Wednesday, December 20, 2017

The Opposite - Deep Value Thoughts Part 2

The Opposite - Deep Value Book Thoughts Part 2

Seinfeld (in my opinion) is one of the funniest shows ever.  And it has great insights into human nature.  A classic show in "The Opposite", where George laments that he always makes the wrong choices.  And Jerry (as seen to the left) comments he should then always do the opposite of his instinct.

That pretty neatly sums of the current chapter of Tobias Carlisle's book, "Catch a Falling Knife - The Anatomy of a Contrarian Value Strategy".  It is a very, very thought provoking chapter.  After reading it, the first thing you will do is never ever rely on another analyst report.  The book (and this chapter) remind me greatly of another book I read, "The Undoing Project", by Michael Lewis.

The point both authors make, with a bunch of psychological and back-testing data, is that people bring biases to the table when investing.  It is very difficult to buy a much hated stock in a much hated industry.  I often write about that, for example in my "Gut Check" post I comment how I am not sure that I would buy any one stock from a screen I had run.

Carlisle then runs through a bunch of studies that show that buying out-of-favor stocks can be an optimal strategy.  Here are some key findings:
  • split stocks into a Glamour Portfolio and a Contrarian Value Portfolio. Glamour is stocks with highest historical sales growth and highest valuation (generally based on P/B. Contrarian Value is opposite, lowest sales growth and lowest P/B.  Over a five year holding period (looking at years between 1963 and 1990), the Contrarian Value stocks were up 78% to 104% more than the "Glamour" stocks.
  • The second split was just looking at just "value" stocks (defining value in various ways) and splitting them by "growth" value stocks and "contrarian" value stocks. In this split the contrarian value stocks were those that had recently performed poorly.  Again, same time frames, 1963-90 and 5 year holding periods and again a solid beat by Contrarian Value. Not as large, but a range of 35 to 55 percentage points over five years.
Carlisle then states (1) valuation is more important than growth and (2) if valuations relatively cheap, the low or no growth stocks within that subset tend to outperform.  That seems counterintuitive.  Here we are "It's Opposite".

Now before I go further, I thought about that.  I think we can all agree that stocks making the MFI screen are virtually all value stocks.  So we meet (1).  So this would imply that over time (and a 5 year holding period, longer than MFI) that you would then be best picking the MFI stocks that have low or no growth.  I doubt I do that, though I don't hold for five years.  For kicks though, I will go back 5 years and look at one of my top 200 lists and see if the low/no growth stocks did well/better.

I also thought about my attempt to create my "Dogs of MFI" approach... which is kind of inline with this "Falling Knife" chapter.  I looked to see if a stock was on the MFI list a year ago and still on the list and it had dropped at least 30%, how does it do?  My results were not definitive.  It was very volatile.  You had a few stocks like WTW or ESI (at one time) that just exploded upwards over the next year.  But you had a fair share that just continued to go down.  Like I said, it was volatile.

Here are some more thoughts/findings from the chapter:
  • Tom Peters book "A Search For Excellence" defined characteristics of "excellent" companies. Surely Excellent companies would have better stock performance than Unexcellent companies. But a study running from 1972 to 2013 showed Unexcellent companies averaging a return of 13.7% versus 9.8%.
  • The final one, which really really surprised me was using S&P stock ratings versus stock returns.  S&P looks at Financial metrics to rank a company with a letter grade between A+ and D.  From 1986 to 1994 here are annual returns by rating:
    • A+  9%
    • A     9%
    • A-   10%
    • B+   10%
    • B  13.5%
    • B-   12.8%
    • C/D   18.8%
Whoa.  Something seems wrong with this picture.The stocks with the worst financial metrics and highest financial leverage did the best???  BY A LOT.

So some takeaways.  I guess an A+ stock just doesn't have any upside. Just like a stock where all the analysts say "Buy".  But a C or a D is beaten down and if there is one phrase used a ton in this chapter, it is "Reversion to the Mean".  Another takeaway is that it is okay to be holding your nose when you buy a value stock.  I mean look at USMO.  This was a maker of pagers for gods-sake in an era of smartphones.  Talk about no or low growth.  But it was a great buy!

Let me parse through some old MFI stocks and see where some went after five years.

Here are the 50 stocks from December 2012:


Stock
AGX
APOL
BAH
CA
CF
CPLA
CSCO
DELL
DLB
DLX
DMRC
EGY
ESI
GME
GNI
GTAT
HFC
HLF
IDCC
INTX
JCOM
KLIC
LPS
MANT
MSFT
NATR
NSU
NTI
NUS
PBI
PDLI
PETS
POOSF
POZN
QCOR
RPXC
RTN
SAI
SAVE
STRA
STX
SVLC
TNAV
TZOO
UIS
USMO
USNA
VCI
VG
WCRX

Now let us try and figure out which were down the most in the previous year (so the Contrarian Value stocks).

