@bheeshma EV/EBIT is just one metric that people use. The point is to think of quantifying each aspect.
For example, let me walk you through a simple exercise… the framework I most often use is QGLP. So, let’s see how we can retrofit QGLP in some quant format.
Parameters for QGLP framework
-
Q meaning Quality (of business & management):
ROE , ROCE, Promoter pledging, OPM, tax rate, dividend payout ratio -
G meaning Growth:
Revenue growth - 1,3,5 years CAGR, PAT growth - 1,3,5 years CAGR -
L meaning longevity: (this is a more subjective parameter but we can have some view by looking into the past)
Revenue growth - 10 yrs CAGR
Order book size / Annual revenue -
P meaning Price:
PE, PEG, EV/EBITDA
You can also add technical factors in the price parameter. Factors like say, 200 day moving average etc.
These are parameters that I use for a QGLP strategy. You can come up with a different set or a bigger or smaller set. The values you use for filtering will also vary. There are literally millions of combinations that can occur by varying the parameters and their threshold values. You need to tinker and come up with your own for create a strategy for yourself.
So, there is no hard and fast rule as what parameters to use. You need to think of a strategy and there has to be a rationale for having that strategy. Then try to quantify it. One of the biggest challenges in quants systems these days is people are using too much on ML (machine learning) and are trying to find patterns in large data sets. Once they find a pattern, they think it can be utilised. But unless there is an underlying logic to that pattern, it usually fails as it ends up being a random pattern.