Category: Speculation

Reaching For Yield

Reaching For Yield

15 months ago I wrote a piece called Expensive High Yield ? II. ?High yield is still expensive. ?I won’t post all of the regressions, but I have re-run them. ?The results are largely the same as before. ?Yields are low, and spreads are overly tight for everything except CCC bonds.

Much of this is the result of the Fed’s low fed funds rate and quantitative easing, which forces investors to take more risk. ?Another aspect is the strong equity market.

Also, CCC bonds offering opportunity may not adjust for the loosening of covenant protections. ?There is a tendency for investors to try to maintain yield levels while letting quality & covenants sag. ?In a low interest environment, with more and more people retiring, there is a growing desire for the simplicity of yield.

My conclusion last time was this:

All of the corporate bond market is expensive relative to history, perhaps excluding CCC bonds.? That?doesn’t?mean it can?t get more?expensive, particularly if stocks continue to move upward.?? But this won?t last for more than two years; the signs of speculation are here, and that should make us cautious.

As a result, I am investing my bond strategy cautiously now.? What little yield I get comes from emerging market sovereigns.? Credit risk from corporates is small.

Well, I blew it with emerging markets; what a kick in the teeth. ?I would have been better off in high yield. ?As it is, for me and my bond clients, the strategy is?Fire and Ice. ?20% long Treasuries for deflation, 80% short credit instruments for inflation. ?So far, so good.

Be wary in this environment. ?So many are reaching for yield amid a weak economy with yields that are low relative to past trends. ?But also be aware that a rising stock market can support the corporate bond market. ?That has worked for the last two years, but it can’t work forever.

Classic: Know Your Debt Crises: This Too Shall Pass

Classic: Know Your Debt Crises: This Too Shall Pass

The following was published at RealMoney on August 6th, 2007:

Editor?s Summary

The illiquid debt instruments at the heart of the current crisis are subject to regime shifts.

  • ?We?re in a periodic repricing of illiquid debt instruments.
  • Look for the time when the bulk of the losses will be reconciled.
  • Stick with the companies that have strong balance sheets.

I appreciated Cramer’s piece Friday morning, which picks up on many themes that I have articulated for the last four years here on RealMoney.? Here are a few:

  • Hedge fund-of-funds demand smooth returns that are higher than that which a moderate quality short-term fixed-income fund can deliver.
  • This leads to the creation of hedge funds that seek yield through arbitrage strategies.
  • And the creation of hedge funds that seek yield through buying risky debts, unlevered.
  • And the creation of hedge funds that seek yield through buying less risky debts, levered.
  • And the creation of hedge funds that seek yield through buying risky debts, levered.

In the short run, yield-seeking strategies work.? If a lot of players pursue them, they work extra-well for a time, as late entrants to the trade push up the returns for early entrants, with greater demand for scarce, illiquid securities with extra yield.? Pricing grids are a necessity for such securities, because the individual securities don’t have liquid secondary markets.? The pressure of demand raises the value not only of the securities being bought, but also of those securities that are like them.? (Smart managers begin to exit then.)

I’ve been through regime shifts in the markets for collateralized debt obligations (CDOs), asset-backed securities (ABS), residential-backed securities (RMBS) and commercial mortgage-backed securities (CMBS).? Something shifts at the back of the chain that forces everything to reprice.? For example:

1989-1994: After the real estate boom of the mid-1980s, many banks, savings & loans and insurance companies get loose in their lending standards and real estate investment, leading to a crisis when rent growth can?t keep up with financing terms; defaults ensue, killing off a great number of S&Ls, some major insurance companies and a passel of medium and small banks.

Late 1991-early 1993: The adjustable-rate mortgage market, fueled by demand from ARM funds, overbids for ARMs in an effort to provide a high floating rate yield.? As the FOMC loosens monetary policy, higher than expected prepayments force losses onto the ARM funds

Late 1993-late 1994: The FOMC threatens to, and does, start raising interest rates, which throws the residential mortgage-backed market into crisis.

Mid-1998-mid-1999: Long Term Capital Management blows up, forcing all manner of exotic ABS, CMBS and RMBS into the market for bids.? The bids back up, until the entire market reprices and then tightens in the space of one year.

1998-1999: Home equity ABS blow up, as defaults threaten to, and then do, emerge at levels far higher than anticipated.? Almost no originators survive.

1999-2001: Cruddy high-yield bonds reveal their true value as defaults threaten to, and then do, emerge.

2002-2003: The manufactured-housing ABS market blows up, as originators don?t take initial losses but roll borrowers over into new loans that reduce payments and extend payment terms, technically keeping the loans current.? The system collapses when the buildup of bad debts and repossessed homes becomes too great to roll over.

(Of the existing large securitization markets, only the CMBS market so far has not faced a real crisis, partly due to the influence of the B-piece buyers cartel: six or so firms that buy the junk-rated debt of deals and enforce credit quality standards on the individual loans by kicking out poorly underwritten loans.? But who knows?? Even that could be overwhelmed under the right circumstances.)

In each of these situations, there was a boom-bust cycle.? The markets did not adjust slowly and evenly to changing conditions; the transitions between ?boom? pricing, and ?bust? pricing were swift.? This is the nature of markets, particularly when enough debt is employed to amplify the process.

There is no conspiracy necessary to make the shift happen (though often the media will make it seem like there was one); the bubble pops when the financing proves insufficient to carry the assets.? After the bubble pops, it becomes a question of what the underlying assets can be liquidated for, allocating losses mercilessly according to the loan documents and bankruptcy priority.

Today the crises are nonprime lending, leveraged buyouts and other high-yield debt and over-leverage in the CDO market.? These will get worked out, as all other crises do, handing losses to those who speculated unwisely and allowing those who financed properly to prosper on the other side of the crisis.

As you invest, look for the time when more than half of the losses will be reconciled.? That will be near the bottom for homebuilders and housing finance.

That time may not come for another two years or so, but there will be money to be made once the crisis is mostly reconciled.? Just stick with the companies that have strong balance sheets.

Limit Repo Financing

Limit Repo Financing

If you have a moment, read this Bloomberg article. ?The brokers are utterly dishonest when they say:

Brokers contend that their borrowing is generally less risky than bank lending. Repo borrowing, for instance, is backed by collateral that can be readily sold to raise cash in case the other party defaults, said Steven Lofchie, co-chairman of the financial services group at Cadwalader, Wickersham & Taft LLP.