Here are the worst 17:

Stock  Start  Change
ESI       70.87 -76%
APOL       54.08 -61%
GTAT         7.11 -57%
PBI       18.64 -46%
STRA       97.87 -43%
QCOR       44.04 -40%
HLF       51.79 -38%
GNI       90.89 -36%
DELL       14.76 -32%
NSU         5.62 -27%
TZOO       26.11 -27%
RPXC       12.40 -27%
BAH       17.50 -26%
NUS       47.46 -23%
MANT       32.45 -23%
INTX       11.20 -22%
USMO       14.13 -20%

Here were the best 17:

Stock  Start  Change
HFC       23.34 87%
STX       16.16 83%
LPS       14.85 64%
EGY         6.09 42%
CF     144.15 39%
DLX       22.83 38%
VCI       18.90 31%
KLIC         9.38 28%
NATR       11.25 16%
RTN       49.07 14%
AGX       15.27 14%
SAVE       15.69 13%
USNA       30.38 8%
VG         2.21 7%
JCOM       28.06 7%
PDLI         6.16 6%
PETS       10.12 5%

So following the book (ok, I know this is a limited sample), we would expect the worst 17 (Contrarian Value) to do better than best 17 (high growth value) over the next five years.  But we would expect both to beat the market.

Ok, here are top and bottom 17 as of today or when they were bought (everyone should eyeball for potential missed stock splits or special dividends):


Stock Category Dec-12 Dec-17 Dividends Change
HFC High Growth       43.60       49.46               9.91 36.2%
STX High Growth       29.59       41.53             10.85 77.0%
LPS High Growth       24.30       37.30               0.60 56.0%
EGY High Growth         8.65         0.70                    -   -91.9%
CF High Growth    201.02    204.40             36.00 19.6%
DLX High Growth       31.47       75.88               5.75 159.4%
VCI High Growth       24.69       34.00                    -   37.7%
KLIC High Growth       11.99       24.65                    -   105.6%
NATR High Growth       13.02       12.10               5.00 31.3%
RTN High Growth       56.15    186.67             14.07 257.5%
AGX High Growth       17.37       45.55               4.10 185.8%
SAVE High Growth       17.73       44.49                    -   150.9%
USNA High Growth       32.93       74.35                    -   125.8%
VG High Growth         2.37       10.15                    -   328.3%
JCOM High Growth       29.91       74.87               4.95 166.9%
PDLI High Growth         6.54         2.90               1.90 -26.6%
PETS High Growth       10.61       46.07               2.85 361.1%
USMO Contrarian       11.26       15.90               1.88 57.9%
INTX Contrarian         8.72         2.18               1.00 -63.5%
MANT Contrarian       25.14       50.96               3.15 115.2%
NUS Contrarian       36.38       68.26               5.10 101.6%
BAH Contrarian       12.88       38.84               3.73 230.5%
RPXC Contrarian         9.04       13.79                    -   52.5%
TZOO Contrarian       18.99         6.60                    -   -65.2%
NSU Contrarian         4.08         2.24               0.60 -30.4%
DELL Contrarian         9.97       13.86                    -   39.0%
GNI Contrarian       58.55       13.90             14.50 -51.5%
HLF Contrarian       32.17       68.23               1.50 116.8%
QCOR Contrarian       26.23       93.60               0.80 259.9%
STRA Contrarian       56.17       92.01               1.00 65.6%
PBI Contrarian       10.03       11.38               3.01 43.4%
GTAT Contrarian         3.03              -   -100.0%
APOL Contrarian       20.92       10.00                    -   -52.2%
ESI Contrarian       17.31         0.36                    -   -97.9%


Summary

Ok,  the top 17 (high growth value) are up an aggregate average 116.5%. I was not surprised to see PETS near the top.  But VG?  I had forgotten about them. I had to check to make sure there wasn't a reverse split or something.

The bottom 17, Contrarian Value were up a mere 36% on average for the 5 year stretch.  GTAT declared bankruptcy. ESI is no more as well.  Actually some pretty bad names in there.  Again, I am not saying the studies listed in Deep Value are wrong... this is just one small sample for fun.

Finally, how did the Russell 3000 do in the past 5 years?  Up 94%.

So it was beaten by the High Value Growth.  But not the composite of Growth and Contrarian.  There is a small caveat.  Several companies got bought during the five years, and I have assumed no reinvestment (VCI, LPS and DELL).

I did find it exceedingly interesting that buy these stocks and hold for 5 years and you actually do pretty well.  All the churning (buying and selling once a year) may not be that necessary (of course Greenblatt did discuss that).

Ok, I think I've rambled long enough.






1 comment:

Applying Value said...

Very interesting that you went through some old MFI stocks from 5 years ago. A bit disheartening that they produced so poor results, but I'm hoping that it is the quality component of MFI that causes these to not perform as you would expect Contrarian value stocks to do.

Regarding the last part about holding periods: I just recently wrote a post about the impact of different holding periods on one's CAGR in quantitative investing. In it, I go through a bunch of studies comparing these when screening using different value ratios. The post is in Swedish, but I can recommend the original articles if you ever want to dig deeper into that topic.

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