How do you deal with a risk that has never been seen before?? I’m going to focus on financial risks here, but clever people can generalize to other classes of human risk, like war and terrorism.
By “emergent phenomena” I mean what happens when people act as a group pursuing the same strategy.? One person doing a given strategy means nothing.? But when millions do it, that can be significant.? Same for corporations, but the numbers are lower, because corporations are far bigger economically than the average household.
Here are some examples of emergent phenomena:
1987 — Strategies for dynamic hedging became a large enough part of the market that the market became unstable, where parties would buy as the market rose, and sell as the market fell.
Tech stocks were the only place to be 1998-2000, until they weren’t 2000-2003.
Too much hedge fund money was playing the quantitative value plus momentum trade in 2007.? Many players borrowed money to goose returns in 2006-7.? It blew up in August 2007.
The fear of not getting “free money” caused many to overinvest in residential real estate 2004-7, until the free money was not only not free, but billing you for past indiscretions.
There was a frenzy among commercial real estate investor toward the end of the 1980s, which bid prices up amid more buying power from then-cheap commercial mortgage debt, leading to an overshoot, and fall in property value in the early 1990s.
In 2005, the CDO Correlation Trade led to a panic in the corporate bond market, and in auto stocks.
Into the late 1980s, Japanese households and some foreigners plowed progressively more liquid capital into the Japanese stock and warrant markets.? That was the peak, and few if any have made their money back.
Emergent phenomena stem from:
Many people and institutions doing the same thing at the same time.
Using debt to substitute for equity in a trade that has become a “sure thing.”
Multiple companies and industries pursuing the essentially same trade, but in different corners of the markets.? (Think of the real estate bubble.? There were so many different angles that the bulls played: mortgage insurance, financial guaranty, subprime loans and derivatives thereof, weakened lending standards on prime loans, etc.)
And it is more intense when economic agents borrow short-term to finance their efforts, because when things go wrong, the feedback loop is quick.
Everyone runs to the exits in a burning theater, and so, fewer get out amid the struggle, than if everyone patiently walked out.? In financial terms, this is why markets are more volatile than expected, particularly on the downside.? Too many people want to sell in a panic, after having pursued a well-known strategy that had been successful for quite a while.
But no tree grows to the sky.? The intelligent investor notes several things:
Where is the most new debt being applied, and to increasingly little effect?
What fad are players investing in, that you think can’t be maintained long-run?
What is happening that would not be happening if it were not for price momentum?
Where are players relying on price appreciation or else their levered positions will collapse?
Where is money being borrowed short-term to fund long-term assets?
People are prone to imitate past success, even when a rational person would conclude that it doesn’t make any sense to borrow money and buy an asset at a high price.? It’s easier to imitate than to think independently.
In the present market, I see large increases in government debt and student loans.? Beyond that, there is the income craze in investing.? Don’t look at the yield; look at the underlying business.
Be wary.? The stock market has run hard the last ~5 years, and I see valuation-sensitive investors retreating.? Even with bond rates low, that doesn’t mean stocks are better.
A few days ago, I was reading Felix Salmon’s piece Pension politics.? (Nice title, the type that Tadas likes — the shorter the better.)? I wrote a short response in the comments, largely agreeing with Felix.? Here it is:
Here are the facts:
1) DB pension funding accounting rules are more liberal than life insurance accounting rules.
2) Pension actuaries have long assumed investment earnings rates well in excess of what can be achieved.
3) Longevity has long been increasing for those that buy annuities, and take pensions.
4) Average people are lousy investment managers, they panic and get greedy at the wrong times. Pension asset managers aren?t great, but they largely avoid panic & greed.
5) The PBGC is horribly underfunded, as are most municipal pension plans.
6) Overseas, things can be bad, like Poland, Argentina, India, etc. In those cases being on your own is better. Our custodial systems here are pretty good. (Please ignore MF Global.)
7) Fees are generally too high in asset management, and most people should go for passive management, or a few clever value investors.
8 ) Hedge funds, commodities, and private equity are not the answer. Analyze the returns on an dollar-weighted [IRR] basis and they will be much lower than the illustrated buy & hold returns.
9) Highly paid workers lose out in bankruptcy. Multi-employer trusts are prone to a run on the pension plan if a major employer goes BK.
10) the average person is at best a budgeter, and not an investor. That said, buying inflation insurance is very expensive, if you can achieve it at all.
Summary: in general, you are right, Felix, but it is a question of cost to the corporations funding the DB plans. I think the cost is worth it, but maybe it needs to be shared with workers, taking pre-tax dollars to buy more future DB plan payments. How many people would do that? Sadly, not many.
Pensions have always been a bit of a compromise.? In order to get employers to create Defined Benefit [DB] pensions, the government allowed for funding methods that were liberal — a plan sponsor wouldn’t have to put in as much at the beginning; it can catch up over time.? More than that, the assumptions that DB pensions could use were far more liberal than what life insurers could use for similar contingencies.? Life insurers had to use best estimates and then add risk margins.? Pensions could dream of returns, with no risk margins.
The 401(k) was an accident.? It was tossed into a much larger bill, and no one noticed.? After passage, some benefits consultants, notably Ted Benna, found ways to use it, creating the boom in Defined Contribution [DC] plans.
Corporations initially added DC plans to their DB plans, but as the 90s ended, and equity performance sank, many terminated their DB plans.? Part of it was the asset markets, but another part of it was aging workforces, because the funding rules were weak (unlike life insurance).? Sponsors realized that they would have to spend a lot more on DB plans in the future than they would otherwise want to.? Now stingy corporations cut back on their DC matches, or accept kickbacks out of investment manager fees.
There are two great virtues in defined benefit plans: 1) Investing is handled by professionals.? 2) Level payments are made.? Most people can budget.? Few can invest.? Yes, there is the problem of inflation, should it occur, but pensioners should have assets outside of their pension to deal with inflation.? They need longevity insurance, so that they avoid outliving their assets.
Though it might be hard managing a fixed income versus uncertain inflation over an uncertain lifespan, it is much harder to manage a lump sum over a full retirement.? When finances are tight, it is much harder to make the right decisions.? Hope biases average investors in favor of taking chances, whether the market favors taking chances or not.
Add in the troubles with defaults of DB plan sponsors, and significant benefits can be lost, particularly if you have been highly paid.
I would want to tell most asset allocators that there is little to no magic in alternative investments.? The alternatives face the same risk factors as ordinary investments, and they are not underinvested by pension investors.
Closing Notes
Sorry, I forgot to blame the IRS for limiting overfunding for tax reasons, when the overfunding was really funding, and would have been useful today.
Even without the introduction of the 401(k), corporations would have cut back on DB pensions because of costs.? A lot of that was due to bad funding methods, but without those bad funding methods, many DB plans would never have been done.
Just be grateful you don’t live in other parts of the world, where governments are more graspy, and pension assets are a target to plug holes in the government deficit.
My main industry model is illustrated in the graphic. Green industries are cold. Red industries are hot. If you like to play momentum, look at the red zone, and ask the question, ?Where are trends under-discounted?? Price momentum tends to persist, but look for areas where it might be even better in the near term.
If you are a value player, look at the green zone, and ask where trends are over-discounted. Yes, things are bad, but are they all that bad? Perhaps the is room for mean reversion.
My candidates from both categories are in the column labeled ?Dig through.?
You might notice that? I have no industries from the red zone. That is because the market is so high. I only want to play in cold industries. They won?t get so badly hit in a decline, and they might have some positive surprises.
If you use any of this, choose what you use off of your own trading style. If you trade frequently, stay in the red zone. Trading infrequently, play in the green zone ? don?t look for momentum, look for mean reversion. I generally play in the green zone because I hold stocks for 3 years on average.
Whatever you do, be consistent in your methods regarding momentum/mean-reversion, and only change methods if your current method is working well.
Huh? Why change if things are working well? I?m not saying to change if things are working well. I?m saying don?t change if things are working badly. Price momentum and mean-reversion are cyclical, and we tend to make changes at the worst possible moments, just before the pattern changes. Maximum pain drives changes for most people, which is why average investors don?t make much money.
Maximum pleasure when things are going right leaves investors fat, dumb, and happy ? no one thinks of changing then. This is why a disciplined approach that forces changes on a portfolio is useful, as I do 3-4 times a year. It forces me to be bloodless and sell stocks with less potential for those with more potential over the next 1-5 years.
I like some technology stocks here, some industrials, some consumer stocks, particularly those that are strongly capitalized.