?If you think about a bank that is lending 90 percent against a house, versus a broker-dealer taking in 102 percent against a loan of a security, the broker-dealer?s credit risk is exponentially less,? Lofchie said.

This is true under ordinary circumstances, but not in a crisis, as we saw in 2008. ?Seemingly safe securities were no longer safe, because too many overleveraged parties could not hold their positions when the prices of their seemingly safe securities started to fall. ?This led to a panic, because of the structural error of financing long-dated securities with short-dated funding. ?In a crisis, that is the fatal flaw of repo financing.

I think the proposals of the SEC are decent, and those that the broker-dealers propose are not. ?I would go further and abolish repo markets. ?They are crisis-bait. ?The asset-liability mismatch invites trouble.

The proposal of the broker-dealers is flawed, because they don’t adopt a model where they match assets and liabilities. ?Stable systems match assets and liabilities. ?Until they do so, they should not be taken seriously. ?The math of risk control wars against them.

As Light As Hydrogen

As Light As Hydrogen

Okay let?s roll the promoted stocks scoreboard:

Ticker Date of Article Price @ Article Price @ 3/18/13 Decline Annualized Splits
GTXO

5/27/2008

2.45

0.040

-98.4%

-50.8%

BONZ

10/22/2009

0.35

0.001

-99.7%

-73.0%

BONU

10/22/2009

0.89

0.001

-99.9%

-79.1%

UTOG

3/30/2011

1.55

0.000

-100.0%

-95.1%

OBJE

4/29/2011

116.00

0.167

-99.9%

-89.7%

1:40

LSTG

10/5/2011

1.12

0.010

-99.1%

-85.7%

AERN

10/5/2011

0.0770

0.0001

-99.9%

-93.4%

IRYS

3/15/2012

0.261

0.000

-100.0%

-100.0%

Dead
RCGP

3/22/2012

1.47

0.300

-79.6%

-55.1%

STVF

3/28/2012

3.24

0.420

-87.0%

-64.5%

CRCL

5/1/2012

2.22

0.026

-98.8%

-90.6%

ORYN

5/30/2012

0.93

0.110

-88.2%

-69.5%

BRFH

5/30/2012

1.16

0.515

-55.6%

-36.3%

LUXR

6/12/2012

1.59

0.009

-99.4%

-94.7%

IMSC

7/9/2012

1.5

0.900

-40.0%

-26.1%

DIDG

7/18/2012

0.65

0.042

-93.5%

-80.7%

GRPH

11/30/2012

0.8715

0.085

-90.3%

-83.5%

IMNG

12/4/2012

0.76

0.045

-94.1%

-88.9%

ECAU

1/24/2013

1.42

0.240

-83.1%

-78.8%

DPHS

6/3/2013

0.59

0.010

-98.3%

-99.4%

POLR

6/10/2013

5.75

0.070

-98.8%

-99.7%

NORX

6/11/2013

0.91

0.210

-76.9%

-85.2%

ARTH

7/11/2013

1.24

0.360

-71.0%

-83.6%

NAMG

7/25/2013

0.85

0.164

-80.7%

-92.2%

MDDD

12/9/2013

0.79

0.320

-59.5%

-96.4%

TGRO

12/30/2013

1.2

0.220

-81.7%

-100.0%

VEND

2/4/2014

4.34

4.900

12.9%

187.3%

3/18/2014

Median

-93.5%

-85.2%

Tonight’s loser-in-waiting is HydroPhi Technologies [HPTG]. ?This one can’t even get basic science right. ?It claims to be able to split water into hydrogen and oxygen, and then recombine them to create energy. ?Circular processes in general lose energy, otherwise we would have perpetual motion machines.

And behind the vapid analysis is an uber-loser. ?His analyses never pan out over one year. ?A clever speculator might make money occasionally, but not regularly, because the stocks he pumps are like this one. ?Little revenues, negative earnings, negative net worth. ?This is a recipe for disaster.

Think about it — if you had a miracle energy technology, would you merge your company with a failed internet advertising company “BigClix?” ?I would think not. ?You would keep your company private and enjoy the significant profits.

As it is, there are no profits, so where is this great energy technology? ?This is a scam, and laws should be revised to allow prosecution of those who write such promotional garbage as we have seen. ?It is no good to have the 4-point type disclaimers telling some of the truth, while the big type says “Buy, buy BUYYY!!!” ?Also, as far as the web version of this promotion goes, the promoters pour in half a million. ?As it says in the 4-point type:

Third Party Advertiser IMPORTANT NOTICE: Esquire Media Services Inc (EMS) has managed up to a $500,000 USD advertising production budget as of January 21, 2014 in an effort to build industry and investor awareness for HydroPhi Technology Group Inc (ticker symbol: HPTG).?

It’s easy to affect the price of a company that has bad fundamentals. ?It’s overvalued to start; it will only be more overvalued at the crest of the promotion. ?If you attract a bunch of people to the pump-and-dump who want to play the momentum, some may think they will be clever enough to scalp a quick profit along with the insiders. ?Some of them win, and others lose. ?Others believe the advertising, and stay to lose a ton.

Seth Klarman recently said,??It might not look like it now, but markets don?t exist simply to enrich people.? ?This needs to be remembered by all. ?Markets are for trading, and trading is a negative-sum game. ?Those who buy & hold valuable businesses for a span — that is a positive-sum game, because the underlying asset is appreciating.

To close: don’t buy promoted stocks. ?Never. ?Those who are paid directly or indirectly to encourage you to buy are at best sub-agents for the seller — they aren’t on your side. ?In buying promoted stocks, it’s like going to Vegas, minus the fun. ?You will lose. ?You will lose a lot. ? The house edge is fixed — it’s only a question of how much you will lose.

Avoid promoted stocks. ?As I often say: “Don’t buy what someone else wants to sell you, buy what you have researched and know has value.”

The Rules, Part LX

The Rules, Part LX

Rapid upward moves in volatility almost always presage a bounce rally.

Again, I am scraping the bottom of the barrel, but this is a common aspect of markets. ?When things get tough, scaredy-cats buy put options. ?That pushes up option implied volatilities. ?The same doesn’t happen when prices are rising, because that happens slower. ?Prices fall twice as fast as they rise in the stock market.

