Methodology

Last updated: 28 June 2026

This page explains where FundMonkey's data comes from, how the metrics are calculated, and what the known limitations are. It's for users who want to understand what they're looking at rather than just take the numbers on trust.

Fund universe

FundMonkey covers UK retail open-ended investment funds (OEICs and unit trusts) and UK-listed ETFs available through major retail investment platforms. The universe is refreshed periodically; the exact size at any point in time is shown in the funds-pane header (e.g. "of 5,988 funds").

The dataset is filtered to exclude duplicate share classes where multiple share classes track the same underlying portfolio. Where multiple share classes exist, FundMonkey typically retains the one with the most representative cost basis and broadest retail availability.

Data sources

Performance data

Cumulative percentage returns over standard periods (3 months, 6 months, 1 year, 3 years, 5 years) are sourced from third-party fund data providers and platform aggregators. These figures are typically reported on a total return basis (including reinvested distributions) in GBP, and may be net of ongoing fund charges depending on the source.

Holdings data

Top holdings (typically the top 10 disclosed positions for each fund) are sourced from fund factsheets and managers' periodic disclosures. Holdings disclosures are point-in-time snapshots and can lag the actual portfolio by weeks or months, depending on each fund's disclosure schedule.

Sector classifications

Funds are mapped to Investment Association (IA) sectors where available, supplemented by issuer-provided categorisations for funds outside the IA framework. Sector boundaries are not always crisp and a fund's classification may shift if its mandate changes.

Active share

Active share is a measure of how much a fund's holdings differ from its benchmark index. It runs from 0% (identical to the index) to 100% (no overlap with the index).

activeShare = (1/2) · Σ |wfund,i − wbench,i|

Where wfund,i is the fund's weight in stock i and wbench,i is the benchmark's weight in stock i, summed across the union of holdings in both portfolios.

On FundMonkey, active share is calculated from the disclosed top-holdings list against an appropriate benchmark proxy for each fund's stated mandate. Because we don't have access to the full holdings of every fund (most disclose only top 10), the figure is an approximation based on disclosed positions, not a regulatory-grade calculation. It is most reliable for concentrated funds where the top 10 captures a large share of the portfolio.

Funds where active share could not be reliably calculated (e.g. because of insufficient holdings disclosure or no comparable benchmark) are flagged accordingly.

Aggregate top holdings ("combined top holdings")

The pie-chart icon in the funds pane computes a combined top-10 across whatever funds are currently displayed. It uses two independent rankings:

Equal-weighted

Treats each displayed fund as an equal-sized slice. For each stock:

equalWeighted = (sum of stock's weight across all displayed funds) ÷ N

Where N is the number of displayed funds that have holdings data available. Funds that don't hold the stock count as 0%, dragging the average down — this is what you'd actually own if you put equal money into all displayed funds.

Prevalence

Counts how many displayed funds hold each stock at all, regardless of weight:

prevalencePct = (funds holding the stock) ÷ N × 100

For each stock, we also show the range of weights observed: the lowest and highest individual fund weight for that stock across all funds in the cohort. A narrow range (e.g. 2.5–3.8%) indicates consensus tracking; a wide range (e.g. 0.5–12.0%) suggests one or more funds have a concentrated conviction position.

Caveats

Head-to-Head sector comparison

Head-to-Head mode lets you compare the average sector allocation of two performance cohorts — for example, funds returning >7% in the last year versus those returning <0%. Sector weights for each cohort are computed by averaging individual fund sector exposures across all funds in that cohort, treating each fund as equally weighted.

Cumulative performance

All percentage returns shown are cumulative over the stated period (not annualised), expressed in GBP, and aim to be on a total return basis. The exact reporting basis (gross or net of fees, distribution treatment) follows the source data provider's convention.

"Negative" filtering (< 0%) finds funds with a negative cumulative return over the selected period.

Update cadence

Different data types update on different cycles:

Figures shown on FundMonkey should be treated as indicative, not real-time. For decision-grade data, always consult the relevant fund factsheet or KIID directly.

Known limitations

How to read the UI

Funds table

Each row is one fund. The columns show fund name, active share, and cumulative performance over 3m / 6m / 1y / 3y / 5y. Click any column header to sort. Hover any row to see the fund's top holdings.

Performance filter pills

The pills (>3%, >5%, >7%, etc.) filter the table to funds whose return over the currently selected period exceeds the threshold. "< 0%" shows funds with negative returns. "ALL" clears the filter.

Sector filters

Click any sector chip to filter the table to funds in that sector. Multi-select mode lets you build a multi-sector cohort.

Toolbar buttons

Source attribution and accuracy

FundMonkey is not a primary data source. We aggregate and present data sourced from fund providers and third-party data aggregators, and we apply derived calculations on top of it. We make reasonable efforts to ensure accuracy but errors are possible at any stage — in the source data, in our ingestion, or in our calculations.

If you spot a number that looks wrong, please tell us: info@fundmonkey.co.uk

Changes to this methodology

This methodology will evolve as the service grows. We will update this page when material changes are made; the "Last updated" date at the top reflects the most recent revision.