I?m looking for undervalued industries. I?m not saying that there is always a bull market out there, and I will find it for you. But there are places that are relatively better, and I have done relatively well in finding them.
At present, I am trying to be defensive. I don?t have a lot of faith in the market as a whole, so I am biased toward the green zone, looking for mean-reversion, rather than momentum persisting. The red zone is pretty cyclical at present. I will be very happy hanging out in dull stocks for a while.
That said, some dull companies are fetching some pricey valuations these days, particularly those with above average dividends. This is an overbought area of the market, and it is just a matter of time before the flight to relative safety reverses.
The Red Zone has a Lot of Financials; be wary of those. I have been paring back my insurers, but I have been adding to P&C reinsurers.? What I find fascinating about the red momentum zone now, is that it is loaded with cyclical companies.
In the green zone, I picked almost all of the industries. If the companies are sufficiently well-capitalized, and the valuation is low, it can still be an rewarding place to do due diligence.
Will cyclical companies continue to do well?? Will the economy continue to limp along, or might it be better or worse?
But what would the model suggest?
Ah, there I have something for you, and so long as Value Line does not object, I will provide that for you. I looked for companies in the industries listed, but in the top 5 of 9 balance sheet safety categories, and with returns estimated over 12%/year over the next 3-5 years. The latter category does the value/growth tradeoff automatically. I don?t care if returns come from mean reversion or growth.
But anyway, as a bonus here are the names that are candidates for purchase given this screen. Remember, this is a launching pad for due diligence, not hot names to buy.
I?ve loosened my criteria a little because the market is so high, but I figure I will toss out lot when I do my quarterly evaluation of the companies that I hold for clients and me.
Strategy One: “Consistent Losses, with Occasional Big Gains when the Market is Stressed”
Strategy Two: “Consistent Gains, with Total Wipe-out Risk When Market is Highly Stressed”
How do these two strategies sound to you?? Not too appealing?? I would agree with that.? The second of those strategies was featured in an article at Bloomberg.com recently — Inverse VIX Fund Gets Record Cash on Calm Market Bet.? And though the initial graph confused me, because it was the graph for the exchange traded note VXX, which benefits when the VIX spikes, the article was mostly about the inverse VIX?exchange traded note XIV.
Why would someone pursue the second strategy?? Most of the time, it makes money, and since January 2011 we haven’t a horrendous market event like the one from August 2008 through February 2009, it makes money.
I would encourage you to look at the decline in the second half of 2011, where it fell 75% when the VIX briefly burped up to around 50.? But given the amazing comeback as volatility abated, the lesson that some investors drew was this: “Volatility Spike? Time to buy XIV!”? And that explains the article linked above.
You might remember a recent book review of mine — Rule Based Investing.? In that review, I made the point that those that sell insurance on financial contracts tend to win, but it is a volatile game with the possibility of total loss.? To give another example from the recent financial crisis: most of the financial and mortgage insurers in existence prior to 2007 are gone.? Let me put it simply: though financial risks can be insured, the risks are so volatile that they should not be insured.? You are just one colossal failure away from death, and that colossal failure will tend to come when everyone is certain that it can’t come.
But what of the first strategy?? How has it done?
Wow!? Look at the returns over the last few weeks!? Rather, look at a strategy that consistently loses money because it rolls futures contracts for the VIX where the futures curve is upward-sloping almost all the time, leading to buy high, sell low.
Does it pay off in a crisis?? Yes.? Can you use it tactically?? Yes.? Can you hold it and make money?? No.
Back to the second strategy.? People are putting money into XIV because they “know” that implied volatility always mean-reverts, and so they will make easy money after a volatility spike.? But what if they arrive too early, and volatility spikes far higher than expected?? Worse yet, what if Credit Suisse goes belly-up in the volatility?? After all, it is an exchange-traded note where owners of XIV are lending money to Credit Suisse.
Back to Basics
Do I play in these markets?? No.
Do I understand them?? Mostly, but I can’t claim to be the best at this.
What if I try both strategies at the same time?? You will lose.? You are short fees and trading frictions.
What if I short both strategies at the same time?? Uncertain. It comes down to whether you can hold the shorts over the long term without getting “bought in” or panic when one side of the trade runs the wrong way.
Recently, someone pinged me to speak to CFA Institute, Baltimore, where he wanted to talk about “not all correlations of risky assets go to one in a crisis” and pointed to volatility investing as the way to improve asset allocation.? Sigh.? I’m inclined to say that “you can’t teach a Sneech.”
I favor simplicity in investing, and think that many exchange traded products will harm investors on average because the investors do not understand the underlying economics of what they own, while Wall Street uses them as a cheap way to hedge their risk exposures.
There may be some value to speculators in using “investments” like strategy one for a few days at a time.? But holding for any long time is poison.? Worse, if you are accidentally right, and the world comes to an end — this is an exchange-traded note, and the bank you lent to will be broke.? That will also kill strategy two.
So, my advice to you is this: avoid either side of this trade.? Stick with simple investments that do not invest in futures or options.? Complexity is the enemy of the average investor.? I can understand these investments and they don’t work for me.? You should avoid them too.
I would encourage you to have a read of the 2014 Baltimore Business Review.? Produced by the CFA Institute? — Baltimore, and Towson University, it? is a great example of how academics and practitioners can work together.? Here is my article, reformatted so that it looks better on my blog:
Differences in US States? Unemployment over the Last 36 Years
Unemployment is often treated as a national issue, but unemployment is often driven by regional or industry sector issues. This article pries apart the causes of unemployment since 1976, state-by-state.
Though there is a national component to every US state?s unemployment level, it is notable that local factors often dominate national trends. Here are some examples:
North Dakota has an energy boom amid increasing unemployment following the housing bust in 2008.
Texas had increasing unemployment in the mid-1980s as energy prices fell dramatically, in the midst of an economic boom.
Coastal economies benefited during the housing boom (pre-2008), and were punished in the bust ? this is parallel to the US economy as a whole, but more severe.
The Rust Belt prospered slowly in the early 1980s as the rest of the nation began to prosper rapidly.
The rest of this article will explain the causes of unemployment over the last 36 years, related to how connected a state is to the rest of the US economy, and how well the industry mix in a given state is doing.
