Extreme number of nodes (300)– does it damage the ranking system?

I’m assuming you’re looking at this factor with lower numbers being better. In general, anything that measures debt reduction would, in my opinion, be a good factor to include. Is this the best expression of debt reduction? I usually favor PYQ factors over PQ factors because of seasonality, but you may be able to make a good argument here. And perhaps using DbtTot2CapGr%PQ is better than DbtTotGr%PYQ. It hadn’t occurred to me before now. What matters is your reason for including it. Are you including it because you feel that your system needs to have some debt-reduction measure in it, and that this is really the best one because [I’m sure you can come up with a good argument for it]? In that case, great. Or maybe you have another debt-reduction measure in there and you think this would be a nice supplement to it. That would be fine too. In short, I can’t really think of many reasons not to include a debt-reduction factor that you think would work well with your system, especially if it gives your system a better backtested return. But, of course, you want to look at the alternatives and decide what debt-reduction factors make the most sense to you from a financial standpoint. Lastly, you’ll want to look at NAs here. If a company has no debt to reduce, it should ideally rank higher on this factor than a company that reduces its debt but still has a lot of it. So run a screen with this factor and look at the debt load of companies that score NA. If all of them are debt-free, perhaps you’ll want to use IsNA(DbtTot2CapGr%PYQ,-1000000) so that those companies have the lowest score.

One other thing: don’t use PQ factors on European stocks. Too many of them report semiannually, and PQ will be NA for those. PYQ and TTM should work fine.

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