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Predicting EPS Growth

Mar. 02, 2018 2:07 PM ETACOR, BLMN, BOOM, CHGG, CROX, CTXS, CWST, DIOD, EIGI, ENV, LAB, FSTR, HSII, KDMN, MOH, OFIX, PAY-OLD, SPLK, TWTR, UIS12 Comments

Summary

  • Lists the factors most likely to result in strong EPS growth over the next year or so.
  • Explains why these factors work.
  • Suggests some stocks with strong growth potential.

A few weeks ago a question came to me: how can we best predict a company's earnings growth? So I designed an experiment to answer that question. The experiment is a little complicated, so I'll discuss it at the end of this article. I'll instead lead with my results, in reverse order: the factors most likely to predict future earnings growth.

In a tie for fourth and fifth place, with a 25% advantage over a random selection:

Stocks with strong operating earnings growth as measured by comparing the most recent quarter's operating earnings (or EBIT) to the same quarter last year and dividing by the absolute value of the latter

and

Stocks with strong volume-weighted momentum, as measured by the ratio of the three-week volume-weighted moving average to the ten-month volume-weighted moving average.

On the whole, I found that measurements of past earnings growth were relatively useless for predicting future earnings growth. In fact, there tends to be a reversion to the mean. The stocks whose earnings per share have grown the most over the last twelve months are less likely to exhibit strong growth over the next twelve months than a random selection. But there was one exception: operating income growth, as measured by the most recent quarter. And indeed, if you look at Seeking Alpha's articles on individual stocks, they very often use precisely this comparison. It's a damn good one.

As for volume-weighted momentum, the reason this works is that companies with strong growth prospects attract investors, who bid up the price and are increasingly interested in buying shares.

In third place, with 32% and 26% advantages:

Stocks with low cash-flow accruals, as measured by the difference between net income and operating cash flow, divided by total assets (32% advantage); and stocks with low balance-sheet accruals

This article was written by

Yuval Taylor profile picture
2.82K Followers

Yuval Taylor is an author and analyst with 8 years of experience using multifactor ranking systems to buy and sell stocks. He focuses on microcaps and emphasizes evaluating every stock from as many angles as possible via algorithm. He is the leader of the investing group The Stock Evaluator.

Features of the service include: disclosure of Yuval’s personal positions, 2 unique portfolios, a spreadsheet of nearly 10,000 stocks rated from 0 to 100 weekly, and live chat for questions. Learn more.

Analyst’s Disclosure: I am/we are long FSTR. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.

Seeking Alpha's Disclosure: Past performance is no guarantee of future results. No recommendation or advice is being given as to whether any investment is suitable for a particular investor. Any views or opinions expressed above may not reflect those of Seeking Alpha as a whole. Seeking Alpha is not a licensed securities dealer, broker or US investment adviser or investment bank. Our analysts are third party authors that include both professional investors and individual investors who may not be licensed or certified by any institute or regulatory body.

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Comments (12)

Ryan Telford profile picture
Great article and methodology Yuval. I'm curious though, how did you deal with negative NP Margin & negative ROA? Did you set a minimum value for the income numerators? If left alone the ranking system will find companies with (very) negative earnings for the NP and ROA factors. Thanks
Yuval Taylor profile picture
Ryan, you bring up a good point. Companies with very negative earnings are more likely to show strong earnings growth than companies with good earnings simply because of the law of reversion to the mean. Companies with very strong sales (profit margin) or tons of assets (ROA) are even more likely to be able to increase those earnings. So you're looking for companies with terrible earnings and terrific sales or tons of assets. In addition, since sales and assets are far more stable than earnings, these formulae make comparisons between companies work pretty well.
Ryan Telford profile picture
Thanks Yuval. I understand and appreciate the mean reversion aspect you're trying to take advantage of here, my point is that some of the NPM and ROA metrics are very negative, i.e. more than -100% and I was curious if that would have an impact on results. For example, if net income is so low relative to assets or sales, it may be a sign that the company is in serious trouble.

I know your approach here is to predict EPS growth, but if you extend that to overall factor/strategy performance, without any minimum ROA/NPM values a 20 year rank backtest in a R3000 universe (no financials) rebalanced 4 weeks looks better with all the factors above except the NPM and ROA. i.e. with NPM & ROA, top decile is about 11% and a choppy descending deciles.

Remove the NPM and ROA, and top decile is just under 14%, with smoother descending deciles.

Set a minimum NPM and ROA of -100%, and the top decile is just shy of 14%, with descending deciles not as smooth without NPM/ROA, but smoother than if you do not set a minimum limit.

This ranking system is purely based on the 8 factors above, there is no valuation or quality/earnings quality factored in yet. ROA and NPM are TTM values.

I'd be curious to know your thoughts.

Thanks again,
Ryan
Yuval Taylor profile picture
That makes a lot of sense to me. This article was only about predicting EPS growth, not predicting rising prices. You could probably set your minimum quite a bit higher and get better results. Also try using only ROA and not NPM (in my own ranking system, that's what I do). Lastly, look at ten-year backtests, not just twenty-year backtests. It's a lot tougher to make ten-year backtests work than twenty-year ones.
ScottHB profile picture
Very clever test design! Great observation on what analysts are good for. Just curious - any particular rationale for picking 15%?
Yuval Taylor profile picture
Not really. It seemed like a good midpoint. About 40% of companies in the Russell 3000 achieve it.
Yuval Taylor profile picture
The analyst estimate data often don't apply to those stocks. But, although I haven't tested them specifically on those stocks, I think the other criteria would. In general, factors that work well for a large population of stocks tend to work even better for microcaps and nanocaps.
mikeonmicrocaps profile picture
I enjoyed reading your article. It made me reflect on stock analysis and investing style
I wonder if these criteria hold for micro and nano cap stocks
m
How many companies in the Russell 3000 have a current quarter's EPS estimate or a current year's EPS estimate? I would think most in the Russell 1000, but fewer in the Russell 2000. If there are many (say 1/4) that don't pass, is it still valid to use these in a ranking since by not having estimates they will score lower?
Yuval Taylor profile picture
90% of the stocks in the Russell 3000 have a current quarter's EPS estimate, and 91% have a current year's.
d
Another fascinating article. However, if you have 8 winning factors, why do you have two factors in position 1, two in position 2, two in position 3, and then positions 4 & 5?
Yuval Taylor profile picture
Because the factors in positions 1, 2, and 3 are extremely similar. I didn't think it would be fair to give the current quarter's EPS estimate and the current year's EPS estimate two separate positions. Same with net profit margin and ROA, which share identical numerators. Same with two different accrual ratios. The other two factors--volume-weighted momentum and operating income growth--are entirely different.
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