Data & Method
Unemployment data for each state and the US as a whole was obtained from the St. Louis Federal Reserve?s Federal Reserve Economic Data (FRED) database. The data covers the period from 1976 to August 2013. Ordinary least squares regression was used to calculate how sensitive unemployment rates were in each state relative to overall US unemployment rates. The equation looks like this:
Ustate,t = ?state + ?stateUUS,t + ?state,t
The intuition behind this equation is that the unemployment rate of a given state can be explained by the amount that it varies in proportion to the unemployment rate for the US as a whole (the beta term), a fixed difference (the alpha term), and the error term. Here were the results by State:
State
Alpha
Beta
Alpha SD
Beta SD
R-squared
Alpha T-stat
Beta T-Stat
Correlation Group
Michigan
???? (2.50)
?1.67
??????? 0.25
????? 0.04
81.46%
?????????? (9.98)
???????? 17.82
3
Nevada
???? (2.44)
?1.42
??????? 0.22
????? 0.03
80.77%
???????? (11.22)
???????? 12.80
2
Indiana
???? (2.47)
?1.35
??????? 0.20
????? 0.03
81.90%
???????? (12.42)
???????? 11.63
3
Alabama
???? (1.80)
?1.32
??????? 0.23
????? 0.03
75.95%
?????????? (7.72)
????????? 9.06
6
West Virginia
????? 0.28
?1.24
??????? 0.48
????? 0.07
40.15%
??????????? 0.59*
????????? 3.42
6
Ohio
???? (1.10)
?1.23
??????? 0.17
????? 0.03
83.93%
?????????? (6.49)
????????? 9.21
3
Rhode Island
???? (1.03)
?1.17
??????? 0.26
????? 0.04
65.95%
?????????? (3.88)
????????? 4.33
5
Illinois
???? (0.51)
?1.17
??????? 0.14
????? 0.02
87.48%
?????????? (3.64)
????????? 8.08
3
Tennessee
???? (0.86)
?1.17
??????? 0.15
????? 0.02
85.25%
?????????? (5.65)
????????? 7.29
3
North Carolina
???? (1.44)
?1.14
??????? 0.19
????? 0.03
77.35%
?????????? (7.40)
????????? 4.85
2
Oregon
???? (0.00)
?1.13
??????? 0.17
????? 0.03
80.95%
?????????? (0.03)*
????????? 5.11
3
South Carolina
???? (0.72)
?1.13
??????? 0.18
????? 0.03
79.11%
?????????? (3.94)
????????? 4.69
2
California
????? 0.20
?1.12
??????? 0.18
????? 0.03
79.43%
??????????? 1.14*
????????? 4.61
5
Washington
????? 0.07
?1.09
??????? 0.15
????? 0.02
83.84%
??????????? 0.49*
????????? 3.98
6
Florida
???? (0.53)
?1.07
??????? 0.18
????? 0.03
78.09%
?????????? (2.93)
????????? 2.80
5
Pennsylvania
???? (0.33)
?1.07
??????? 0.14
????? 0.02
85.43%
?????????? (2.40)
????????? 3.52
6
Wisconsin
???? (1.30)
?1.07
??????? 0.17
????? 0.03
78.88%
?????????? (7.49)
????????? 2.57
3
Arizona
???? (0.50)
?1.06
??????? 0.18
????? 0.03
77.62%
?????????? (2.81)
????????? 2.28
2
Kentucky
????? 0.20
?1.05
??????? 0.20
????? 0.03
72.97%
??????????? 1.00*
????????? 1.56*
3
New Jersey
???? (0.10)
?1.01
??????? 0.21
????? 0.03
68.87%
?????????? (0.47)*
????????? 0.32*
5
Mississippi
????? 1.57
?0.99
??????? 0.27
????? 0.04
57.37%
??????????? 5.86
???????? (0.29)*
3
Missouri
???? (0.28)
?0.97
??????? 0.12
????? 0.02
86.47%
?????????? (2.35)
???????? (1.54)*
4
Georgia
???? (0.22)
?0.96
??????? 0.16
????? 0.02
78.07%
?????????? (1.37)*
???????? (1.81)*
2
Delaware
???? (0.83)
?0.95
??????? 0.20
????? 0.03
67.93%
?????????? (4.05)
???????? (1.73)*
1
Connecticut
???? (0.41)
?0.91
??????? 0.23
????? 0.03
61.44%
?????????? (1.80)*
???????? (2.79)
5
Utah
???? (0.60)
?0.88
??????? 0.15
????? 0.02
76.69%
?????????? (3.91)
???????? (5.13)
3
Idaho
????? 0.36
?0.88
??????? 0.20
????? 0.03
65.13%
??????????? 1.77*
???????? (4.09)
6
Colorado
???? (0.01)
?0.87
??????? 0.17
????? 0.03
71.86%
?????????? (0.04)*
???????? (5.06)
4
Maine
????? 0.31
?0.87
??????? 0.19
????? 0.03
66.45%
??????????? 1.61*
???????? (4.49)
1
Massachusetts
????? 0.17
?0.86
??????? 0.24
????? 0.04
55.28%
??????????? 0.72*
???????? (3.94)
5
Minnesota
???? (0.29)
?0.82
??????? 0.12
????? 0.02
82.17%
?????????? (2.43)
???????? (9.78)
3
District of Columbia
????? 2.45
?0.81
??????? 0.18
????? 0.03
66.11%
????????? 13.40
???????? (6.86)
1
New York
????? 1.48
?0.81
??????? 0.18
????? 0.03
67.90%
??????????? 8.45
???????? (7.28)
1
Arkansas
????? 1.46
?0.79
??????? 0.18
????? 0.03
66.27%
??????????? 8.23
???????? (7.87)
6
Virginia
???? (0.30)
?0.78
??????? 0.08
????? 0.01
90.79%
?????????? (3.84)
??????? (18.90)
1
Maryland
????? 0.31
?0.78
??????? 0.12
????? 0.02
81.92%
??????????? 2.66
??????? (12.83)
1
Iowa
???? (0.17)
?0.77
??????? 0.19
????? 0.03
61.15%
?????????? (0.86)*
???????? (7.98)
3
Vermont
????? 0.06
?0.74
??????? 0.19
????? 0.03
60.28%
??????????? 0.34*
???????? (9.04)
1
Louisiana
????? 2.45
?0.73
??????? 0.38
????? 0.06
26.41%
??????????? 6.40
???????? (4.69)
6
New Hampshire
????? 0.12
?0.68
??????? 0.20
????? 0.03
52.48%
??????????? 0.60*
??????? (10.73)
1
New Mexico
????? 2.67
?0.64
??????? 0.21
????? 0.03
48.44%
????????? 12.78
??????? (11.36)
6
Montana
????? 1.84
?0.61
??????? 0.21
????? 0.03
45.25%
??????????? 8.65
??????? (12.16)
6
Oklahoma
????? 1.49
?0.59
??????? 0.22
????? 0.03
41.23%
??????????? 6.70
??????? (12.25)
3
Wyoming
????? 1.48
?0.56
??????? 0.29
????? 0.04
26.35%
??????????? 5.08
??????? (10.17)
3
Alaska
????? 4.52
?0.53
??????? 0.28
????? 0.04
25.87%
????????? 16.05
??????? (11.13)
6
Hawaii
????? 1.46
?0.52
??????? 0.27
????? 0.04
27.58%
??????????? 5.52
??????? (12.07)
1
Texas
????? 2.89
?0.52
??????? 0.19
????? 0.03
41.71%
????????? 15.10
??????? (16.90)
4
Kansas
????? 1.68
?0.48
??????? 0.13
????? 0.02
55.86%
????????? 12.53
??????? (25.79)
4
Nebraska
????? 0.61
?0.46
??????? 0.13
????? 0.02
54.10%
??????????? 4.62
??????? (27.48)
3
South Dakota
????? 0.95
?0.45
??????? 0.11
????? 0.02
63.95%
??????????? 8.93
??????? (34.82)
3
North Dakota
????? 1.49
?0.39
??????? 0.18
????? 0.03
31.54%
??????????? 8.14
??????? (22.19)
6
* Indicates not statistically significant from zero for alpha, and one for beta at a 5% level.
The difference in sensitivity to the US unemployment rate is considerable by state. If the unemployment rate rose 1% in the US, Michigan?s unemployment rate would tend to rise 1.67%, while the North Dakota?s unemployment rate would only tend to rise 0.39%.
The states were then divided into five beta groups, symmetric around 1.0, with a width of 0.2 for the three middle groups. On a map, it looks like this:
The highest sensitivity states to US unemployment rates are largely found in states with high exposure to the Auto and Gambling industries. When times are bad, people shepherd their money more carefully. They cut back on buying new cars, and gambling. High sensitivity states tend to have a lot of gearing to industrial activity, which tends to be more boom-bust than other economic activity. Average sensitivity states tend to have balanced economies, reflecting a mix of business similar to that of the US as a whole. Low-sensitivity states tend to have a large amount agriculture, resource extraction, financial sector concentration, or Federal government work.
Note that the recent boom and bust would argue that financials are more cyclical than previously believed, but that was during a small period during the study period.? The same applies in reverse to agriculture and resource extraction, which benefited from increased demand for raw materials from the developing world, making these industries appear less cyclical than previously believed.
Betas reflect the overall sensitivity to moves in US unemployment rates from 1976 to 2013, but the correlation of the residuals of the states highlight hidden factors that were influential in unemployment rate movements.
Typically, the factors stemmed from the economic sectors prominent in each group of states, as their profitability waxed and waned.
Starting with ten groups of states randomly divided, the groups were iteratively adjusted, combining groups that were highly correlated with each other until there were no more improvements possible, ending with six groups. Here is the average correlation matrix:
Avg Corr
1
2
3
4
5
6
Group 1
40%
Group 2
-4%
43%
Group 3
-34%
-15%
43%
Group 4
-37%
12%
24%
36%
Group 5
41%
26%
-51%
-22%
61%
Group 6
-14%
-43%
30%
-5%
-46%
50%
And here is the map identifying the groups:
Groups 1, 2 and 5 correlate strongly internally and moderately among each other. The same is true for 3, 4 and 6. The rest of the group correlations are weak if not negative.
Groups 3, 4, and 6 cover the center of the US. They have proportionately more economic sectors in agriculture, energy, consumer cyclicals, and basic materials.? Much of the area is rural. Groups 1, 2 and 5 cover the coasts of the US and are more heavily urbanized. Their economic sectors have a greater proportion of finance, healthcare, and technology.? Post-2007 unemployment was relatively worse in groups 1, 2 and 5 versus the other groups, because they were part of the hot housing markets, and lost more construction jobs as a result.