Emotions play a big role with options, and many do not use them rationally. ?Rather than using them when the market is rising in order to hedge, more commonly they hedge after the market has fallen.

As implied volatility rises, the ability to make money from hedging falls, as the cost of insurance goes up. ?As a result, hedging peters out, and the market will be receptive to positive news, given that most who want to hedge have hedged. ?Their pseudo-selling is over, and a bounce rally will happen.

Volatility tends to mean-revert, and as the reversion from high levels of volatility happens, the value of stocks rise. ?People buy equities as fears dissipate.

Volatility, both actual and implied, are tools to have in your arsenal to help you understand when markets might be overvalued (low volatility) or undervalued (very high volatility). ?Use this knowledge to guide your portfolio positioning. ?At present, it is more reliable then many other measures of the market.

Next time, I end this series. ?Till then.

On Finding Neglected Companies

On Finding Neglected Companies

While at RealMoney, I wrote a short series on data-mining. ?Copies of the articles are here: (one, two). I enjoyed writing them, and the most pleasant surprise was the favorable email from readers and fellow columnists. As a follow up, on April 13th, 2005, I wrote an article on analyst coverage — and neglect. Today, I am writing the same article but as of today, with even more detail, and comparisons to prior analyses.

As it was, in my Finacorp years, I wrote a similar piece to this but it has been lost; I can?t find a copy of it, and Finacorp is in the ash-heap of financial firms. (Big heap, that.)

For a variety of reasons, sell-side analysts do not cover companies and sectors evenly. For one, they have biases that are related to how the sell-side analyst’s employer makes money. It is my contention that companies with less analyst coverage than would be expected offer an opportunity to profit for investors who are willing to sit down and analyze these lesser-analyzed companies and sectors.

I am a quantitative analyst, but I try to be intellectually honest about my models and not demand more from them than they can deliver. That’s why I have relatively few useful models, maybe a dozen or so, when there are hundreds of models used by quantitative analysts in the aggregate.

 

Why do I use so few? Many quantitative analysts re-analyze (torture) their data too many times, until they find a relationship that fits well. These same analysts then get surprised when the model doesn’t work when applied to the real markets, because of the calculated relationship being a statistical accident, or because of other forms of implementation shortfall — bid-ask spreads, market impact, commissions, etc.

This is one of the main reasons I tend not to trust most of the “advanced” quantitative research coming out of the sell side. Aside from torturing the data until it will confess to anything (re-analyzing), many sell-side quantitative analysts don’t appreciate the statistical limitations of the models they use. For instance, ordinary least squares regression is used properly less than 20% of the time in sell-side research, in my opinion.

 

Sell-side firms make money two ways.They can make via executing trades, so volume is a proxy for profitability.They can make money by helping companies raise capital, and they won?t hire firms that don?t cover them.Thus another proxy for profitability is market capitalization.

 

Thus trading volume and market capitalization are major factors influencing analyst coverage. Aside from that, I found that the sector a company belongs to has an effect on the number of analysts covering it.

 

I limited my inquiry to include companies that had a market capitalization of over $10 million, US companies only, and no ETFs.

 

I used ordinary least squares regression covering a data set of 4,604 companies. The regression explained 82% of the variation in analyst coverage. Each of the Volume and market cap variables used were significantly different from zero at probabilities of less than one in one million. As for the sector variables, they were statistically significant as a group, but not individually.Here’s a list of the variables:

 

Variable

?Coefficients

?Standard Error

?t-Statistic

?Logarithm of 3-month average volume

?0.57

0.04

?15.12

?Logarithm of Market Capitalization

?(2.22)

0.15

(14.69)

?Logarithm of Market Capitalization, squared

?0.36

0.01

?31.42

?Basic Materials

?(0.53)

0.53

?(1.01)

?Capital Goods

?0.39

0.54

?0.74

?Conglomerates

?(0.70)

1.95

?(0.36)

?Consumer Cyclical

?0.08

0.55

?0.14

?Consumer Non-Cyclical

?(1.40)

0.55

?(2.52)

?Energy

?2.56

0.53

?4.87

?Financial

?0.37

0.48

?0.78

?Health Care

?0.05

0.50

?0.11

?Services

?(0.30)

0.49

?(0.61)

?Technology

?0.82

0.49

?1.67

?Transportation

?2.92

0.66

?4.40

?Utilities

?(1.10)

0.60

?(1.82)

 

In short, the variables that I used contained data on market capitalization, volume and market sector.

An increasing market capitalization tends to attract more analysts. At a market cap of $522 million, market capitalization as a factor adds no net analysts. At the highest market cap in my study, Apple [AAPL] at $469 billion, the model indicates that 11 fewer analysts should cover the company. The smallest companies in my study would have 3.3 fewer analysts as compared with a company with a market cap of $522 million.

 

Market Cap

?Analyst additions

?10.00

?2.30

?30.00

?3.40

100.00

?4.61

300.00

?5.70

522.20

?6.26

?1,000.00

?6.91

?3,000.00

?8.01

10,000.00

?9.21

30,000.00

?10.31

100,000.00

?11.51

300,000.00

?12.61

469,400.30

?13.06

 

The intuitive reasoning behind this is that larger companies do more capital markets transactions. Capital markets transactions are highly profitable for investment banks, so they have analysts cover large companies in the hope that when a company floats more stock or debt, or engages in a merger or acquisition, the company will use that investment bank for the transaction.

 

Investment banks also make some money from trading. Access to sell-side research is sometimes limited to those who do enough commission volume with the investment bank. It’s not surprising that companies with high amounts of turnover in their shares have more analysts covering them. The following table gives a feel for how many additional analysts cover a company relative to its daily trading volume. A simple rule of thumb is that (on average) as trading volume quintuples, a firm gains an additional analyst, and when trading volume falls by 80%, it loses an analyst.

 

Daily Trading Volume (3 mo avg)

Analyst Additions

3 0.6
10 1.3
30 1.9
100 2.6
300 3.2
1,000 3.9
3,000 4.5
10,000 5.2
30,000 5.8
100,000 6.5
300,000 7.1
1,000,000 7.8
3,000,000 8.4
4,660,440 8.7

 

An additional bit of the intuition for why increased trading volume attracts more analysts is that volume is in one sense a measure of disagreement. Investors disagree about the value of a stock, so one buys what another sells. Sell-side analysts note this as well; stocks with high trading volumes relative to their market capitalizations are controversial stocks, and analysts often want to make their reputation by getting the analysis of a controversial stock right. Or they just might feel forced to cover the stock because it would look funny to omit a controversial company.

