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How Factors, Screens, and Systems Can Improve Your Odds of Beating the Market

Updated: Jan 10

Insights from a Stockopedia Study on Quality, Value, and Momentum

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This article breaks down a Stockopedia study exploring how investors can improve their chances of beating the market using factors, screens, and systematic processes. We examine why most active fund managers fail, how factor investing has historically outperformed benchmarks, and why combining quality with other factors dramatically improves results. The key takeaway is clear: removing discretion, tightening filters, and focusing on quality and momentum shifts the odds decisively in the investor’s favour.

Introduction


In today’s video, we discuss an insightful study conducted by Stockopedia, titled:

“Fine-tuning your strategy using factors, screens, and systems to improve the odds of beating the market.”


Markets have become increasingly efficient over time, making consistent outperformance extremely difficult. The evidence is stark:


  • Over 77% of actively managed UK funds failed to beat their benchmarks over the last decade

  • More than 95% globally underperformed

  • In the US, over 90% of active managers failed across a 20-year period


animation images from video

What makes this particularly sobering is that these results come from institutions with enormous resources elite analysts, privileged access, and vast data capabilities yet outcomes remain poor, often after charging significant fees.


Ironically, this inefficiency at the professional level creates an opportunity for individual investors, who are nimbler, unconstrained, and able to focus on smaller, higher-return opportunities.


Ark fund performance chart
ARK Fund performance

Why Factors Matter More Than Discretion


Rather than relying heavily on judgement and discretion, Stockopedia argues that investors are far better served by adopting a factor-based philosophy.


Factors narrow the investable universe by focusing on characteristics that markets have historically rewarded. This approach removes emotional bias and replaces it with statistical edge.

Factor Performance Over 30 Years (US Markets)


Looking at US data through to 2021:


  • Momentum was the clear outperformer

  • Quality ranked second

  • Value lagged but still beat the S&P 500


A $10,000 investment grew to:


  • Nearly $900,000 in the momentum portfolio

  • Around $500,000 in the quality portfolio


fama and french equity chart

This aligns perfectly with my own long-term findings:👉 Quality and momentum drive returns

Why Screens Are Essential


Factors alone often produce too many stocks for individual investors to analyse effectively. This is where screening systems become invaluable.


Stockopedia demonstrated this with a Buffett-style screen applied to UK stocks.



  • The screened portfolio delivered a 1000× return

  • Berkshire Hathaway’s public portfolio delivered ~100×


stock chart

This does not suggest Buffett is wrong rather, Berkshire’s scale restricts its investable universe. As individual investors, we don’t have that limitation.

The lesson is powerful:

Small investors can outperform legends by using disciplined screens

The Problem With Picking a Single Screen


At inception, selecting which screen to trust is difficult. Markets rotate:


  • UK markets historically favoured quality and value

  • US markets favoured growth and momentum


No investor could have predicted this divergence ahead of time.


This introduces a behavioural problem: Different personalities choose different factors:


  • Patient → value

  • Defensive → quality

  • Aggressive → growth


Without structure, portfolio construction becomes subjective, inconsistent, and outcome-dependent.

The Random Portfolio Experiment (UK Stocks)


To explore this further, Stockopedia ran a revealing simulation.


The Setup:


  • Loose screens for quality, value, and growth

  • Large stock pools generated

  • An algorithm randomly selected 20 stocks

  • Portfolio rebalanced annually

  • Process repeated for 8 years

  • Simulations run hundreds and then thousands of times


The Results:


stock chart trend
Study Returns
  • Average return: ~40%

  • Individual outcomes varied wildly:

    • Some portfolios negative

    • Others returned nearly 300%

  • Even after 10,000 runs, most outcomes clustered below 60%, with occasional extreme outliers


This highlights a crucial truth:

Loose rules + discretion = unpredictable outcomes

Which Factor Actually Worked?