Here is a graph of the average unemployment residuals for the six correlation groups over the 36-year study period:
Description of the Correlation Groups
Group 1 ? composed of Maryland, other Mid-Atlantic States, New England and Hawaii, this ? had high unemployment relative to the rest of the US in 1976 and 1997, and low unemployment in 1987. It has high relative exposure to the consumer noncyclicals and financials sectors, and low relative exposure to energy and technology. The high weight in financials helps explain the employment gains from 1976 to 1987, as financial companies benefited from falling interest rates, rising equity markets, and expanding product offerings.
Group 2 ? composed of the Carolinas, Georgia, Arizona and Nevada ? had high unemployment relative to the rest of the US in 2011, and low unemployment in 1984 and 1991. It has a lot of relative exposure to the consumer noncyclicals and utilities sectors, and low relative exposure to energy, financials, and technology.? During the mid-1980s to early 1990s, this group benefited from the growth in demand for noncyclical goods from the Baby Boomers. After the popping of the financial bubble in 2008, weakness in construction and gambling in Arizona and Nevada led to higher levels of unemployment.
Group 3 ? composed of the Midwest, parts of the South, Utah and Oregon ? had high unemployment relative to the rest of the US in 1976 and 1992, and low unemployment in 1986. It has high relative exposure to the consumer cyclicals and noncyclicals and basic materials sectors, and low relative exposure to energy and technology. The US economy as a whole peaked and troughed along with group 3, which makes sense given their relatively large exposure to cyclical sectors.
Group 4 ? composed of Texas, Missouri, Kansas and Colorado ? had high unemployment relative to the rest of the rest of the US in 1987 and 2003, and low unemployment in 1976. It has a lot of relative exposure to the energy and utilities sectors, and low relative exposure to financials and technology. Performance of the energy sector is the critical factor here ? it was relatively strong in the mid-to late 1970s, but weak after oil prices bottomed out in the mid-1980s and late 1990s.
Group 5 ? composed of the densely populated coastal states of California, Florida, New Jersey, Massachusetts, Connecticut and Rhode Island ? had high unemployment relative to the rest of the rest of the US in 1976, 1992 and 2012, and low unemployment in 1986. It has a lot of relative exposure to the healthcare and technology sectors, and low relative exposure to energy and consumer noncyclicals. In the early 1990s, the aerospace industry in California went bust while the commercial property markets were at the deepest point of their slump. Most of the rest of the unemployment cyclicality can be attributed to the more cyclical nature of the industries in this group ? an amplified version of the US economy.
Group 6 looks like a bunch of leftovers, but it is not.? Composed of states in the Northwest and Alaska, New Mexico, Louisiana, Arkansas and Alabama, West Virginia and Pennsylvania, this group had high unemployment relative to the rest of the rest of the US in 1987, and low unemployment in 1976 and 2009.? It has a lot of relative exposure to the agriculture and basic materials sectors, and low relative exposure to financials. The stagflation of the mid-1970s benefited agriculture and basic materials, as did growth in demand from emerging markets in 2009. Those factors were
absent in 1987, as financial firms were booming.
Maryland?s unemployment rates have held down well being next to Washington, DC. The growth in the US government during the last 10 years has supported employment in Maryland. The grand question to ponder is what would ever happen to Maryland, Washington, DC and Virginia if significant cuts were made to Federal payrolls?
Conclusion
There are two main conclusions:
1) State level unemployment is a result of sensitivity to US unemployment levels and the mix of local industries. Policymakers should know how sensitive their state is to the national economy, and what industries are doing well or poorly before taking credit for low unemployment rates. More often than not, the employment rates are low or high due to factors beyond the control of policymakers.
2) In general, greater employment stability exists when that industry mix is more diversified. This is something policymakers can limitedly affect. Most states have efforts to attract businesses to their states. If you want unemployment levels to be more stable, aim your efforts at attracting businesses that diversify your existing mix.
I know that much of the money management business sets target prices for buying and selling, particularly value managers, and sell-side analysts.? I don’t set target prices.? Why?
Think of what a target price means.? It says that at a certain price you are willing to exchange securities for cash (sell), or vice-versa (buy).? The trade-off between an individual security and cash is difficult to calculate.? Even if you have a really good dividend discount model, the target prices are very sensitive to model inputs.? I think the question of whether I would rather have cash or an individual stock or bond is a difficult question.
So why don’t we focus on easier questions?? It is simpler to rank stocks versus other stocks at least in broad, and bonds versus bonds.? I am not saying that you have to optimize.? You can’t be exact in ranking the desirability of stocks or bonds, but if we can’t identify a group of stocks outside the portfolio that are better than a group of stocks inside the portfolio, there is not much sense in trading.? Same for bonds.
With bonds, the tradeoff is more obvious, because you can consult yield relationships, and make all of the adjustments necessary to decide whether a trade is a good one or not.? Even then, there had better be a good yield advantage after all adjustments, or the trad will not make sense.? As an example, back in the first half of 2002, I engaged in a wide number of trades that gave up some absolute yield, but improved the portfolio’s credit quality dramatically at a time when credit spreads were narrow.? Though overall yield went down, the portfolio was in better shape.? This was the opposite of what we did after 9/11 — buy distressed bonds while spreads were very wide, accepting more credit risks when it paid to do so.
Thus, most of my portfolio management is not so much “Aim for the best.”? I’m not sure I can do that.? “Aim for something better than what I currently have” is achievable.? In cases where I can find no clear improvements, sitting on my hands it the best strategy.? After all, time is on the side of a portfolio representing great relative value.
This is not to denigrate those that are better than me, like Seth Klarman.? He has a strong sense of when he would rather hold cash versus taking any risk, and so he manages value in an absolute sense, even giving back money to clients when? he doesn’t have anything to do with it.
I’m still finding some attractive assets to buy, though not many.? Later this month, I will do my formal quarterly reshaping of the portfolio, where I will trade away a few stocks I like less for those I like more.? And if I can’t find any that I like more, I don’t have to do anything, because if I’ve got a really good group of stocks, doing nothing may be the best idea of all.
This article is prompted by the following article by John Hempton of Bronte Capital.? This is not meant as a criticism of him; I have nothing but respect for him.? The article triggered memories of my own experiences with position sizing at a hedge fund.
The hedge fund I once worked for had great expertise with financial companies, and I worked for them in the boom years of the 2000s.? Our leader was bearish on depositary financials, a view that would eventually be right.? Of course “eventually right” is another way to say “wrong in the short run.”
Let me describe the problem from another angle.? When I was a corporate bond manager, I would mentally set three levels with the bonds that I held.
Spread necessary for an ordinary-sized position.
Spread necessary for a big position.
Spread necessary for a maximum position.
These spreads I would adjust for premium vs discount, optionality, and a bunch of other things.? The point is that I would always have a schedule for where I would be willing to buy more, or lighten up (sell some).? I often dealt in some of the least liquid corporate bonds, and I was patient, and even willing to break rules by holding more than 20% of a given issue.? My analysts almost always did good work, and I trusted them.
When markets are illiquid, they “trade by appointment.”? If you have a balance sheet behind you that is not worried about liquidity, you can do interesting things by buying assets that most ordinary managers won’t touch, because the issue is too small.
I came to the hedge fund after I managed corporate bonds.? In one sense, I had managed a far more complex long-only portfolio.? But being able to short creates complexities of its own.
I can’t tell you how many times at meetings at the hedge fund we had tough discussion on position sizing, more frequently on short positions. We were perpetually long quality, short market capitalization, long insurers, short banks, and long value.? Great idea, if too early. This would be an extreme example:
Boss: “This short position is killing us, it is up 50% from where we shorted it, and now we have a 6% short position, what do we do?”
Others answered in front of me, essentially suggesting no change.? He asked me personally and I said:
David: “If you had no position, and you were approaching this company today, what would you do?”
Boss: “I would short the maximum — 4%.”
David: “Then buy in 2%.”
Boss: “But that locks in the loss.”
David: “Do you want to risk locking in a bigger loss?”
The boss once said to me that I was the only one on his team that was natively a portfolio manager rather than an analyst.? (That said, I remained an analyst, while an analyst was made an assistant portfolio manager.? I think it would have been too difficult to have the insurance guy to manage the portfolio of what was a banking shop.? That said, as a corporate bond manager, I managed the financials, which were mostly banks.)
Setting position sizes on shorts is always harder than longs.? When your thesis goes wrong on a short, your risk increases, as the position size gets larger.? When it goes wrong on a long position your risk decreases, as the position size gets smaller.