Analyst Neglect

The first two variables that I considered, market capitalization and volume, have intuitive stories behind them as to why the level of analysts ordinarily varies. But analyst coverage also varies by industry sector, and the reasons are less intuitive to me there.

 

Please note that my regression had no constant term, so the constant got embedded in the industry factors. Using the Transportation sector as a benchmark makes the analysis easier to explain. Here’s an example: On average, a Utilities company that has the same market cap and trading volume as a Transportation company would attract four fewer analysts.

 

Sector ?Addl Analysts ?Fewer than Transports
?Transportation ?2.92
?Energy ?2.56 ?(0.37)
?Technology ?0.82 ?(2.10)
?Capital Goods ?0.39 ?(2.53)
?Financial ?0.37 ?(2.55)
?Consumer Cyclical ?0.08 ?(2.84)
?Health Care ?0.05 ?(2.87)
?Services ?(0.30) ?(3.22)
?Basic Materials ?(0.53) ?(3.46)
?Conglomerates ?(0.70) ?(3.63)
?Utilities ?(1.10) ?(4.02)
?Consumer Non-Cyclical ?(1.40) ?(4.32)

 

Why is that? I can think of two reasons. First, the companies in the sectors at the top of my table are perceived to have better growth prospects than those at the bottom. Second, the sectors at the top of the table are more volatile than those toward the bottom (though basic materials would argue against that). As an aside, companies in the conglomerates sector get less coverage because they are hard for a specialist analyst to understand.

 

My summary reason is that “cooler” sectors attract more analysts than duller sectors. To the extent that this is the common factor behind the variation of analyst coverage across sectors, I would argue that sectors toward the bottom of the list are unfairly neglected by analysts and may offer better opportunities for individual investors to profit through analysis of undercovered companies in those sectors.

Malign Neglect

Now, my model did not explain 100% of the variation in analyst coverage. It explained 82%, which leaves 18% unexplained. Some of the unexplained variation is due to the fact that no model can be perfect. But the unexplained variation can be used to reveal the companies that my model predicted most poorly. Why is that useful? If my model approximates “the way the world should be,” then the degree of under- and over-coverage by analysts will reveal where too many or few analysts are looking. The following tables lists the largest company variations between reality and my model, split by market cap group.

 

Behemoth Stocks

?

Ticker Company Sector Excess analysts
BRK.A Berkshire Hathaway Inc. 07 – Financial (25.75)
GE General Electric Company 02 – Capital Goods (20.47)
XOM Exxon Mobil Corporation 06 – Energy (19.32)
CVX Chevron Corporation 06 – Energy (14.64)
PFE Pfizer Inc. 08 – Health Care (14.57)
MRK Merck & Co., Inc. 08 – Health Care (12.76)
GOOG Google Inc 10 – Technology (11.44)
JNJ Johnson & Johnson 08 – Health Care (11.39)
MSFT Microsoft Corporation 10 – Technology (10.39)
PM Philip Morris International In 05 – Consumer Non-Cyclical (10.21)

?

Too many

?

Ticker Company Sector Excess analysts
V Visa Inc 09 – Services ?2.58
DIS Walt Disney Company, The 09 – Services ?2.95
SLB Schlumberger Limited. 06 – Energy ?4.15
CSCO Cisco Systems, Inc. 10 – Technology ?5.22
QCOM QUALCOMM, Inc. 10 – Technology ?5.34
ORCL Oracle Corporation 10 – Technology ?5.98
FB Facebook Inc 10 – Technology ?8.28
AMZN Amazon.com, Inc. 09 – Services ?9.34
AAPL Apple Inc. 10 – Technology ?10.57
INTC Intel Corporation 10 – Technology ?11.85

?

Large Cap Stocks

?

Ticker Company Sector Excess analysts
SPG Simon Property Group Inc 09 – Services (16.15)
BF.B Brown-Forman Corporation 05 – Consumer Non-Cyclical (16.03)
LUK Leucadia National Corp. 07 – Financial (15.93)
L Loews Corporation 07 – Financial (15.90)
EQR Equity Residential 09 – Services (15.87)
ARCP American Realty Capital Proper 09 – Services (15.75)
IEP Icahn Enterprises LP 09 – Services (15.50)
LVNTA Liberty Interactive (Ventures 09 – Services (15.36)
ABBV AbbVie Inc 08 – Health Care (15.01)
GOM CL Ally Financial Inc 07 – Financial (14.87)

?

Too Many

?

Ticker Company Sector Excess analysts
UA Under Armour Inc 04 – Consumer Cyclical ?16.68
BRCM Broadcom Corporation 10 – Technology ?17.29
RRC Range Resources Corp. 06 – Energy ?17.33
SWN Southwestern Energy Company 06 – Energy ?17.70
RHT Red Hat Inc 10 – Technology ?18.08
NTAP NetApp Inc. 10 – Technology ?19.82
CTXS Citrix Systems, Inc. 10 – Technology ?19.84
COH Coach, Inc. 09 – Services ?20.87
VMW VMware, Inc. 10 – Technology ?21.60
CRM salesforce.com, inc. 10 – Technology ?22.64

?

Mid cap stocks

?

Ticker Company Sector Excess analysts
FNMA Federal National Mortgage Assc 07 – Financial (13.84)
UHAL AMERCO 11 – Transportation (12.23)
O Realty Income Corp 09 – Services (12.06)
CIM Chimera Investment Corporation 07 – Financial (11.49)
SLG SL Green Realty Corp 09 – Services (11.46)
NRF Northstar Realty Finance Corp. 09 – Services (11.34)
FMCC Federal Home Loan Mortgage Cor 07 – Financial (11.14)
EXR Extra Space Storage, Inc. 11 – Transportation (10.97)
KMR Kinder Morgan Management, LLC 06 – Energy (10.94)
CWH CommonWealth REIT 09 – Services (10.51)

?

Too Many

?

