Why is the stock market going up?

You’ve likely noticed a seemingly bizarre divergence between the stock market performance over the past month (going up) while everything around you in real life seems to be going the opposite direction (negative sentiment, difficult public health situation globally, severe claims in unemployment). What gives?

Let’s be clear about one thing, sometimes the bizarre is indeed bizarre, so this isn’t an attempt to rationalize what is happening in the stock market, and frankly, it could still very well go down further from where it is now. However, I have been quite unsatisfied with the popular explanation that the market is up because “it has already priced the news in”. If that truly was the case, then you would expect prices to be much lower because the impact of current events on company current and future earnings is far larger than the -14% decline from the February 20,2020 peak in stock market prices (proxied by the S&P500). Unless of course, someone wants to argue that the pricing mechanism was for some reason “broken” in February or even January or December of 2019, rendering the stock price level of those months an underestimation of true value and as a result, the current drop was sufficient to capture changes. That argument, however, stands zero grounds because:

• A) There isn’t much to claim that pricing is more or less efficient at different times of the year
• B) February prices were already high and inflated relative to earnings and GDP

What moves the market

With that cleared up. Let’s talk about what moves the market prices. There is a lot of academic and professional literature on the topic, from one extreme claiming the market to be completely efficient in pricing, to another that claims the opposite. Staunch old school thinkers argue that prices are purely a function of earnings, however, reality shows otherwise (e.g current situation being an example). Moreover, projected company earnings are based on a series of assumptions, and those could also lead to variations. So there is no such thing as a perfect price stock, only ranges of reasonable prices vs unreasonable ones. But earnings are not the only driving factor. Roughly, here is what I noticed moves prices (a combination of):

Earnings + Perception + Algorithmic Trading + Appeal

• Earnings is a company’s net profit after all expenses are paid
• Perception represents investor perception and sentiment
• Algorithmic Trading drives supply and demand and thus prices but based less so on earnings and more so on identifying different favorable trading patterns. Since it introduces buy/sell actions at a significant volume though, it can affect prices though likely within a narrow range
• Appeal stands for the appeal of an investment. This is driven by things like easy access to money or other context-dependent factors that influence opportunity cost and relative comparisons (e.g if I can borrow at 1% a year and make 15% return in the stock market, I’d want to do so, but if my borrowing cost is 12%, then the return is less favorable which would reduce my demand for stocks and as a result the price).

Perception and Appeal are the two wild cards that can explain a lot of the seemingly bizarre. For example in 2018, earnings grew 22%, yet the P/E multiple (Price to earnings ratio) went from 21.4x down to 16.5x, so prices went down when you expected them to go up. In the opposite direction, In 2019, earnings of the S&P 500 grew by 2.8%, yet the index appreciated by 15%, and the P/E multiple went from 16.5x to 20.7x, so prices went up when you expected them to go down.

What is happening now in 2020 during Covid-19

Now back to the current 2020, I think there are a couple of things that investors bullish on the market are working from. Partially, it’s the Perception/Appeal given the government bailout which would bolster companies’ financials and help them avoid bankruptcy. If investors also expect rising inflation due to a large stimulus, they will want to allocate their cash into goods and services producing companies since prices would rise with inflation. However, I think there might be another not widely spoken of reason, and that is the opportunity for companies to “trim the fat”. Here is a chart of The Productivity-Pay Gap between 1948 – 2020. You can see how starting around 1970, the growth in wages has not kept up with growth in productivity.

Data sources:
Productivity: EPI analysis of unpublished Total Economy Productivity data from Bureau of Labor Statistics (BLS) Labor Productivity and Costs program,
Compensation: BLS Current Employment Statistics, BLS Employment Cost Trends, BLS Consumer Price Index, and Bureau of Economic Analysis National Income and Product Accounts

A couple of clarifications are warranted here. Company productivity is a combination of labor (e.g how much can one person output) as well as non-labor productivity (e.g companies finding ways to make more products from the same amount of raw material). Also, “Hourly Compensation” is both wages and benefits of producing nonsupervisory workers in the private sector. “Net productivity” is the growth of output of goods and services less depreciation per hour worked.

Outro

This doesn’t fully explain everything, because even if companies can generate earnings more efficiently, they still need spending consumers to grow their top-line revenue, and unemployed consumers are not spending consumers. Indeed there is also a lot of literature showing that the slowing down in growth economic growth generally (despite COVID-19) is being driven by lower aggregate demand rather than issues of productivity. That said, productivity efficiency is one key in the bigger puzzle, as capital favors efficiency and returns, whether it’s generated by machine or hand.

Moreover, where the market goes next is unknown, anyone who claims otherwise is making just that, a claim. Short of any insider information, this is actually always true. With that said, here is a table I put together showing market returns 3-6-12 months after a pandemic. This is not a projection nor investment advice.

Month	Year	Event	3 month % Change	6 month % Change	12 month % Change
Jun	1981	HIV	-12.12%	-6.06%	-18.94%
Sep	1994	Pneumonic Plague	-2.76%	5.10%	23.78%
Sep	2001	Anthrax	22.00%	18.00%	-13.00%
Aug	2002	West Nile Virus	-1.06%	-9.79%	5.64%
Jan	2003	SARS	4.30%	15.91%	32.52%
Aug	2005	Bird Flu	0.33%	2.93%	2.93%
Sep	2006	E Coli	7.31%	9.28%	16.06%
Apr	2009	Swine Flu	12.54%	18.13%	35.23%
Mar	2014	Ebola	5.55%	6.73%	10.99%
Feb	2015	Disney Measles	1.24%	-0.24%	-11.07%
Jan	2016	Zika	10.64%	14.95%	20.96%
Jan	2019	Measles	12.73%	16.03%	26.39%
Jan	2020	Coronavirus	-13.67%
		Average	3.62%	6.58%	10.96%