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.