As I have often said, being short is not the opposite of being long, it is the opposite of being leveraged long.? When you are short, or leveraged long, you do not fully control your trade.? The margin desk can take you out of your trade if the equity in the account gets small enough.? They are ruthless in doing so, because the margin desks at brokerages do not want to take losses.
That makes it all the more important to set a schedule of sizes on short positions.? The first question should be: at what price would I put my maximum position on?? That would help in sizing introductory and normal positions.? They would be far smaller than what most hedge funds do.
Again, the same exercise is easier in a long-only format, but the protocol is the same.? Establish introductory, normal and maximum position sizes, and hold to them.? Also put into effect the idea that analysts must give greater scrutiny to large positions.
All That Said
This is a reason I am not a fan of most hedge funds.? I believe in the funds of my former employer and those of Mr. Hempton.? But the difficulties of dealing with bad decisions with a weak balance sheet kills a lot of hedge funds.? Long only — it might survive.? But when you go long and short with leverage, the risk arises of total loss.
So don’t think you are a “cool kid” because you invest in hedge funds.? Long only does better over the long haul, because it is less risky, and compounds value.
What happens when a crisis hits?? There are demands for cash payment, and the payments can’t be made because the entities have short liabilities requiring immediate payment, and long illiquid assets that no longer can be sold for a price consistent with average market conditions.? When there are many firms for which this is true, and they rely on each other’s solvency, that creates a systemic crisis.
Whether through:
Owning long assets, and financing short, or
Using the repo market to hold long assets, thus disguising it for accounting purposes as short assets
Taking deposits, and investing long,
it creates an imbalance.? It is almost always more profitable in the short-run to finance short and lend long.? But when there is a demand for cash, such institutions are on the ropes and might not survive.? Less than half of the major American investment banks existing in 2007 were alive in 2009 to today.
But what if you were clever as a financial institution, and had liability structures that were long, or distributed the risk of what you were doing back to clients.? You would always have adequate liquidity, and would not be in danger of default for systemic reasons.
Issued guaranteed investment contracts that would be immediately payable on ratings downgrade.
Issued P&C reinsurance contracts that would be immediately payable on ratings downgrade.
Aside from that, there were badly run companies that failed but no systemic risk.? There was also AIG, which faced a call on cash from its derivatives counterparty, but not the insurance entity.
As for investment managers, they have no systemic risk.? It does not matter if Blackrock, Pimco, Fidelity and Vanguard would all fail.? Mutual fund holders would find their funds transferred to solvent entities, and any losses? they might receive are the ordinary losses they could receive if the management? firms were still solvent.
Someone lend the FSOC a brain.? Big size does not equal systemic risk.? Systemic risk stems from a call on liquidity at financial firms that borrow short and lend long for their own accounts.? That does not include asset managers and insurers, no matter how big they are.
What this says to me is that financial reform in DC is brain-dead.? (Surprised?? Nothing new.)? They have fixated on the idea that big is bad, when the real problem is asset-liability mismatches, amplified by size and connectedness.? Big banks are a problem.? Big insurers and asset management firms are not.
Imagine for a moment that the average person submitting a bracket had a 78.6% chance of getting each game right, and the maximum 10 million people sent in their brackets.? What is the likely number of correct brackets?? One.
But does the average person get more than three out of four games right?? I don’t think so.? Are there some people that are better than others so that they get games right 90% of the time?? Well, if they are 1,163 out of the ten million, on average, one of them will have a perfect bracket.
Here’s a further problem.? Every tournament has significant upsets.? Someone who has a good understanding of how good the teams are will know how to pick the most likely team to win.? It is tough to pick the upsets, and tougher to pick all of the upsets.? There is no good model for upsets, or they wouldn’t be upsets.
=-=-=-=-=-=–=-=-
As an aside, the prize is $500 million as a lump or $25 million for 40 years.? The breakeven yield rate on that is 4.21%.? Buffett knows he can beat 4.21%.
This contest is like the lottery.? If I had one piece of advice for lottery winners it would be to take the payments over time.? The discount rates on most lotteries are far higher than 4.21%, and really, taking them over time gives you a chance to learn how to manage more money then you know what to do with.? Taking the payments over time gives you the freedom to learn from mistakes.? We all make mistakes, but when we get all the money at once, we make more.
I really appreciate my readers.? Here’s an e-mail from one:
David,
Just read your recent blog post ?E-mails on Insurance.?
You made the comment that ?aside from non-sponsored ADRs no good companies trade on the pink sheets.?
Of course that is true in a general sense. I also am sure you have been inundated with lots of email taking exception to that comment.
One company I have loosely followed over time (that I came across just by chance many years ago) is Computer Services (CSVI) [www.csiweb.com]. There is no volume in the stock so institutional managers have no ability to take a position, but the firm has done a great job of growing the business while maintaining profitability (been an opportunistic acquirer of small bank processor companies) and is probably a candidate for consolidation by a Fiserv or someone like that. Anyhow, I think if you take a look at the firm, you will see that there is at least one solid company traded on the pinks (and I am sure there are others, I just don?t go fishing there).
My comment ?aside from non-sponsored ADRs no good companies trade on the pink sheets.? is an overstatement.? To prove that, I give you a list of 148 companies that:
Have been profitable for the last four fiscal years.
Are US companies
Are not ADRs
2370 companies that trade over-the-counter reduce to 148 companies — 6.24% of the whole, explaining why my overstatement is largely, but not totally correct.? I would not tell someone to look amid these companies to find good ones, but there are some good ones there.? I have listed them in declining order of market capitalization.
Company
Ticker
Sector
Industry
Mkt Cap
Dollar Volume
P/E
P/B
P/S
Belk Inc
BLKIA
09 – Services
0951 – Retail (Department & Discount)
?? 2,057.80
??????????? –
?? 12.40
???? 1.66
???? 0.51
First National Bank Alaska
FBAK
07 – Financial
0727 – Regional Banks
????? 604.00
??????????? –
?? 14.90
???? 1.23
???? 5.45
First Citizens Bancorporation,
FCBN
07 – Financial
0727 – Regional Banks
????? 572.70
???? 33.20
???? 9.60
???? 0.64
???? 1.87
Computer Services, Inc.
CSVI
10 – Technology
1036 – Software & Programming
????? 476.10
?? 146.81
?? 18.20
???? 3.80
???? 2.31
Hills Bancorporation
HBIA
07 – Financial
0727 – Regional Banks
????? 345.00
?????? 3.65
?? 13.30
???? 1.29
???? 4.03
Farmers & Merchants Bancorp
FMCB
07 – Financial
0727 – Regional Banks
????? 324.40
???? 20.85
?? 13.60
???? 1.54
???? 4.27
FRMO Corp.
FRMO
07 – Financial
0721 – Misc. Financial Services
????? 302.80
???? 23.45
?? 26.90
???? 3.66
?? 16.64
HomeFed Corporation
HOFD
02 – Capital Goods
0215 – Construction Services
????? 299.80
???? 22.83
?? 62.40
???? 1.79
???? 7.93
First Opportunity Fund, Inc.
FOFI
07 – Financial
0721 – Misc. Financial Services
????? 262.10
?? 269.95
???? 7.20
???? 0.86
?? 58.25
International Wire Group Holdi
ITWG
01 – Basic Materials
0127 – Misc. Fabricated Products
????? 255.40
?????? 2.61
?? 19.60
???? 6.69
???? 0.21
Canandaigua National Corporati
CNND
07 – Financial
0724 – Money Center Banks
????? 249.90
?????? 6.65
?? 12.20
???? 1.66
???? 3.41
Viskase Companies, Inc.
VKSC
01 – Basic Materials
0109 – Containters & Packaging
????? 237.90
?? 214.50
?? 24.10
???? 0.67
Conrad Industries, Inc.
CNRD
11 – Transportation
1118 – Water Transportation
????? 226.80
?? 249.58
???? 9.10
???? 1.95
???? 0.86
United Capital Corp.
UCAP
10 – Technology
1024 – Electronic Instruments & Controls
????? 187.40
?????? 4.80
?? 13.40
???? 1.34
???? 1.58
Isabella Bank Corp
ISBA
07 – Financial
0727 – Regional Banks
????? 184.70
???? 52.67
?? 15.50
???? 1.14
???? 3.39
Profire Energy, Inc.