Ticker Company Sector Excess analysts
AEO American Eagle Outfitters 09 – Services ?17.00
DRI Darden Restaurants, Inc. 09 – Services ?17.40
RVBD Riverbed Technology, Inc. 10 – Technology ?17.50
CMA Comerica Incorporated 07 – Financial ?17.74
GPN Global Payments Inc 07 – Financial ?18.30
WLL Whiting Petroleum Corp 06 – Energy ?19.67
DO Diamond Offshore Drilling Inc 06 – Energy ?21.57
URBN Urban Outfitters, Inc. 09 – Services ?24.06
RDC Rowan Companies PLC 06 – Energy ?24.48
ANF Abercrombie & Fitch Co. 09 – Services ?26.02

?

 

Small cap stocks

 

Ticker Company Sector Excess analysts
BALT Baltic Trading Ltd 11 – Transportation ?(7.96)
ERA Era Group Inc 11 – Transportation ?(7.45)
PBT Permian Basin Royalty Trust 06 – Energy ?(7.42)
SDR SandRidge Mississippian Trust 06 – Energy ?(7.18)
PHOT Growlife Inc 02 – Capital Goods ?(6.79)
SBR Sabine Royalty Trust 06 – Energy ?(6.74)
CAK CAMAC Energy Inc 06 – Energy ?(6.64)
FITX Creative Edge Nutrition Inc 09 – Services ?(6.57)
BLTA Baltia Air Lines Inc 11 – Transportation ?(6.53)
VHC VirnetX Holding Corporation 10 – Technology ?(6.49)

 

Too many

 

Ticker Company Sector Excess analysts
WLT Walter Energy, Inc. 06 – Energy ?12.19
ANGI Angie’s List Inc 10 – Technology ?12.31
FRAN Francesca’s Holdings Corp 09 – Services ?12.58
ZUMZ Zumiez Inc. 09 – Services ?13.49
GDP Goodrich Petroleum Corp 06 – Energy ?15.02
DNDN Dendreon Corporation 08 – Health Care ?15.89
ACI Arch Coal Inc 06 – Energy ?16.04
HERO Hercules Offshore, Inc. 06 – Energy ?16.19
AREX Approach Resources Inc. 06 – Energy ?17.64
ARO Aeropostale Inc 09 – Services ?20.80

 

Microcap Stocks

 

Ticker Company Sector Excess analysts
SGLB Sigma Labs Inc 06 – Energy ?(6.18)
AEGY Alternative Energy Partners In 10 – Technology ?(5.97)
WPWR Well Power Inc 06 – Energy ?(5.83)
TTDZ Triton Distribution Systems In 10 – Technology ?(5.53)
SFRX Seafarer Exploration Corp 11 – Transportation ?(5.15)
PTRC Petro River Oil Corp 06 – Energy ?(4.99)
UTRM United Treatment CentersInc 08 – Health Care ?(4.82)
BIEL Bioelectronics Corp 08 – Health Care ?(4.80)
DEWM Dewmar International BMC Inc 01 – Basic Materials ?(4.74)
FEEC Far East Energy Corp 06 – Energy ?(4.61)

 

Too many

 

Ticker Company Sector Excess analysts
PRSS CafePress Inc 09 – Services ?3.99
SANW S&W Seed Company 05 – Consumer Non-Cyclical ?4.03
KIOR KiOR Inc 01 – Basic Materials ?4.06
PRXG Pernix Group Inc 02 – Capital Goods ?4.08
EYNON Entergy New Orleans, Inc. 12 – Utilities ?4.17
PARF Paradise, Inc. 05 – Consumer Non-Cyclical ?4.40
SUMR Summer Infant, Inc. 05 – Consumer Non-Cyclical ?4.52
LAND Gladstone Land Corp 05 – Consumer Non-Cyclical ?4.57
JRCC James River Coal Company 06 – Energy ?6.38
GNK Genco Shipping & Trading Limit 11 – Transportation ?7.11

My advice to readers is to consider buying companies that have fewer analysts studying them than the model would indicate.? This method is certainly not perfect but it does point out spots where Wall Street is not focusing its efforts, and might provide some opportunities.

 

 

Full disclosure: long BRK/B & CVX

Conservation of Liquidity, under most Conditions

Conservation of Liquidity, under most Conditions

Have you ever seen the graphs showing “Look at all the money sitting on the sidelines!? This market has to go up!”? Those analyses are bogus.? Why?

Several reasons, but the leading one is that much cash has to be held as part of portfolio margining, securities lending, or derivative agreements.? What would be valuable, maybe is a graph of cash that is free to be spent on new securities.

The word “new” is important.? With most trading, liquidity does not disappear.? Instead, liquidity moves from the account of the buyer to that of the seller.? When is that not so?

With initial public offerings, where the proceeds are not solely going to selling shareholders, liquidity disappears into the coffers of the new company, that it can do business.?? That’s not a bad thing, aside from periods in the ’60s and late ’90s where there was a craze that led people to invest in bogus businesses that sounded cool.

When there is too much liquidity available to invest, Wall Street produces new companies to absorb the liquidity, many of which will be of dubious value, because there is money to be made.? Trot out the speculative stocks and bonds, especially near the end of the boom phase of the credit cycle.

Liquidity disappears into new corporations, and reappears when corporations are bought for cash.? Aside from a few other similar events, secondary trading has no effect on liquidity.? So when you hear that there is a lot of liquidity on the sidelines, review the above arguments and say, “There is almost always a lot of liquidity on the sidelines, but is it buying up new stock issues?”

Therefore, look at the quality of new IPOs.? Quality is a thermometer for whether the market is cold to overheating.? The same applies to corporate M&A to a lesser extent when they purchase poor assets for cash.? On the other hand, if corporate M&A is finding inexpensive assets that they buy for cash, the market as a whole may be cheap.

Secondary trading does not inform us much about market valuations.? Look to the primary markets, where cash creates new assets, and where old assets get sold for cash.? Valuations are on display there, and should inform our investing.

This May Be Gold, But It Is Not Golden

This May Be Gold, But It Is Not Golden

I’ve done a number of articles on dollar-weighted returns in mutual funds.? There are rare cases where the shareholder base is smart, usually in value funds, where the shareholders add more money on declines, and lighten up when things are going too well.

