulae, asymmetric dependence concepts,