Why I Stopped Relying on Fund Managers (And What I Do Instead)
- Alpesh Patel
- 2 days ago
- 6 min read
Updated: 2 days ago
I spent years watching clients pay talented, well-credentialed fund managers to deliver less than the index they were supposed to beat. This is not a fringe observation. It is the central finding of 25 years of systematic performance data.
The S&P Indices Versus Active (SPIVA) UK Scorecard is the most comprehensive independent analysis of active fund manager performance. Its 2024 findings: over a 10-year period, 87% of actively managed UK equity funds underperformed their benchmark index. Over 15 years, the figure is higher still. This is not because most fund managers are incompetent. It is because the structural economics of active management make consistent outperformance mathematically improbable for the vast majority of participants.
I stopped relying on fund managers for my clients’ pension and investment portfolios not because I stopped respecting the profession — I was part of it — but because the data made the alternative impossible to ignore.
Alpesh Patel OBE is a hedge fund manager, Bloomberg TV alumnus, Financial Times author, and former Visiting Fellow at Corpus Christi College, Oxford. The Great Investments Programme is the systematic, quantitative alternative to fund manager dependency he built from this conviction.
The Data: What Active Fund Managers Actually Deliver
The SPIVA UK Scorecard, published twice yearly by S&P Dow Jones Indices, is the authoritative reference. Its methodology is rigorous: it accounts for survivorship bias — the tendency to ignore funds that closed or merged — which itself inflates the apparent performance of the active management industry. When closed and merged funds are included, active fund performance looks considerably worse than what is typically cited.
The key findings from SPIVA UK 2024, across all periods:
Over 1 year: approximately 55–60% of UK active equity funds underperform their benchmark. Even over short periods where luck can play a significant role, the majority underperform.
Over 5 years: approximately 75–80% underperform.
Over 10 years: approximately 87% underperform.
Over 15 years: approximately 90–92% underperform. The longer the horizon, the more pronounced the underperformance of active management.
The DALBAR Quantitative Analysis of Investor Behaviour adds another dimension: the average fund investor performs materially worse than the average fund itself, because they buy after performance and sell during drawdowns. The combination of fund underperformance and investor timing error is the single largest destroyer of wealth in the UK retail investment market.
Why Active Managers Structurally Cannot Win
The active management industry’s chronic underperformance is not primarily a talent problem. It is a structural one. There are four structural forces that make consistent active outperformance improbable for most managers over most time horizons.
1. The Cost Drag is Permanent and Compounding
The average UK active equity fund charges approximately 0.75–1.0% per year in ongoing charges. A comparable index tracker charges 0.07–0.20%. The active manager starts every year needing to outperform the index by 0.7–0.9 percentage points just to break even on cost, before delivering any value to the investor. Over 20 years on a £200,000 portfolio, a 0.85% annual cost drag — compounded — is worth approximately £140,000 in foregone capital.
2. Size Is the Enemy of Alpha
When a fund has £500 million or £1 billion under management, it cannot take meaningful positions in smaller, more inefficiently priced companies where genuine alpha opportunities exist. A £1 billion fund cannot hold a 2% position in a £200 million company without moving the market against itself. This forces large active funds into the same large-cap, well-researched stocks as their benchmark — where outperforming the collective wisdom of thousands of professional analysts is extremely difficult. Funds that genuinely outperform when small typically close to new investors or become closet indexers as they grow.
3. Career Risk Produces Benchmark Hugging
A fund manager who significantly diverges from the benchmark to make high-conviction bets takes enormous career risk. If the bets fail, they lose their job. If the bets succeed, the institution typically captures most of the benefit. The rational response from the manager’s personal financial perspective is to broadly mirror the benchmark while taking enough selective positions to justify the active fee. This produces what Morningstar calls ‘closet indexing’: funds that charge active fees while delivering benchmark-like performance before costs, and below-benchmark performance after them.
