Sunday, December 11, 2016

The Bad and The Ugly

The Bad & The Ugly (Very Interesting)

In my previous post, I rambled about the two problems with MFI - (1) it is very streaky and (2) there is a lot of volatility between individual stocks.  I showed that since I started tracking in 2006, 14% of stock-years had a 40% decline or greater.

If we could find a means of recognizing some of the bad & ugly in advance, we could certainly improve our returns.  Obviously, there is no way to pre-determine them all,but if you could, it would take your average return per stock from 8.2% to 19.3%.  So there is gold in them thar hills.

It is just too overwhelming to go all the way back.  So I looked at my tracking portfolios 2011 & forward. That gave me 3000 stock years to look at.  325 of them fell in the B&U buckets (a bit shy of the 14% overall).  Here they are:


Stock Average Change Count Since 2011
ACHI -58.8% 5
AFAM -52.3% 2
amed -61.2% 8
APOL -58.1% 22
ASTX -44.5% 1
ASYS -48.9% 1
AVEO -41.1% 1
AVID -48.9% 5
BCOR -55.7% 4
BKE -40.8% 2
BODY -53.1% 2
BTH -43.0% 1
CECO -66.3% 16
CHKE -40.3% 1
CJREF -57.0% 1
COCO -51.9% 2
CREG -48.6% 2
CRME -68.3% 4
DELL -42.9% 1
DEPO -41.3% 1
DXM -50.3% 1
EGL -52.3% 2
ENTA -47.4% 4
ESI -67.9% 27
GME -45.6% 1
GNI -62.6% 11
GORO -50.2% 3
GPRO -51.2% 1
GTAT -56.8% 11
HLF -52.6% 3
HPQ -48.4% 1
ICON -45.5% 2
IDCC -40.1% 2
INTX -52.7% 6
LCI -52.1% 5
LFVN -49.2% 5
LHCG -46.1% 1
LINC -42.8% 3
LPS -48.2% 2
LQDT -54.6% 12
MANT -44.8% 1
MPAA -51.2% 7
MSB -64.0% 5
NEP -60.9% 2
NLNK -71.9% 8
ONE -48.3% 2
OSK -40.7% 1
OUTR -43.9% 2
PDLI -47.4% 9
PFMT -63.8% 14
POOSF -100.0% 3
PTIE -61.7% 8
PWER -51.2% 7
RGR -48.6% 3
RPXC -45.1% 1
SCEI -75.5% 4
SMT -69.8% 3
SPRT -46.3% 4
STRA -43.2% 3
TDC -43.6% 1
TNAV -51.6% 4
TPUB -56.8% 4
TZOO -45.0% 4
UIS -53.0% 14
VECO -45.3% 3
VIAB -45.3% 4
VNCE -58.7% 4
VNDA -42.4% 1
WILN -58.2% 2
WTW -66.9% 10
XENE -49.1% 1
YLWPF.PK -97.2% 1
Grand Total -57.4% 325


First let us do a couple of easy calculations.  Our total population is 10.8% Ugly.

If you just bifurcate each tranche, splitting by market cap into the 25 biggest and 25 smallest.  You find that 129 are "big" and 196 are "small".  So you are much more likely (8.3% to 13%) to get a stinker in smaller cap stocks.

Then let us look by dividend flag (greater than 2.6%).  272 of stinkers had dividend less than 2.6%. So only 53 had dividend greater than 2.6%.  1005 had dividend flag in total.  So percentages:

Stinkers with Dividend < 2.6%:  13.6%
Stinkers with Dividend > 2.6%:  5.3%

So you can see why my formula has worked pretty well.  Now using all data here is a table showing splits by big/small versus Div Flag:


Yield Small Big Total
<2 .6="" td="">         2,273         2,032         4,305
>2.6%            702            910         1,612
Total         2,975         2,942         5,917


This first table now goes back to 2006.  It simply shows count of stocks in each quadrant.

