What is a Lipper Index?
Lipper indices, produced by Lipper, a subsidiary of Thomson Reuters, are a set of benchmarking tools used to track the performance of a portfolio or of various mutual funds.
There are more than 400 Lipper classifications which investors use to compare funds with similar investment mandates to benchmark fund performance.
Lipper Indices are composed of the top 15 to 30 funds for each category. Lipper includes mutual funds, closed-end funds, ETFs, hedge funds, retirement and pension funds, and insurance products.
According to Thomson Reuters, the indices are “designed to be usefully employed as a good representation of the combined peer group performance and thus act as relevant benchmarks to measure single fund manager performance and rankings within that peer group”.
The 2015 Thomson Reuters Lipper Indices Methodology Document says:
“Thomson Reuters Lipper Indices are indicators of the average performance of funds in different Lipper peer groups over time. A particular fund can have different peer groups over time and therefore contributes to different Lipper indices at different times. A fund could have contributed to an index historically even it is no longer active (liquidated or merged). A Lipper index tells us what performance you would get if you were to invest passively in a portfolio of funds in a certain peer group according to the Lipper Index methodology. Lipper indices are better indicators of a peer group’s performance over time.
“Lipper averages reflect the average performance of the active funds in a particular peer group at the time of calculation. No matter what peer groups a fund had before, the fund contributes the same Lipper average over time. Inactive funds at the time of calculation are excluded fromthe Lipper averages. Lipper averages could be different when calculated at different times,even when the performance period is the same. Lipper averages are more appropriate for peer group comparisons at a point of a time. It is possible to calculate rolling sub-period Lipper averagesto generate a return time series for statistical analysis.”