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Will the stock market crash soon?

You have got to love the human mind.  Despite all the evidence to the contrary, so many people believe we can predict the future.  I often think to myself, if there is life outside of earth and they are looking down on us, they must think we are idiots for making the same mistakes over and over again.

Markets were at less than 100 in 1900.   They hit 26,500 this year.  Many charlatans and delusional types make money by trying to scare people about the next crisis.  As Warren Buffett said, the Dow will hit $1M one day.  The most profitable companies always get bigger and stronger, and US Stocks have always risen over time.

However, can we tell when stocks will go up and down and will the stock market crash soon in 2018 or 2019?  We might know that prices go up in the long-term,  but can we predict the short-term?

Joseph Davis,Roger Aliaga-Díaz and Charles J. Thomas did a paper for Vanguard, which I have put a link to in the bottom of this article.   In full they looked at these factors, and whether they can help us predict the future of the futures:

Price/earnings ratios, or P/Es

1.Components of a simple “building block” dividend growth model (dividend yield + earnings growth)

3. Trailing 1-year dividend yield.

4. Trend of real corporate earnings growth (trailing 10-year average real earnings, or “E10”).

5. “Consensus” expected real earnings growth (proxied by trailing 3-year average growth rate).

Economic fundamentals

  1. Trend of U.S. real GDP growth (trailing 10-year average growth rate).
  2. “Consensus” expected real GDP growth (proxied by trailing 3-year average growth rate).
  3. Yield of the 10-year U.S. Treasury note (reflects inflation expectations and anticipated Fed policy).
  4. Federal government debt/GDP ratio. (Hypothesis: Higher debt levels today imply a lower future return.)
  5. Corporate profits as a percentage of GDP. (Hypothesis: Higher profit margins today imply a lower future return.)

Common multi-variable valuation models

  1. Fed Model: the spread between U.S. stock earnings yield and the long-term government bond yield (the spread between the inverse of P/E1 and the level of the 10-year Treasury yield).
  2. Building-block model with trend growth (a combination of 3 and 4 above).
  3. Building-block model with consensus growth (a combination of 3 and 5 above).     

Here are the findings:                                                                                                                      1..First, stock returns are essentially unpredictable at short horizons. 

The highest correlation—an R2 of just 0.12—was produced by the building-block model using trailing dividend yield and trend real earnings growth.

2. Many commonly cited signals have had very weak and erratic correlations with realized future returns even at long investment horizons.

3.  They also found, to the surprise of some readers I’m sure,  “that some widely cited economic variables displayed an unexpected, counterintuitive correlation with future returns. The ratio of govern- ment debt to GDP is an example: Although its R2makes it seem a better performer than others, the reason is actually opposite to what one would expect—the government debt/GDP ratio has had a positive relationship with the long-term realized return. In other words, higher government debt levels have been associated with higher future stock returns, at least in the United States since 1926″.

4.  The biggest indicators were the P/E ratios, which looks at how expensive a company is related to their current market price.  Government debt to GDP AND treasury yields have close to a 0% correlation.  I put the and in capitals, as so much has been made about US Treasury Yields hitting 3% on CNBC and Bloomberg recently.

You will notice the formatting of this blog hasn’t been perfect and I after 1-2 tries to change the bullet points, I stopped trying.  It proves a point really.  Flash marketing won’t change the facts and the academic evidence about investing!

Anyway the full paper is available here – https://personal.vanguard.com/pdf/s338.pdf


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