Demographics appear to be a major influence behind elevated stock market valuations the last 17 years. Those influences appear to be in transition to the opposite extreme. While timing is far from certain, 2014 could be the year the market collapses.
We'll start with a chart of the PEses and a model of it based on four demographic influences. Then I will describe a series of seven alternating correlations between demographics and the stock market. After that we will look at charts of the four influences that make up the model. The PEses is based on the S&P 500 (NYSEARCA:SPY), more information about it is in this article.
During the last 17 years the market has averaged about twice the valuation that it had in the prior hundred years. The model suggests valuation will fall toward the low range of history in the next few years. The model basically indicates that the number of people headed into the peak ages of pushing stocks up are in sharp decline while the number of people headed into the peak ages of pushing stock prices down are about to have the fastest increase ever.
Demographics have multi-year lead times, but are not precise timing tools. The variables may have different lead times for different generations. One generation may retire at a different age from a previous one. The age at which people tend to reach their peak earnings appears to have increased over time. So while the model above suggests the crash should have already started it could still be a year away, or maybe more.
As baby Booms and birth dearths move through the life cycle they have a series of bullish and bearish impacts. Actually, it starts before birth, about 9 months to a year after the economy and markets have been strong there is a positive impact on the number of births.
Between birth and age 2 a baby boom has a modest negative impact on stocks and GDP. While raising children well is the most important investment for the long term future of an economy, new parents' contributions to production measured in GDP is often depleted. Schedules, routines and sleep suffer shocks, especially since children under two are more frequently sick.
When children go off to school and become more independent the parent's ability to contribute to GDP gets an immediate boost. Having children also inspires parents to provide and focus on the future. This positive influence on stocks appears to maximize around age eight.
In their late twenties or early thirties young adults have a negative impact on stocks. They tend to consume more then they produce and take on debt to finance the consumption. This is the opposite of investment. They also have a large appetite for risk. Sometimes the risks pay off big, often they don't. Jerome Kerviel, a 31-year old trader, lost $7 billion for Societe Generale in 2008. Nicholas Leeson, age 28, lost a billion dollars to bankrupt Barings Bank in England at age 28. Many of the dot com companies that went bust in the 2001 recession were run by people in their twenties and early thirties. In the US stock market the negative impact seems to be the worst when a baby boom turns 27.
People tend to reach their peak income and productivity in their late forties or early fifties. At this age they are likely to take more calculated risk. Perhaps this is the age where people tend to reach an optimal balance between experience and command of resources on one hand and creativity and stamina on the other. The peak positive impact on stock markets appears to come when a baby boom is about 43 years old.
As people move into retirement they again consume more than they produce. Retirement accounts move from being built up to being depleted. Often people in their sixties and seventies become more risk averse and lighten up on equities even if think they won't need the proceeds in their lifetime. Presently, the best correlation suggests a baby boom turning 67 is the worst for the stock market.
There is one last correlation where assets are turned over from one generation to the next and perhaps invested a bit more aggressively or spent which stimulates the economy. This modest influence appears to peak when a baby boom turns 80.
To summarize: Strong markets are good for births. Taking care of two year olds not so good for the markets. Getting children established in school at age 8 is great for the markets. "Bullet proof" 27 year olds are hard on the market. Seasoned employees and entrepreneurs at age 43 are great for the market. Retires at 67 are bad for the market. Passing on assets to the next generation is good for the market.
Now we'll start looking at the demographic variables in the model. The first one is the number of births in the United States. In the chart below the number of births is shown with a best fit growth rate. Below that births are de-trended where the trend is stationary at the value of 100.
De-trended births are plotted with an 8 year lead time with the PEses below to show the influence of baby booms and birth dearths turning 8.
The 1929 peak corresponded with a baby boom that peaked in 1921. The surge in value in the 1950s and 60s corresponds with the post WWII baby boom. The birth dearth of the 1970s corresponds with valuations bottoming in 1982. The rise in births to 1990 supported the rise in stocks through 1998. Births came to another peak in 2006 which supports stocks into 2014, but then suggests falling valuations as far as the data goes.
Just as the number of births were de-trended above the number of people that are age 20, 35 and 50 have also been de-trended in the charts below.
The negative effect of a baby boom turning 27 is shown with the plot of the de-trended number of people who are age 20 with a 7 year lead time. The red trend scale is inverted so that a rise in 20 year olds is plotted as a decline on the chart.
The birth dearth of the Great Depression corresponds with the market valuation peak in the 1960s. The first big leg of the baby boom in 1947 turned 20 in 1967 and corresponds with the deep bear market in 1974. The birth dearth of the 1970s corresponds with the all time high valuation. The PEses hit its high in December 1999 and remained near that high through 2000. This measure suggests modestly weakening valuations for the next three years.
The positive impact of age 43 is shown below with an 8 year lead time of the de-trended population at age 35. The high valuation in the 1960s corresponds with the 1921 baby boom. The low valuation in the 1970s and early 1980s lines up with the birth dearth of the depression. The post WWII baby boom lines up with the all time peak valuation. In the next few years the birth dearth of the 1970s will be reaching their peak negative impact on the economy and stock market valuations.
The influence of retirement is shown with a 17 year lead time on the population at age 50. The trend scale is inverted to show that as people reach age 67 there is a downward influence on valuation.
For the last 17 years the birth dearth of the Great Depression has been working their way into retirement. So the number of people reaching this age that is bad for stocks has been lower than usual. The 1947 surge in births will turn 67 in 2014. We are now poised for the baby boom to have their main downward influence on valuation and economic growth.
The combination of the above four influences were combined into the model shown in the first chart above. The lead times shown were chosen to maximize the correlation in the model. Some of the lead times would be different if I were maximizing the correlation with the individual indicator. For example, by itself population age 50 has its strongest correlation with PEses at a 16 and a half year rather than a 17 year lead time. While the charts go back to 1927 the correlations were maximized for the 1937 to 2013 period. Fitting to this period probably does not show the best timing for the coming year.
The model shows the PEses hitting a low of 8 in July 2014. This would be an 82% decline from the 44.1 in November. While I am expecting a 50% to 90% decline in stock prices sometime in the next three years, I do not really expect an 82% decline in the next 8 months.
Demographics are a plausible explanation of the higher than normal valuation of the last 17 years. To the extent they were a major influence behind the elevated valuation, they should lead to dramatically lower valuations in the next few years. While the current valuation is not high compared to the peaks in 2000 and 2007 it could be monstrously high compared to what is coming.
Additional disclosure: There is no guarantee analysis of historical data their trends and correlations enable accurate forecasts. The data presented is from sources believed to be reliable, but its accuracy cannot be guaranteed. Past performance does not indicate future results. This is not a recommendation to buy or sell specific securities. This is not an offer to manage money.