Why Compare Mutual Fund Holdings?
Comparing the holdings of different mutual funds can help investors make better portfolio decisions. Here’s why it matters:
- Diversification: By analyzing fund holdings, you can spot overlapping investments and avoid unnecessary duplication, helping you build a more balanced portfolio.
- Risk Management: Understanding a fund’s underlying assets allows you to assess its risk level and make more informed investment choices.
- Performance Insights: Identifying key holdings helps you understand what drives a fund’s performance, making it easier to choose the best options.
- Cost Efficiency: Some funds have similar investment objectives but different expense ratios. Comparing holdings helps you find cost-effective alternatives.
What We Built
We created a tool that compares the holdings of multiple mutual funds to measure their similarity. Using cosine distance, we analyze how much two funds overlap and display the results in a table. The underlying data was queried and filtered with our SECeek platform. Try SECeek for yourself.
How Cosine Distance Works
Cosine distance is a statistical method to numerically score the similarity of two sets. The cosine distance values range from 0 (no common holdings) to 1 (identical holdings). Here are a couple of examples:
- If two funds each have 10 holdings and share 5 of them, the cosine distance is 0.5.
- If one fund’s holdings are a subset of another but contain half as many elements, the distance is 0.707.
Understanding the Results
Comparing Funds from the Same Company (Invesco)
The table below shows the similarity of each pair of funds. Column headers are omitted to simplify the table. The (omitted) column headers correspond to the row headers such that the heading for the first column is the same as the first row, second column heading is the same as the second row, and so on.
The diagonal values are always 1.000 (since a fund is identical to itself). The table is symmetrical because distance is commutative (i.e., comparing A to B is the same as comparing B to A). The darker the color the greater similarity between funds.
The most similar two funds in this dataset have a similarity of 0.250 (both have 24 holdings, with 6 in common). No distances are 1.000, meaning no funds are identical. Similarly, no distances are 0.000, so all fund pairs have at least one common holding.
This result is to be expected since the funds from the same company are likely to exist for different objectives. An interesting follow-on question is “Which holding(s) appears in the most funds?” to understand the common ‘staples’ between the funds.
Comparing Funds from Different Companies
This table highlights stronger similarities between funds from different companies specializing in large cap growth. There is remarkable similarity between these funds. None of the values are zero, so there is always some overlap between the holdings of any two of these large cap growth funds. The most similar two funds, at 0.577, are Putnam Large Cap Growth Fund and Allspring Large Cap Growth Fund, which have 48 and 36 holdings, respectively, with 24 holdings in common.
By using this tool, investors can quickly assess how much funds overlap and make better-informed investment decisions.
Comparing One Fund Over Time
An interesting analysis is to compare the same fund over a series of reporting periods. This will allow an analyst to quickly determine how little or much a fund has been changing over time.
The following table shows the similarity between the same fund (Putnam Ultra Short MAC Series) over six quarters.
Values adjacent to the main diagonal show the similarity from one quarter to the next. Unsurprisingly, the similarity is high but not identical. Also, similarity between quarters is decreasing (ie, more change in holdings) as the funds ages.
Summary: Unlocking Investment Insights with Fund Similarity Analytics
Understanding mutual fund holdings is crucial for making smarter investment decisions, and our Fund Similarity Analytics tool provides a new way to compare and analyze funds efficiently. By leveraging cosine distance, investors can:
- Identify Overlap & Diversification Gaps – Avoid redundancy and build a more balanced portfolio.
- Manage Risk Effectively – Gain a deeper understanding of a fund’s underlying assets.
- Uncover Performance Drivers – See what’s influencing returns across different funds.
- Optimize Cost Efficiency – Compare funds with similar objectives but different expense ratios.
Our analysis reveals valuable insights, such as the nuanced differences between highly similar funds and unexpected commonalities between seemingly distinct funds. Additionally, tracking a single fund over time uncovers how its composition evolves across reporting periods.
With Fund Similarity Analytics, investors can make data-driven decisions with confidence—spotting hidden trends, improving diversification, and optimizing fund selection for long-term success.