When results were analysed by factor:


Median Performance:


  • Quality: +41% (clear winner)

  • Value: Slight underperformance vs benchmark

  • Growth: –3% (significant underperformance)


Downside Risk:


  • Quality worst case: –31%

  • Value worst case: –40%

  • Growth worst case: –61%


Probability of Loss:


  • Quality: 4%

  • Value: 17%

  • Growth: 55%


Quality clearly delivered:


  • Higher median returns

  • Lower downside

  • Much lower probability of loss


animation image

Combining Factors: Where the Magic Happens


The most important insight from the study came next.


When quality metrics were added to:


  • Value screens → results improved meaningfully

  • Growth screens → performance transformed

Growth + Quality:


  • Median return jumped from –3% to +50%

  • Outperformed pure quality by 9 percentage points


The conclusion is unavoidable:

Loose growth filters fail — growth + quality thrives

Tighter filters also naturally reduce stock count, making analysis more practical and consistent.

Why Discretion Still Hurts Results


man with question marks around his head

Most investors don’t mechanically buy everything a screen produces. As soon as human judgement is introduced:


  • Bias creeps in

  • Outcomes diverge

  • Consistency disappears


Two investors using the same screen can build completely different portfolios.

This is why the real edge lies in:


  • Letting screens do the heavy lifting

  • Building a repeatable process

  • Reducing discretion wherever possible

Stockopedia’s StockRank System


To simplify this, Stockopedia created StockRank, a composite ranking system built around:


line diagram
Key Factors

Quality Rank


  • 9 financial ratios

  • Scores from 1–99

  • Top decile easily filtered (e.g. Quality > 90)


Value Rank

  • 6 ratios

  • Earnings, assets, income metrics


Momentum Rank

  • 9 ratios

  • Price and earnings momentum combined


Instead of juggling dozens of filters, investors can:


  • Select factor ranks

  • Combine factors easily

  • Focus on the strongest candidates quickly

Case Study 1: Plus500 (Quality + Value Winner)


Stockopedia Screen
Stockopedia Screen

In 2017, Plus500 ranked:


  • Quality: 95

  • Value: 89


Key strengths:


  • Strong return metrics

  • High Piotroski F-Score

  • EPS growth:

    • 65.8% over 6 years

    • 78% over 3 years

  • Consistent margin strength

  • Regular earnings beats

  • £509m in buybacks since 2017


The stock more than doubled within a year, validating the factor signals.

Case Study 2: Kier Group (Value Trap)


Kier ranked highly on value, but failed everywhere else.


Key red flags:

crashing stock chart

  • Weak quality

  • Falling price momentum

  • Liquidity stress

  • Rising debt

  • Share dilution

  • CEO resignation

  • Industry peers collapsing


The stock fell from £9 to under 50p.


A textbook example of why:

Cheap can always get cheaper

Final Thoughts


This study reinforces a critical lesson:


  • Factors work

  • Screens improve consistency

  • Quality matters most

  • Combining factors improves outcomes

  • Discretion introduces risk

  • Process beats prediction


No system captures every winner, but a disciplined framework dramatically improves long-term odds.


If you follow a solid process and apply it consistently, short-term volatility becomes irrelevant.


video image showing 3 projector screens
Video Image

Frequently Asked Questions (FAQs)


Why do most active fund managers fail? Because fees, size constraints, discretion, and behavioural bias erode returns over time.


Which factor performed best in the study? Quality delivered the highest median returns with the lowest downside risk.


Is growth investing broken? No—but loose growth filters fail. Growth combined with quality performs well.


Why are screens better than discretionary stock picking? Screens remove emotion, bias, and inconsistency while improving repeatability.


Can individual investors really beat institutions? Yes—because individuals are unconstrained, flexible, and can exploit inefficiencies.


Do I need Stockopedia to apply this approach? No—but tools like StockRank significantly reduce complexity and save time.

For those interested in a 25% discount on Stockopedia, use the link below:👉 https://bit.ly/2YIcAIn

For traders who prefer combining fundamental quality with breakout timing, we also offer bespoke scanning software focused on quality stocks breaking out of consolidation.


breakout screener screenshot
FW Breakout Screener

Related Reading


Published by FinancialWisdomTV.com Rules-Based Trading | Quality & Momentum | Probability-Driven Execution


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