UK Small & Mid Cap Equity
Montanaro UK Smaller Companies Investment Trust
Last updated: 2026-09-03
The Verdict
Montanaro UK Smaller Companies Investment Trust charges an expense ratio of 1.01%. On a $100,000 portfolio, that's $1,010 per year in fees, and it scales with the amount invested. Supreme.PM's decoded model tracked it at 95% correlation, for a flat monthly subscription that does not change with portfolio size.
Expense Ratio
1.01%
Star Rating
3/ 5
Market Beta
1.41
Model Correlation
95%
Sharpe Ratio
-0.05
Max Drawdown
50.49%
Supreme.PM Cost
Flat monthly subscription
Not a percentage of your assets
Performance
Performance comparison — 1Y: Fund 7.7% vs Model 7.2%; 3Y: Fund 25.2% vs Model 26.4%; 5Y: Fund -15.3% vs Model -4.7%.
Alpha After Fees
Supreme.PM's model achieves 95% correlation with Montanaro UK Smaller Companies Investment Trust, providing similar exposure at a flat subscription cost.
Fee Analysis
Montanaro UK Smaller Companies Investment Trust charges 1.01% of assets annually. Supreme.PM charges a flat monthly subscription instead, so its cost does not rise as a portfolio grows.
Data sources: Refinitiv Lipper, SEC EDGAR Filings, Supreme.PM Analytics
Past performance does not guarantee future results. Model returns are backtested and may not reflect actual trading conditions.
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Our Methodology
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Frequently Asked Questions
What is the expense ratio of Montanaro UK Smaller Companies Investment Trust?
Montanaro UK Smaller Companies Investment Trust has an expense ratio of 1.01%, charged as a percentage of the amount invested. Supreme.PM's decoded model is offered for a flat monthly subscription instead.
How does Supreme.PM replicate Montanaro UK Smaller Companies Investment Trust?
Supreme.PM builds a transparent, rules-based model of listed securities designed to track this fund's return profile. Over the measured period it tracked the fund closely, at 95% correlation. The model is published in full, so its positions are visible rather than disclosed with a delay.
What are the risks of fund replication?
While our models aim for high correlation, they may not perfectly match the fund's returns due to timing differences in rebalancing, transaction costs, and disclosure delays. Backtested results may not reflect future performance.
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