PFIE
02 – Capital Goods
0209 – Construction – Supplies and Fixtures
????? 160.20
???? 98.83
?? 41.90
?? 10.81
???? 5.97
Cambridge Bancorp
CATC
07 – Financial
0727 – Regional Banks
????? 150.50
???? 59.33
?? 11.50
???? 1.47
???? 3.20
Citizens Financial Services In
CZFS
07 – Financial
0718 – Investment Services
????? 148.30
???? 24.55
?? 10.90
???? 1.64
???? 4.06
Mestek, Inc.
MCCK
02 – Capital Goods
0218 – Misc. Capital Goods
????? 144.40
?????? 0.86
???? 8.80
???? 1.03
???? 0.41
Webco Industries, Inc.
WEBC
01 – Basic Materials
0127 – Misc. Fabricated Products
????? 143.50
???? 16.95
?? 15.50
???? 0.57
???? 0.22
First Keystone Corp.
FKYS
07 – Financial
0727 – Regional Banks
????? 137.80
???? 18.75
?? 12.80
???? 1.42
???? 4.32
MVB Financial Corp
MVBF
07 – Financial
0724 – Money Center Banks
????? 135.30
???? 14.40
?? 22.10
???? 1.67
???? 5.34
First Mid-Illinois Bancshares,
FMBH
07 – Financial
0727 – Regional Banks
????? 130.30
?????? 4.40
?? 12.90
???? 1.32
???? 2.43
First Real Estate Investment T
FREVS
09 – Services
0933 – Real Estate Operations
????? 126.70
???? 13.69
?? 42.40
???? 7.73
???? 3.08
First Manitowoc Bancorp, Inc.
BFNC
07 – Financial
0730 – S&Ls/Savings Banks
????? 120.80
???? 33.30
?? 11.30
???? 1.19
???? 3.07
Peoples Financial Services Cor
PFIS
07 – Financial
0727 – Regional Banks
????? 120.40
???? 62.40
?? 14.60
???? 1.90
???? 4.37
First Farmers & Merchants Corp
FFMH
07 – Financial
0727 – Regional Banks
? ????111.20
?????? 3.30
?? 13.30
???? 1.05
???? 3.05
Yasheng Group
HERB
05 – Consumer Non-Cyclical
0509 – Crops
????? 105.50
?????? 3.88
???? 0.80
???? 0.05
???? 0.11
Farmers & Merchants Bancorp In
FMAO
07 – Financial
0727 – Regional Banks
???? ?105.10
???? 62.01
?? 11.40
???? 0.98
???? 3.37
Nova Lifestyle Inc
STVS
04 – Consumer Cyclical
0421 – Furniture & Fixtures
???????? 89.20
???? 93.77
?? 16.80
???? 2.50
???? 1.17
Golden Growers Coop
GGROU
05 – Consumer Non-Cyclical
0509 – Crops
???????? 89.10
?????? 1.44
?? 18.50
???? 2.30
???? 0.93
First Guaranty Bancshares, Inc
FGBI
07 – Financial
0727 – Regional Banks
???????? 88.20
?????? 7.01
?? 10.50
???? 1.03
???? 1.72
QNB Corp
QNBC
07 – Financial
0730 – S&Ls/Savings Banks
??? ?????83.40
???? 49.82
???? 9.70
???? 1.12
???? 2.62
CCFNB Bancorp Inc
CCFN
07 – Financial
0727 – Regional Banks
???????? 78.40
???? 26.99
?? 12.00
???? 1.05
???? 3.75
Calvin B. Taylor Bankshares, I
TYCB
07 – Financial
0727 – Regional Banks
??? ?????75.70
?????? 3.84
?? 17.80
???? 0.95
???? 5.11
Juniata Valley Financial Corp
JUVF
07 – Financial
0730 – S&Ls/Savings Banks
???????? 73.20
?????? 7.85
?? 18.80
???? 1.50
???? 4.35
Northwest Indiana Bancorp
NWIN
07 – Financial
0730 – S&Ls/Savings Banks
???????? 72.70
?????? 7.68
???? 9.80
???? 1.08
???? 2.76
Franklin Financial Services Co
FRAF
07 – Financial
0727 – Regional Banks
???????? 71.80
???? 36.33
?? 13.10
???? 0.77
???? 1.97
Rand Worldwide Inc
RWWI
10 – Technology
1036 – Software & Programming
???????? 67.60
???? 24.38
?? 41.70
???? 2.05
???? 0.85
Centrix Bank & Trust
CXBT
07 – Financial
0727 – Regional Banks
???????? 67.40
?????? 7.17
?? 12.00
???? 1.29
???? 2.26
Peoples Bancorp
PBNI
07 – Financial
0730 – S&Ls/Savings Banks
???????? 66.80
?????? 7.20
?? 21.60
???? 0.88
???? 3.59
Reserve Petroleum Co
RSRV
06 – Energy
0609 – Oil & Gas Operations
???????? 66.20
???? 20.75
?? 10.90
???? 2.05
???? 3.49
Harleysville Savings Financial
HARL
07 – Financial
0730 – S&Ls/Savings Banks
???????? 65.60
???? 19.95
?? 13.90
???? 1.10
???? 2.09
William Penn Bancorp Inc
WMPN
07 – Financial
0730 – S&Ls/Savings Banks
???????? 65.50
???? 28.80
?? 23.40
???? 1.15
???? 4.86
Kentucky Bancshares, Inc.
KTYB
07 – Financial
0727 – Regional Banks
???????? 65.30
?????? 6.00
???? 9.10
???? 0.92
???? 2.36
Community Bancorp Vermont
CMTV
07 – Financial
0727 – Regional Banks
???????? 64.50
?????? 5.31
?? 13.70
???? 1.50
???? 2.82
Hennessy Advisors Inc
HNNA
07 – Financial
0718 – Investment Services
???????? 64.30
?????? 9.81
?? 13.10
???? 2.23
???? 2.74
Monarch Cement Co
MCEM
02 – Capital Goods
0212 – Construction – Raw Materials
???????? 63.40
???? 13.42
?? 21.00
???? 0.96
???? 0.69
Armanino Foods Of Distinction
AMNF
05 – Consumer Non-Cyclical
0515 – Food Processing
???????? 63.10
???? 47.48
?? 21.90
???? 9.85
???? 2.25
Q.E.P. Co., Inc.
QEPC
02 – Capital Goods
0209 – Construction – Supplies and Fixtures
???????? 62.10
???? 17.14
???? 5.80
???? 1.08
???? 0.21
Commercial National Financial
CNAF
07 – Financial
0727 – Regional Banks
???????? 60.10
???? 17.85
?? 12.10
???? 1.33
???? 4.17
Croghan Bancshares, Inc.
CHBH
07 – Financial
0727 – Regional Banks
???????? 57.90
?????? 8.63
?? 12.80
???? 0.86
???? 2.72
Burnham Holdings Inc
BURCA
02 – Capital Goods
0209 – Construction – Supplies and Fixtures
???????? 57.20
?????? 6.66
?? 12.80
???? 1.29
???? 0.42
Standard Financial Corp.
STND
07 – Financial
0727 – Regional Banks
???????? 56.10
???? 51.56
?? 19.30
???? 0.71
???? 3.39
Choiceone Financial Services I
COFS
07 – Financial
0727 – Regional Banks
???????? 54.90
???? 13.34
?? 11.30
???? 0.90
???? 2.85
LICT Corporation
LICT
09 – Services
0915 – Communications Services
?????? ??54.00
??????????? –
???? 6.70
Capital Properties Inc
CPTP
09 – Services
0939 – Rental & Leasing
???????? 52.80
?????? 4.80
?? 34.80
?? 34.78
???? 6.86
Middlefield Banc Corp
MBCN
07 – Financial
0727 – Regional Banks
???????? 52.70
?? 101.40
???? 8.10
???? 1.00
???? 1.87
CSB Bancorp Inc (Ohio)
CSBB
07 – Financial
0730 – S&Ls/Savings Banks
???????? 52.00
???? 20.90
?? 10.10
???? 1.00
???? 2.49
Jeffersonville Bancorp
JFBC
07 – Financial
0727 – Regional Banks
???????? 51.70
???? 17.69
?? 11.80
???? 1.03
???? 2.71
Georgia-Carolina Bancshares In
GECR
07 – Financial
0727 – Regional Banks
???????? 51.70
???? 59.45
???? 7.80
???? 0.90
???? 2.78
PSB Holdings Inc (Wisconsin)
PSBQ
07 – Financial
0727 – Regional Banks
???????? 50.60
???? 10.72
???? 8.30
???? 0.90
???? 1.86
Consumers Bancorp, Inc.
