I'm working on a data that deals with start-up/similar companies data. A lot of the companies have negative P/E and/or little to no sales. Is there good ways to create meaningful data (like averages, medians) from this?
I obviously should not use negative values in calculations, since low P/E is meant be a positive factor. So far, I've tried two alternative ways, neither of which are great:
Ignore all negative P/E and huge/undividable P/S data. However, this significantly does skew the data as you are easily dropping over 50% of the companies and thus gives much rosier picture of the market than it should.
Assign a large dummy value for negative P/E and huge/undividable P/S. For example, any negative P/E becomes positive 50, while any missing P/S becomes 100. However, since these numbers are picked arbitrarily, it can unnecessary skew the data to higher-than-real averages.
Any ideas about better approaches? (And yes, I know this question is not necessarily a perfect fit for quant finance, but there really isn't any better place for it either...)