Tonight’s target is the Gold ETF SPDR Gold Shares [GLD].? As with most volatile mutual funds, people tend to get greedy or panic.? They chase performance.? Consider this list of inflows and outflows from GLD. Cash flows are assumed to occur at mid-period.

Date

Cash Flow

9/30/2004

???????????? 13,081

3/31/2005

?????? 2,902,381

3/31/2006

?????? 3,152,826

3/31/2007

?????? 4,129,118

3/31/2008

?????? 5,163,301

3/31/2009

??? 10,326,761

3/31/2010

?????? 8,197,457

3/31/2011

??? (3,046,769)

3/31/2012

?????? 5,499,978

3/31/2013

? (18,958,700)

11/15/2013

??? (4,320,084)

12/31/2013

? (30,887,920)

Dollar-weighted

8.20%

Time-weighted

11.13%

Difference

-2.92%

Versus a buy-and-hold investor, the average holder gives up almost 3% of returns via market mistiming.? Technicians may talk down buy and hold, but buy and hold usually outperforms the average trader.? This is similar to what my friend Josh Brown talks about in his article Flows Don?t Follow Value, They Follow Performance.? Very few investors are rational businessmen, estimating likely returns over their funding horizon.? Rather they chase past success, and flee past failures.

Such has been true of the SPDR Gold Shares ETF.? Say what you will about the cheapness of large ETFs, people will still misuse them.? They will buy late in a bull phase, and sell late in a bear phase.

And so I say to all: Guard your emotions.? Be forward-looking.? Analyze likely value five years out.? Don’t make snap decisions out of regret.? Think about risk control before you buy shares, bonds, whatever.

Now, as a personal aside, it took me around eight years to learn to control my emotions.? Over the last 20 years, I have made at most a handful of errors reacting to bad market events.? I learned to analyze rather than panic back in the 90s.? It doesn’t mean that I am always right, but it does mean that I act.? I almost never react.

As for GLD, be wary about paper gold.? Is it really fully collateralized by audited gold in a warehouse?? There are lots of promises of gold being traded, but how much physical gold could you have delivered to you, should you want it?

That’s all for now.? Be careful in all of your investing; it is easy to err.

Classic: The Fundamentals of Real Estate Market Tops

Classic: The Fundamentals of Real Estate Market Tops

I’ve mentioned before how all of my old articles at RealMoney were lost.? This was the draft version of Real Estate’s Top Looms published on 05/20/05.? I followed it up with? Housing Bubblettes, Redux on 10/27/05 and? September 2005 — The Residential Real Estate Inflection Point on 02/14/06.? Also, there was Wrecking Ball Looms for Big Housing Spec on 11/27/06, where I explained why it was likely that the subprime residential mortgage market was likely to blow up (can’t find the draft of that one).

But those links above no longer work — a real pity, and the one link below is corrected to point to the republished article at my blog.? Anyway, enjoy this if you want, because it outlines my thinking on how to recognize whether you are getting near the end of the bull phase of a market.

(Note: the italicized, indented portions, quote the original article The Fundamentals of Market Tops.? Much of what I write compares how residential real estate is similar to and different from stocks.)

-==-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=–=

About a year and a half ago, I wrote a piece called The Fundamentals of Market Tops.? It was an important piece for me because I received a lot of positive feedback from readers.? It was also important because it disagreed with the view of the firm that I worked for, and nearly led to my termination there, because they encouraged me to stop writing for RealMoney.? Neither termination happened, but it was touch-and-go for a while.

This piece unofficially represents the views of the firm that I work for, because my views of macroeconomics have become the firm?s views, but I don?t directly control our investment actions.? What I will try to accomplish here is to try to apply the logic of my prior article to the residential real estate market.? As opposed to my earlier article, I will try to show why I think we are close to a market top in residential real estate.? There is reason for pessimism.

The Investor Base Becomes Momentum-Driven

Valuation is rarely a sufficient reason to be long or short a market. Absurdity is like infinity. Twice infinity is still infinity. Twice absurd is still absurd. Absurd valuations, whether high or low, can become even more absurd if the expectations of market participants become momentum-based. Momentum investors do not care about valuation; they buy what is going up, and sell what is going down.

This is what I see in many residential real estate markets now: panicked buyers are saying ?this is my last chance,? and buying houses using risky forms of financing.? At the same time, I read stories of despair as some potential buyers give up and say that a house is out of their reach for now; they waited too long.? Occasionally, I see a few articles or e-mails regarding people who seem to be bright selling their homes and renting, but this is a minority behavior.

In the face of this, residential real estate prices continue to rise, particularly in the hot coastal markets, which tells me that the price momentum can continue a little while longer until it fails because there is no incremental liquidity available to expand the bubbles.

You’ll know a market top is probably coming when:

  1. The shorts already have been killed. You don’t hear about them anymore. There is general embarrassment over investments in short-only funds.

  2. Long-only managers are getting butchered for conservatism. In early 2000, we saw many eminent value investors give up around the same time. Julian Robertson, George Vanderheiden, Robert Sanborn, Gary Brinson and Stanley Druckenmiller all stepped down shortly before the market top.

  3. Valuation-sensitive investors who aren’t total-return driven because of a need to justify fees to outside investors accumulate cash. Warren Buffett is an example of this. When Buffett said that he “didn’t get tech,” he did not mean that he didn’t understand technology; he just couldn’t understand how technology companies would earn returns on equity justifying the capital employed on a sustainable basis.

  4. The recent past performance of growth managers tends to beat that of value managers. (I am using the terms growth and value in a classic sense here. Growth managers attempt to ascertain the future prospects of firms with little focus on valuation. Value managers attempt to calculate the value of a firm with less credit for future prospects.) In short, the future prospects of firms become the dominant means of setting market prices.

  5. Momentum strategies are self-reinforcing due to an abundance of momentum investors. Once momentum strategies become dominant in a market, the market behaves differently. Actual price volatility increases. Trends tend to maintain themselves over longer periods. Selloffs tend to be short and sharp.

  6. Markets driven by momentum favor inexperienced investors. My favorite way that this plays out is on CNBC. I gauge the age, experience and reasoning of the pundits. Near market tops, the pundits tend to be younger, newer and less rigorous. Experienced investors tend to have a greater regard for risk control, and believe in mean-reversion to a degree. Inexperienced investors tend to follow trends. They like to buy stocks that look like they are succeeding and sell those that look like they are failing.

