We examine the relative weights hedge fund investors attach to past information in the fund selection process. The weighting scheme appears inconsistent with econometric forecasting models that predict fund returns, alphas or Sharpe ratios. In particular, investor flows are highly sensitive to performance streaks despite their limited predictive power regarding fund performance. Further, allocations based on forecast models' out-of-sample predictions beat investor allocations by a significant margin, which suggests that the latter are suboptimal and reflect overreaction to certain types of information. Our findings do not support the notion that sophisticated investors have superior information or superior information processing abilities.
hedge funds money flows extrapolative expectations law of small numbers performance streaks relative weights smart money