This screen is based on the characteristics Distressed Investing analyst Marty Fridson identified in The Little Book Of Picking Top Stocks, which he published in 2023, as the common features among the market’s best-performing stocks.
“Marty Fridson’s Stock Screen” is based on Marty’s extremely effective method for picking outperforming stocks.
In 2023, Marty published The Little Book Of Picking Top Stocks, in which he focuses on analyzing the best-performing stocks in the S&P 500 in prior years, and on the factors that led to their market-beating returns.
Today’s screen is based on the following characteristics Marty identified in The Little Book Of Picking Top Stocks as the common features among the market’s best-performing stocks:
- Bond ratings of Baa3 or lower by Moody’s and BBB- or lower by Standard & Poor’s
- Fridson-Lee statistic (defined below) of 18% or greater – meaning analysts’ estimates of the company’s earnings per share (“EPS”) vary widely
- Price volatility over the previous year of at least 1.5x that of the stock that ranked #250 that is the median of the S&P 500 by total return
- Market capitalization equivalent to 50% or less of the market capitalization of the stock that ranked #250 by total return in the previous year (some #1 stocks have been exceptions to this rule)
To further explain our methodology…
We apply Marty’s first criterion by screening for bond ratings of Baa3 or lower by Moody’s and BBB- or lower by Standard & Poor’s.
Marty explains:
Stick to below-investment-grade companies or, at most, those that are rated just one notch higher than that. If anything, consider the lack of a Moody’s rating a favorable sign. Equity analysts may not pay a lot of attention to bond ratings, but you should if you’re searching for #1.”
We apply Marty’s second criterion to our screen by only including stocks with a Fridson-Lee statistic of 18% or higher.
The Fridson-Lee statistic is calculated by subtracting the lowest earning per share (“EPS”) estimate from the highest, and then dividing by the lowest estimate. Historically, #1 stocks have shown a greater spread in EPS forecasts than their #250 counterparts, with a median difference of 33.9 percentage points.
Marty’s research revealed that #1 performers have a wide dispersion in Wall Street analysts’ EPS estimates – for instance, last year Palantir Technologies (PLTR), the top-performing S&P 500 stock, had EPS estimates ranging from $0.25 to $0.40. Wider EPS estimates suggest there’s greater uncertainty and potential upside.
Explains Marty: “In 90% of the cases we examined, the Fridson-Lee statistic just prior to takeoff was 18% or higher, with some stocks clocking in at nearly 200%. Those numbers identify the territory where you have the best chance of finding #1.”
We apply this next component to the screen by only including stocks with a beta of at least 1.5.
These top performers will also experience significant price fluctuations, with a beta greater than 1.5 (a beta of 1 equals the volatility of the overall stock market, while those above 1 are more volatile and those below 1, less volatile) and therefore carry a greater risk of substantial losses – but are more likely to double compared to those with betas closer to 1.
Writes Marty:
Stocks that trade within a narrow range aren’t prime candidates to double in price in the space of 365 days. That would be the financial equivalent of a leopard changing its spots.”
The last characteristic of Marty’s screen includes stocks with a market capitalization equivalent to 50% of the prior year’s average-performing stock.
Smaller market-cap stocks tend to outperform larger, more established companies due to their higher-growth potential. Historically, half of the #1 performers had market caps less than one-third of this benchmark. However, some outliers like Tesla (TSLA) in 2020 showed that exceptions can occur. Therefore, this parameter should be used in conjunction with other metrics rather than as a standalone filter.
Conventional equity research, overly focused on metrics like EPS, fails to pinpoint these high flyers. The conventional wisdom can’t be applied to finding the best performers – that is, the outliers. Instead it requires a blend of quantitative and qualitative criteria that should be used in conjunction to spot them before their meteoric rise.
In addition to Marty’s criteria from The Little Book Of Picking Top Stocks, we’ve added a quality screen to include companies with a return on assets (“ROA”) or return on equity (“ROE”) greater than 15%.