Traits of the Best Bets & Why it Matters
Find the Best 1% of Stocks - Avoid the Worst
We rank 5,000 stocks using over 100 variables to identify the biggest winners and biggest risks
1. Earnings Estimate Revisions (Most Powerful Near-Term Signal) This is consistently the #1 short-to-medium term predictor: |
Stocks where sell-side analysts are rapidly revising estimates upward — especially when the revision is broad (multiple analysts, not just one)
The effect is strongest when revisions follow a positive earnings surprise that also beats on revenue
Academic research shows estimate revision momentum has a 1–3 month half-life but can persist 6–12 months in strong trending stocks
This is forward-looking, which is why it outperforms trailing metrics alone
2. Earnings Acceleration (Not Just Growth — Acceleration)
The top 1% aren't just growing — they're growing faster than they were growing before:
EPS growth of 25% is less predictive than EPS growth accelerating from 10% → 18% → 31%
The acceleration signal is most powerful when it coincides with revenue acceleration (not just margin expansion)
William O'Neil's CANSLIM research (studying every top 1% stock from 1880–2009) found that 71% of top performers showed EPS acceleration in the 3 quarters before their big move
3. Relative Price Strength / Momentum
Counterintuitive but one of the most robust findings in 100 years of data:
Stocks already in the top 10–20% of 12-month price performance are dramatically more likely to enter the top 1% than cheap, beaten-down stocks
The momentum factor has been documented in every developed market globally since the 1800s
This directly contradicts "buy low" intuition — the best stocks are usually already expensive by traditional metrics
The effect is strongest at the 3–12 month lookback window; reverses at 1 month (mean reversion) and beyond 3–5 years
4. Revenue Growth + Revenue Surprise
Often overlooked in favor of EPS, but revenue is harder to manipulate:
Top 1% performers show revenue growing at 20%+ annually in the 2–4 quarters before their big move
Revenue beats (actual vs. consensus estimate) are more predictive than EPS beats because they signal demand, not just cost-cutting
Small/mid cap stocks with revenue growing faster than their sector peers are disproportionately represented in the top 1%
5. Expanding Margins at Scale
This separates the durable top performers from the one-year wonders:
Gross margin expanding while revenue is also growing signals a business gaining pricing power or operating leverage
The combination of revenue acceleration + margin expansion + positive estimate revisions is sometimes called the "triple threat" — it shows up in roughly 60–70% of multi-year top performers
Pure deep value (cheap but shrinking margins) almost never produces top 1% returns
6. Institutional Accumulation
The smart money signal:
Stocks seeing rising institutional ownership — especially from high-quality funds with strong track records — tend to outperform
The signal is strongest when ownership is increasing from a low base (early accumulation phase), not when a stock is already widely held
13F filings, fund flow data, and unusual volume patterns all proxy this
Top 1% stocks frequently show volume 1.5–3x average during accumulation phases before the big move
7. Market Leadership in an Emerging Theme
The single biggest differentiator for truly spectacular returns:
The absolute top 1% in any given year are almost always #1 or #2 in an emerging industry theme: cloud computing, genomics, AI, EVs, cybersecurity
Being the leader (not a follower) in a nascent TAM expansion is the closest thing to a repeatable top 1% recipe
O'Neil's research found the leading stock in a new theme outperforms the #2 stock by an average of 3–5x over the same cycle
8. What Deep Value Does NOT Do
This surprises most investors:
Classic deep value (low P/E, low P/B, low EV/EBITDA) underperforms as a top 1% predictor
Value stocks occasionally produce massive returns but as a group they are far more likely to produce mediocre + volatile outcomes
The "value trap" — cheap because fundamentals are deteriorating — is heavily overrepresented in the bottom 1%
Pure value without growth, momentum, or estimate revision has been the weakest major factor since the mid-2000s, and especially post-2010
The Composite Portrait of a Top 1% Stock
Based on O'Neil, Greenblatt, Piotroski, Carhart, Fama-French 5-factor, and proprietary fund research, the typical top 1% performer looks like this before its big move:
Trait | Typical reading |
|---|---|
EPS growth (recent quarter) | +25% or more, accelerating |
Revenue growth | +20% or more |
Estimate revisions | Strongly positive, multiple analysts |
12-month price momentum | Top 20% of market |
Institutional ownership trend | Rising from low base |
Gross margin trend | Expanding |
Industry group rank | Top 10–20% |
Float / market cap | Often small-to-mid cap |
Narrative / theme | Leader in emerging sector |
The Regime Shift Factor
One thing that makes this hard: the dominant factor rotates by market regime:
Rate rising environments (2022): quality + value temporarily outperforms growth
Bull/expansion (2009–2021, 2023–present): momentum + growth + estimate revisions dominate
Recessions: defensive quality + free cash flow matter most
Early recovery: the most beaten-down high quality names (not junk) produce the biggest snapbacks
This is exactly why a 100-factor multi-regime model like your Oddsmaker has a structural edge — it can weight factors dynamically based on the current environment rather than being married to one style.
