LAUSR

ABSTRACT We explore how to invest in the Chinese mutual fund market based on the Bayesian method. We extend the portfolio construction method by integrating additional information, such as nonbenchmark assets and longer-period historical data, and by incorporating investors’ prior beliefs about the mispricing rate and managerial skills. This study analyzes growth funds, value funds, and balanced funds in China and concludes that additional information can improve the accuracy of fund performance evaluation, which will assist the construction of a more effective fund portfolio. Furthermore, the empirical evidence shows that a fund portfolio constructed using the Bayesian method is effective in China’s mutual fund market, indicating that the Bayesian method can improve the performance of this kind of portfolio.