# Statistics And Finance

## Statistics And Finance

Statistics have become crucial in Finance, especially in stock investments. For example, the statistic helped me identify cheap companies for #mergersandacquisitions /investments. For instance, if i want to identify undervalued growth companies, i screen stocks with low P/E ratios, high #EPS, and high #ROE.

The logic is simple, companies with high expected growth will report higher P/E multiples. Still, when we correlate P/E and development, the correlation is only 20%, i.e., only 20% of the increase in a stock P/E is due to higher growth.

Then, to identify undervalued companies in a sector, i do a regression of the P/E ratio against the EPS growth of all the companies in that sector. When i do that for Indian IT companies, i get the following:

Predicted P/E = 19.86 + 44.10 *(growth rate)

At a 10% growth rate, the predicted P/E is 23.27. Therefore, if the stock P/E trades below 23.37, it is undervalued. We can extend this regression from a single variable to multi-variables by running a multiple regression of P/E against EPS growth and ROE.

I believe a firm understanding of DCF is crucial if you want to pick stocks on fundamentals. However, if you choose stocks on pricing, statistics is the defacto tool one must master to adjust for biases and understand the relationship between multiple variables.