CBKM
07 – Financial
0730 – S&Ls/Savings Banks
???????? 49.30
?????? 2.72
?? 14.00
???? 1.33
???? 2.86
Quality Products, Inc.
QPDC
02 – Capital Goods
0218 – Misc. Capital Goods
? ???????47.70
?????? 3.78
???? 8.30
???? 4.84
???? 1.63
Northway Financial, Inc.
NWYF
07 – Financial
0727 – Regional Banks
???????? 47.10
???? 10.26
???? 6.70
???? 1.03
???? 1.41
Granite Falls Energy LLC
GFGY
01 – Basic Materials
0103 – Chemical Manufacturing
???????? 45.90
??????????? –
?? 15.30
George Risk Industries Inc
RSKIA
09 – Services
0972 – Security Systems & Services
???????? 45.20
?????? 9.89
?? 11.40
???? 1.40
???? 4.27
F&M Bank Corp
FMBM
07 – Financial
0727 – Regional Banks
???????? 43.30
???? 11.21
???? 9.00
???? 0.84
???? 1.63
Southern Michigan Bancorp
SOMC
07 – Financial
0727 – Regional Banks
???????? 42.50
?????? 5.33
???? 9.40
???? 0.77
???? 2.15
Noble Roman’s, Inc.
NROM
09 – Services
0942 – Restaurants
???????? 42.30
???? 69.62
?? 30.90
???? 3.28
???? 5.63
Minden Bancorp Inc
MDNB
07 – Financial
0730 – S&Ls/Savings Banks
???????? 41.60
?????? 3.50
?? 12.80
???? 0.98
???? 4.07
Surrey Bancorp
SRYB
07 – Financial
0727 – Regional Banks
???????? 41.50
?????? 4.68
?? 16.50
???? 1.36
???? 3.91
Corning Natural Gas Holding Co
CNIG
12 – Utilities
1206 – Natural Gas Utilities
???????? 40.20
?????? 7.99
?? 20.40
???? 1.78
???? 1.74
Pioneer Railcorp
PRRR
11 – Transportation
1112 – Railroads
??? ?????37.00
?????? 6.72
?? 21.30
???? 2.80
???? 1.77
Ziegler Companies, Inc., The
ZGCO
07 – Financial
0718 – Investment Services
???????? 35.70
???? 27.00
?? 17.60
???? 1.10
???? 0.45
XCel Brands Inc
XELB
07 – Financial
0721 – Misc. Financial Services
???????? 35.60
?????? 0.35
???? 5.70
???? 1.04
???? 2.33
Security Federal Corporation (
SFDL
07 – Financial
0730 – S&Ls/Savings Banks
???????? 35.40
?????? 8.42
?? 13.20
???? 0.63
???? 1.14
Regency Affiliates Inc
RAFI
12 – Utilities
1203 – Electric Utilities
???????? 33.90
?????? 1.44
???? 9.00
???? 1.05
New Ulm Telecom Inc
NULM
09 – Services
0915 – Communications Services
???????? 33.50
?????? 5.90
???? 8.90
???? 0.59
???? 0.90
Heritage Bankshares, Inc.
HBKS
07 – Financial
0727 – Regional Banks
???????? 29.60
?????? 8.45
?? 14.10
???? 1.00
???? 2.79
Home Loan Financial Corporatio
HLFN
07 – Financial
0730 – S&Ls/Savings Banks
???????? 29.50
?????? 2.60
???? 8.60
???? 1.17
???? 2.82
High Country Bancorp, Inc.
HCBC
07 – Financial
0730 – S&Ls/Savings Banks
???????? 29.50
?????? 9.90
?? 15.20
???? 1.24
???? 3.15
Commercial Bancshares, Inc. \O
CMOH
07 – Financial
0727 – Regional Banks
???????? 29.10
???? 14.76
?? 10.30
???? 0.95
???? 2.06
South Street Financial Corp.
SSFC
07 – Financial
0730 – S&Ls/Savings Banks
???????? 28.70
?? 121.25
?? 28.50
???? 1.05
???? 2.29
CreditRiskMonitor.Com Inc
CRMZ
10 – Technology
1018 – Computer Services
???????? 27.90
?????? 1.75
?? 87.50
???? 6.48
???? 2.38
Smtp Inc
SMTPD
10 – Technology
1018 – Computer Services
???????? 25.80
???? 27.23
?? 20.60
?? 15.57
???? 4.46
West End Indiana Bancshares In
WEIN
07 – Financial
0730 – S&Ls/Savings Banks
???????? 25.70
?????? 7.40
?? 18.30
???? 0.80
???? 2.10
Northeast Indiana Bancorp
NIDB
07 – Financial
0730 – S&Ls/Savings Banks
???????? 25.50
?????? 6.21
???? 9.30
???? 0.92
???? 2.55
Summit Financial Services Grou
SFNS
07 – Financial
0718 – Investment Services
???????? 25.20
???? 23.80
?? 15.40
???? 2.51
?? ??0.31
First Bancorp of Indiana, Inc.
FBPI
07 – Financial
0730 – S&Ls/Savings Banks
???????? 24.90
?????? 2.85
?? 16.00
???? 0.86
???? 1.88
Spindletop Oil & Gas Co
SPND
06 – Energy
0609 – Oil & Gas Operations
???????? 24.40
?????? 3.17
???? 7.30
???? 1.28
???? 1.89
Frederick County Bancorp (MD)
FCBI
07 – Financial
0727 – Regional Banks
???????? 24.10
?????? 7.20
?? 15.80
???? 0.91
???? 1.90
Meritage Hospitality Group Inc
MHGU
09 – Services
0942 – Restaurants
???????? 24.00
?????? 3.26
???? 6.60
???? 2.35
???? 0.21
Pinnacle Bankshares Corp
PPBN
07 – Financial
0727 – Regional Banks
???????? 24.00
?????? 7.95
?? 17.90
???? 0.85
???? 1.54
CNB Financial Services Inc
CBFC
07 – Financial
0727 – Regional Banks
???????? 23.60
??????? ????-
?? 15.10
???? 0.83
???? 1.97
Investors Heritage Capital Cor
IHRC
07 – Financial
0709 – Insurance (Life)
???????? 23.50
?????? 8.28
?? 11.70
???? 0.44
???? 0.29
Trans World Corporation
TWOC
09 – Services
0912 – Casinos & Gaming
???????? 22.50
?????? 3.32
?? 12.80
???? 0.53
???? 0.63
Pinnacle Bancshares, Inc.
PCLB
07 – Financial
0727 – Regional Banks
???????? 21.70
?????? 4.46
???? 9.10
???? 0.82
???? 2.33
FFW Corporation
FFWC
07 – Financial
0730 – S&Ls/Savings Banks
???????? 21.40
?????? 6.74
???? 9.10
???? 0.93
???? 1.66
ASB Financial Corp. (OH)
ASBN
07 – Financial
0730 – S&Ls/Savings Banks
???????? 20.70
?????? 5.85
?? 13.40
???? 0.98
???? 1.96
SBT Bancorp Inc
SBTB
07 – Financial
0727 – Regional Banks
???????? 20.50
???? 21.95
?? 13.50
???? 1.06
???? 1.72
Seychelle Environmental Techno
SYEV
02 – Capital Goods
0218 – Misc. Capital Goods
???????? 20.40
???? 20.22
?? 19.80
???? 4.65
???? 3.46
Great American Bancorp
GTPS
07 – Financial
0727 – Regional Banks
???????? 19.80
?????? 2.70
?? 13.40
???? 0.80
???? 2.26
Sierra Monitor Corporation
SRMC
10 – Technology
1030 – Scientific & Technical Instruments
???????? 19.70
???? 12.68
?? 15.00
???? 2.41
???? 1.10
Logansport Financial Corp.
LOGN
07 – Financial
0724 – Money Center Banks
???????? 19.60
?????? 2.50
???? 9.00
???? 0.86
???? 2.30
Seneca-Cayuga Bancorp Inc
SCAY
07 – Financial
0724 – Money Center Banks
???????? 19.60
?????? 1.24
???? 9.50
???? 1.00
???? 1.64
Micropac Industries, Inc.
