I was dusting off an old market prediction model I posted about ten years ago.
It’s pretty basic: How many of the VL stocks are cheap, i.e., P/E under 10?
Rather surprisingly it’s not a bad predictor of one-year-forward returns.
FWIW, 18.62% of VL stocks are notionally “cheap” on that definition at the moment.
That’s pretty high…somewhere around the 82nd percentile of history.
That is historically consistent with average one year forward returns of around 18.5% to 21.5% for an equally weighted VL stock portfolio, depending on the data smoothing you use.
(emphasis on “average”…an average can hide a lot of variation)
Normally the market valuation level is a terrible predictor of forward returns on time frames under a few years.
(with the exception that very cheap moments tend to lead to good results fairly quickly)
This metric seems to avoid that trap, perhaps specifically because the earnings figures being used are NOT cyclically adjusted.
It captures the apparent current earning power, rather than sustainable earning power: apparent earning power might matter more for price movements.
Incidentally, the predictor works with roughly similar variation and similar numbers among the S&P 500 set.
The percentage of “cheap” S&P 500 stocks right now is only 11.6% measured the same way.
So, to the extent that any of this reasoning holds water, the speculation would be that valuation
levels and forward one year prospects are worse among the S&P 500 set than among the rest of the VL set right now.
So, what would be the lesson? Go small or stay home?
That’s a thoughtful slicing and dicing of data and accompanying commentary, which both corroborates and is corroborated by quite a lot of research regarding the longer-term effectiveness of the Value Line appreciation metric. Much patience is required if the reader adheres to those numbers while flipping the pages of Value Line week by week, having to endure the fear of missing out over the past year or so.
There’s a decent book concerning the use of The Value Line Investment Survey Median Appreciation Potential (VLMAP) as a longer-term market timing tool, written by Daniel Seiver, “Outsmarting Wall Street” (1994–available used for less than $5), which more bluntly addresses percent return levels at which to consider buying and selling , in addition to the use of other Value Line tools.
Using the approach Seiver advocates in the book, appreciation potential below 70% indicates time to sell, 70-95% is neutral, and 100% or over constitutes a safe time to buy. Currently, the VLMAP is 70% (neutral). At the last market bottom on 3/23/20, the VLMAP was 145%. In November 2021, VLMAP was 30%. Incidentally, on the basis of how the bond market was behaving and the operating earnings on the underlying stocks, the S&P 500 was probably trading at a circa 25% premium to what it was worth at that time.
There’s a decent book concerning the use of The Value Line Investment Survey Median Appreciation Potential (VLMAP) as a longer-term market timing tool…
I’ve done research on that too.
The VLMAP isn’t an available in the VL exports, but the Projected 3-5 year annual return field is.
By taking the media of those, I reproduced what I presume is about the same thing.
It’s not bad.
They tend to extrapolate a little too much optimism late in a bull–sometimes it’s a bit too slow to become bearish as prices rise.
And, as with many metrics which are at heart intended to be valuation based, sometimes its predictive power is low at shorter time frames.
For start dates 1986-2013 inclusive, average return in subsequent one and four years on S&P Equal Weight nominal total return,
based on median value of Projected 3-5 year annual total return field on purchase date among VL 1700:
From To 4 year 1 year
0 9 3.5% 5.6%
10 11 5.8% 9.6%
12 13 12.4% 13.0%
14 15 14.4% 10.9%
16 17 14.4% 14.8%
18 19 13.7% 18.9%
20 21 17.9% 30.6%
22 999 22.0% 47.3%
The current medium number is 15, so these numbers are implicitly pretty bullish.
Bear in mind the “extrapolating optimism” warning above–maybe they are, maybe they’re not.
The reason that recent data aren’t included is simply that I haven’t updated the analysis in a few years.