We Now Turned to S&P 500

Contrary to our initial expectations that increased liquidity would inflate P/E ratios, it appears that there seems to be a negative relationship between the change in M1 and P/E ratios, this means that increases in M1 were typically met by lower P/E ratios and vice versa. When we put this data into a regression analysis, it showed that only about 13.5 % of the variation in P/E ratios could be explained by variation in the change in M1, even though all variables were statistically significant.

So moving logically, our next move was to compare trading volumes to P/E ratios, we assumed that an increased supply of funds should lead to an increase in the quantity demanded of earnings.  So we should see increases in the volume of trades taking place (an imperfect assumption, but a starting point nonetheless, hey and we had 2 beers already!):

So what’s interesting about the above graph is that as long as volume remained below 1E+11, the Price/Earnings ratio tended to remain in the 10 to 30x range. Beyond that level of volume,  the P/E ratio became much more dispersed due to either massive selling or buying pressure. But we see that this relationship didn’t do much to answer the question about what we were asking about current price levels.

So we now turned to S&P 500 P/E ratio as of July 1, 2017, and compared a range of values dating back to January 1, 1959. As we expected, the P/E ratio of 24x on July 1 is considerably higher than the usual average of 19.0x – in fact it is well inside of the upper quartile of monthly P/E ratios, placing it at a historically high level. As we would say about any investment, high earnings multiples can be justified by strong fundamentals, so at this point, we thought to take a look at the three major factors that influence multiple levels: size, risk, and growth.