Yield Small Big Total
<2 .6="" td="">            430            276            706
>2.6%              86              41            127
Total            516            317            833


So this table shows the count in each quadrant that are bad/ugly.

Now the final table just divides the first two tables to get percentages:

Yield Small Big Total
<2 .6="" td=""> 18.9% 13.6% 16.4%
>2.6% 12.3% 4.5% 7.9%
Total 17.3% 10.8% 14.1%


So this is fascinating.  While 14% of overall stocks are stinkers. If you just pick stocks in the top 1/2 of market cap and a yield greater than 2.6%, you drop that to 4.5%. Whoa. I am not sure we can do better than that... that seems pretty good. Doing what I am already doing (pat self on back).  What if we use $600m market cap instead of big small and dividend yield of 2.4% (what I am doing)?  Here is the table:


Yield Small Big Total
<2 .4="" td=""> 20.2% 13.9% 16.7%
>2.4% 14.5% 3.8% 7.6%
Total 18.8% 10.7% 14.1%


Wow, excellent.  I suppose I could just stop there and call it a day.  Just by those two splits, we have reduced the stinker percentage from 14.1% to 3.8%.

Other Thoughts

When you look at the very first table of 325 stinkers, the first thing that one would note is that there are serial offenders.  While there are 72 stocks that make up the 325 stock years, just 9 of the 72 make up 42% of the stinker stock years:

Stock Average Change Count Since 2011
ESI -67.9% 27
APOL -58.1% 22
CECO -66.3% 16
PFMT -63.8% 14
UIS -53.0% 14
LQDT -54.6% 12
GNI -62.6% 11
GTAT -56.8% 11
WTW -66.9% 10


The sharp-eyed of you will note the top three are for profit education.  It is interesting that CPLA and STRA (other FPE stocks) are not in that list and they paid dividends. PFMT and LQDT lost government contracts. GNI was a trust that was diminishing/being exhausted.  So my point here is most of these names had earnings that were falling off a cliff for some reason.  While I am not going to quantify this rule - I would suggest looking at net income in past 2 quarters against net income from a year ago past two quarters. That should give some feel on whether falling off a cliff.

By Industry

Let us now return to the original 325 stinkers and sort them by industry:


Stock Average Change Count Since 2011
Aerospace & Defense -48.6% 3
Apparel Manufacturing -54.3% 6
Apparel Stores -40.6% 3
Auto Parts -51.2% 7
Biotechnology -58.1% 36
Business Services -60.9% 17
Communication Equipment -58.2% 2
Computer Systems -64.4% 4
Consumer Electronics -51.2% 1
Data Storage -43.6% 1
Drug Manufacturers - Specialty & Generic -50.3% 6
Education & Training Services -63.3% 68
Electronic Gaming & Multimedia -48.9% 5
Gold -50.2% 3
Household & Personal Products -49.6% 9
Information Technology Services -53.0% 14
Internet Content & Information -50.8% 12
Media - Diversified -45.3% 4
Medical Care -58.2% 11
Personal Services -66.9% 10
Publishing -56.8% 4
Semiconductor Equipment & Materials -46.2% 4
Software - Application -44.8% 1
Software - Infrastructure -46.3% 4
Specialty Retail -52.6% 15
Staffing & Outsourcing Services -52.3% 2
Telecom Services -40.1% 2
Truck Manufacturing -40.7% 1
#N/A -59.3% 70
Grand Total -57.4% 325


Hmm, we see Education services is at top of list.  We also have a bunch of n/a... what are those?