  7. Defined benefit pension plans tend to be net sellers of stock. This happens as they rebalance their funds to their target weights.

Houses aren?t like stocks for several reasons:

  1. Unlike stocks, houses are used by their owners every day.
  2. We can short stocks, but we can?t short houses.? (Personally, I hope no one comes up with a clever way to do so.? We have enough volatility already.)? The most someone can do is sell his home and rent.
  3. Perhaps the equivalent of a long-only manager is someone who owns his property debt-free, like me, and doesn?t see the need to lever up by moving up to a larger home.? Measured against the standard of ?what might have been? is a terrifying taskmaster from an investment standpoint.? I avoid it in equity investing, and in home ownership.
  4. I am aware of a number of people (I have been assured that they are not mentally incompetent) who have sold their homes and started renting.? This to me is the equivalent of going totally flat in equities, or other risky assets.? Not that one faces negative carry, because the ratio of rent to in the hot markets is pretty low.? In many markets, you can earn more off the proceeds than you pay in rent (leaving tax consequences aside).? This leaves aside the issue of appreciation/depreciation of housing values, but when one can rent more cheaply than buying, it is a negative for the housing market.
  5. My point about momentum strategies is definitely pertinent here.? With the existence of contract-flipping, a high level of amateur investment (seemingly under the guise of ?buy what you know?), and a high level of investor interest (10%+), there is a lot of momentum in real estate investment.? People buy because prices are going up.? Some buy because it is ?the last train out,? and they have to jump rather than be stranded.? Nonetheless, momentum tends to maintain in the short run, and the slowdown posited last fall definitely has not occurred.
  6. Value vs. Growth does not exactly apply here, but in the housing market, people are paying up for future prospects more than they used to, which is akin to growth investing.
  7. This is just an opinion, but those who are making money in residential real estate today are inexperienced and less rigorous than most good businessmen.? They see the potential for profit, but not the possibility of loss.
  8. Unfortunately, it is difficult to partially own a home.? Home ownership is largely a discrete phenomenon.
  9. Using a concept from value investing we can look at the earnings yield that residential real estate is throwing off.? Compare the rents one could receive from a property versus the cost that it would take to finance the property on a floating rate basis.? What I am seeing is that more and more hot coastal markets earn less from rents than they require in mortgage payments.? Property price appreciation is no longer a nice thing; it is required to bail out inverted investors.? Contrast this with those that invested in tech stocks on a levered basis in early 2000; they paid cash out to hold appreciating positions, before they paid cash to hold depreciating positions, before they blew the positions out in panic.

Corporate Behavior

Corporations respond to signals that market participants give. Near market tops, capital is inexpensive, so companies take the opportunity to raise capital.? Here are ways that corporate behaviors change near a market top:

  1. The quality of IPOs declines, and the dollar amount increases. By quality, I mean companies that have a sustainable competitive advantage, and that can generate ROE in excess of cost of capital within a reasonable period.
  2. Venture capitalists can do no wrong, so lots of money is attracted to venture capital.
  3. Meeting the earnings number becomes paramount. What is ignored is balance sheet quality, cash flow from operations, etc.
  4. There is a high degree of visible and/or hidden leverage. Unusual securitization and financing techniques proliferate. Off balance sheet liabilities become very common.
  5. Cash flow proves insufficient to finance some speculative enterprises and some financial speculators. This occurs late in the game. When some speculative enterprises begin to run out of cash and can’t find anyone to finance them, they become insolvent. This leads to greater scrutiny and a sea change in attitudes for financing of speculative companies.
  6. Elements of accounting seem compromised. Large amounts of earnings stem from accruals rather than cash flow from operations.
  7. Dividends become less common. Fewer companies pay dividends, and dividends make up a smaller fraction of earnings or free cash flow.

In short, cash is the lifeblood of business. During speculative times, watch it like a hawk. No array of accrual entries can ever provide quite the same certainty as cash and other highly liquid assets in a crisis.

  1. Every time a new home is sold, a privately placed IPO is held, with one buyer.
  2. When rates are low, it is no surprise that the homebuilders try to take advantage of the situation, and provide supply to meet the demand.? But if it is only rate-driven, rather than from growth in real incomes in the economy, the quality of the new buyers will be low, because now they can just barely finance the house they could not previously.? If their income level falters, they will not have any safety margin allowing them to hold onto the house.
  3. Private investors in residential real estate have multiplied at present.? This is akin to an increase in venture capital.
  4. Leverage for new buyers has never been higher.? This occurs through second and third mortgages, as well as subprime mortgages.? Interest only mortgages are commonplace among new mortgages.? Beyond this, investors hide themselves so that they can get the cheap rates associated with owner-occupied housing.
  5. With housing, making the earnings estimate means being able to pay the mortgage payment each month.? The degree of slack here is less than in the past.

Other Gauges

These two factors are more macro than the investor base or corporate behavior but are just as important.? Near a top, the following tends to happen:

  1. Implied volatility is low and actual volatility is high. When there are many momentum investors in a market, prices get more volatile. At the same time, there can be less demand for hedging via put options, because the market has an aura of inevitability.
  2. The Federal Reserve withdraws liquidity from the system. The rate of expansion of the Fed’s balance sheet slows. This causes short interest rates to rise, making financing more expensive. As this slows down the economy, speculative ventures get hit hardest. Remember that monetary policy works with a six- to 18-month lag; also, this indicator works in reverse when the Fed adds liquidity to the system.

One final note about my indicators: I have found that different indicators work for market bottoms and tops, so don’t blindly apply these in reverse to try to gauge bottoms.

?There is no options market for residential housing, but the Federal Reserve is still a major influence in the housing market.? When the Fed is withdrawing liquidity from the system, the price of housing tends to slow down, if not reverse.? Like the equity market, this is not immediate but follows a six- to 18-month lag.? This is another case of ?Don?t fight the Fed.?

