π What is this tool, in simple terms?
Imagine two friends, both runners. One runs the 100m in 12 seconds. Impressive β or is it? To judge fairly, you need to know: how much training do they do? Are they naturally fast? What's their age? Once you account for all those factors, you can see who's truly fast versus who just has natural advantages.
This tool does the same thing for stocks. Every stock has built-in "advantages" β being part of a rising market, being a small growth company, being cheap, or recently going up. We strip all of that away using a mathematical model called Fama-French. What's left over β the performance that can't be explained by those advantages β is called alpha. A stock with positive alpha is genuinely outperforming. A stock with negative alpha is underperforming even when you give it every benefit of the doubt.
π The 4 factors β what are they?
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Market (MKT)
When the whole stock market goes up, most stocks go up with it. A stock with a high Market score moves more than average when the market moves. We strip this out because rising with the market isn't skill β it's just being invested.
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Size (SMB β Small Minus Big)
Historically, smaller companies have outperformed larger ones over time. So if a small company is going up, some of that is just the "small company effect." We adjust for this. If SMB is negative, the stock is a large-cap β and that's already counted in.
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Value (HML β High Minus Low)
Cheap stocks (measured by book value vs price) have historically beaten expensive growth stocks. If a stock is doing well partly because it's cheap, the Value factor captures that. A negative HML score means it's a growth stock β which tends to have lower expected returns baked in.
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Momentum (MOM)
Stocks that have gone up in the past 6β12 months tend to keep going up in the near term. This is one of the most reliable patterns in markets. If a stock is riding a momentum wave, we factor that in too β because the model needs to know how much of today's return is just yesterday's trend continuing.
π¦ How to read the signals
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Strong (Green) β the model is saying this stock is genuinely outperforming
After accounting for all four factors, this stock is still delivering extra return. The number is statistically significant β meaning we're at least 95% confident this isn't just random luck. Think of it like a test score that's so high it can't be a fluke. These are the stocks worth researching further.
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Marginal (Amber) β positive but not conclusive
The alpha is positive β the stock appears to be doing better than its factors would predict β but the statistical confidence isn't high enough to call it definitive. There might be something there, but there might not. Good for a watchlist, not a buy list yet.
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Avoid (Red) β underperforming on a factor-adjusted basis
This stock is delivering less than what its factor exposures would predict. Even accounting for all the tailwinds it has, it's still falling short. A red signal doesn't mean the stock will definitely fall β but it means there's no evidence of genuine outperformance here.
π’ What does the alpha number actually mean?
The alpha is shown as a percentage per year. For example, +8.9% per year means: after we account for everything the four factors explain, this stock has been generating an extra 8.9% per year above and beyond what the model predicts. That extra return has no obvious explanation β it's genuine outperformance.
A -5.4% per year means the stock has been underperforming its factor expectations by 5.4% annually β which is a serious warning sign, especially if that signal is statistically significant (and marked red).
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Which stocks should you consider buying?
The factor screener narrows the field β it doesn't make the final decision for you. Here's how to use it sensibly:
1.
Start with green signals only. Filter the table to "Strong" signals. These are the stocks that have demonstrated genuine factor-adjusted outperformance at a 95% confidence level. This is your starting shortlist.
2.
Read the interpretation column. Each stock has a plain English explanation of why it has alpha β is it momentum? Quality earnings? A genuine business edge? Understanding the reason matters as much as the number.
3.
Don't buy everything on the green list. Pick 6β10 stocks with different factor profiles β some momentum, some quality, some value β so you're not all betting on the same thing. If 8 of your picks are all high-momentum tech stocks, one sector rotation wipes everything out together.
4.
Avoid red signals entirely. Stocks with negative, statistically significant alpha (like INTC or WBA in the current screen) are underperforming on every dimension we can measure. There may be turnaround stories inside them β but that requires a separate deep-dive analysis, not a momentum-based screen.
5.
Check the lookback period. A stock that's green on a 1-year lookback but red on 3 years is a recent winner that may be mean-reverting. A stock that's green across all three lookback periods (1y, 2y, 3y) has a much more robust signal.
β οΈ Important: Alpha is a backwards-looking signal. A stock that has outperformed in the past two years is more likely than average to keep outperforming β but there are no guarantees. Always combine this screen with your own research on the business, the valuation, and your personal risk tolerance. This tool narrows the field β it does not replace judgement. This is not financial advice.