Abstract
Many institutional traders split large orders into smaller orders sent over some time period. This schedule may be optimized to reduce price impact. I have developed performance metrics to assess how effective funds are at (i) executing these smaller orders, (ii) deciding when to wait for orders to be filled (i.e. market timing), and (iii) scheduling the smaller orders. The performance metrics have sound theoretical backing and let us separate trading-related performance from noise. I propose to use data on orders and trades for a selection of investment funds to characterize these skills. For the initial work, I will study: (i) the relative magnitudes of these skills, (ii) how these skills vary across funds, (iii) what fraction of firms seem to possess superior trading-related skills, (iv) how firms’ skills change over time due to learning, and (v) the savings in transactions costs which accrue to investors. For possible further work, I suspect this data would help answer further questions including: (vi) how firms’ trading-related performance changes with macroeconomic factors, (vii) whether changes in trading-related skills result in fund inflows, (viii) the value of these inflows to the funds.