No Top Now

There are reasons for concern in the present environment. Valuations are getting stretched in some parts of the market. Debt capital is cheap today. There are an increasing number of momentum investors in the market. Making the earnings estimate is once again of high importance. Nonetheless, a top in the market is not imminent, for these reasons:

  • The Fed is on hold for now. Liquidity is ample, perhaps too much so.
  • Actual price volatility is muted.
  • Since all of the accounting scandals of the last few years, many corporations have cleaned up their accounting and become more conservative.
  • Cash flow from operations comprises a high proportion of current earnings. More dividends are getting paid.
  • Leverage has not declined, but most corporations have succeeded in refinancing themselves in a low interest rate environment.
  • Conservative asset managers have not been fired yet.
  • Most IPOs don’t seem outlandish.

Not all of the indicators that I put forth have to appear for there to be a market top. A preponderance of them appearing would make me concerned, and that is not the case now.

?Some of my indicators are vague and require subjective judgment. But they’re better than nothing, and kept me out of the trouble in 1999 and 2000. I hope that I — and you — can achieve the same with them as we near the next top.

The current market environment is not as favorable as it was a year ago, but there are still some reasonably valued companies with seemingly clean accounting to buy at present. Right now, being long the market is more compelling to me than being flat, much less short.

I would retitle this the ?The Top is Coming Soon.?? The reasons that I mentioned to be worrisome remain:

  • Valuations are getting stretched in some parts of the market.
  • Debt capital is cheap today.
  • There are an increasing number of momentum investors in the market.
  • Making the earnings estimate is once again of high importance. (Gotta pay my mortgage!)

But there is more that makes me even more bearish:

  • The Fed is on the warpath, and liquidity is scarce.
  • Appraisals overstate the value of property that financial institutions lend against.
  • Homeowners have a smaller margin of safety than they have had in the past.
  • Leverage has increased for the average homebuyer.
  • People are paying more than they ought to for new and existing homes.

I am decidedly a bear on housing prices (at least in the hot coastal markets) at present, but I recognize that momentum can carry prices far beyond sustainable levels.? That?s the way markets work.

Nonetheless, I am still a bear on those who build homes, and those who finance them.? We are at an unsustainable place in the ability to finance the residential hosing market.? Either an increase in interest rates or a decrease in ability to pay for housing can derail the market.? This is the inflection point that we are at over the next year.

Mimicking the 1980s Value Line Contest

Mimicking the 1980s Value Line Contest

A letter from a reader:

Dear Mr. Merkel,

I am organizing an investment contest in my university and I want to do it properly. Can you provide me with data of stock divided into 10 groups based on volatility? I searched for it in Yahoo Finance, but if you have it compiled in a better way, it would be really helpful.?

Also, what do you mean when you say a minimum capitalization limit? Do you mean that the students should hold a certain amount of cash, that they are not allowed to invest?

Sometime in 1985-1986, [Corrected from 1983-1984 — DM] Value Line held a contest where it asked participants to pick ten stocks, one from each of ten price volatility groups, ranked from lowest to highest.? Why such a contest design?? Well, with most stock picking contests, the winner picks a really volatile stock, it soars, and he is the winner by accident.? I say “by accident” because there were others with similarly volatile stocks that lost.

Forcing players to pick a portfolio of stocks, including less volatile stocks, creates a real challenge that resembles real portfolios.?? Even though the contest will still run over 6 months[Corrected from 3-6 months — DM], the luck component is substantially reduced, even though results over a short time horizon are highly affected by luck and momentum.

Well, I’ve created a file that divides the US-traded market into 10 volatility buckets for you, using data from a screening package.?? Here’s the link.

3,589 stocks made the cut.? No ETFs, closed-end funds, etc.? No market caps below $100 million. No stocks with less than 3 years of trading history.? The market cap limit is there because really teeny stocks can fly, and skew the results.? And no, no cash is in the results, just the average returns of 10 stocks.

Here are the average price volatilities by bucket.? [Volatility is actual price volatility for 36 trailing months]

Bucket Avg Price Volatility
1 15.04
2 19.80
3 23.28
4 26.67
5 30.01
6 33.69
7 38.16
8 44.38
9 54.21
10 107.02

As for industries, the volatilities are what you might expect:

Ten Least Volatile

  • 1206 – Natural Gas Utilities
  • 1203 – Electric Utilities
  • 1209 – Water Utilities
  • 0512 – Fish/Livestock
  • 0506 – Beverages (Non-Alcoholic)
  • 0524 – Tobacco
  • 0715 – Insurance (Property & Casualty)
  • 0503 – Beverages (Alcoholic)
  • 0933 – Real Estate Operations
  • 0730 – S&Ls/Savings Banks

Ten Most Volatile

  • 0912 – Casinos & Gaming
  • 0930 – Printing Services
  • 0124 – Metal Mining
  • 0409 – Audio & Video Equipment
  • 0427 – Photography
  • 0969 – Schools
  • 0118 – Gold & Silver
  • 0803 – Biotechnology & Drugs
  • 0966 – Retail (Technology)
  • 0424 – Jewelry & Silverware

That said, such a contest would force some choices from both safe and volatile investments.

Smaller stocks are a lot more volatile than large stocks on average:

Mkt Cap Bucket

Average Vol Decile

100-300M

7.03

300M-1B

6.58

1-3B

5.36

3-10B

4.47

10-30B

3.90

30-100B

3.40

Over 100B

2.61

Finally, some countries are more or less volatile than others.? Of the 50 countries represented, trading on US exchanges, here are the most and least volatile:

Least Volatile

  • Colombia
  • Denmark
  • Panama
  • Philippines
  • Turkey
  • Belgium
  • United Kingdom
  • Chile
  • Switzerland
  • Japan

Most Volatile

  • Israel
  • Bahamas
  • Finland
  • Portugal
  • Russian Federation
  • India
  • Monaco
  • Greece
  • China
  • Argentina

Summary

My point in showing some of the divisions is to give an idea of ways to analyze and play the game.? You could also do it by momentum or valuation variables.? Momentum would probably work best in a short contest.

As for me in the early ’80s, I was a busy graduate student, so I looked at the stocks rank ed highest for Timeliness by Value Line in each volatility group, and selected the one for each group that I thought was the most promising.? As it was, I finished in the top 1%, but not high enough to win a prize.

Anyway, I think this is a great contest design, because it minimizes the ability of players to pick volatile stocks.? With ten stocks of varying volatility in the portfolio, stock-picking skill has a greater chance of being revealed.? Better would be a longer-term contest, but few have the patience for that, and players will argue that they should be allowed to trade, making for a more complex contest.

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