This paper assesses the economic value of modeling conditional correlations for mean–variance portfolio optimization. Using sector returns in three major markets we show that the predictability of models describing empirical regularities in correlations such as time-variation, asymmetry and structural breaks leads to significant performance gains over the static covariance strategy. Investors would be willing to pay a fee of up to 983 basis points to switch from the static to the dynamic correlation portfolio and about 100 basis points more for capturing asymmetries and shifts in correlations. The gains are robust to the crisis, transaction costs and are most pronounced for monthly rebalancing.

Using a sample of Chinese Initial Public Offerings (IPOs) from 2006 to 2011, we document that politically connected (PC) underwriters increase the likelihood of clients’ IPO applications being approved by the Chinese Securities Regulatory Commission (CSRC). We further show that PC underwriters charge premium underwriting fees. Consistent with the rent-seeking argument, we find that minority shareholders’ interests may be impaired as indicated by post-IPO underperformance. We do not detect significant differences in the underpricing of IPO deals underwritten by PC versus non-PC investment banks.