Price to Sales ratio
Price to Sales ratio is another number to look at. A company’s earnings, profits, or even book value easily can be manipulated, however it is really hard to manipulate sales numbers, and that is why Marc Faber prefers this metric when evaluating markets.
For every industry there is a profit margin that you can expect from a well-run company. Based on the sales, possible profits can be estimated. If the profit margin is very high, probably it will not stay there for long, because competition will appear, and push down prices.
The data fro this mertic is quite limited, it starst from 2000 to 2015.
The correlation between this metric and the returns that we can expect in the coming years is quite remarcable.
This means that the market works well. If the Price to Sales ratio is high we can expect low returns in the coming years even if currently profits are high. This is because it means that profits are stretched.
The maximum Price to Sales ratio was reached in 2000 with 1.8, the mean and median values are near 1.4 and the minimum was reached in 2009 touching 0.8.
Based on this data, a company is overpriced if its market cap is bigger 1.4 times his sales number.
The interesting thing about this metric is that the correlation is strongest for the one year investment horizon just like in the case of the Price to Book Value ratio.
Based on this metric, the best time to buy was in 2009 and the best time to sell on 2000.
If somebody would have invested in the S&P500 index only when the Price to Sales ratio was below 1.4 it would have turned out to be an acceptable investment.
During the dot com Bubble it got to 1.8.
This metric works best for an investment horizon from one to three years, with the best results of one year investment time horizon.
Based on this limited data we can conclude, that the long term profitability of a company depends on the sales, because to high profit margins cannot be maintained for long periods of time.
So this is a really good metric, measurable, hard to counterfeit and with really good correlation with the returns for the next year.
The really disturbing thing about this metric is, that the maximum of 1.77 was reached in 2000 and now the S&P 500 stands at 1.76. Based on this a 2000 like crash can be right around the corner.