Statistician needed for combining % scores and $ values, into 1 composite score.

Heres the following problem; I have 70 assets (e.g. stocks) and each has a given quality score. These assets are also described by their equivalent market caps (e.g. P*Q of stocks) or value.

I need an advanced statistician, ideally with xp in finance, to combine the two in a new score, that is non-distortive (as a %*mcap is). Heres a little more on whats expected here:

- Show alternative routes - this might include (but not limited to) different types of normalization etc.
- Experiment with score or market cap percentiles (scoring bands) - capture the apples to apples comparisons.

Consider the following: 2 assets (A & B) that score in the 60%-65% band. (A) has $10m mcap, (B) has 100m mcap. (A) is likely to be undervalued compared to (B).

Now consider the following: Asset (A) from before and a new one (C) which scores in the 50%-55% scoring band, and has a market cap of $8m.

There is a clear relationship between (A) and (C) - similar band in mcap, choose (A) because of higher score, but an unclear one between (B) and (C) - how much of the mcap difference is explainable by the score?

This is exactly what I need the new metric to solve for!

Thank you :)
About the recuiter
Member since May 20, 2018
Navin Kumar
from Podkarpackie, Poland

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