An Examination of Some Financial Adages

This post scrutinizes some of the big-picture narratives, largely accepted as truth, that are often shared about the financial markets. It looks to determine if there are any relationships between these ideas and S&P 500 index levels; by no means was this pursuit meant to be an all inclusive or exhaustive assessment.

Anyone interested in checking out my data wrangling, the statistical analysis utilized, or how I created the visualizations used in this post, can find my notebook here.

Peter Lynch, head of the Magellan Fund at Fidelity Investments between 1977 and 1990, ran the best-performing mutual fund in the world.

He famously stated, “If you can follow only one bit of data, follow the earnings — assuming the company in question has earnings.”

The Global Financial Crisis of 2007–2008 was met by a strong response from the Federal Reserve. The central bank provided trillions of dollars through expansive fiscal and monetary policy, to offset the decline in consumption and lending capacity. While the economy was healing, the stock market, ever forward looking, bid up stock prices in response.

The phrase, “Don’t fight the Fed” was coined.

More recently, the Federal Reserve has again provided trillions of dollars to the system in response to the Covid-19 pandemic — the M2 money supply has increased an eye-popping 22% in 2020.

This go around, there’s a new phrase coined about the central banks actions, “Money printer go brrrrr.

The Capital Market Line (CML) is the tangent line drawn from the point of the risk-free asset to the feasible region for risky assets.

If an investor requires an equity risk premium of 5% in order to invest in quality stocks, and the risk-free rate is 3%, then the investor’s cost-of-capital would be 8%. A risk-free-rate of 1% would imply a cost-of-capital of 6%.

There is an inverse relationship between the required return and the stock price investors assign to a stock.Investopedia

So is there any relationships between these ideas and the S&P 500 index level?

To try and make determinations about these ideas, I first sourced three data sets from the Federal Reserve Bank of St. Louis. The FRED site only provides the last 10-years worth of data regarding the S&P 500 index, so the scope of this project was limited to this timeframe.

It should also be noted that I have proxied the U.S. 10-year Treasury as the risk-free rate (the U.S. is the world’s reserve currency, and has never defaulted on it’s debt).

Let’s quickly take a look visually at the data:

Now let’s begin to examine some of the independent variables with the response variable, the S&P 500 index.

Earnings appear to be a bit more cyclical, and swing wider, than movements in the S&P500 index, however, there appears that a relationship may exist between earnings and the index level.

As the money supply has increased, so has the S&P 500 index levels. Note the over 20% increase in the M2 money supply this year alone. This is a visualization of the Federal Reserve’s response to the effects of the Covid-19 pandemic on the economy. It looks like it may have contributed to the recovery in stock prices.

There are two-periods in this graph worth noting that do not appear to support the notion of an inverse relationship between required returns and stock prices. During the mid-2012 and through the entire 2013 period, 10-year Treasury yields were on the rise, right along with a rising stock market. This happened again throughout 2017.

Let’s pair plot the variables and examine for possible relationships.

Looks like there may be relationships between the S&P 500 index and after-tax corporate profits (earnings), as well as between the S&P 500 index and the money supply. The risk-free rate does not appear to have a strongly defined relationship.

Let’s put this all in perspective. In order to do this, I ran some statistical testing.

First, I looked at the the correlation coefficients to examine the strength in the relationships between the S&P 500 index and

  • Corporate Profits
  • Money Supply
  • Risk-Free Rate

Next, ordinary least squares testing was used to determine if we are able to reject the null hypotheses that there are no relationships between the explanatory variables and the dependent variable, the S&P 500 index.

We are able to reject the null hypothesis for corporate earnings at the 0.05 alpha level and indicate that there is a relationship between earnings and the S&P 500 index level.

We are also able to reject the null hypothesis regarding M2 money supply and the S&P 500 index level at the 0.05 alpha level [see notebook], and state there is a relationship between the two variables.

The t-score and p-value for the 10-year Treasury and the S&P 500 index came out as -1.360 and 0.182 respectively [see notebook]. We were unable to reject the null hypothesis that there is no relationship between these two variables at the 0.05 alpha level.

It was also found that after accounting for differences in the money supply, corporate profits appear to be significantly associated with SP500 Index levels [see notebook]. The null hypothesis 𝛽2 = 0 was refuted at the 0.05 alpha level.

So, what did we learn about the adages presented?

I believe Peter Lynch was onto something with his famous quote directing investors to “follow the earnings” . His recommendation appears to be supported by statistical analysis.

The same holds true regarding the saying,Don’t fight the Fed”.

And when the “Money printer goes brrr”, stocks also appear to be on the rise.

These adages seem to hold some water; how much, however, was not part of the scope of this post.

In the future, it would be interesting to examine these variables in relation to other interesting features, and expand upon the model. Examination of the data outliers, and their impacts, may turn up something interesting. Expansion of the timeframes examined would also be a worthwhile pursuit.

Regardless, seeing the money supply increase over 20% in 2020, with mass vaccination now underway, corporate earnings should be on the mend. It appears to be a nice setup for stock prices in the near-to-medium term.

Oh yeah, what was the phrase David Portnoy coined this year ???

Stocks always go up.” LOL

Studying Data Science at Lambda School | UCONN Alumni