As we looked back at the record setting week that was, the analyst
team came in to the office this weekend and over a few beers sought
figure out what constitutes a fair P/E multiple for the current S&P
500, and figure out if there is any sort of correlation between the
amount of currency in circulation and the above historic average P/E
multiples that investors and traders are currently willing to pay for
stocks. Yes we agree that as we write this that it sounds much less
fun than we intended but this is what we live for.
We are sure that many of you have noticed that from the beginning of the year, there seems to be a disconnect between the optimism provided by soft data, and the negative to stagnant signals provided by hard data (we know that is a general statement), particularly in when we look at retail, automobile, and housing markets.
We note that the S&P 500 P/E ratio sat at 24.2x as of July 1, the question is whether irrational exuberance has stepped into the driver’s seat, or if there is legitimacy to current market expectations. So as we opened our second beer, someone also brought up the theory that increased levels of currency warrant higher trading multiples by devaluing how much earnings are worth to a single investor and also increasing the means to invest, rendering a value comparison to Ben Graham era P/E ratios useless. Yes exciting stuff.
So its safe to assume that easy credit policies and Quantitative Easing have contributed to a price increase of real assets and consumer goods, but if we drill down we want to see how this relates to the price investors are willing to on corporate earnings.
So our first move was to collect data on the amount of M1 (funds readily available for spending), monthly values for the S&P 500, historical Price/Earinings for the S&P 500, historical monthly volume for the S&P 500, and monthly trailing-twelve month Earnings Per Share for the S&P 500.
Our first move was to compare M1 and P/E, to see if the money
investors are readily able to pour into the stock market had some sort
of material impact on investor demand for earnings.
The problem with this comparison is that M1 is always increasing (Hey Janet keep the printing press banging on), on the other hand P/E tends to be more volatile due to its many other input factors.
When the gears of the economy stop grinding and earnings collapse, P/E ratios explode because stock prices don’t fall proportionately, but high P/E ratios can also signify high expectations of growth or stability, so this graph in itself didn’t tell us as much as we would have liked.
Next we took a look at the relationship between the annual change in M1 and the average yearly P/E ratios and found something interesting:
We are sure that many of you have noticed that from the beginning of the year, there seems to be a disconnect between the optimism provided by soft data, and the negative to stagnant signals provided by hard data (we know that is a general statement), particularly in when we look at retail, automobile, and housing markets.
We note that the S&P 500 P/E ratio sat at 24.2x as of July 1, the question is whether irrational exuberance has stepped into the driver’s seat, or if there is legitimacy to current market expectations. So as we opened our second beer, someone also brought up the theory that increased levels of currency warrant higher trading multiples by devaluing how much earnings are worth to a single investor and also increasing the means to invest, rendering a value comparison to Ben Graham era P/E ratios useless. Yes exciting stuff.
So its safe to assume that easy credit policies and Quantitative Easing have contributed to a price increase of real assets and consumer goods, but if we drill down we want to see how this relates to the price investors are willing to on corporate earnings.
So our first move was to collect data on the amount of M1 (funds readily available for spending), monthly values for the S&P 500, historical Price/Earinings for the S&P 500, historical monthly volume for the S&P 500, and monthly trailing-twelve month Earnings Per Share for the S&P 500.
The problem with this comparison is that M1 is always increasing (Hey Janet keep the printing press banging on), on the other hand P/E tends to be more volatile due to its many other input factors.
When the gears of the economy stop grinding and earnings collapse, P/E ratios explode because stock prices don’t fall proportionately, but high P/E ratios can also signify high expectations of growth or stability, so this graph in itself didn’t tell us as much as we would have liked.
Next we took a look at the relationship between the annual change in M1 and the average yearly P/E ratios and found something interesting:
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