Evaluating Metrics for Fund Selection – III

What works, what doesn’t?

March 2026. Reading Time: 10 Minutes. Author: Nicolas Rabener.

SUMMARY

  • Combining metrics for fund selection has merit
  • Investors can identify which funds will likely outperform
  • However, this is better viewed as a risk management system

INTRODUCTION

Selecting stocks based on a single metric – such as low valuations or past outperformance – can be a rational strategy, but it often tests investors’ patience. Individual factors may underperform for years, even decades, before eventually rebounding. Because of this, many investors choose to combine multiple factors, aiming for slightly lower but more stable returns. For instance, while cheap stocks are broadly appealing, investors tend to favor those that also exhibit strong quality characteristics rather than those that do not.

In a recent research report on fund selection, we found that commonly used metrics such as past outperformance and Sharpe ratios have little predictive power for future performance, except for low expense ratios (see Evaluating Metrics for Fund Selection – II). However, similar to factor investing, combining several metrics may still offer advantages when selecting funds – a possibility we explore further in this article.

METHODOLOGY

We consider all mutual funds and ETFs trading in the U.S. market between 2000 and 2025, including both currently active and liquidated funds, to avoid survivorship bias. From an initial universe of roughly 50,000 funds, we exclude multiple share classes and funds employing leveraged, short, volatility, or option-based strategies, resulting in a final sample of approximately 11,000 funds.

Our analysis uses a universe of 45 benchmark indices spanning equities, fixed income, multi-asset, and commodities. Each fund is assigned a benchmark using our standard methodology, which evaluates the ratio of tracking error to correlation. At the end of each financial year, we rank funds within each benchmark category by percentiles across several metrics: excess return, excess Sharpe ratio, information ratio, consistent outperformance, factor alpha, R² relative to the benchmark, and total expense ratio.

We calculate thes