N/A Stocks

Stock  Initial Price   End Price  Percent Change
ACHI                 5.38              1.76 -67.3%
MSB               15.03              8.96 -40.4%
ACHI                 5.66              2.39 -57.8%
MSB               14.96              6.20 -58.6%
ACHI                 5.83              2.65 -54.5%
MSB               17.15              4.35 -74.6%
ACHI                 6.10              2.50 -59.0%
MSB               16.80              4.40 -73.8%
ACHI                 5.85              2.62 -55.2%
MSB               16.60              4.52 -72.8%
CJREF               17.64              7.59 -57.0%
GNI               43.87           13.90 -68.3%
GNI               51.07           23.77 -53.4%
INTX                 8.24              4.00 -51.5%
GNI               48.93           20.11 -58.9%
CREG                 2.66              1.23 -53.8%
INTX                 8.44              3.91 -53.7%
GNI               55.92           23.45 -58.1%
CREG                 2.44              1.38 -43.4%
INTX                 8.66              3.50 -59.6%
GNI               52.63           23.80 -54.8%
INTX                 8.95              3.81 -57.4%
GNI               51.47           19.33 -62.4%
INTX                 8.13              4.71 -42.1%
GNI               51.43           20.32 -60.5%
INTX                 9.19              4.43 -51.8%
GNI               55.40           17.47 -68.5%
DXM               19.95              9.92 -50.3%
GNI               55.93           17.41 -68.9%
GNI               60.69           19.30 -68.2%
BODY                 7.83              3.12 -60.2%
POOSF                 1.26                   -   -100.0%
GNI               64.99           21.82 -66.4%
POOSF                 1.42                   -   -100.0%
POOSF                 5.19                   -   -100.0%
BODY                 9.98              5.38 -46.1%
GTAT                 6.74              3.66 -45.7%
GTAT                 7.92              3.30 -58.3%
GTAT                 9.02              3.15 -65.1%
GTAT                 8.75              3.27 -62.6%
GTAT                 7.11              3.03 -57.4%
GTAT                 7.30              3.36 -54.0%
GTAT                 8.95              5.12 -42.8%
DELL               16.18              9.24 -42.9%
GTAT               11.39              6.34 -44.3%
GTAT               13.64              5.02 -63.2%
PWER                 7.80              4.47 -42.7%
GTAT               15.30              4.75 -69.0%
ASTX                 3.26              1.81 -44.5%
PWER                 8.13              3.83 -52.9%
GTAT               11.53              4.30 -62.7%
SCEI                 4.12              1.61 -60.9%
PWER                 7.69              3.81 -50.5%
PWER                 8.44              4.64 -45.0%
SCEI                 6.79              1.64 -75.8%
PWER                 9.07              4.67 -48.5%
LINC               15.15              8.99 -40.7%
SCEI                 6.59              1.30 -80.3%
PWER               10.39              4.53 -56.4%
LINC               14.55              8.70 -40.2%
LPS               31.17           16.78 -46.2%
COCO                 5.44              2.95 -45.8%
NEP                 5.32              2.33 -56.2%
YLWPF.PK                 6.38              0.18 -97.2%
SCEI                 6.98              1.06 -84.8%
PWER               10.13              3.83 -62.2%
LINC               15.13              7.96 -47.4%
LPS               29.80           14.85 -50.2%
COCO                 5.12              2.15 -58.0%
NEP                 5.81              2.00 -65.6%


So let me manually change a few:

Stock Average Change Count Since 2011
Aerospace & Defense -48.6% 3
Apparel Manufacturing -54.3% 6
Apparel Stores -40.6% 3
Auto Parts -51.2% 7
Biotechnology -58.1% 36
Business Services -60.9% 17
Chinese -54.7% 4
Communication Equipment -58.2% 2
Computer Systems -64.4% 4
Consumer Electronics -51.2% 1
Data Storage -43.6% 1
Diversified Investments -63.0% 16
Drug Manufacturers - Specialty & Generic -50.3% 6
Education & Training Services -62.1% 73
Electronic Components -56.8% 11
Electronic Gaming & Multimedia -48.9% 5
Gold -50.2% 3
Household & Personal Products -49.6% 9
Information Technology Services -53.0% 14
Internet Content & Information -50.8% 12
Media - Diversified -45.3% 4
Medical Care -58.4% 16
Personal Services -66.9% 10
Publishing -56.8% 4
Semiconductor Equipment & Materials -46.2% 4
Software - Application -51.6% 7
Software - Infrastructure -46.3% 4
Specialty Retail -52.6% 15
Staffing & Outsourcing Services -52.3% 2
Telecom Services -40.1% 2
Truck Manufacturing -40.7% 1
#N/A -63.2% 23
Grand Total -57.4% 325

