How Factors, Screens, and Systems Can Improve Your Odds of Beating the Market
Updated: 23 hours ago
How Factors, Screens, and Systems Can Improve Your provides a useful framework for turning market observations into repeatable trading decisions. This updated guide preserves the original Financial Wisdom material while adding clearer rules, evidence checks and risk controls.
Beating The Market: In This Guide
Key lessons and practical rules
The original Financial Wisdom guide and media
Evidence, limitations and risk controls
Frequently asked questions
Related guides and authoritative sources
Key Takeaways
Define the setup, trigger and invalidation level before entering.
Confirm signals with price, volume and the wider market context.
Test complete rules across different regimes and include trading costs.
Size every trade so one failed setup cannot materially damage the account.
Original Financial Wisdom Guide
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
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.
Practical Checkpoint
Define the setup, entry and invalidation level before acting.
Compare the potential payoff with risk-reward planning.
Set the trade size using consistent position-sizing rules.
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
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.
When backtested:
Evidence Check
Is the sample broad enough to include difficult markets?
Do the results include spreads, fees, slippage and failed signals?
Could hindsight, survivorship or selective examples explain the result?
The screened portfolio delivered a 1000× return
Berkshire Hathaway’s public portfolio delivered ~100×
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:
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
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
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:
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)
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:
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.
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.
Related Reading
Inside the Financial Wisdom Weekly Consolidation Breakout Framework
Risk Management in Trading: The Foundation of Long-Term Profitability
Published by FinancialWisdomTV.com Rules-Based Trading | Quality & Momentum | Probability-Driven Execution
Practical Limitations
Historical examples, interviews, backtests and indicator results are educational illustrations rather than forecasts. Outcomes depend on the market, timeframe, data, transaction costs, financing, taxes and execution assumptions. Test complete rules across varied conditions and define the maximum acceptable account risk before taking a position.
Put This Into Practice
These ideas become more useful when selection, entry, stop placement, position sizing and trade management form one repeatable process. The Financial Wisdom Trading Blueprint connects those decisions in a practical weekly framework.
Further Reading
References and Further Reading
Educational information only. Trading and investing involve risk, including the possible loss of capital. Examples are illustrative, not guarantees of future performance, and nothing in this article is personalised financial advice.
About the Author
Written by Gareth, MBA
Gareth, founder of Financial Wisdom, has more than 30 years of personal trading experience. He competes in the United States Investing Championship, creates award-winning trading content and has been featured in Technical Analysis of Stocks & Commodities.
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