4. Past Performance Is Genuinely Not Predictive
Standard & Poor’s Persistence Scorecard which tracks whether top-quartile funds remain top-quartile in subsequent periods consistently shows that top-quartile performance in one period has essentially no predictive power for the next. Investors who chase the best-performing fund of the previous three years are, on average, buying peak momentum and locking in future underperformance. The manager who outperformed in the last bull market did so partly through stock selection and partly through luck, in a macro environment that no longer exists.
What I Do Instead: The Quantitative Framework
The GIP framework does not attempt to compete with active fund managers on their own terms finding the next undiscovered story, timing the macro cycle, rotating between sectors. Instead, it applies a systematic, rules-based quantitative screen to a universe of 8,000 publicly listed stocks every week, identifying the 40–50 that simultaneously pass five objective criteria:
CROCI above 10%: the business genuinely generates cash on its invested capital.
PEG below 1.0: the stock is not overvalued relative to its growth rate.
Sortino above 1.0: returns adequately compensate for downside volatility.
Sharpe ratio: total risk-adjusted return is strong.
Calmar ratio: returns adequately compensate for maximum historical drawdown.
The system removes the human judgment that is the active manager’s primary value proposition — and simultaneously their primary source of inconsistency. It does not have career risk. It does not get excited about a compelling narrative. It does not panic during a market correction. It runs the same five screens every week and produces the same output: a list of stocks that pass all five criteria, reviewed quarterly.
The Compounding Case: What the Gap Looks Like Over 20 Years
Take a £200,000 SIPP over 20 years:
Average active UK fund (7% net after charges): grows to approximately £773,000
Low-cost index tracker (9.5% net): grows to approximately £1,272,000
GIP self-directed SIPP (13% net): grows to approximately £1,918,000
The gap between an average active fund and the GIP framework on £200,000 over 20 years is approximately £1,145,000. The gap between an active fund and a simple low-cost tracker is £499,000 — that is the cost of paying for management that consistently fails to add value. Run your own numbers at campaignforamillion.com/tools.
The Honest Caveat: Why Some Active Management Still Has a Role
I am not arguing that all active management is worthless or that no manager ever adds value. There are genuine exceptions: specialist managers in small-cap markets, emerging markets, or alternative asset classes where information asymmetry is real and markets are genuinely less efficient. A handful of managers — Fundsmith, Scottish Mortgage historically, Terry Smith’s approach — have demonstrated sustained long-run outperformance through concentrated, conviction-based approaches that are closer in spirit to quantitative quality investing than traditional active management.
The argument is not ‘never use active managers’. It is: ‘most active managers in large-cap developed market equities, over most time horizons, after fees, underperform the index — and the few that outperform cannot reliably be identified in advance’. For the majority of SIPP and ISA investors whose pension assets are sitting in default multi-asset managed funds from Prudential, Royal London, Aviva, or L&G, switching to a systematic approach is not a radical act. It is the mathematically rational one.
If you are currently holding pension assets in actively managed funds and want to understand what a systematic quantitative approach would look like applied to your specific portfolio, book a free portfolio review here.
Sources & Further Reading
S&P Dow Jones Indices — SPIVA UK Scorecard (2024). The definitive analysis of active fund manager performance vs benchmark, accounting for survivorship bias. spglobal.com/spdji/en/research-insights/spiva
S&P Dow Jones Indices — Persistence Scorecard. Analysis of whether top-quartile fund performance repeats across periods. spglobal.com/spdji/en/research-insights/spiva
DALBAR — Quantitative Analysis of Investor Behaviour (QAIB). Annual study of investor returns vs fund returns, documenting the cost of timing errors. dalbar.com
Fama, E. & French, K. (2010) — ‘Luck versus Skill in the Cross-Section of Mutual Fund Returns’. Journal of Finance. Foundational academic research on active manager skill vs luck. onlinelibrary.wiley.com
AQR Capital Management — Research on factor investing, active management, and the cost of alpha. aqr.com/insights/research
Financial Times — Active vs passive fund management, closet indexing, and UK fund performance. ft.com/investing
Disclaimer: This article is for educational purposes only. Past performance is not a reliable indicator of future results. All investing carries risk. This does not constitute personal financial guidance or a recommendation to switch any investment.
Alpesh Patel OBE
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