MPAD
10 – Technology
1033 – Semiconductors
???????? 18.90
?????? 3.67
?? 20.90
???? 0.96
???? 0.97
Texas Vanguard Oil Co
TVOC
06 – Energy
0609 – Oil & Gas Operations
???????? 18.60
?????? 1.31
?? 22.60
???? 1.40
???? 3.04
Issuer Direct Corp
ISDR
09 – Services
0909 – Business Services
???????? 18.30
???? 46.92
?? 20.90
???? 7.19
???? 3.26
Environmental Tectonics Corpor
ETCC
02 – Capital Goods
0203 – Aerospace and Defense
???????? 17.90
?????? 3.22
?? 21.70
???? 2.47
???? 0.55
Wells Financial Corp.
WEFP
07 – Financial
0730 – S&Ls/Savings Banks
???????? 17.80
???? 13.50
?? 13.60
???? 0.67
???? 1.99
Sono-Tek Corporation
SOTK
02 – Capital Goods
0218 – Misc. Capital Goods
???????? 17.40
???? 37.68
?? 60.00
???? 2.79
???? 1.89
DynTek, Inc
DYNE
10 – Technology
1036 – Software & Programming
???????? 17.00
?????? 0.80
???? 5.00
???? 2.23
???? 0.13
Riverview Financial Corporatio
RIVE
07 – Financial
0727 – Regional Banks
???????? 16.90
???? 12.81
?? 12.00
???? 0.63
???? 1.30
Paradise, Inc.
PARF
05 – Consumer Non-Cyclical
0515 – Food Processing
???????? 16.60
?????? 3.20
?? 18.80
???? 0.78
???? 0.66
Bank McKenney (VA)
BOMK
07 – Financial
0727 – Regional Banks
???????? 16.60
?????? 4.30
???? 9.10
???? 0.73
???? 1.55
Quaint Oak Bancorp Inc
QNTO
07 – Financial
0730 – S&Ls/Savings Banks
???????? 15.60
???? 30.88
?? 23.60
???? 0.85
???? 2.38
Greenville Federal Financial C
GVFF
07 – Financial
0730 – S&Ls/Savings Banks
???????? 15.40
?????? 2.20
?? 17.50
???? 0.82
???? 2.55
BV Financial Inc
BVFL
07 – Financial
0730 – S&Ls/Savings Banks
???????? 14.40
?????? 1.20
?? 30.00
???? 1.15
???? 2.49
Jaclyn, Inc.
JCLY
04 – Consumer Cyclical
0403 – Apparel/Accessories
???????? 13.70
?????? 2.70
?? 15.40
???? 0.62
???? 0.08
OPT-Sciences Corp
OPST
10 – Technology
1030 – Scientific & Technical Instruments
???????? 13.50
?????? 1.74
?? 12.90
???? 1.05
???? 2.04
Citizens Bancshares Corporatio
CZBS
07 – Financial
0727 – Regional Banks
???????? 13.30
?????? 1.94
?? 11.40
???? 0.40
???? 1.02
Chino Commercial Bancorp (CA)
CCBC
07 – Financial
0727 – Regional Banks
???????? 13.20
?????? 2.39
?? 19.20
???? 1.45
???? 3.09
IEH Corporation
IEHC
10 – Technology
1024 – Electronic Instruments & Controls
???????? 12.10
???? 20.74
???? 8.50
???? 1.26
???? 0.82
ITEX Corporation
ITEX
07 – Financial
0718 – Investment Services
???????? 11.60
???? 15.20
?? 10.50
???? 0.88
???? 0.72
Zynex Inc.
ZYXI
08 – Health Care
0812 – Medical Equipment & Supplies
???????? 11.20
?????? 9.67
???? 1.20
???? 0.39
Great Lakes Aviation, Ltd.
GLUX
11 – Transportation
1106 – Airline
???????? 10.50
?????? 8.07
???? 0.27
???? 0.08
Fairmount Bancorp Inc
FMTB
07 – Financial
0727 – Regional Banks
?????????? 9.80
?????? 1.01
?? 49.40
???? 0.70
???? 2.58
Solitron Devices, Inc.
SODI
10 – Technology
1033 – Semiconductors
?????????? 9.50
???? 32.63
?? 11.20
???? 0.85
???? 1.10
Repro-Med Systems, Inc.
REPR
08 – Health Care
0812 – Medical Equipment & Supplies
?????????? 7.70
?????? 3.80
?? 21.00
???? 1.62
???? 0.96
Union Electric Company
UELMO
12 – Utilities
1203 – Electric Utilities
?????????? 7.60
?????? 4.70
?? 25.40
???? 2.39
???? 2.78
Surge Components, Inc.
SPRS
10 – Technology
1024 – Electronic Instruments & Controls
?????????? 7.50
???? 10.84
???? 4.10
???? 0.74
???? 0.32
Home Financial Bancorp
HWEN
07 – Financial
0730 – S&Ls/Savings Banks
?????????? 7.50
?????? 1.68
?? 13.30
???? 0.92
???? 2.21
Alliance Distributors Holding,
ADTR
10 – Technology
1015 – Computer Peripherals
?????????? 7.50
?????? 2.70
???? 5.70
???? 1.31
???? 0.11
Community Investors Bancorp In
CIBN
07 – Financial
0730 – S&Ls/Savings Banks
?????????? 7.10
?????? 6.48
?? 73.60
???? 0.57
???? 1.15
M&F Bancorp, Inc.
MFBP
07 – Financial
0727 – Regional Banks
?????????? 7.10
?????? 4.38
???? 0.30
???? 0.65
China Industrial Steel Inc
CDNN
01 – Basic Materials
0121 – Iron & Steel
?????????? 6.60
?????? 1.38
???? 4.50
???? 0.03
FPB Financial Corp.
FPBF
07 – Financial
0730 – S&Ls/Savings Banks
?????????? 5.20
??????????? –
???? 8.90
???? 0.97
???? 1.78
NexCore Healthcare Capital Cor
NXCR
08 – Health Care
0806 – Healthcare Facilities
?????????? 5.10
?????? 0.02
???? 2.00
???? 0.45
???? 0.37
Precision Auto Care
PACI
09 – Services
0909 – Business Services
?????????? 5.00
?????? 0.17
???? 7.30
???? 0.26
???? 0.19
Scientific Industries, Inc.
SCND
10 – Technology
1030 – Scientific & Technical Instruments
?????????? 4.80
?????? 2.34
?? 12.40
???? 0.89
???? 0.68
Tidelands Royalty Trust B
TIRTZ
07 – Financial
0721 – Misc. Financial Services
?????????? 4.70
?????? 9.01
???? 9.20
???? 7.91
???? 6.73
Foxby Corp
FXBY
07 – Financial
0721 – Misc. Financial Services
?????????? 4.70
?????? 1.09
???? 6.50
???? 0.77
?? 23.62
TNR Technical, Inc.
TNRK
10 – Technology
1024 – Electronic Instruments & Controls
?????????? 3.80
?????? 4.31
?? 12.30
???? 0.99
???? 0.41
Information Analysis Incorpora
IAIC
10 – Technology
1036 – Software & Programming
?????????? 2.40
?????? 1.97
???? 1.19
???? 0.44
Microwave Filter Co., Inc
MFCO
10 – Technology
1024 – Electronic Instruments & Controls
?????????? 1.70
?????? 1.50
???? 1.03
???? 0.53
Bayou City Exploration, Inc.
BYCX
06 – Energy
0609 – Oil & Gas Operations
?????????? 1.50
?????? 0.81
???? 2.70
???? 0.73
???? 0.44
Tongli Pharmaceuticals (USA) I
TGLP
08 – Health Care
0803 – Biotechnology & Drugs
?????????? 0.90
?????? 0.01
???? 0.40
???? 0.04
???? 0.07
Lotsa little banks and tech companies.? Hey, I’m going to throw those with over $100 million of market cap into my next portfolio reshaping.? I’m still small enough as a manager to deal with small companies if they are well-managed.? This can bring me back to my microcap value days, where I invested 1992-1998.? Once I made an offer to buy more than 5% of a company, and I asked my bosses if they would have any problems if I had to make a 13F filing.? They gave me the go ahead; I made my offer and it was turned down.? Pity, because if it had worked, it would have been a great investment.
The table above is a beginning for due diligence.? I do not recommend any of the stocks there.? I do note that my reader’s stock is high on the list.
Some of these stocks could be good investments, but you would have to do the research to figure out which ones are good.? On the bright side, almost no one is analyzing these companies, so your analysis has more punch relative to company outsiders.? Insiders will still do better.
All that said, I suspect that these stocks will do well on average.