Ok.  Now let us ratio this against overall counts.  Then we are looking for industries significantly worse than 11% stinker rate.


Industry Overall Count Stinker Count Stinker Rate
Advertising Agencies 2 0 0.0%
Aerospace & Defense 121 3 2.5%
Agricultural Inputs 15 0 0.0%
Airlines 13 0 0.0%
Apparel Manufacturing 24 6 25.0%
Apparel Stores 51 3 5.9%
Auto Parts 11 7 63.6%
Biotechnology 139 36 25.9%
Broadcasting - Radio 5 0 0.0%
Business Equipment 22 0 0.0%
Business Services 170 17 10.0%
Chinese 6 4 66.7%
Communication Equipment 88 2 2.3%
Computer Distribution 1 0 0.0%
Computer Systems 25 4 16.0%
Conglomerates 1 0 0.0%
Consumer Electronics 25 1 4.0%
Copper 25 0 0.0%
Data Storage 55 1 1.8%
Diagnostics & Research 18 0 0.0%
Diversified Investments 50 16 32.0%
Drug Manufacturers - Specialty & Generic 118 6 5.1%
Education & Training Services 227 73 32.2%
Electronic Components 35 11 31.4%
Electronic Gaming & Multimedia 57 5 8.8%
Engineering & Construction 74 0 0.0%
Gold 13 3 23.1%
Health Information Services 1 0 0.0%
Home Furnishings & Fixtures 2 0 0.0%
Household & Personal Products 102 9 8.8%
Information Technology Services 75 14 18.7%
Internet Content & Information 82 12 14.6%
Leisure 13 0 0.0%
Luxury Goods 20 0 0.0%
Marketing Services 2 0 0.0%
Media - Diversified 41 4 9.8%
Medical Care 80 16 20.0%
Medical Devices 3 0 0.0%
Medical Instruments & Supplies 6 0 0.0%
Metal Fabrication 2 0 0.0%
Oil & Gas E&P 23 0 0.0%
Oil & Gas Equipment & Services 9 0 0.0%
Oil & Gas Refining & Marketing 9 0 0.0%
Packaged Foods 12 0 0.0%
Pay TV 8 0 0.0%
Personal Services 58 10 17.2%
Pharmaceutical Retailers 46 0 0.0%
Publishing 11 4 36.4%
Recreational Vehicles 4 0 0.0%
Resorts & Casinos 4 0 0.0%
Restaurants 5 0 0.0%
Semiconductor Equipment & Materials 103 4 3.9%
Semiconductors 17 0 0.0%
Software - Application 73 7 9.6%
Software - Infrastructure 107 4 3.7%
Specialty Retail 84 15 17.9%
Staffing & Outsourcing Services 43 2 4.7%
Telecom Services 141 2 1.4%
Tobacco 33 0 0.0%
Truck Manufacturing 10 1 10.0%
#N/A 379 23 6.1%
Grand Total 2999 325 10.8%

Ok. I think this is the motherlode.  One can look at it two ways.  Industries that have a high percentage of stinkers (avoid those) and industries that have no stinkers, but still a large count (good candidates).

I am not going to go through them all.  We have already discussed many (Chinese, FPE and the Trusts).  Biotech seems like one to definitely avoid.  Electronic components is just GTAT. Smattering of retail.

On flip side telecom services, Semiconductors, software and aeospace/defense have been solid.

Time for lunch. Have a great day.


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